the impact of firm’s internationalisation on corporate
TRANSCRIPT
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The Impact of Firm’s Internationalisation on Corporate Governance:
Evidence from Russia
By: Kirill Osaulenko
UCL
PhD in Strategic Management
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I, Kirill Osaulenko confirm that the work presented in this thesis is my own.
Where information has been derived from other sources, I confirm that this has
been indicated in the thesis.
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Abstract
This PhD thesis is rooted in the broad field of “Strategic Management” and
examines the key determinants of corporate governance in large Russian firms, during
periods of rapid internationalisation and up-sizing from small, modest firms to large,
multinational companies. After the introductory literature review (Chapter 2), the thesis
adopts a multi-method approach in responding to its main research focus, through
qualitative research (Chapter 3), theoretical approaches (Chapter 4) and empirical
research (Chapters 5 and 6). Chapter 3 offers an in-depth analysis of a unique, face-
to-face interview with top management at Kaspersky. Next, a game theory model
informs the conceptual framework and aims to predict whether a firm (such as
Kaspersky) expanding outside its domestic market, should strategically adopt new
corporate governance mechanisms, or whether it should continue to exploit pre-
existing internal mechanisms (Chapter 4). The empirical evidence builds on a brand-
new database, based on a unique level panel database of 300 Russian firms, covering
a time-span of 19 years from 2000-2018, showing variables such as the structure of
the board of directors, the geographical presence of the firm abroad, mergers and
acquisitions, financials, and so on (Chapter 5). The empirical findings highlight how the
development of corporate governance is closely linked with a strategically sound
mechanism of a firm’s internationalisation (Chapter 6). Firms need to establish an
incremental knowledge acquisition process, via internationalisation, that leads to a
fully-fledged exploitation of competitive advantages, both internationally and
domestically. This latter point has been scantly analysed by the existing literature.
Chapter 7 concludes.
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Impact Statement
This thesis fills a gap in current research in the field of strategic
management. It highlights the important strategic decisions that should be
taken by any firm going through the internationalisation process, in terms of
corporate governance restructuring. The theoretical framework of this thesis
provides vital evidence that corporate governance adjustments are required for
successful internationalisation. This thesis will, therefore, primarily impact the
corporate business sector, especially, small and medium firms pursuing rapid
internationalisation. The theoretical framework, developed in the thesis,
provides senior managers and business owners with a robust plan of action to
be taken during the internationalisation process, dependent on the market of
entry, market concentration, and the current developmental stage of the entrant
firm. With evidence from a case study, this research proves that application of
the theoretical framework could change the trajectory of internationalisation
from failure to success.
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Table of Content Abstract .................................................................................................................. 3
Impact Statement ................................................................................................... 4
Chapter 1 ...................................................................................................................... 12
Introduction .............................................................................................................. 12
Literature Review..................................................................................................... 21
Definitions of Terms .......................................................................................... 21
Theories of Internationalisation ............................................................................... 22
Economic Theories of Internationalisation .............................................................. 24
The Transaction Cost Approach. ......................................................................... 24
The Eclectic Paradigm ......................................................................................... 26
Behavioural Approach ............................................................................................. 28
Original Uppsala Model (U – Model) .................................................................. 28
Innovation Models (I –Models) ........................................................................... 33
Network Model of Internationalisation ................................................................ 36
International New Ventures (INV) .......................................................................... 39
Organisational theory of Internationalisation .......................................................... 42
Holistic framework of industry factors and INV ..................................................... 44
Theories of Corporate Governance .......................................................................... 46
Agency Theory..................................................................................................... 46
Stewardship Theory ............................................................................................. 52
Stakeholder Theory .............................................................................................. 54
Resource Dependency Theory (RDT) ................................................................. 56
Corporate governance lifecycle perspective ........................................................ 58
Institutional Theory .............................................................................................. 60
Discussion of Theories. ............................................................................................ 62
Relationship between corporate governance and internationalisation ..................... 65
Board of Directors and firm’s internationalisation .............................................. 65
Transparency and Disclosure (T&D) and firm internationalisation .................... 67
Shareholder rights and firm’s internationalisation ............................................... 69
Corporate Governance & Internationalisation in Russia ......................................... 71
Conclusion ............................................................................................................... 77
References ............................................................................................................ 79
Chapter 2 ...................................................................................................................... 94
Kaspersky Lab case study ........................................................................................ 94
Methodology ............................................................................................................ 97
Background .............................................................................................................. 99
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Establishment of the frim ....................................................................................... 102
First stage of internationalisation (1997 -2000) ..................................................... 104
Second stage of internationalisation (2000-2006) ................................................. 109
Third Stage of internationalisation (2007 – 2016) ................................................. 115
Discussion and Conclusion .................................................................................... 119
Appendix A. ........................................................................................................... 125
Reference: .............................................................................................................. 130
Chapter 3 .................................................................................................................... 132
Internationalisation and strategic decisions on corporate governance ................... 132
Cost function of implementing corporate governance mechanisms. ..................... 138
Methodology .......................................................................................................... 143
Low cost of corporate governance investment ...................................................... 144
Separating Equilibrium Subcase One (Low Cost) ............................................. 152
Separating Equilibrium Subcase Two (Low Cost) ............................................ 156
Pooling Equilibrium Subcase Three (Low Cost) ............................................... 160
Pooling Equilibrium Sub-Case Four (Low Cost)............................................... 166
High cost and changes in the payoff structure ....................................................... 172
Separating Equilibrium Subcase Five (High Cost) ............................................ 175
Separating Equilibrium Subcase Six (High Cost) .............................................. 179
Pooling Equilibrium Sub-Case Seven (High Cost) ............................................ 182
Pooling Equilibrium Sub-Case Eight (High Cost) ............................................. 189
Looking beyond the duopoly game ........................................................................ 195
Discussion and Conclusion .................................................................................... 198
Reference: .............................................................................................................. 202
Chapter 4 ................................................................................................................... 204
Dataset for the analysis ......................................................................................... 204
Sectoral Distribution .............................................................................................. 208
Regional Distribution of the Sample...................................................................... 210
Sectoral and Regional Concentration..................................................................... 212
Control Variables in the Sample ............................................................................ 213
The Dependent Variable ........................................................................................ 217
Board Size .......................................................................................................... 221
Board Age .......................................................................................................... 223
Board Gender Diversity ..................................................................................... 224
Foreign Directors vs. Domestic Directors ......................................................... 226
Executive and Non-executive Members of the Board ....................................... 227
Internationalisation Variables ................................................................................ 230
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Foreign and Domestic Subsidiaries ................................................................... 230
Foreign and Domestic Merges and Acquisitions ............................................... 236
Geographical Diversification ............................................................................. 241
Geographical Efficiency of the Board ............................................................... 242
Graphical Analysis of Internationalisation and Corporate Governance ............ 245
Reference: .............................................................................................................. 250
Appendix B. ........................................................................................................... 252
Chapter 5 .................................................................................................................... 261
Regression analysis ................................................................................................ 261
Methodology .......................................................................................................... 262
Regression Results ................................................................................................. 263
Board of Directors and Internationalisation ........................................................... 265
Average Age of the Board ................................................................................. 268
Number of Male Directors ................................................................................. 270
Number of Female Directors ............................................................................. 271
Number of Executive Directors ......................................................................... 273
Number of Independent Directors. .................................................................... 275
Number of Russian Directors on the Board ....................................................... 277
Number of Foreigners on the Board .................................................................. 279
Robustness Checks................................................................................................. 281
Margin Analysis ..................................................................................................... 286
Board of Directors.............................................................................................. 287
The Dominance of Russian Executive Male Directors on the Board ................ 289
Average Age of the Board ................................................................................. 292
Number of Foreign Directors on the Board ....................................................... 294
Number of Female Directors on the Board ........................................................ 297
Number of Non-Executive Directors on the Board ........................................... 299
Discussion and conclusion ..................................................................................... 302
Appendix C. ........................................................................................................... 306
Chapter 6 .................................................................................................................. 325
Conclusion ................................................................................................................. 325
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FIGURE 1-1: INCREMENTAL PROCESS OF INTERNATIONALISATION (JOHANSON AND VAHLNE 1997). .............................................................................................................................. 28
FIGURE 1-2: THE BASIC MECHANISM OF INTERNATIONALISATION (JOHANSON AND VAHLNE, 1977) ............................................................................................................................... 29
FIGURE 1-3: COMPARISON OF UPSSALA MODEL WITH INNOVATION MODELS ............... 35 FIGURE 1-4: NETWORK MODEL OF INTERNATIONALISATION BY JOHANSON AND MATTSSON
(1988) .............................................................................................................................. 36 FIGURE 1-5: INTERNATIONALISATION PROCESS OF INTERNATIONAL NEW VENTURES
MCDOUGAL & OVIATT (1994)......................................................................................... 40 FIGURE 1-6: ORGANISATIONAL THEORY OF INTERNATIONALISATION ................................... 42 FIGURE 1-7: INTERNATIONALISATION OF SME BASED ON THE SPEED, SCOPE & MODE OF
INTERNATIONALISATION. ............................................................................................... 45 FIGURE 1-8: STEWARDSHIP THEORY BY DONALDSON & DAVIS (1991) .................................. 52 FIGURE 1-9: PRINCIPAL-MANAGER CHOICE MODEL ............................................................... 53 FIGURE 2-1.SHARE OF KASPERSKY LAB IN THE US MARKET IN 2008 .................................... 114 FIGURE 2-2: THEORETICAL FRAMEWORK OF DYNAMIC INTERNATIONALISATION OF INV
(NUMMELA, SAARENKETO & LOANE, 2016) ................................................................. 120 FIGURE 2-3.THE ROADMAP OF KASPERSKY LAB INTERNATIONALISATION PROCESS AND
CHANGES IN THE CORPORATE GOVERNANCE STRUCTURE. ......................................... 125 FIGURE 2-4 FINANCIAL PERFORMANCE OF KASPERSKY LABORATORY BY REGION .............. 126 FIGURE 2-5 RESTRUCTURING OF THE CORPORATE BOARD .................................................. 127 FIGURE 3-1.INTERNATIONALISATION AND CORPORATE GOVERNANCE ............................... 136 FIGURE 3-2.COST FUNCTION OF INVESTMENT INTO CORPORATE GOVERNANCE AND ITS
RELATIONSHIP WITH PROFIT MAXIMIZATION. ............................................................. 141 FIGURE 3-3. SIMULTANEOUS GAME UNDER THE LOW COST ............................................... 146 FIGURE 3-4.SEQUENTIAL GAME WITH PERFECT INFORMATION UNDER THE LOW COST .... 148 FIGURE 3-5. SEQUENTIAL GAME WITH IMPERFECT INFORMATION UNDER THE LOW COST 150 FIGURE 3-6. SEPARATING EQUILIBRIUM SUBCASE 1 (LOW COST) ........................................ 155 FIGURE 3-7. SEPARATING EQUILIBRIUM SUBCASE 2 (LOW COST) ........................................ 158 FIGURE 3-8. POOLING EQUILIBRIUM SUBCASE 3 (LOW COST) ............................................. 165 FIGURE 3-9. POOLING EQUILIBRIUM SUB-CASE 4 (LOW COST) ............................................ 171 FIGURE 3-10. SIMULTANEOUS GAME UNDER THE HIGH COST OF CORPORATE GOVERNANCE
...................................................................................................................................... 173 FIGURE 3-11. SEQUENTIAL GAME WITH PERFECT INFORMATION UNDER THE HIGH COST . 174 FIGURE 3-12. SEQUENTIAL GAME WITH IMPERFECT INFORMATION UNDER THE HIGH COST
...................................................................................................................................... 176 FIGURE 3-13.SEPARATING EQUILIBRIUM SUBCASE 5 (HIGH COST) ...................................... 178 FIGURE 3-14. SEPARATING EQUILIBRIUM SUBCASE 6 (HIGH COST) ..................................... 180 FIGURE 3-15. POOLING EQUILIBRIUM SUBCASE 7.2 (HIGH COST) WHEN P=0 AND Λ = 0 .... 186 FIGURE 3-16. POOLING EQUILIBRIUM SUBCASE 7.3 (HIGH COST) WHEN P=0 AND Λ = 0 .... 187 FIGURE 3-17. POOLING EQUILIBRIUM SUBCASE 7.4 (HIGH COST) WHEN P=0 AND Λ = 1 .... 188 FIGURE 3-18. POOLING EQUILIBRIUM SUBCASE 8 (HIGH COST) WHEN P=0 AND Λ =0 ........ 193 FIGURE 3-19. POOLING EQUILIBRIUM SUBCASE 8 (HIGH COST) WHEN P=1 AND Λ =0 ........ 194 FIGURE 3-20. POOLING EQUILIBRIUM SUBCASE 8 (HIGH COST) WHEN P=0 AND Λ=1 ......... 195 FIGURE 3-21. SIMULTANEOUS GAME WITH N NUMBER OF PLAYERS IN THE MARKET ........ 196 FIGURE 3-22 RESULTS OF THE GAME THEORY ANALYSIS ...................................................... 201 FIGURE 4-1 TOTAL NUMBER OF FIRMS, AVERAGE AGE AND NUMBER OF FIRMS WHICH WERE
INCORPORATED DURING THE TIME SPAN OF THE ANALYSIS (BY YEAR) ...................... 206 FIGURE 4-2. FOREIGN DIRECT INVESTMENT INTO RUSSIA. SOURCE: WORLD DEVELOPMENT
INDICATORS. ................................................................................................................. 207 FIGURE 4-3. BREAKDOWN OF THE SAMPLE BY SECTOR OF ECONOMIC ACTIVITY. .............. 208
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FIGURE 4-4 PERCENTAGE SHARE OF THE SAMPLE BY THE SECTOR OF ECONOMIC ACTIVITY. ...................................................................................................................................... 209
FIGURE 4-5 SHARE OF GDP IN RUSSIA BY SECTOR OF ECONOMIC ACTIVITY (2018) ............. 210 FIGURE 4-6. GEOGRAPHICAL BREAKDOWN OF THE SAMPLE. ............................................... 211 FIGURE 4-7 SHARE OF GDP BY GEOGRAPHICAL REGION (2017) ..................... 212 FIGURE 4-8 SHARE OF STATE-OWNED ENTERPRISES ........................................ 215 FIGURE 4-9. PERCENTAGE OF LISTED AGAINST NON-LISTED FIRMS. .................................... 217 FIGURE 4-10. SHARE OF THE FIRMS IN THE SAMPLE WITH THE BOARD OF DIRECTORS ...... 219 FIGURE 4-11. CORPORATE STRUCTURE OF THE BOARD, BY YEAR ........................................ 221 FIGURE 4-12. AVERAGE BOARD SIZE IN THE SAMPLE, BY YEAR ............................................ 222 FIGURE 4-13. THE AVERAGE AGE OF THE BOARD, BY YEAR. ................................................. 223 FIGURE 4-14. BOARD GENDER DIVERSITY IN LISTED AND NON-LISTED FIRMS ..................... 224 FIGURE 4-15. GENDER DIVERSITY OF THE BOARD OF LISTED FIRMS .................................... 225 FIGURE 4-16. AVERAGE NUMBER OF FOREIGN AND RUSSIAN DIRECTORS ON THE BOARD. 226 FIGURE 4-17. AVERAGE NUMBER OF EXECUTIVE AND NON-EXECUTIVE DIRECTORS ON THE
BOARD. ......................................................................................................................... 228 FIGURE 4-18. PERCENTAGE OF FIRMS WITH AND WITHOUT SUBSIDIARIES. ........................ 233 FIGURE 4-19. DESCRIPTIVE STATISTICS OF FOREIGN AND DOMESTIC SUBSIDIARIES. .......... 234 FIGURE 4-20. GROWTH DYNAMIC OF FOREIGN AND DOMESTIC SUBSIDIARIES. ................. 235 FIGURE 4-21. DESCRIPTIVE STATISTICS OF FOREIGN M&A AND DOMESTIC M&A OF THE
PARENT COMPANY. ...................................................................................................... 238 FIGURE 4-22. PERCENTAGE OF FIRMS WITH AND WITHOUT M&A DEALS ........................... 239 FIGURE 4-23. GROWTH RATE OF FOREIGN AND DOMESTIC M&AS ...................................... 240 FIGURE 4-24. DESCRIPTIVE STATISTICS OF GEOGRAPHICAL DIVERSIFICATION .................... 242 FIGURE 4-25 INDEX OF THE BOARD EFFICIENCY WEIGHTED BY THE NUMBER
OF FOREIGN ACQUISITIONS. ............................................................................... 244 FIGURE 4-26 INDEX OF THE BOARD EFFICIENCY WEIGHTED BY THE NUMBER OF FOREIGN
SUBSIDIARIES. ............................................................................................................... 245 FIGURE 4-27 COMPARISON OF THE AVERAGE NUMBER OF NON-EXECUTIVE DIRECTORS ON
THE BOARD BETWEEN THE FIRMS WITH AND WITHOUT INTERNATIONAL ACTIVITY .. 246 FIGURE 4-28 COMPARISON OF 1-TIER BOARD SYSTEM ACROSS FIRMS WITH AND WITHOUT
INTERNATIONAL ACTIVITY. ........................................................................................... 247 FIGURE 4-29 COMPARISON OF THE TWO-TIER BOARD SYSTEM ACROSS
FIRMS WITH AND WITHOUT INTERNATIONAL ACTIVITY. ............................ 248 FIGURE 4-30 COMPARISON OF THE AVERAGE NUMBER OF INTERNATIONAL
DIRECTORS ON THE BOARD BETWEEN THE FIRMS WITH AND WITHOUT INTERNATIONAL ACTIVITY ................................................................................... 249
FIGURE 4-31. CORRELATION BETWEEN THE DEPENDENT AND INDEPENDENT VARIABLES. 252 FIGURE 4-32. DISTRIBUTION OF FOREIGN AND DOMESTIC SUBSIDIARIES BY SECTOR OF
ECONOMIC ACTIVITIES. ................................................................................................ 253 FIGURE 4-33 DISTRIBUTION OF FOREIGN AND DOMESTIC M&A DEALS BY SECTOR OF
ECONOMIC ACTIVITIES. ................................................................................................ 254 FIGURE 4-34. HISTOGRAM OF LOG: NUMBER OF EMPLOYEES ............................................. 255 FIGURE 4-35. HISTOGRAM OF LOG TOTAL ASSETS IN THOUSANDS OF RUBBLES ................. 256 FIGURE 4-36. HISTOGRAM OF LOG” TOTAL FIXED ASSETS IN THOUSANDS OF RUBBLES ..... 257 FIGURE 4-37. HISTOGRAM OF LOG: AGE OF THE FIRM ......................................................... 258 FIGURE 4-38. HISTOGRAM OF LOG: OPERATING REVENUE IN THOUSANDS OF RUBBLES. .. 259 FIGURE 4-39 WHAT DOES RUSSIA EXPORT? (2018) .............................................................. 260 FIGURE 5-1 CORRELATION MATRIX OF INDEPENDENT VARIABLES ....................................... 265 FIGURE 5-2 REGRESSION RESULTS, DEPENDENT VARIABLE “SIZE OF THE BOARD OF
DIRECTORS” ..................................................... ОШИБКА! ЗАКЛАДКА НЕ ОПРЕДЕЛЕНА.
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FIGURE 5-3REGRESSION RESULTS, DEPENDENT VARIABLE “AGE OF THE BOARD OF DIRECTORS” .................................................................................................................. 269
FIGURE 5-4 REGRESSION RESULTS, DEPENDENT VARIABLE “NUMBER OF MALE DIRECTORS ON THE BOARD” ........................................................................................................... 270
FIGURE 5-5 REGRESSION RESULTS, DEPENDENT VARIABLE “NUMBER OF FEMALE DIRECTORS ON THE BOARD” ........................................................................................................... 272
FIGURE 5-6 REGRESSION RESULTS, DEPENDENT VARIABLE “NUMBER OF EXECUTIVE DIRECTORS ON THE BOARD” ........................................................................................ 274
FIGURE 5-7 REGRESSION RESULTS, DEPENDENT VARIABLE “NUMBER OF NON-EXECUTIVE DIRECTORS ON THE BOARD” ........................................................................................ 276
FIGURE 5-8 REGRESSION RESULTS, DEPENDENT VARIABLE “NUMBER OF RUSSIAN DIRECTORS ON THE BOARD” ........................................................................................................... 278
FIGURE 5-9 REGRESSION RESULTS, DEPENDENT VARIABLE “NUMBER OF FOREIGN DIRECTORS ON THE BOARD” ........................................................................................ 279
FIGURE 5-10 RESULTS OF THE GMM REGRESSION MODELS ................................................. 282 FIGURE 5-11 MARGIN ANALYSIS OF THE BOARD SIZE FOR LISTED AND NON-LISTED FIRMS
BASED ON THE NUMBER OF FOREIGN MARKETS ......................................................... 287 FIGURE 5-12 MARGIN ANALYSIS OF THE BOARD SIZE FOR LISTED AND NON-LISTED FIRMS
BASED ON THE NUMBER OF FOREIGN SUBSIDIARIES. ................................................. 288 FIGURE 5-13MARGIN ANALYSIS OF THE BOARD SIZE FOR LISTED AND NON-LISTED FIRMS
BASED ON THE NUMBER OF FOREIGN ACQUISITIONS ................................................. 289 FIGURE 5-14 MARGIN ANALYSIS OF THE NUMBER OF RUSSIAN DIRECTORS FOR LISTED AND
NON-LISTED FIRMS BASED ON THE NUMBER OF FOREIGN MARKETS ......................... 290 FIGURE 5-15 CORRELATION MATRIX OF THE DEPENDENT VARIABLES ................................. 291 FIGURE 5-16 MARGIN ANALYSIS OF THE AVERAGE AGE OF THE BOARD FOR LISTED AND
NON-LISTED FIRMS BASED ON THE NUMBER OF FOREIGN MARKETS. ........................ 292 FIGURE 5-17 MARGIN ANALYSIS OF THE AVERAGE AGE OF THE BOARD FOR LISTED AND
NON-LISTED FIRMS BASED ON THE NUMBER OF FOREIGN .......................................... 293 FIGURE 5-18 MARGIN ANALYSIS OF THE AVERAGE AGE OF THE BOARD FOR LISTED AND
NON-LISTED FIRMS BASED ON THE NUMBER OF FOREIGN M&AS .............................. 294 FIGURE 5-19 MARGIN ANALYSIS OF THE AVERAGE NUMBER OF FOREIGN DIRECTORS ON THE
BOARD FOR LISTED AND NON-LISTED FIRMS BASED ON THE NUMBER OF FOREIGN MARKETS ....................................................................................................................... 295
FIGURE 5-20 MARGIN ANALYSIS OF THE AVERAGE NUMBER OF FOREIGN DIRECTORS ON THE BOARD FOR LISTED AND NON-LISTED FIRMS BASED ON THE NUMBER OF FOREIGN SUBSIDIARIES. ............................................................................................................... 296
FIGURE 5-21 MARGIN ANALYSIS OF THE AVERAGE NUMBER OF FOREIGN DIRECTORS ON THE BOARD FOR LISTED AND NON-LISTED FIRMS BASED ON THE NUMBER OF FOREIGN M&AS. ........................................................................................................................... 296
FIGURE 5-22 MARGIN ANALYSIS OF THE AVERAGE NUMBER OF FEMALE DIRECTORS ON THE BOARD FOR LISTED AND NON-LISTED FIRMS BASED ON THE NUMBER OF FOREIGN MARKETS ....................................................................................................................... 297
FIGURE 5-23 MARGIN ANALYSIS OF THE AVERAGE NUMBER OF FEMALE DIRECTORS ON THE BOARD FOR LISTED AND NON-LISTED FIRMS BASED ON THE NUMBER OF FOREIGN SUBSIDIARIES. ............................................................................................................... 298
FIGURE 5-24 MARGIN ANALYSIS OF THE AVERAGE NUMBER OF FEMALE DIRECTORS ON THE BOARD FOR LISTED AND NON-LISTED FIRMS BASED ON THE NUMBER OF FOREIGN M&AS. ........................................................................................................................... 299
FIGURE 5-25 MARGIN ANALYSIS OF THE AVERAGE NUMBER OF NON-EXECUTIVE DIRECTORS ON THE BOARD FOR LISTED AND NON-LISTED FIRMS BASED ON THE NUMBER OF FOREIGN MARKETS ....................................................................................................... 300
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FIGURE 5-26 MARGIN ANALYSIS OF THE AVERAGE NUMBER OF NON-EXECUTIVE DIRECTORS ON THE BOARD FOR LISTED AND NON-LISTED FIRMS BASED ON THE NUMBER OF FOREIGN SUBSIDIARIES................................................................................................. 301
FIGURE 5-27MARGIN ANALYSIS OF THE AVERAGE NUMBER OF NON-EXECUTIVE DIRECTORS ON THE BOARD FOR LISTED AND NON-LISTED FIRMS BASED ON THE NUMBER OF FOREIGN M&AS ............................................................................................................ 301
FIGURE 5-28 DESCRIPTIVE STATISTICS OF THE KEY VARIABLES. .................. 306 FIGURE 5-29. CORRELATION MATRIX BETWEEN THE DEPENDENT AND INDEPENDENT
VARIABLES ..................................................................................................................... 307 FIGURE 5-30 WINSORIZING RESULTS OF THE GMM ............................................................. 308 FIGURE 5-31. MARGIN RESULTS FOR THE SIZE OF THE BOARD. ........................................... 309 FIGURE 5-32. MARGIN RESULTS FOR THE AVERAGE AGE OF THE BOARD ............................ 310 FIGURE 5-33. MARGIN RESULTS FOR THE NUMBER OF MALE DIRECTORS ON THE BOARD . 311 FIGURE 5-34. MARGIN RESULTS FOR THE NUMBER OF FEMALE DIRECTORS ON THE BOARD
...................................................................................................................................... 312 FIGURE 5-35. MARGIN RESULTS FOR THE NUMBER OF FOREIGN DIRECTORS ON THE BOARD
...................................................................................................................................... 313 FIGURE 5-36. MARGIN RESULTS FOR THE NUMBER OF RUSSIAN DIRECTORS ON THE BOARD
...................................................................................................................................... 314 FIGURE 5-37. MARGIN RESULTS FOR THE NUMBER OF EXECUTIVE DIRECTORS ON THE
BOARD .......................................................................................................................... 315 FIGURE 5-38. MARGIN RESULTS FOR THE NUMBER OF NON-EXECUTIVE DIRECTORS ON THE
BOARD .......................................................................................................................... 316 FIGURE 5-39 HAUSMAN TEST FOR FIXED EFFECT AND RANDOM EFFECTS MODELS WITH
BOARD SIZE AS A DEPENDENT VARIABLE ..................................................................... 317 FIGURE 5-40HAUSMAN TEST FOR FIXED EFFECTS AND RANDOM EFFECTS MODELS WITH THE
AGE OF THE BOARD AS A DEPENDENT VARIABLE ........................................................ 318 FIGURE 5-41 HAUSMAN TEST FOR FIXED EFFECTS AND RANDOM EFFECTS MODELS WITH
THE NUMBER OF MALE DIRECTORS ON THE BOARD AS A DEPENDENT VARIABLE ..... 319 FIGURE 5-42 HAUSMAN TEST FOR FIXED EFFECTS AND RANDOM EFFECTS MODELS WITH THE
NUMBER OF FEMALE DIRECTORS ON THE BOARD AS A DEPENDENT VARIABLE ........ 320 FIGURE 5-43 HAUSMAN TEST FOR FIXED EFFECTS AND RANDOM EFFECTS MODELS WITH THE
NUMBER EXECUTIVE DIRECTORS ON THE BOARD AS A DEPENDENT VARIABLE ......... 321 FIGURE 5-44 HAUSMAN TEST FOR FIXED EFFECTS AND RANDOM EFFECTS MODELS WITH THE
NUMBER OF NON-EXECUTIVE DIRECTORS ON THE BOARD AS A DEPENDENT VARIABLE ...................................................................................................................................... 322
FIGURE 5-45 HAUSMAN TEST FOR FIXED EFFECTS AND RANDOM EFFECTS MODELS WITH THE NUMBER OF RUSSIAN DIRECTORS ON THE BOARD AS A DEPENDENT VARIABLE ........ 323
FIGURE 5-46 HAUSMAN TEST FOR FIXED EFFECTS AND RANDOM EFFECTS MODELS WITH THE NUMBER OF FOREIGN DIRECTORS ON THE BOARD AS A DEPENDENT VARIABLE........ 324
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Chapter 1 Introduction
The international activity of emerging market firms has experienced
phenomenal growth over the past decade (Guillen & Garcia-Canal, 2009;
Ramamurti & Singh, 2009). The share of emerging markets, in the global
economy, has grown from just below 20% in 1990 to about 44% in 20191. This
growth has generated significant interest among scholars in understanding the
internationalisation process of emerging market firms.
In academic literature, the idea most widely studied and debated is that
the process of internationalisation for emerging market firms differs from
companies in developed countries (Luo & Tung, 2007; Mathews, 2006; Peng &
Delios, 2006). The reason for this lies in the shift in strategic behaviour of
emerging market firms. Before the year 2000, the primary target for
geographical expansion of emerging market firms was other emerging markets,
that display similar economic conditions and are close in terms of geographical
proximity and cultural domain. Such behaviour follows the traditional approach
to internationalisation represented in Johanson and Vahlne’s (1977) paradigm
of incremental internationalisation.
After the 2000s, however, emerging market firms began to target
developed economies in the internationalisation process, applying new
mechanisms such as cross-border mergers and acquisitions (OECD,
2005). This aggressive internationalist approach was motivated by the desire
to take advantage of resources and markets, and to increase global
1 Source: The Role of Emerging Markets in a New Global Partnership for Growth by IMF
Managing Director Christine Lagarde. International Monetary Fund
13
competitiveness (Gaur, Kumar, & Singh, 2009). At the same time, the
internationalisation process became a major objective for most new emerging
market firms.
McDougal & Oviatt (1994) describe these type of firms as International New
Ventures (INV) and provide a theoretical framework to explain the
phenomenon. The theory established a new direction in internationalisation
literature, shedding light on the internationalisation process of small and
medium enterprises. In response to this, several other academic papers have
also focused on examining entry modes into foreign markets (Ripollés & Blesa,
2017), operational strategies (Bell, Crick & Young, 2004; Crick & Spence, 2005;
Martin & Javalgi, 2016), survival challenges (Coeurderoy et al, 2012) and
growth and performance beyond the inception stage (Ghannda & Ljungquist,
2005; Li et al, 2017).
Rather than examining successful internationalist processes of INVs, the
literature has largely focused on unsuccessful cases, which have been the
result of three main factors. These include managerial incompetence, which
has led to falling profits, liquidity difficulties and eventually to bankruptcy
(Hayward et al, 2006; Ooghe & De Prijcker, 2008), entrepreneurial strategic
failures (Van Gelder et al, 2007) and external factors beyond the control of the
entrepreneur (Carter & Wilton, 2006). The first two factors signify that emerging
market firms have failed to address the rise in complexity that is an inevitable
by-product of internationalisation.
When a firm expands outside its country of origin, complexity and
information asymmetry increases (Sanders & Carpenter, 1998; Michael &
Pearce, 2004; Lee et al, 2008), making it more difficult and costly to monitor the
14
performance of Top Management Teams (TMT) (Zajac & Westphal, 1994), thus
leading to typical agency problems. To mitigate against such failures, emerging
market firms should implement new or additional corporate governance
mechanisms, that may not have been needed in domestic markets. This
relationship, between internationalisation and the development of corporate
governance mechanisms in emerging market firms, has not been addressed in
the literature.
To study this relationship, this PhD thesis focuses on emerging market
firms in the Russian Federation. The Russian market provides an appropriate
setting for testing this relationship for a number of reasons. First, as one of the
world’s emerging markets, Russian firms experienced aggressive
internationalisation in the early 2000s. Between 2000 and 2008, Russia topped
the list of BRIC countries in outward foreign direct investment2, handing this
position to China after the financial crisis of 2008. Although most of this
investment came from Russian companies operating in industries linked to
natural resources (oil and gas primarily), a growing number of Russian firms in
other sectors also committed to establishing themselves abroad during this
period. This expansion focused primarily on advanced European countries with
well-established corporate governance standards.
Then, having transitioned from a centralised economy into a market
economy, the Russian Federation began shaping its corporate governance
standards. These were only partially modelled on the standard of developed
countries such as UK, with its Anglo-American practices, and Germany with its
2 Source: https://unctadstat.unctad.org/wds/TableViewer/tableView.aspx
15
European continental system of corporate governance. As a result, the
corporate governance standards in Russia are a mixture of corporate
governance practices introduced in the corporate governance code of 2002.
The fact that the 2002 corporate governance code was a non-compulsory set
of guidelines, has therefore had only a limited effect on the corporate
governance mechanisms of Russian firms.
At the same time, despite the privatisation process of the 90s,
(Filatotchev, Wright, & Buck, 1995), leading Russian companies in different
sectors of the economy, are still owned by the state. Examples include
Gazprom and Rosneft (energy sector), Sberbank (banking sector), Aeroflot,
Russian Railway (RZD) (transportation) and so on. After 2004, the acquisition
of firms by the state became regular practice, steadily increasing the presence
of the state in major Russian firms. It is also important to point out that, due to
the pyramidal structure of ownership, the Russian state also indirectly owns a
significant portion of Russian enterprise (Lazareva et al, 2007). The state’s
share in market capital overall increased from 20% in the year 2003, to 50% in
2012 (Enikolopov & Stepanov, 2013).
The literature indicates that adoption of best corporate governance
practices, in Russian firms with concentrated state ownership, remains quite
limited (Grosman et al, 2016). The Russian Institute of Directors report (2014)
suggests that the proportion of independent and non-executive directors in
state-owned enterprise remains low. At the same time, this report concludes
that voluntary disclosure of information is relatively lower in comparison to
publicly traded firms without state control.
16
The Russian market, between 2000 and 2018, was characterised by
aggressive internationalisation of Russian firms, combined with poor corporate
governance standards of Russian firms, when compared with firms from
developed markets. It is in this context that this PhD thesis concentrates on the
300 largest Russian companies, based on their size in the year 2016, and uses
the multi-method approach to develop and test the hypothesis. The outline of
the thesis is presented below.
This thesis begins with an extensive literature review in Chapter 1, that
examines two streams of academic literature relevant to the study. The first part
of the chapter concentrates on the main theories of firm based
internationalisation. The second part analyses numerous theories of corporate
governance. Using both theoretical and empirical perspectives, this chapter
points to the one-sided approach that dominates the literature in the field of
corporate governance of large multinational companies. The literature primarily
focuses on how strong corporate governance mechanisms determine the
success of internationalisation. This approach, however, overlooks the
possibility of international growth of firms from modest, small firms to large,
multinational companies, therefore missing the important strategic decisions
that should be taken in regard to corporate governance restructuring.
Chapter 2 of the thesis examines a real-case example. It considers how
rapid internationalisation was the cause of multiple corporate crises,
significantly impacting the firm’s performance, and occasionally leading to
unsuccessful internationalisation efforts. The case study is based on an in-
depth analysis of a unique face-to-face interview conducted with the top
17
management of Kaspersky. Such an approach illustrates how the adjustment
of corporate governance structure, allowed Kaspersky Laboratory to change its
trajectory from failure to success during the process of rapid
internationalisation. For a more comprehensive qualitative analysis, the
interview data was combined with additional information from the public press,
Kasperky’s corporate webpage, press releases, books, and academic articles
on Kaspersky Laboratory. In this chapter, the thesis develops the first two
hypotheses which are tested later in the thesis.
Hypothesis 1:
Firm’s internationalisation, which occurs through opening a subsidiary or
foreign acquisition in the foreign market, will be positively correlated with the
number of corporate governance mechanisms.
Hypothesis 2
Increase in the geographical diversification of the firm will be positively
correlated with the share of foreign directors represented on the board.
The theoretical method, adopted in Chapter 3, is based on the game
theory model which informs the conceptual framework, to predict whether a firm
(such as Kaspersky) expanding outside its domestic market, should
strategically adopt new corporate governance mechanisms or if it should keep
exploiting pre-existing internal mechanisms. Based on the theoretical
framework, the third hypothesis will be developed.
Hypothesis 3:
Internationalisation of the firm, from a country with low levels of corporate
governance, to a country with high levels of corporate governance, will be
correlated with a restructuring of corporate governance mechanisms.
18
After the theoretical framework, this thesis presents empirical evidence
from a proprietorial level panel database of 300 Russian firms, that draws on
data collected over 19 years, from 2000-2018 (Chapter 4). The database
includes detailed variables related to the board of directors’ structure such as:
size, age, gender diversity, the degree of board independence and the share of
foreign representatives on the board. The data also examines the
internationalisation of the firm through geographical diversification of the firm,
foreign mergers and acquisitions, and expansion of the subsidiaries outside if
its domestic market. The fifth chapter also investigates the detailed structure of
Russian boards and analyses the difference in structure between listed and
non-listed firms and how these differences influence the relationship between
internationalisation and corporate governance.
Hypothesis 4:
After the IPO of the firm there is a statistically significant relationship between
the internationalisation and its corporate governance restructuring.
The empirical findings highlight how the development of corporate
governance mechanisms correlate with a firm’s sound internationalisation
strategy (Chapter 5). Firms need to build an incremental knowledge acquisition
process, via internationalisation, that leads to a fully-fledged exploitation of
competitive advantages both internationally and domestically.
The final chapter (Chapter 6) summarises the findings of qualitative,
theoretical, and empirical methods used in this thesis, discusses the main
contributions and limitations of the current thesis, and considers ideas for future
research.
19
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21
Literature Review Definitions of Terms
In the existing academic literature on corporate governance and
internationalisation, different authors have used different definitions of those
terms. Therefore, before going examining the academic literature in depth, it is
important to understand the variations of those definitions.
A large number of scholars have used different meanings for the term
corporate governance (CG henceforth) in academic papers. Wieland (2005)
defined corporate governance from the business ethic perspective “…as
leadership, management, and control of a firm by formal and informal, public
and private rules” while from the economics and law perspective Zingales
(1997) described CG as “the complex set of constraints that shape the ex-post
bargaining over the quasi-rents generated in the course of a relationship.” The
definition by Shleifer and Vishny (1997) concentrated more on the financial
aspect stating that CG is “…the ways in which suppliers of finance to
corporations assure themselves of getting a return on their investment.” On the
other hand, most of the comparative studies on corporate governance use a
general definition presented by Aoki (2000), which states CG is “…the structure
of rights and responsibilities among the parties with a stake in the firm”. In
summary, the OECD (2004) defined CG as “The system by which business
corporations are directed and controlled”. The difference among the definitions
is primarily linked to the academic field and the research question that the
academics are targeting. Therefore, each social scientist is forming their own
scope and concerns
22
Exactly the same can be said about the term internationalisation, which
also has some variation in its definition across scholars. Ahokangas (1998)
describes it as “the process of mobilizing, accumulating and developing
resource stocks for international activities”. Another definition of this term can
be seen from the perspective of business networks. For example, as suggested
by Lehtinen and Penttinen (1999) internationalisation is the process of
“developing networks of business relationships in other countries through
extension, penetration and integration”. Johanson and Vahlne (1990) stated
that internationalisation is a “cumulative process in which relationships are
continually established, developed, maintained and dissolved in order to
achieve the firm’s objectives”. The definition by Welch and Luostarinen, (1988)
states that internationalisation is “The process of increasing involvement in
international operations"
Theories of Internationalisation
Over the past couple of decades, there has been an impressive increase
in the number of multinational enterprises (MNEs) around the globe (Fishwick,
1981; Hamilton 1986; Dunning, 1993; Young, Hood, & Peters 1994; Caves
1996; Mudambi 1999; Enright 2000; Andreff 2002; Child & Rodrigues 2005;
Dimitratos et. al., 2009; Filippov, 2010; Kalman 2017; Esho & Verhoef 2020) .
The Organisation for Economic Co-operation and Development (OECD) and
United Nations Conference on Trade and Development (UNCTAD)
define multinational (or transnational) enterprises as companies which are
engaged in foreign direct investment (FDI) and either own or control the value-
added assets in more than one country.
23
In the academic sphere, a large number of scholars have described the
different benefits for companies to extend their performance outside of their
origin market and have explored the various characteristics of MNEs (Buckley
P., J., & Casson M. C. 1976; Rugman A., M., 1981; Kogut B., & Zander U.,
1993; Markusen, J. R. 1995; Dunning, J. & Lundan, S. 2008). While some
scholars have described advantages of becoming an MNE, others
concentrated on the process of internationalisation itself. In the past half a
century, scholars examined the internationalisation process of a firm from
different perspectives and were able to determine several theories of
internationalisation. We could list the so-called economic models of
internationalisation such as Transaction Cost Approach (Williamson, 1981) &
Eclectic Paradigm (Dunning 1979); Behavioural models of internationalisation
such as Uppsala Model developed by Johanson & Vahlne (1977) as well as
innovation related models developed by Bilkey & Tesar (1977) Cavusgil (1980)
Reid (1981) and Czinkota (1982) and finally entrepreneurial approaches such
as International New Ventures model (McDougal & Oviatt, 1994), among
others. The following sections will describe various theories of
internationalisation from different perspectives and will highlight their
advantages and disadvantages.
24
Economic Theories of Internationalisation
The Transaction Cost Approach.
Having its roots in new institutional economics, transaction cost theory
(TCT henceforth) “... is an interdisciplinary approach to the study of
organizations that joins economics, organization theory, and aspects of
contract law” (Williamson, 1981). In 1937, economist Ronald Coase noticed
that production of final goods and services involves a succession of processes
and assembly activities. During these stages the firm is involved in internal and
external exchanges and monitoring processes (i.e.: exchange of materials,
money etc.) with other market actors. Each exchange will have a transaction
cost that depends on asset specificity, uncertainty and frequency of the
exchange (Williamson, 1981). TCT assumes that decision makers employ
opportunistic behaviour due to three main constraints: limited information,
limited ability to evaluate the process and a limited time scale to make the
decision (in other words bounded rationality3). At the same time, an important
assumption of the TCT approach is that markets are competitive and, therefore,
there are multiple suppliers. Based on those assumptions the transaction cost
theory focuses on the inter-organisational governance of a seller-buyer
relationship and its economisation process (Andersen, 1997).
Later, the TCT framework was extended into the international context
and used to explain the selection of the entry mode into a foreign market
(Anderson & Gatignon, 1986; Klein et al., 1990). Based on the characteristics
of the transaction costs, decision makers will select the most appropriate entry
3 The concept was introduced by the Nobel Prise winner Herbert A. Simon (1991) Bounded rationality and organisational learning
25
mode by taking into account a fundamental trade-off between the need for
stricter control and the implicit cost of further resource commitments. Later,
Erramilli and Rao (1993), suggested additional modification to the original
model by adding non-transactional cost advantages, which are gained through
multinational cooperation. An improved framework explained the selection of
the market entry mode for the service industry where the main specific assets
are intangibles.
The transaction cost theory, was exposed to some criticism. David and
Han (2004) made a systematic assessment of 63 empirical articles related to
transaction cost theory and concluded mixed results due to methodological
problems such as self-selection variable issues, survivorship bias, sample
selection (i.e.: most studies did not used Longitudinal data). One of the
questions that the authors brought to the attention of the literature was the
problem of measuring transaction costs, as in most studies they are measured
indirectly using the characteristics of the transaction (asset specificity,
uncertainty, the interaction of asset specificity and uncertainty, frequency, and
opportunism). Similar conclusions were made by Ghoshal and Moran (1996),
Masten and Saussier (2000), Carter and Hodgson (2006), and Macher and
Richman (2008). Therefore, most empirical studies shifted away from the
original unit of the analysis (transaction cost) and used firm level as the unit of
analysis. (Andersen, 1997)
26
The Eclectic Paradigm
Another significant theoretical framework that is used to determine the
international production activities of MNEs and the mode of entry is “The
eclectic paradigm” conceived and developed by John Dunning (1979, 1980,
1985, 1988, 2000, and 2008). The initial theory took a static approach and
suggested that companies are getting involved in international production
based on three main factors: Ownership advantages (O), Location advantages
(L) and Internalisation advantages (I) (OLI). The first factor (O) corresponds to
the possession of assets, which competitors do not have. The author justifies
three main types of ownership specific advantages such as those relating to
the possession and exploitation of monopoly power, scarce or unique
resources and those relating to managers’ competences. The second, (L), is
the attractiveness of the specific country for FDI (e.g. low production costs, high
market potential). The third factor (I), relates to the ways through which firms
may organise and exploit their core competencies (hierarchical or external
modes of operation) (Dunning 1993). Later Dunning (2001) proposed looking
at OLI theory as an ‘envelope’ for other economic and business theories, which
means that the explanatory power of the model would increase if it is used
together with other models (like resource based theory or evolutionary theory).
OLI paradigm was further developed by Guisinger (2001) in his ‘evolved
eclectic paradigm’. First, he replaced the Internalisation factor with the mode of
entry (M). This allows researchers to differentiate between factors affecting
different modes of entry in different countries. The second and major
modification of OLI by Guisinger (2001) is the adaptation of the firm’s operations
to the international business environment building on institutional theory, hence
27
adding ‘A’ in the OLMA. According to Guisinger (2001) “there must be a
compelling distinction’ between foreign and domestic components of the
environment”.
As tends to happen with all theories, the eclectic paradigm has been
criticised by a number of authors. Rugman (2010) suggests the model is too
eclectic. It has a broad and loose structure in all three advantages categories.
Itaki (1991) also supported this point, stating that the concept «ownership
advantage» is redundant in the sense that it can logically be classified as
internationalisation advantages. Solberg and Askeland (2005) stated that the
broadness and multiplicity of the eclectic framework makes it vulnerable to
complexity, leading to difficulties in predicting causality. Finally, unlike the
behavioural approaches, which will be discussed in the next section, the initial
eclectic paradigm approach is static; a major drawback considering that
internationalisation is intrinsically a dynamic process. This point, however was
targeted by the author of the theory himself (Dunning 2000) who extended his
theory and discussed how best a firm may organize its activities to create future
assets, rather than optimize the use of its existing assets
.
28
Behavioural Approach
Original Uppsala Model (U – Model)
Presented by Jan Johanson and Jan-Erik Vahlne in the Journal of
International Business Studies in 1977, this was the first theoretical model to
represent internationalisation as a series of incremental decisions. It was based
on the earlier empirical study of the export organisation of Swedish firms, in
which firms were entering foreign markets in small steps (stages) following a
chain of establishment where each successive stage represented a higher
degree of international involvement (Johanson & Wiedersheim-Paul, 1975).
Based on the pattern from the study, the authors assumed that the
internationalisation process frequently starts in markets that are closely related
to the domestic market in terms of geographical distance. Such distance was
defined as “factors that make it difficult to understand foreign environment”.
In order to justify why internationalisation of firm occur through incremental
steps, Johanson and Vahlen (1977) used a dynamic model (figure 1.1), in which
the outcome of one set of decisions provided the input of the next. They
determined a mechanism that is divided into two sets of internationalisation
variables: state aspect and change aspect (figure 1.2).
Stage 1
No regular
export
activity
Export
(sales) via
agent
Sales
Subsidiary
establishment
Establishment of
Production
subsidiary
Stage 2 Stage 3 Stage 4
Figure 1-1: Incremental process of internationalisation (Johanson and Vahlne 1997).
29
As seen on the above figure, the U-model assumes that a change in the state
aspects (market commitment & market knowledge) will influence the change
aspects (commitment decisions & current activities), and this in turn will have
an impact on a state aspect.
All four elements are assumed to be important factors for the growth of
international activity. Market commitment, in this model, represents the
perception of risk and opportunities that a firm have. It consists of two parts,
the degree of commitment and amount of committed resources. The first refers
to the difficulty to find an alternative use to the resource and transfer it to the
other market and the second, represents the amount of firm’s investment.
Market knowledge also consists of two elements: objective knowledge
(knowledge about market methods and tools, which can be applied to different
markets) and experiential knowledge (knowledge about culture, customers’
preferences and characteristics, which are different across markets). For the
U-model, the latter element is vital. Such experiential knowledge provides a
framework for perceiving and formulating opportunities. There is also a direct
relationship between market knowledge and market commitment. Knowledge
Market
Knowledge
Market
Commitment
State Aspects
Commitment
Decisions
Current
Activities
Change Aspects
Figure 1-2: The Basic Mechanism of internationalisation (Johanson and Vahlne,
1977)
30
0.can be considered as a resource, therefore the better the knowledge about
the market the more valuable are the resources and the stronger is the
commitment to the market. It is also claimed that experiential knowledge
reduces a firm’s perception of market uncertainty or risk, which in turn has an
impact on commitment to international markets.
Regarding the change aspect of the mechanism, Johanson and Vahlne
(1977) assumed that the major source for the experience is the current
business activities of the firm. At the same time, most of the firm’s current
activities have lag effects (i.e. there is no perceived immediate effect of the
action). Therefore, it was assumed the longer the lag effect the higher is the
market commitment of the of firm.
The commitment decision (decision to commit resources to foreign
operations) is the second change aspect that depends upon what decisions
are made and how they are made. Regarding the first part, it is assumed that
decisions are made in response to perceived problems and / or opportunities
in the market. Awareness of need and possibilities for business actions are
assumed to be dependent on experience. Regardless of whether decisions
are made in response to problems or in response to opportunities,
commitment will be made in relation to current business activities.
The Uppsala model drew interest from different researchers and also
gathered some criticism. For example, a number of authors stated that the
model is deterministic (Reid, 1983, Turnbull, 1987) as it does not take into the
account other external factors, which can influence internationalisation, such
as strategic actions taken by the decision maker. Anderson (1993) claims that
the model does not explain why or how the process starts, in other words there
31
are no initial conditions. Engwall and Wallenstal (1988) were able to provide
empirical evidence that confirms the Uppsala model is not suitable for
explaining internationalisation in the service industry, for example. Forsgren
(1989) also concluded that the model is only applicable as an explanation of
the initial stages of firms’ internationalisation during which market knowledge
and resources are still a restriction. It has also been argued that the model
does not take into the account interdependencies between different country
markets (Johanson & Mattsson, 1988).
Later in 1990, Johanson and Vahlne revisited their own model, making
two main changes to fulfil the gaps identified. First, the authors looked at how
the Uppsala internationalisation process model and Eclectic Paradigm
(Dunning 1988) can be used as complementary frameworks, in order to
increase their respective explanatory power. As the process model relies on
the notion of market knowledge and market resources, its explanatory power is
limited to the early stages of firms’ internationalisation, at which time these
factors are still a constraint for a firm (Forsgren, 1989). On the other hand, the
eclectic paradigm assumes that decision makers have perfect information,
which is more applicable to the firms that have activities in different countries
and can therefore explain the later stages of internationalisation.
Secondly, the model was linked to the concept of industrial networks in
which firms obtain knowledge and resources through the production network,
and in which they are tied to each other through different bonds, thus allowing
the firm to enter foreign market (Johanson & Vahlne, 1990). As the network can
be far beyond the country’s borders, such relationships among firms are
considered as bridges to other networks, which are important in the initial steps
32
abroad and in the subsequent entry of new markets. The authors also claim
that it is possible to enter such network only if the firms inside are motivated to
start the collaboration process.
The most recent paper by Johanson & Vahlne (2009) shifted the original
model even more towards the network approach. The Authors concluded “…
successful internationalisation requires a reciprocal commitment between the
firm and its counterparts” (Johanson & Vahlne, 2009). Firms still have to
develop knowledge for the internationalisation process; however, this
knowledge will come through the company’s position in the network. The
position is determined by the trust and commitment among partners. At the
same time, Johanson and Vahlne (2009) stated that the explanatory power of
the establishment chain, which was in the original view, is decreasing. Modern
companies tend to start internationalisation sooner, choose a more rapid mode
of entry into the foreign market and select markets that are not necessarily
related in terms of geographical distance (Hedlund & Kverneland, 1985; Oviatt
& McDougall, 1994; Madsen & Servais, 1997). This leads to the fact that they
may just leapfrog certain stages of the chain.
33
Innovation Models (I –Models)
There are a number of models developed by Bilkey and Tesar (1977),
Cavusgil (1980), Reid (1981) and Czinkota (1982) that are quite closely related
to the U-model in terms of their approach on incremental stages and
geographical distance (See Table 1.1). However, the core difference was that
those scholars saw the internationalisation process as an innovation-adoption
cycle. In other words, the internationalisation decision is considered as an
innovation for the firm (Anderson 1993).
Bilkey and Tesar’s (1977) 6-stage model was empirically related to the
sample of Small and Medium Enterprises (SMEs) in which firms gradually
increase the level of exporting to the countries that are psychologically further
away if the firm’s management is seeking to explore exporting opportunities.
Cavusgil’s (1980) manufacturing firms in Maine and New Mexico model is
founded on management’s successive decisions regarding exporting over a
period of time. Based on empirical evidence, the author suggests that several
firm-specific characteristics and managerial factors act as determinants in the
process of facilitating or inhibiting the progress of firms from one
internationalisation stage to the next, as presented in Figure 1.3.
Czinkota (1981) based his analysis on small and medium firms
manufacturing industrial goods. He adapted the first four stages of his model
from Bilkey and Tesar’s (1977) study. He used several criteria for differentiating
among stages: past export volume, absolute export volume, length of export
experience, types of countries exported to, number of export customers,
number of export transactions, and manpower committed to exporting. He has
also segmented firms so as to be able to target government export assistance
34
requirements effectively. The empirical investigation revealed that firms, at
various stages, significantly differed in terms of their organisational and
managerial characteristics.
Reid (1981) views internationalisation as an innovation adoption
process. Export adoption was believed to require a favourable management
attitude to exporting, an available foreign market opportunity and the presence
of spare resource capacity within the firm. He points out the need to distinguish
between the foreign entry expansion process of small and large firms.
Regarding small firms, he assumed that the individual decision-maker
influences the export behaviour of the firm while the entry behaviour in large
firms is a complex process, which involves a much higher number of decision
bodies. This model differs from other I-models, as it is not focused on the
organisational form adopted by the firm for exporting, but on the attitude and
behaviour of the decision-maker and the requirements of the firm in terms of
allocated resources at each stage of the adoption process.
Based on the above descriptions, innovation-related models concentrate
primarily on the export-oriented behaviour of firms and do not provide any
support for the later stages of internationalisation. They share similar
characteristics and seem to have semantic differences rather than real variants
about the nature of internationalisation process, apart from the initiating
mechanism (Anderson 1993). In addition, these models are restricted to a cross
sectional studies of SMEs and, based on this, it is not possible to conclude how
firms get from one stage to another, as only one point in time is analysed.
Anderson (1993) suggests that a longitudinal study will be more appropriate for
analysing establishment chains that are reported in I-model.
35
Figure 1-3: Comparison of Upssala Model with Innovation Models
Johanson & Vahlne (1977) Bilkey & Tesar (1977) Cavusgil (1980) Reid (1981) Czinkota (1982)
Stage 1
No regular export activities Management is not
interested in exporting
Domestic marketing: the firm sells only to the home market
Export awareness: problem of opportunity recognition, arousal of need
The completely uninterested firm
Stage 2
Export via independent representatives
Management is willing to fill unsolicited orders, but makes no effort to explore the feasibility of active exporting
Pre-export stage; the firm searches for information and evaluates the feasibility of undertaking exporting
Export intention: motivation, attitude, beliefs, and expectancy about export
The partially interested firm
Stage 3
Establishment of an overseas sales subsidiary
Management actively explores the feasibility of active exporting
Experimental involvement: the firm starts exporting on a limited basis to some psychologically close country
Export trial: personal experience from limited exporting
The exploring firm
Stage 4
Overseas production / manufacturing units
The firm exports on an experimental basis to some psychologically close country
Active involvement: exporting to more new countries – direct exporting – increase in sales volume
Export evaluation: results from engaging in exporting
The experimental firm
Stage 5
The firm is an experienced
exporter
Committed involvement: management constantly makes choices in allocating limited resources between domestic and foreign markets
Export acceptance: adoption of exporting / rejection of exporting
The experienced small exporter
Stage 6
Management explores the feasibility of exporting to other more psychologically distant countries
The experienced large
exporter
Sources: Anderson (1993) p213; Johanson &Vahlne (1977) p25
36
Network Model of Internationalisation
Behavioural models’ approaches, which were described in the previous
sections, rely on the notion of experiential knowledge. Firm acquires this type of
knowledge while operating in the international marketplace and can use it later on to
resolve issues in the foreign markets (Brockman & Anthony, 1998). The obvious
problem that arises from this concept is how the firm that does not operate within the
international market can gain experiential knowledge. The network model of Johanson
and Mattsson (1988) suggests that external factors (such as actors or organisations)
can influence internationalisation process (figure.1.4).
Figure 1-4: Network model of internationalisation by Johanson and Mattsson (1988)
The original model was based on the industrial markets in which firms are
interconnected with other market actors (i.e. suppliers, distributors, customers, etc.)
through the network of long-lasting relationships. It is also assumed that such networks
are stronger and more developed in the home market in comparison to the export
market (Johanson and Mattsson, 1988). This model was determining firm
internationalisation level as a result of its position in the network (Hadley & Wilson,
2003). The authors were able to distinguish two elements that influence
internationalisation process: level of firm internationalisation and level of market
Degree of market internationalisation
Low High
Degree of internationalisation
of the firm
Low The Early
Starter Late Starter
High The lonely
International
The international
among others
37
internationalisation. Based on these criteria they derived four categories of firms: The
early starter, later starter, lonely international and the international among others.
Johanson and Mattsson (1988) characterised the early starter as a firm that has
few unimportant relationships with firms in the foreign markets and similar firms in the
production network. Similarly, at this stage, suppliers, customers and competitors do
not have strong international relationship in either their home or international market.
Due to such poor relationships, the firm does not have knowledge about the
international markets, and according to Johanson and Mattsson (1988), it is not
possible to gain that knowledge only through domestic relationships. Therefore, to
start international activity, the firm requires resources (including knowledge) to
increase its market commitment, which can be obtained through agents in the foreign
markets, and expand internationalisation through the original establishment chain
(Johanson & Wiedersheim-Paul, 1975).
‘The lonely international’ category describes a firm with the high level of
internationalisation but where the internationalisation level of the market environment
is low. In other words, this firm has a higher level of internationalisation in comparison
to its competitors in the production network. Therefore, this firm has the competence
to pass obtained knowledge about foreign markets to its own network and thus
promote internationalisation within the production network (Hollensen, 2007).
The ‘late starter’ has a low degree of internationalisation, however the degree
of market internationalisation is high (Hadley & Wilson, 2003). Based on the
characteristics of the late starter by Johanson and Mattsson (1988), such as low level
of market commitment and activity in the foreign markets, it is very similar to the early
starter typology. However, there is an important difference. The late starter has an
indirect international relationship through suppliers, customers and competitors,
38
creating a knowledge advantage relative to the early starter (Hadley & Wilson, 2003).
Academic literature suggests that such inter-network relationship can influence the
decision making process of the firm (Johanson & Mattsson, 1988; Bonaccorsi, 1992;
McKiernan, 1992). Bonaccorsi (1992) also pointed out that small firms generally make
decisions to commit resources towards internationalisation based on network
collective experience. At the same time, author suggests that some companies can
simply imitate the decisions of other companies, thus imitating the same
internationalisation process.
The ‘international among others’ typology has a high degree of both market and
firm level of internationalisation. A highly internationalised environment will allow the
firm to benefit from a higher level of experiential knowledge in comparison to ‘lonely
international’. This, in turn, allows for building a solid relationship between different
production networks, utilising firm’s production capacity and product specialisation
(Johanson & Mattsson, 1988).
Such a model of internationalisation goes beyond the original Uppsala model
by taking into the account the business environment of the firm, thus bringing the
concept of interconnectedness into the internationalisation process (Andersson,
2002). The model suggests that cooperation among different actors of the network
will lead to the efficient development of the firm, in comparison to competition within
the production network. Bjorkman and Forsgren (2000) also pointed out that within the
network model the firm could have the majority of its physical assets in the home
market, but at the same time play a significant role in the international network
development. According to the model, it is also plausible to gain experiential
knowledge from the production network without going through the direct experience of
work in the foreign markets (Eriksson et al., 1998; Bonaccorsi, 1992).
39
On the other hand, quite a few authors criticised the network approach. For
example, Bjorkman and Forsgren (2000) pointed out that the model does not predict
the internationalisation process but just differentiates the typologies of the companies.
At the same time, it is not clear how the shift occurs from one typology into another
(Chetty & Blankenburg, 2000). Nummela (2002) claims that another limitation is that
the model concentrates primarily on the large companies and it does not describe the
behaviour of the small and medium enterprises (SME) within the networks. It is also
claimed that the model does not take into the account the decision maker, who might
have the opportunity to internationalisation but is unwilling to do so for any reason, i.e.
is afraid to lose control of the company (Chetty & Blankenburg, 2000). Another issue
that was raised by Chetty and Wilson (2003) was that the model does not explain the
way to create network relationships, thus it is not clear how the ‘early starter’ can begin
the internationalisation process.
International New Ventures (INV)
In contrast, to the incremental process of internationalisation (Johanson &
Vahlne, 1977; Johanson and Mattsson, 1988; Brockman and Anthony, 1998),
McDougal and Oviatt (1994) developed a theory, which drew attention to the
phenomena of rapid internationalisation into the global markets. The authors called
these firms ‘International New Ventures’. The theory suggested that such companies
are international from inception and concentrated more on the age of the company
rather than size. Partly, that phenomenon became possible as the international
environment was changing. The rapid growth of technology reduced transactions
costs, communication costs and made it easier for the small start-up companies to
identify business opportunities in the foreign markets (McDougal & Oviatt, 1994). The
40
other reason was the rise of entrepreneurs with international experience through which
they were able to identify and connect resources in different markets and establish
competitive advantages, allowing new companies to internationalise without actually
owning resources (McDougal & Oviatt, 1994).
In their theory, McDougal & Oviatt (1994) distinguish four types of international
new ventures: Export/Import start-ups, Geographically Focused start-ups, Global
start-ups, Multinational trader (Fig. 1.5). To differentiate between the groups the
authors used two main criteria: Coordination of value chain activities and number of
countries involved.
Figure 1-5: Internationalisation process of International New Ventures McDougal & Oviatt
(1994)
Number of Countries involved
Few Many
Coordination of value chain
activities
Few Export/Import Start-
ups Multinational Trader
Many Geographically
focused start-ups Global Start-ups
Both Export/Import start-ups and Multinational trader can be grouped by their
ability to establish disproportions of resources between countries, thus providing them
with opportunities to create markets. The only difference is the number of countries in
which these new ventures operate. Geographically focused start-ups are constrained
to a specific region in which they are specialising in the several value chain activities,
while the global start-ups are specialising in the several value chain activities in
different geographic regions (McDougal & Oviatt, 1994).
Source: McDougal & Oviatt (1994) p59
41
The theory established a new turn in internationalisation literature, especially
shedding some light on rapid internationalisation process of small and medium
enterprises. However, this approach has some limitations. First of all, McDougal &
Oviatt (1994) pointed out that it is hard to establish the exact starting point of new
venture. That occurs due to the difference of firms’ development process prior to the
official launch. Zahra (2005) also states that existing companies could establish some
international new ventures. On the one hand, those firms can be counted as a new
venture, but on the other, they can benefit from the resources and relationships that
already exist in the parent company, which means that the parent company can drive
their internationalisation process. The author also mentions that original theory does
not inspect firms’ survival rate between international new ventures typologies, thus
making it questionable whether these types are equally feasible (Zahra, 2005). In
addition, the theory does not take into account the industry specific characteristics,
which can influence the internationalisation process (Andersson, 2006; Evers, 2010;
Evers 2011)
42
Organisational theory of Internationalisation
Figure 1-6: Organisational theory of Internationalisation
One of the recent frameworks that take into the account industry specific
characteristics, which can influence the internationalisation process is “the
organisational model” created by Malhorta and Hinings (2010). These authors claim
that the internationalisation process varies between different organisation types and
each type reacts differently to three critical elements of the internationalisation
process: physical presence, degree of presence and focus of entry. Theoretical
background of the framework combines some characteristics of the original Uppsala
model framework (Johanson & Vahlne, 1977; Bowen et al. 1989). From the Uppsala
model, Malhorta and Hinings (2010) take the idea of incremental stage development
of internationalisation. However, the authors allow for leapfrog behaviour of the firm
(skipping some stages of the process) depending on the different scenarios of firm
development and its characteristics. From Bowen et al.’s (1989) framework,
organisational model picked characteristics to distinguish between firms’ typology:
Organisation type
Differentiating characteristics
Nature of production
activity
Nature of Dominant asset
Degree of centrality of client
Mass Production
organisation
Mass production
Least people intensive
Low
Disaggregated production
organization
Disaggregated production
Moderate people intensive
Medium
Project-based organization
Project-based production
Highly people intensive
High
Source: Malhotra & Hinings (2010) p336
43
standardised / customised output, capital / labour intensity in the firm, high / low degree
of client centralisation.
Those characteristics can be represented on a continuum and suggest three
main types of organisations. At one end of the continuum is a ‘mass production’
company that is capital intensive, produce standardise products and has the low
degree of client centrality. Typical examples of such typology are automobile
production companies, service factories, chemical plants etc. At the other end of the
continuum is a ‘project-based firm’ with high levels of labour intensity and customised
products, which is based around the client needs, for example professional services,
consulting, accounting etc. Those firms are more knowledge intensive and primarily
selling their intangible goods to the client. The third type is situated in the middle of
these continuums and they represent a ‘disaggregated production organisation’ with
some degree of product customisation, moderate degree of labour intensiveness and
medium degree of client centrality. Companies such as restaurants, hotels, car rentals
etc. can be included in this category.
Each type of organisation has a different internationalisation process
depending on a physical presence, degree of presence and focus of entry. Malhorta
and Hinings (2010) claim that for mass production firms’, physical presence in the
foreign market will be the major determiner of the internationalisation process. If
physical presence is not required, the firm can follow the standard Uppsala model
stages of internationalisation starting from export and licencing. However, if the
physical presence is a critical element for the firm’s internationalisation the firm will
leapfrog the initial stage and will chose a joint venture or a wholly owned venture as
an entry mode. Disaggregated organisations, based on their characteristics, will
primarily choose the contractual paths (engagement through contracts or franchises)
44
of internationalisation as their physical presence in foreign market is driven by
moderate people intensiveness. For projects-based organisations, physical presence
and the degree of this presence depends on each individual project (client), which
typically is very high, as these organisations heavily rely on their employees as main
source of delivering the service. In order to remain in the foreign market, project-based
organisations should sustain a continuous inflow of projects. Therefore, the
commitment of the resources varies according to the demand in the market.
Holistic framework of industry factors and INV
Another recent paper by Andersson, Evers and Kuivalainen (2014) also emphasised
the role of industry factors in the internationalisation process of the firm. The main
difference with the organisational model (Malhorta and Hinings, 2010) is the origin of
the theoretical concept. The Andersson, Evers and Kuivalainen (2014) framework
takes its roots from the theory of international new ventures (McDougal and Oviatt,
1994). Using the original assumptions of McDougal and Oviatt (1994), those managers
who possess knowledge of international markets and who are able to link the
resources between these markets prefer rapid internationalisation from the inception
and pursuing revenues from different international markets. The conceptual
framework identifies key industry factors as well as emergent factors that influence the
new venture internationalisation process in terms of speed, geographical scope and
entry strategy. Such key influencing factors are competition and structure, industry life
cycle, industry concentration, knowledge intensity, local cluster internationalisation
and global industry integration. The emergent factors are identified as new business
models, technology and industry network dynamics.
45
Andersson, Evers and Kuivalainen (2014) based this conceptual theory on the
empirical evidence, which studied rapid internationalisation process of small and
medium enterprises primarily in high-tech industries (Bloodgood et.al. 1996; Burgel
and Murrey, 2000; Crick, 2000; Johnson, 2004; Spence and Crick, 2006; Fernhaber
et.al., 2007; Kuivalanen et.al., 2007). According to the Organisation of Economic
Cooperation and Development (OECD), industry can be classified as high tech if firms
inside this industry invest more than 4% of their revenue in research and development
(R&D).
At this point, in summing up the framework factors, which will influence the
speed, scope and mode of internationalisation of new international ventures, the
Andersson, Evers and Kuivalainen (2014)
Figure 1-7: Internationalisation of SME based on the Speed, Scope & mode of
internationalisation.
46
authors point out that the framework is very abstract, thus further empirical research
is recommended. As the majority of studies concentrated on the high-tech sectors, it
is important to see if similar factors will have an influence on internationalisation in the
low or mid-tech industries (Evers, 2011). Furthermore, research should be scrutinising
the internationalisation strategy and especially attempting to define what is meant by
INV internationalisation (Andersson, Evers and Kuivalainen, 2014).
Theories of Corporate Governance
Agency Theory
The field of corporate governance takes its roots from the work of Berle and
Means in 1932, in which they draw attention to the separation of ownership and control
in modern organisations. They noticed that due to the increase in the size of modern
corporations’ owners (principals) hire managers (agents) to perform the work. They
argued that the agents might use the property of the firm for their own benefit resulting
in an intrinsic principal agent conflict. Later, the financial literature (Arrow, 1971;
Wilson, 1968) charachterised the conflict between the agent and principal through the
problem of risk sharing, suggesting that these two groups have different risk attitude
and as a result will act differently. The owners (principals) invest their own capital and
bear the risk of failure, which correlates with the decisions made by managers (agents)
who are risk averse and act to maximise their own benefit. Furthermore, Jensen and
Meckling (1976) developed the idea that a company is a nexus of contracts, thus
describing the firm not as an individual but a legal entity, which is joined by contracts
among suppliers, customers and creditors. However, the interest of the parties differs,
the conflict of interest arises, and it can only be relegated through managerial
47
ownership and control. Eisenhardt (1989) categorised the agency theory in two
models: Positive agency theory and Principal-agent research. The first concentrated
on thinking about specific situations in which the principal-agent conflict arise and then
suggesting a mechanism to resolve it. Typically, it was applied only to large
corporations and scholars looked at the relationships between managers and owners.
The second path concentrated on general agency problem that could occur between
employer and employees, buyers and suppliers. Academics in this field made general
assumptions and were looking for a generalised theory rather than a case study
specific approach (Eisenhardt, 1989).
Looking at the evolution of the agency theory it is possible to derive three main
types of the agency problems. The first type is the conflict between the agent
(manager) and the principal (owner), which arises due to information asymmetry. The
potential setbacks that may emerge from this information asymmetry are adverse
selection and moral hazards (Arnold and Lange 2004). The first problem is that owners
cannot conclude if managers have completed the work for which they are paid. The
second problem is that owners cannot check if the work produced by managers is
accomplished to their abilities. The second type is the conflict between the major and
minor shareholders (Shleifer & Vishny, 1997). The major shareholders or blockholders
will have the higher voting power and will swing the decisions in their own interest at
the cost of the minority (Fama & Jensen, 1983). This type of the agency problem exists
in the countries which have high ownership concentration. The third type of the agency
problem that is discussed in the literature is the the conflict between the owners and
creditors (Damodaran, 1997). The owners of the firm may invest in the project that
would be counted as a high risk project by the creditor who provide the funds. The risk
will raise the cost of the finance and depreciate the value of the debt. The successful
48
completion of the project may provide owners with the abnormal returns, however will
not reward the creditors with in the same proportion, because their return will be limited
by the fixed rate of interest. On the contrary, if the project will fail the creditors will bear
some of the losses.
The literature describes number of reasons that cause agency problems such
as: separation of ownership and control (Berle & Means, 1932); information
asymmetry (Jensen & Meckling, 1976); moral hazard (Hölmstrom, 1979), different risk
preferences (Arrow, 1971); and provide the remedies for these problems. To minimise
the agency problem, the scholars discussed several corporate governance
mechanisms to monitor agents and mitigate the principal-agent conflict. A large
number of academic articles explored the role and structure of the board and its
functions as a primary monitoring mechanism (Fama & Jensen, 1983; Baysinger &
Butler, 1985; Lorsch & MacIver, 1989; Baysinger & Hoskisson, 1990; Boyd 1994; Daily
& Dalton, 1994; Johnson Daily and Ellstrand, 1996). The literature suggests that the
outside directors in the board will help to align the interests of owners and managers.
Looking from the perspective that firm is the nexus of contracts (Jensen and
Meckling (1976) the optimal contracting between agents and principals should reduce
the problem of information asymmetry through compulsory information disclosure from
agents to principals (Healy and Palepu 2001) and motivate parties acting in self-
interest to maximise the value of the organisation through accounting remuneration
(Jensen and Murphy 1990). Therefore, contract is another monitoring mechanism,
which should protect shareholder interests and ensure that agents act in the best
interest of principals. The theory of incomplete contracts, however, points out to the
fact that all contracts cannot specify what is to be done in every possible contingency
and the contract will have to be renegotiated later which will have the cost. Thus, an
49
immediate consequence of the incomplete contracting approach is the so-called hold-
up problem (Schmitz 2001). When contracts are incomplete any contract negotiated
in advance must leave some option over the use of the assets. In this case the owner
of the firm is the party to whom the residual rights of control would be allocated and to
minimize the efficiency loss Grossman and Hart (1986) argues that this allocation
should be optimal.
Apart from the internal mechanisms the literature points out to the external
mechanisms of control that can assist in mitigating the conflict between the agent and
the principal. The examples of these mechanisms are efficient labour markets (Fama,
1980) and the market for corporate control (Jensen and Ruback 1983; Kini et. al.,
2004). The first mechanism linked with the idea that efficient managers often strive for
better business conditions and remuneration from the market. The market determines
this reward by the past performance. Therefore, managers need to prove their value
by maximising the value of the firm. The second mechanism relates to the hostile
takeovers that can occur as a result of the poor management of the firm. In this case
the acquirer may eradicate the underperforming management of the targeted firm after
acquisition and the distress of such events may stimulate the managers to perform
efficiently.
However each monitoring activity comes with agency cost, which is “…the sum
of monitoring expenditure by the principal to limit the aberrant activities of the agent,
the bonding expenditures of the agent, and the residual loss in welfare experienced
by the principal as a result of the divergence of interests between the principal and the
50
agent” (Jensen and Meckling, 1976).4 Therefore, it can be concluded that cost
efficiency is the main criterion for assessing the success under the agency theory.
However, even though agency theory is one of the most applicable theories
used to resolve corporate governance issues, it has its own limitations. First of all,
several empirical studies concluded there is a weak relationship between the incentive
payments to agents and firm performances (Jensen and Murphy, 1990; Tosi, Werner,
Katz and Gomez-Meija, 2000) Frydman and Jenter (2010), based on a review of US
executive compensation data covering the period 1936 to 2005, did not find any
evidence to support optimal contracting. Another limitation observed by Johanson and
Ostergen (2010) is that even though agency theory provides a valuable insight into
corporate governance, it applies primarily to countries in the Anglo-Saxon model.
Spanos (2005) also noticed that the agency problem depends on the ownership
characteristics of each country. In countries where ownership structures are
dispersed, if the investors disagree with the management or are disappointed with the
performance of the company, they use the exit options, which will be signalled through
a reduction in share prices. In contrast, countries with concentrated ownership
structures and large dominant shareholders, tend to control (or collude with) the
managers and expropriate minority shareholders in order to gain private control
benefits.
Furthermore, a number of authors have also suggested that agency model is
too simplistic and extended the original theory in the direction of the behavioural school
of though. Pratt and Zeckhauser (1985) suggested that it is important to look at the
agent’s human capital as a function of work motivation, rather than just trying to align
4 Some examples of agency costs are: the costs of recruitment, creation of additional management layers, moral
hazard, stealing, and adverse selection. (Shapiro 2005).
51
agent-principal interests. Wiseman and Gomez-Mejia (1998) expanded the
boundaries of the risk assumption and emphasised that agents can be loss averse.
That means that they will “…prefer to avoid losses altogether over options that limit
the size of the loss”, therefore assuming that agents are unwilling to take more risk on
some occasions. Another issue raised by behavioural theorists was that monetary
compensation is not the only factor that motivates agents to perform at their full
potential (Shafir, Diamond & Tversky, 1997); it also depends on the intangible factors
of compensation. Fehr and Schmidt (1999) call this phenomenon “inequity aversion”.
In such models, the agent’s equity benchmark is subjectively determined according to
market norms and personal referents. One more change to the original agency model
is managers’ time preference. Agents discount future compensation according to a
hyperbolic discount factor so that the implied discount rate varies over time and is not
constant (Frederick, Loewenstein & O'Donoghue, 2002; Graves & Ringuest, 2012).
Pepper and Gore (2012) merged those extensions together and were able to derive a
theoretical framework of behavioural agency theory, which focused on agents’
behaviour and factors that influence agents’ interests.
52
Stewardship Theory
Donaldson & Davis (1991) suggest an alternative theory to agency model in
which managers are perceived as stewards who will act in the best interest of the
owners from inception (Fig.1.8).
Such behaviour eliminates the principal agent problem and reduces agency
costs to its minimum, for example unifying the role of CEO and the chairman of the
board of directors. Davis, Schoorman and Donaldson (1997) claim that agents are
rational and that pro-organisational behaviour will maximise their utility function,
therefore agents receive maximum utility when owners’ wealth is maximised.
According to this theory, there are situational factors (such as collectivistic culture,
involvement-oriented management system) and psychological factors (value
commitment orientation, use of personal power) that influence individuals to become
either agents or stewards (Davis, Schoorman and Donaldson, 1997). Pastoriza and
Adopted from: Pepper A. and Gore J. (2012)
Figure 1-8: Stewardship theory by Donaldson & Davis (1991)
53
Ariño, (2008) claim that the most important is a direct relationship with the principal.
Thus, a decision on whether to become an agent or a steward (for both principal and
manager) can be represented as an assurance game (Davis, Schoorman and
Donaldson, 1997), the result of which can be maximised if the party will select similar
behaviour options. Pastoriza and Ariño, (2008) suggesting that stewardship theory and
agency model should be seen as complementary frameworks to increase the
explanatory power of both models (figure. 1.9).
Figure 1-9: Principal-Manager choice model
Principal Choice
Agent Steward
Manager’s Choice
Agent Minimize Potential cost Mutual Agency Relationship
Agent acts Opportunistically Principal is Angry / betrayed
Steward
Principal acts opportunistically Manager is frustrated/ betrayed
Maximize potential performance Mutual stewardship relationship
Adopted from: Davis, Schoorman and Donaldson (1997)
Based on the empirical evidence from the academic literature, stewardship
theory studies concentrate on the board composition of family owned firms (Chrisman
et.al., 2007; Eddleston & Kellermann, 2007), and non-for profit organisations (Van
Slyke, 2007; Donaldson & Davis, 1991; Muth & Donaldson, 1998; Corbetta & Salvato,
2004). In these firms managers naturally motivated to work for owners or for
organizations to accomplish the tasks and responsibilities with which they have been
trusted.
54
Stakeholder Theory
While the two theories previously discussed concentrated only on the
relationship between the principal and the agent, the stakeholder theory suggests that
the firm has responsibilities to a larger group of stakeholders. Developed by Freeman
(1984), this model suggests that modern companies exist within the society and
therefore should have corporate social responsibilities, consequently shifting the
traditional approach from shareholder’s wealth maximising firm towards perusing the
multiple objectives of different stakeholders (Ayuso & Argandoña, 2007). Stakeholders
are defined as “Any group or individual who can affect or is affected by the
achievement of the organization’s objectives” (Abdullah & Valentine, 2009). As the
model takes into account the interests of different stakeholders, Freeman and Evan
(1990) suggest this should be reflected in the board of directors. In other words, boards
should include representatives of different stakeholders who have a corporate interest
in the firm. Those stakeholders should make decisions in the interest of all stakeholder
groups and no set of interests is assumed to dominate (Donaldson & Preston 1995).
However, different stakeholders can pursue different interests, thus it is argued
in the academic literature that it is important to differentiate stakeholder types.
Rodriguez et al., (2002) proposed three classification categories: consubstantial
(Shareholders/Investors, Employees, and Strategic partners), contractual (sub-
contractors, suppliers, financial institutions, customers) and contextual (local
communities, public administrations, societies, and knowledge and opinion makers).
According to the authors, all three groups are contributing towards firm value creation
and defending their interests will lead to a sustainable and dynamic firm development
process.
55
Jensen (2001) critiques the “Stakeholder theory” for assuming a single-valued
objective. He believes the inherent conflict between the doctrine of shareholder value
maximisation and the objectives of stakeholder theory can be resolved by mixing
together “enlightened” versions of these two philosophies. Jensen defines the
“enlightened” stakeholder theory simply as stakeholder theory with the specification
that maximising the firm’s total long-term market value is the right objective function.
However, in the short-term other key issues such as flow of information from senior
management to lower ranks, interpersonal relations, working environment, etc., are all
critical issues that should be considered.
The empirical evidence of the stakeholder model focused on the relationship
between stakeholder management and firm’s performance. Most of the empirical
papers on that topic, were able to establish the positive relationship (Waddock &
Graves, 1997; Ogden & Watson, 1999; Ruf, Muralidhar, Brown, Janney, & Paul,
2001; Moore, 2001; Hillman & Keim, 2001; Godfrey, 2005; Berrone, Surroca, &
Tribo, 2007). To measure the stakeholder management system the literature proposed
Company index, which includes (a) community relations, (b) workplace diversity, (c)
labor relations, (d) environmental impact, and (e) product safety (e.g., Berman et al.,
1999; Hillman & Keim, 2001; Waddock & Graves, 1997). However, the main criticism
of such approach was related to the assumption that all five indicators are equally valid
parameters of stakeholder management.
56
Resource Dependency Theory (RDT)
Resource dependency theory is based on a cyclical process through which all
companies should pass. In order to stay in the market and produce goods or services
all companies require resources. Those are obtained from other companies who
possess the required resources, thus leading to interdependence. In turn,
interdependence will lead to uncertainty and, in order to decrease this, companies will
try to establish environmental linkages between firms and pool resources together. In
this perspective, directors serve to connect the firm with the resources needed to
survive (Pfeffer, 1978). Therefore, in the context of resource dependency theory, the
board of directors is seen as a crucial mechanism, which provides access to resources
needed and reduces uncertainty.
Directors can be classified into four categories, insiders, business experts,
support specialists and community influential actors (Abdullah & Valentine, 2009).
First, the insiders are current and former executives of the firm and they provide
expertise in specific areas of the firm itself, such as finance and law, as well as general
strategy and direction. Second, the business experts are current, former senior
executives and directors of other large for-profit firms and they provide expertise on
business strategy, decision-making and problem solving. Third, the support specialists
are the lawyers, bankers, insurance company representatives and public relations
experts and these specialists provide support in their individual specialised field.
Finally, the community influential actors are the political leaders and leaders of social
or community organisations. All four types of directors may bring resources such as
information, skills, key constituents (suppliers, buyers, public policy decision makers,
social groups) and legitimacy that will reduce uncertainty (Gales & Kesner, 1994). For
example, outside directors who are partners in a law firm can provide legal advice,
57
either in board meetings or in private communications with the firm executives that
may otherwise be more costly for the firm to secure. Hence, such environmental
linkages or network governance could reduce transaction costs associated with
environmental interdependency (Williamson 1985).
Empirical research focuses primarily on the board composition and size. For
example, Pfeffer (1972) finds the correlation between the board size and firm’s
environmental needs. He determines “that board size and composition are not random
or independent factors, but are, rather, rational organizational responses to the
conditions of the external environment” (Pfeffer, 1972). Pearce and Zahra (1992)
discovered that board size are positively associated with future performance of the
firm. Kaplan and Minton (1994) found an empirical relationship between corporate,
financial directors and the stock performance of a company. Finally, Daily (1995)
identified that the proportion of outside directors was positively associated with
successful bankruptcy reorganisation.
A good deal of research also establishes the need to change board composition
as the environment of the firm changes (Boeker & Goodstein, 1991; Lang & Lockhart,
1990). For example, Peng (2004) explore the relationship between the resource-rich
and resource-poor outside directors. In the context of China’s changing institutional
environment, he determined that the positive relationship between the number of
resource-rich outside directors and firm’s performance. Peng (2004) suggests that if
the board composition is not changed to meet new environmental demands,
performance suffers.
Another stream of resource dependency theory research aligns the board
composition with the stages of a firm’s life cycle in which director resources are most
valuable. This idea was originally proposed by Zahra and Pearce (1989). Authors
58
argue that firm life cycle stage may influence the importance of the resource
dependence role of boards. Contributing to this literature Lynall, Golden, and Hillman
(2003) and Gabrielsson (2007) propose that this is more applicable to the early stages
of the company’s life cycle. The study by Daily and Dalton (1993) support this
empirically, finding a significant relationship between several board characteristics (for
example: board size and composition) and performance in small and medium
corporations.
Corporate governance lifecycle perspective
Building on the work of Zahra and Pearce (1989), Filatotchev et. al. (2006)
proposed the idea that corporate governance parameters may be linked to strategic
thresholds in the firm's life‐cycle, dividing the life cycle of the firm into 4 stages:
founder/IPO threshold; IPO/maturity threshold; maturity and decline, “re-invention”.
At the founder/IPO threshold stage the most important role of the corporate
governance mechanism (board of directors) would be to bring together the resources
and knowledge. In the early stages of firm’s development this will help to increase the
strategic flexibility and ensure the long term survival of the company. Certo et al.
(2001) points out to the fact that newly established firms with rapid expansion do not
suffer from the agency problem at this stage and therefore do not require large
independent boards. The author claims that this type of the mechanisms is more
relevant to the later stage of firm’s life cycle (mature firms). Finkle (1998) also
contributes to that fact pointing out that at this stage it is more important to look at the
knowledge and experience of the board member who can contribute to the firm's
competitive advantage
59
When the firm moves towards the maturity stage, as suggested by the agency
theory (Fama and Jensen, 1983), the firm may experience the separation of ownership
and control. Changes in firm’s ownership structure will change the corporate
governance mechanisms towards the monitoring and control functions. At this stage,
the value‐protecting role of corporate governance mechanisms becomes
predominantly important, while the resource role of corporate governance
mechanisms depreciate
The role of monitoring corporate governance mechanisms becomes more
important when the firm is entering the maturity stage. According to the free cash flow
(FCF) hypothesis (Jensen 1993) agency problem increase as the organisation
matures and start to generate significant rents, which in turn will result in the
managerial opportunisms and encourage self‐serving managerial behaviour (Gibbs,
1993). Furthermore, greater free cash flow diminishes the significance of the resource
and strategy roles of corporate governance mechanisms.
In the 4th stage of firm’s life cycle, when the declining firm is attempting to
reinvent itself and overcome the effects of decline, the firm may once again require
strong strategic management decisions and the linkage to the external resources. In
this case the firm can once again restructure its corporate board which can create new
value creation opportunities. This shift is appropriate, as the FCF literature points out
to the fact that the agency problem diminishes when the company is going through
decline stage.
It can be concluded that following this framework the top management team
and outside investors have to find the right balance between the corporate governance
mechanisms at each stage of firm’s life cycle. If the balance can be reached and
60
maintained the firm would benefit from the competitive advantages, which in turn will
assist firm’s development into the next stages (Filatotchev et. al. (2006)
Some empirical evidence support corporate governance life cycle perspective,
concluding that mature firms tend to practice better overall corporate governance and
firms tend to be most transparent and accountable when they are young
(O'Connor and Byrne, 2015). The evidence from the emerging markets, however,
suggest that the corporate governance mechanisms of the firms, primarily link with the
strategic decisions (such as listing on the exchange) rather than the corporate life-
cycle. Esqueda and O’Connor (2020) suggest that the improvements in corporate
governance mechanisms depend on closeness of the firm to stricter regulations rather
than the life cycle of the firm.
Institutional Theory
Institutional theory highlights that rules and norms form an important element
of national institutional systems (La Porta et al., 2000). This was extended further by
institutional theory scholars who studied how the law on corporate governance is
shaping the corporate governance practices of the firms. In particular, how the firm’s
corporate governance standards vary in relation to the country’s regulatory framework.
At the same time the literature looked into the influence of the voluntary codes such
as the UK corporate governance code, OCED principal of corporate conduct. (Aguilera
& Cuervo-Cazura, 2004; Brammer, Jackson, & Matten, 2012). The authors were able
to identify the profound differences across countries that remain in the rights and
responsibilities of the principals. For example, Japanese company law provide a wider
decision-making power to the shareholders of the Japanese firms in comparison to the
US corporate law (Shishido, 2007).
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The main focus of the institutional theory discussion, however, is how the
institutional framework can eliminate the agency problem that can arise between the
major shareholder and the minority group in the firms with concentrated ownership
structure (Fama & Jensen, 1983). Scholars highlighted the effectiveness of using
courts as an enforcement mechanism in corporate governance. However, the
effectiveness of this mechanism depends on the extent to which the legal system in a
particular country is prepared to consider cases of failed business decisions,
misguided strategy, and other managerial mistakes (Nakajima, 1996, Ramseyer &
Nakazato, 1999, on Japan; Baums, 1993, on Germany; Law Commission 1999 and
Nakajima, 1999, on English and other common law jurisdictions in Southern and East
Asia; and Palmiter, 2006, on the US).
The empirical evidence primarily focused on the family owned firms (with high
ownership concentration) from the emerging and less developed economies
(Claessens, Djankov, & Lang, 2000) and provided the mixed evidence on the
effectiveness of the concentrated ownership. Some studies pointed out to the fact that
family owners may have superior monitoring abilities compared to diffused
shareholders (Bruton et al., 2003; Anderson & Reeb, 2004). While other scholars
emphasise that family ownership creates a principal-principal conflict creating a
negative effect no firm’s performance (Young et al., 2008; Jiang & Peng, 2011). In this
case, the institutional theory resolves these contradictory arguments by suggesting
that the presence of absence of various types of national institutions and their
enforcement will shape the corporate governance of the firm, regardless of ownership
concentration (Zhou and Peng,2010; Filatotchev et al., 2011)
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Discussion of Theories.
Based on the literature review, it is apparent the internationalisation process
has been studied by scholars from different perspectives (Economical, Behavioural,
and Entrepreneurial, Organisational etc.) Some concentrated primarily on the large
companies (Uppsala and TCT) while others determined the internationalisation
process of the small and medium enterprises (Innovation models, INVs, Network
Approach). However, each model has a good explanatory power only within the
assumptions of that model; therefore, each theory only suits certain firm typologies
that follow particular internationalisation process (Uppsala stage model vis-à-vis INV).
It can also be concluded that the research on internationalisation process has
some room for improvement. First of all, all the theories distinguish some stages /
gradation of the internationalisation process. Generally, it can be represented on a
continuum with the firm that has a low level of international activity on one side and
the large global firms on the other. However, all models (apart from INV) were criticised
by scholars for the lack of explanation on how a domestic firm can begin its
internationalisation process. For example, the Upssala model suggests that, at stage
one, the firm does not have any international activity and, at the second stage, it starts
exporting through independent representation. Nonetheless, the theoretical link on
how the firm can find such independent representative is missing.
Another area, which was criticised a lot within all models, is that there is no time
frame for the internationalisation process. For example, when internationalisation
starts there is a certain time period during which the company will shift from one stage
of internationalisation (within one model) into another. Taking into account the
exponential growth of technological progress it seems reasonable to include the speed
of the internationalisation process into the models of internationalisation.
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Academic literature on corporate governance primarily focuses on the agency
theory as the main explanatory model of principal-agent conflict. Based on the
available theories they can be generally divided into two types. First are those where
the conflicts arise within the firm (Agency, Stewardship, and Stakeholder) and the
second type is where the conflict is between society and the company (Social contract,
legitimacy theory). The exception is Resource dependency theory that is looking at the
role of the board from the economic perspective.
All theories of corporate governance that were covered in the literature review
claim that the dominant mechanism of corporate governance is the board of directors.
However, the theoretical reasoning of the role and structure of the board difference
across the models. For example, the main role of the board of directors in the agency
theory is to monitor agents; nonetheless, the resource dependency model suggests
the role of directors is to link resources between companies.
As we concluded, most models concentrate their attention on the board of
directors as the main mechanism of corporate governance. However, it is not the only
one that could potentially reduce the problem between principal and agent. Empirical
literature also was able to determine that transparency and disclosure of information
and minority shareholder protection are vital mechanisms for corporate governance.
Therefore, there is a potential theoretical improvement of the models if they would
include more major mechanisms of corporate governance.
As can be seen from section above the process of internationalisation of any
firm will lead to the growth of the company in terms of total revenue, value of total
assets, number of employees, geographical presence etc. When the firm expands
outside its country of origin it will lead to higher complexity and increased information
asymmetry (Sanders G., and Carpenter, 1998; Michael and Pearce 2004; Lee et.al.
64
2008), making it more difficult and costly to monitor top management teams (TMT)
performance (Zajac and Westphal, 1994), leading to a typical agency problem.
Therefore, the company would require some corporate governance mechanisms in
order to reduce that information asymmetry. At the same time, it is plausible that before
entering international market (starting internationalisation process), the firm can hire
an independent foreign director onto the board in order to use his knowledge, network
connections and skills to enter the new foreign market. Thus, the corporate
governance mechanism such as board of directors can help to start the
internationalisation process. Therefore, it is possible to conclude that the correlation
between corporate governance and internationalisation should exist. The following
section of the literature review will examine the empirical evidence of such correlation
from different perspectives.
65
Relationship between corporate governance and internationalisation
Board of Directors and firm’s internationalisation
As seen in the previous section it is possible to conclude that the board of
directors is a primarily used monitoring mechanism to decrease agency costs and
uncertainty. Based on this, there should be a correlation between firm Board of
Directors and the level of internationalisation (Luo 2005).
Most empirical studies have focused on the effect that board of directors
structure and composition (independent variable) will have on the internationalisation
(dependent variable). Oxelheim et al. (2013) studied the role of international directors
on the board for 346 non-financial Nordic firms, concluding a positive effect in the
increase of international directors on the board and the percentage of international
activity, measured as foreign sales ratio. Another study by Rivas (2012), concentrated
on the tenure, background and age diversity of the board members. Based on a
sample of 108 USA and European firms, he determined a positive relationship of board
members’ tenure and background diversity with the level of internationalisation.
Contrary to his original hypothesis, age variable was negatively correlated to
internationalisation, suggesting that younger board age has a positive relationship with
internationalisation.
Conversely, several papers looked into the reverse relationship between
internationalisation (as in independent variable) and the board of directors structure
(as a dependent variable), however obtained some conflicting results. Based on the
sample of 258 US companies, Sanders and Carpenter (1998) were able to determine
a positive relationship between the level of internationalisation and board size. The
authors were able to confirm a negative link between board duality and level of firm’s
internationalisation. On the other hand, Markarian and Parbonetti (2007) looked at a
66
random sample of 150 companies from 6 industries (utilities, banks, drugs, software,
computers, and hi-tech equipment manufacturers) and found a negative relationship
of firm’s internal and external complexity to the composition of the board5. Internal
complexity was represented by the amount of R&D expenditure and invested capital,
while external expenditure was characterised by the geographical diversity of the
business and a ratio of foreign sales to total sales. Results show that firms with high
level of external complexity substitute outside directors (like retired politicians, or
affiliated to the armed forces, of those who belong to the local community,) for insiders
(those who currently or previously worked in the company).
A much smaller number of studies, concentrated on the developing countries.
Chen (2014) based his research on 150 listed Taiwanese electronic firms, looked at
the human capital factors of international directors of the board (independent variable)
and determined a positive relationship between director’s international
experiences/educational level and the level of firm internationalisation. Lu, Xu, and Liu
(2009) studied a link between the number of outside directors (independent variable)
and the level of export of Chinese listed firms for the period 2002-2005. Using panel
data, which consisted of 2,637 firm-year observations, they determined a positive
relationship between the number of outside directors and a decision to become an
export company. Alpay et al. (2005) compared the board structure (independent
variable) and performance of multinational subsidiaries from USA and Europe to the
board of directors of local Turkish firms. The findings supported their original
hypothesis: the BoD of multinational subsidiary firms in Turkey monitor managers’
5 Board composition was classified into four categories: business experts, support specialists, community
influentials, and insiders. The ratio of each category to the total number of directors on the board was taken as a
dependent variable.
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performance more accurately, have larger board sizes and a higher percentage of
outside directors in comparison with home companies.
Transparency and Disclosure (T&D) and firm internationalisation
Even though the majority of studies concentrated their attention on the board of
directors as a corporate governance control mechanism to diminish agency problem,
there are other potential setbacks that may emerge from the information asymmetry
of MNEs such as adverse selection and moral hazard (Arnold & Lange 2004). The first
problem is that owners cannot conclude if managers completed the work for which
they are paid. The second problem is that owners cannot check if the work produced
by managers is accomplished to their abilities. According to academic literature, the
solution to these drawbacks is optimal contracting between agents and principals
(Healy and Palepu 2001). Such contracts make it compulsory for the managers to
disclosure information, which is required by owners and investors, based on which
they are able to control and monitor top management teams as well as to assess
manager’s performance (Bushman and Smith 2001). Based on financial and non-
financial information, owners stimulate manager’s incentive to maximise shareholder
value through managerial compensation plans (Jensen & Murphy 1990).
Research in this area was trying to determine how this governance tool is
related to internationalisation. Sanders and Carpenter (1998) were able to determine
a positive relationship between the level of internationalisation (independent variable)
and CEO compensation in the listed US companies. Oxelheim and Randøy (2004),
based on the sample of listed Norwegian and Sweden firms, also identified a positive
relationship between all the elements of internationalisation (international-listing,
foreign sales and export) as an independent variable and CEO compensation (as a
dependent). However, the CEO compensation plan is just one of many control
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mechanisms, which uses accounting information. Bushman and Smith (2001)
gathered information from different sources and looked at the accounting information
from the different angles. The “Examples include takeovers (Palepu, 1986), proxy
contests (DeAngelo, 1988), boards of directors (Dechow et al., 1996; Beasley, 1996),
shareholder litigation (Kellogg, 1984; Francis et al., 1994; Skinner, 1994), debt
contracts (Smith and Warner, 1979; Leftwich, 1981; Press and Weintrop, 1990;
Sweeney, 1994), and the audit function (Feltham et al., 1991; DeFond and
Subramanyam, 1998).”6
However, it is not just the amount of disclosed information that matters; it is also
the format and type of accounting information in which it is released (Hirshleifer and
Hong 2003). Two most common formats for international use are the American GAAP
(acronym defined as Generally Accepted Accounting Principles) and the International
Financial Reporting Standards (IFRS). A large number of papers compared the pros
and cons of both standards, however, the results of these studies are mixed. While
some scholars were able to represent a comparative advantage of a certain format
(Harris & Muller 1999; Daske & Gebhardt 2006), others did not find any difference in
the outcome of represented data (Leuz 2003). However, one of the things that
academic literature agrees on is that by presenting the very same financial and
accounting data in different formats (for example Local GAAP and IFRS), multinational
companies increase their disclosure and transparency in comparison to local firms,
thus decreasing information asymmetry. There are several examples to support this
statement. A study by Ding, Jeanjean and Stolowy (2008), based on the cross-
sectional data of 199 French listed firms in the year 2001, supported this argument
6 * These authors are included in the reference section of this study
69
and determined the impact of internationalisation (independent variable) on the
presentation format of the financial information (dependent variable). Companies with
higher levels of internationalisation produced financial reports using both the home
(French) template and IFRS/GAAP format. Khanna, Palepu and Srinivasan (2003)
demonstrated a positive relationship between the level of companies’ Transparency
and Disclosure (independent variable) rating (produced by S&P) and their interaction
with US labour/product/capital markets (dependent variable) by looking at a sample of
794 firms from developed and developing countries. Chiang and Ko (2009) took a
sample of Taiwanese firms between the years 2000-2004, to analyse the relationship
between the internationalisation and the level of R&D. Looking from the agency theory
perspective, they were able to confirm that increasing information transparency
(independent variable) will reduce equity agency cost. Lee et al. (2008), based on a
sample of 9,500 firms, both internationalised and domestic, were able to conclude that
international firms will also present their reports quicker than domestic firms.
Shareholder rights and firm’s internationalisation
Another Important component of corporate governance is shareholder rights.
In particular, potential investors are interested in how they will be protected if they will
acquire stock in the company. If, at the firm level, strong minority shareholder
protection rules and regulations exist, then the investor will prefer to buy shares of that
company, therefore increasing the dispersion of the ownership inside the firm.
According to La Porta et al. (1998), there exist a negative relationship between the
level of shareholder protection and ownership concentration. A country with a stronger
legal system will be more attractive to small and medium investors, thus making firms’
ownership more dispersed. Dispersed ownership might enlarge the gap between
owners and managers or, in other words, the interest of minority shareholders will
70
result in being different to other larger owners, causing an increase in agency costs.
On the other hand, concentrated ownership will work as a control mechanism. Large
shareholders (e.g. financial institutions) will have power to control and monitor
managers better, thus to maximise shareholder value; however, concentrated
ownership will also create a free rider problem (Grossman and Hart 1980). Looking
from the angle of minority shareholders, they will try to bring more outside directors to
the board in order to support their own interests. (Kim et.al. 2007) That discussion
explains why most of the research in this area is dedicated either to the relationship
between shareholder rights and Board Composition (Klapper and Love 2004;
Krishnamurti et.al. 2006; Kim et.al. 2007; Doidge et.al. 2007) or to ownership
concentration (La Porta et.al.1998; Claessens et. al. 2002).
The research output on the relationship between internationalisation and
shareholders’ rights is very scarce. Jiraporn et al. (2006), using the same methodology
as Gompers et al. (2003), constructed a corporate governance index, which measures
the level of shareholders’ rights. Applying a logistic regression model on the sample
of 1862 firm-year observations (between years 1993–1998) they determined a positive
relationship between the level of shareholders’ rights (independent variable) and
diversification (global and industrial) of the company (dependent variable). Other
studies looked at the corporate governance ratings, which combined shareholders’
rights sub index with board of directors and disclosure characteristics. Even though a
positive relationship between the level of internationalisation and corporate
governance was determined, the drawbacks of those studies is that it is hard to tell
how significant the shareholders rights sub index was on its own (Filatotchev et.al.
2001, Sturgess 2011; Carvalhal 2014)
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Corporate Governance & Internationalisation in Russia
After reviewing the literature that is available on the topic of corporate
governance and firms’ internationalisation, it is also important to review the evolution
of corporate governance system in Russia. In comparison to developed economies,
the notion of corporate governance has only appeared recently in the Russian
Federation. The main cause is that during the communism era companies were state-
owned, which limited the agency problem that was driven by the separation between
the ownership and control. A turning point in the modern Russian history is the collapse
of the Soviet Union, where government owned a vast majority of companies. In early
90s, Russia initiated mass privatisation through voucher schemes (Filatotchev et al.
1995). At the same time, privatisation occurred in Central and Eastern Europe (CEE)
and other Commonwealth Independent states (CIS), although its effects varied across
regions (Estrin et al. 2009). Three waves of redistribution of property, privatisation,
expropriation of minority shareholders and hostile bankruptcies in Russia (Sprenger
2002) partially reduced the presence of state-owned companies. However, it created
concentrated ownership of unskilled and unaccountable management and general
lack of competence (Boycko et al. 1997). At the same time, widespread scandals
involving pyramid schemes in 1994-1995, and people’s losses at banks stemming
from the crisis of August 1998, were exacerbated by the Russian weak legal system.
During these riotous years, Russia started to improve its legal environment and
introduced Company Law, Security Market Law and Investor Protection Law
(Sprenger 2002), which shaped corporate governance in Russia7. The Company Law
(1996) has been mainly concentrated on the composition of the BoD. It allowed firms
7 A full list of Laws, which were introduce up to the corporate governance code in 2002 presented in Puffer S.,M.,
and McCarthy D.,J (2003) “The emergence of corporate governance in Russia”, Journal of World Business, Vol
38, pp284–298
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to set up a 2-tier board system, similar to the German Model of corporate governance,
however an implementation of 2-tier board was still optional8.
The security market Law (EBRD 1996) and Investor Protection Law (1999)
concentrated on improving shareholders’ rights, particularly voting rules, and
introduced stricter rules on the amount of disclosed information presented to
shareholders. At the same time, an accounting reform started in 1998, the main aim
of which was to move from the Russian GAAP format to IFRS9. Despite the
introduction of these legislations their efficiency in improving corporate governance
was extremely low, due to the incompetence of the enforcement mechanisms
(Sprenger 2002) and the level of corruption in the regulatory bodies, leaving Russian
companies with high ownership concentration and weak protection of minority
shareholders’ property rights (Lazareva et.al. 2007)
An important point in the development of Russian corporate governance was
an introduction of the CG code in 2002. This was a non-compulsory set of guidelines
for companies, which were based on the standards established by the OECD
(McCarthy and Puffer 2002). Practices from developed countries also had a large
influence on Russian code of CG. For example, the first two Russian companies that
were listed on NYSE were VimpelCom (Telecommunication firm) and Yukos Oil
(Energy Firm). Since the NYSE had a tough rule on Transparency and Disclosure and
8 The comparison between the two-tier board and one-tier board system is widely discussed in the literature (Tüngler, Grit T, 2000; Pillay 2013; Millet-Reyes et al., 2010; Van Camp et al. 2020. The “Anglo-American” model of a one-tier board structure is largely a reflection of the neoliberal norms of shareholder primacy and free-market capitalism. The German two-tier model is in many ways a reflection of stakeholder primacy, codetermination, and managerialism. In the two-tier board structure, a separate board of directors supervise the executive team and provides a recommendation to the executive team. In the one-tier board structure, the executive and non-executive or supervisors are all members of the same board, i.e. they collectively form one company body. The core differences between the boards lie in the segregation of roles, speed of the decision making process, role of the chairman and CEO. 9 White paper on corporate governance in Russia, available online at: http://www.oecd.org/corporate/ca/corporategovernanceprinciples/2789982.pdf
73
minority shareholders’ rights, VimpelCom and Yukos were obliged to comply. That
factor significantly influenced their corporate governance and provided an example for
other large Russian companies, which started to adopt American GAAP voluntarily.
Similarly, Mobile Telesystem (MTS) firstly joined NYSE and London Exchange and
was only then listed on the Moscow Stock Exchange (Judge and Naumova 2004). As
mentioned earlier the 2-tier boar system, which was adopted in Russia, takes its
origins from Germany. McCarthy and Puffer (2002) also draw a parallel with French
law, which obliges companies to announce the remuneration of Top Management
Teams (TMTs), including the parent company and its subsidiaries. However, many
Russians companies still prefer not to provide this information in their reports.
During the early privatisation period in the 90s, the federal government has
locked in substantial shares in certain industries, such as gas, electric energy, oil, and
telecommunications. As a next step, these shares were transferred to specially
created state-controlled holdings (Chernykh 2008). The examples of such firms are
Gazprom and Rosneft (energy Sector), Sberbank (Banking Sector), Aeroflot
(Transportation). In some occasions, to control the strategically important firms, the
state issued a golden share, which grant large control rights, including veto power on
certain important issues, without any cash flow rights (Frye & Iwasaki, 2011). At the
same time, due to the pyramidal structure of ownership, a vast number of companies
are also controlled by the government (Lazareva et.al. 2007, Okhmatovskiy et. al.,
2018).
Looking into the state-owned enterprises in Russia it is also important to look
at the means of control that the Russian state has beyond the ownership (Grosman et
al., 2016). One of the technics of the Russian state to maintain the control over the
firm without direct ownership is the appointment of Russian state active officials as top
74
executives of companies. At the same time there are cases when the government
appoints former government officials as top executive which may also be counted
towards the government control, however there are no systematic studies to show how
such appointment influence the strategic decision of the firm. Another instrument that
is used by the state to maintain the control of the firm is though the provision of
government resources (subsidy, grants, refinancing) in the critical conditions. This
provided state agencies with significant leverage over private companies. Also, the
weak regulatory framework can be seen as one of this instruments, because in
practice this allows the state to create favourable conditions by changing and adjusting
regulatory framework.
Another large group of owners which emerged during the privatisation stage is
the so-called group of “Russian oligarchs” who control around 40% of Russian industry
(Guriev and Rachinsky 2004; Okhmatovskiy 2010; Okhmatovskiy and David, 2012).
Melkumov (2009) Also points out to the relationships between the state and some
oligarchs. The unofficial approval from the state allowed these large tycoons to grow
and benefit from these relationships and in return they were inclined to cooperate with
the state (Adachi, 2013). These oligarchic–state network structures filled the
institutional vacuum left by the collapsed communist economy, ensuring access to the
requisite resources for investments and improving assets’ productivity (Grosman &
Leiponen, 2018).
In summary, the Russian corporate governance model has a high ownership
concentration mostly in the hands of large stakeholders (state or oligarchs) and a weak
legal system to protect minority shareholders, which leads to high private benefit of
control, poor accounting practices with a lack of disclosed accounting information and
no strict compulsory Laws for firms’ corporate governance structure.
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Research suggests that limited number of articles were dedicated to this subject
in previous years. The first papers, presented in the late 1990s, described a general
situation on privatisation and ownership structure, trying to predict the future trajectory
of the corporate governance regime and comparing it with other post-soviet countries
(Filatotchev, Wright and Buck 1995; Goldman 1997; Earle 1998). Based on these
papers, a number of scholars tried to determine the impact of privatisation (ownership
structure) on firms’ performance and analyse how corporate governance influence
firms’ value.
A research on firms’ performance and corporate governance in Russia was
started by Black (2001). From a sample of 21 companies, he determined a positive
relationship between two variables: value ratio (as dependant variable) and
governance ranking provided by an Investment Bank (as independent Variable). Later
Black, Love, Rachinsky (2006) contributed to Black's paper by producing a time-series
study in which they increased the sample size to 80 companies and corporate
governance indexes to six categories, all of which were produced by different rating
agencies and different companies. Kuznecov and Pal (2011) continued this research
and concentrated on the Transparency and Disclosure index (as an independent
variable) produced by Standard and Poor’s (S&P) and used Tobin’s Q as a
performance variable (dependent variable). The most recent research on the structure
of corporate governance board and its effects on firm performance was produced by
Muravyev (2017). This research concentrated on the board of directors of Russian
publicly traded companies and indicated that several characteristics of corporate
boards, such as the proportion of foreign directors and directors’ appointments in other
firms, have a positive effect on company’s performance.
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Research, which focused on ownership concentration, was started by
Filatotchev et al. (2001). In their study, they determined a negative relationship
between large-block shareholders and a firm’s performance and investment. Guriev
and Rachinsky (2004) focused on a specific group of owners – oligarchs. Their main
hypothesis was to check if under the control of big tycoons’ firms would perform better.
However, they could not find any significant differences in regards to firms’
performance. Only employees’ wages in companies owned by oligarchs were higher
in comparison with other firms. Sprenger (2002) produced a survey study in which he
determined an increase in the number of outsiders’ shares between 1995 and 2000.
His survey also concentrated on the minority shareholders’ rights and legal system,
emphasising the importance of strong legal system for corporate governance and
highlighting the incompetence of law enforcement mechanisms. Kuznetsov et al.
(2012) also drew attention to the weak institutional environment and confirmed that
control structures with multiple large shareholders’ increase efficiency.
The research on the Internationalisation of Russian companies is also scarce.
Kalotay (2010) developed a general model for Russian level of internationalisation. He
took outward foreign direct investment (OFDI) as the internationalisation variable and
analysed its relationship with Russian GDP, Policy changes, geographical position,
culture and connection with CIS states etc. While this study concentrated on the macro
level, others have presented the results on the firm level. Podmetina (2011) based on
the sample of 150 R&D oriented Russian companies determined a positive
relationship between internationalisation (independent variable) and innovation
(dependent). Vaatanen et al. (2009) and Sherbakov (2012) were able to show a
positive relation between internationalisation (measured as a ratio of total sales to
foreign sale and total assets to foreign assets) to performance (Tobins’s Q). In
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contrast, the most recent empirical evidence from the Russian market (Grosman et
al., 2017) shows how the proper translation of the foreign practices of corporate
governance from the western countries might mitigate blockholder appropriation.
Most of the studies used a similar regression analysis and some were able to
determine a positive link between firms’ performance and good CG practices.
However, the common drawback of these studies lies in the sample size and variables
selection due to the limitation in the available data. This is why this literature review
leaves room for the urgent need for future research in this area.
Conclusion
Looking through the extensive literature available on the topics of
internationalisation and corporate governance it is clear that the literature on these
topics was primarily developing as the two separate streams of literature. Only some
academic scholars concentrated on the relationship between corporate governance
and internationalisation. In these academic articles the authors were primarily looking
into the fact that the strong corporate governance mechanisms will determine the
success of internationalisation process. The stream of the literature that concentrates
on the internationalities process of the firm focuses of the firm entry modes into the
foreign markets (Ripollés & Blesa 2017) operational strategies (Bell, Crick & Young
2004; Crick & Spence 2005; Martin & Javalgi 2016) and growth and performance
beyond the inception stage (Ghannda & Ljungquist 2005; Li et al., 2017). While the
corporate governance stream of the literature primarily looked into the structure of the
board of directors (Rivas 2012, Oxelheim et. al. 2013), the amount of transparency
and disclosure (Oxelheim and Randøy 2004), and the shareholder protection
78
mechanisms (Jiraporn et.al. 2006) that would assist with the successful
internationalisation process.
However, as mentioned earlier in this chapter, the internationalisation process
of international mew ventures may leapfrog the stages of traditional internationalist
approach and as result will fail to address in full spectrum the important strategic
decisions that SME firms are faced with in the process of rapid internationalisation.
Furthermore, if such firm is coming from the country of origin with weak regulatory
framework of corporate governance standards or low enforcement level of these
standards, this will influence the number of corporate governance mechanism that the
firm apply from the inception. However, the literature put aside the importance of
interaction between the rapid internationalisation and the corporate governance
standards of the firm from the weak corporate governance environment. The rapid
expansion could happen for the small and medium sized firms without the separation
of ownership and control, and will conceal the problem of unchanged corporate
structure that could play a vital role in the success of firms’ internationalisation. The
next chapter will focus on the example of the firm from the Russian market that
experienced such rapid internationalisation and will analyse what was the main
reasons that changed their development path from failure to success.
79
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Chapter 2 Kaspersky Lab case study
The theory of International New Ventures (INV) (McDougal & Oviatt 1994) has
received a lot of attention from international entrepreneurship scholars (Shrader et al.,
2000; McDougall et al., 2003; Zahra 2005; Coviello 2006). On the one hand, this has
been due to the international business fast changing environment. In other words, the
rapid diffusion of ICT reduced transactions and communication costs and has made it
easier for small start-up companies to identify business opportunities in foreign
markets (McDougal & Oviatt, 1994). Another contribution factor is the rise of
entrepreneurs with international experience, through which they are able to identify
and connect resources in different markets and establish competitive advantages
(McDougal & Oviatt, 1994). Consequently, if the entrepreneur is able to connect
resources from different markets, that has allowed INVs not to own their resources for
internationalisation (Zahra 2005). The original definition proposed by McDougal &
Oviatt (1994) is that an INV is “a business organization that, from inception, seeks to
derive significant competitive advantage from the use of resources and the sale of
output in multiple countries”
Within the intellectual framework developed by McDougal & Oviatt (1994), who
looked in details at the characteristics of INV, the main research focus was centred on
the analysis of the small and medium-sized enterprises (SMEs) in knowledge-
intensive sectors (Ojala 2009), in particular software development companies. These
are enterprises that did not require large capital from the inception and therefore had
a significant level of intangible assets in their balance sheet. A large number of other
academic papers have also been focused on examining the entry modes into foreign
markets (Ripollés & Blesa 2017), operational strategies (Bell, Crick & Young 2004;
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Crick & Spence 2005; Martin & Javalgi 2016), survival challenges (Coeurderoy et al.,
2012) and growth and performance beyond the inception stage (Ghannda & Ljungquist
2005; Li et al., 2017).
While the dominant part of the literature was looking at the success case studies,
the parallel channel of INV research focused on unsuccessful cases, where the
international expansion or further survival on the foreign markets was characterised
by INV failures, which can result from three main factors. These include managerial
incompetence, which has led to falling profits, liquidity difficulties and eventually to
bankruptcy (Hayward et al., 2006; Ooghe & De Prijcker, 2008), entrepreneurial
strategic failures (Van Gelder et al 2007) and external factors beyond the control of
the entrepreneur (Carter & Wilton 2006).
The recent paper by Nummela et al (2016) concentrated on these three main
causes of failure in INVs and presented a holistic framework for analysing failure in
future studies, while also identifying critical incidents as well as internal and external
factors that have caused the failure process. The authors’ findings summarises the
key elements of failure in rapid internationalisation, which consists of the antecedents
(managerial incompetence, strategic decisions, external triggers) process (partial or
complete withdrawal from international markets) and consequences of failure
(decreased profitability of business, restructuring of business, business closure).
Nonetheless, the model presented considers internationalisation a dynamic process,
and argues that the company that failed in its initial internationalisation may
successfully re-internationalise later, at the same confirming failure of
internationalisation can result from a single factor (e.g. management incompetence)
or the combination of antecedents (i.e.: management incompetence with incorrect
strategic decisions and external factors).
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However, the framework seems to put aside the link between the management
incompetence and strategic failures. In small and medium size firms, the owner and
manager is often the same person, which means a wrong strategic decision can be
made as a result of scarce management experience. In such owner-managed
enterprises, the decision maker underestimates the significance of a firm’s growth
during the process of internationalisation. On the one hand, when the firm expands
outside its country of origin it will lead to higher complexity and increase information
asymmetry (Sanders and Carpenter, 1998 Michael and Pearce 2004; Lee et.al. 2008),
making it more difficult and costly to monitor management performance (Zajac and
Westphal, 1994) and leading to a typical agency problem (Berle & Means 1932). On
the other hand, an unchanged corporate structure in the process of rapid
internationalisation could lead to overconfident decision making and a strategic failure
(Nummela et al., 2016). This signals the importance of the balanced corporate
structure for INVs, which should not be costly (i.e. creating a large board of directors
with international external members) for the owner, but at the same time would provide
some critical analysis of his strategic decisions and managerial practices. This chapter
will analyse the relevance of corporate governance structure for international new
ventures from emerging markets by presenting a case study of an IT software
development company (Kaspersky Lab) from the emerging market (Russia).
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Methodology
Case studies as instruments for developing and assessment of hypothesis have
provided significant insights into the management field (Penrose,1960; Chandler,
1962; Pettigrew, 1973; Burgelman, 1983; Eisenhardt, 1989; Yin, 1994; Eisenhardt and
Graebner, 2007; Siggelkow, 2007; Weick, 2007). In comparison to Eisenhardt 1991,
who puts a lot of emphasis on comparison of multiple cases, Dyer and Wilkins (1991)
emphasise that the essence of a case study analysis lies in the thorough evalusation
of one case in order to establish new relationships. This classical approach would be
applied in the qualitative analysis in this thesis. There are two primary reasons to use
such approach. First, management theory considers case study to be one of the most
valuable instrument to study the relationship between the key variables in the early
stages of the new theory. (Yin, 1994; Eisenhardt, 1989). Second, using this approach
require close interaction with the specialists in the field of management, which is
suitable for creating managerial relevant knowledge.
The main qualitative data source was provided from in-depth interviews with
the top management team in 2017. During this year two interview were conducted.
The average duration of the interviews was 1 hour and 20 minutes. The main objective
of the first interview was to collect the information on the internationalisation history
focusing on the sequence of events and dates, motivation for rapid internationalisation,
methods of internationalisation (i.e.: joint ventures, mergers and acquisitions, foreign
subsidiaries) and issues that the company faced during the internationalisation
process. The second interview focused on the corporate governance structure asking
the interviewee about the corporate governance mechanisms that were developed in
the history of the firm, in what year, what was the main reason for the implementation
of certain corporate governance mechanisms. Both interviews were unstructured
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allowing interviewees to provide detailed answers and evaluate their knowledge of the
topic.
The collected data will be analysed with the method of contextualized
explanation (Welch et al., 2011) which will examine the main reasons behind the
changes in the corporate governance structure of the firm, taking into the account
firm’s history, their operational environment, rapid internationalisation and the reasons
for aggressive international growth form the inception. In addition to the reasons given
by the top management team during the interviews, this chapter will analyse additional
external factors that influenced strategic decisions inside the firm.
For a more comprehensive qualitative analysis, the data was combined with
additional information from the media, corporate webpage, press releases, books and
academic articles related to Kaspersky Laboratory. The case study in this chapter will
focus on rapid internationalisation process and analyse in what way the adjustment of
corporate governance structure has allowed Kaspersky Lab to change its trajectory
from failure to success.
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Background
Kaspersky Lab (KL) is an IT-security firm that was established in 1997 by four
colleagues, Eugene Kaspersky, Natalia Kaspersky, Aleksey De-Monderik and Vadim
Bogdanov10 “with zero investment”11. It has grown from a small office to a large
international corporation with almost 3000 employees and 30 offices around the globe
Eugene Kaspersky graduated from Moscow’s institute of Cryptography,
Telecommunications and Computer Science and decided to start his career at the
military Scientific and Research Institute. However, as his defence sector job did not
provide him with sufficient income, parallel with job he began to search for side projects
and even tried being an IT sales representative for one of the co-operatives. However,
the experience was unsuccessful.
It was in 1989 that Eugene caught his first computer virus «Cascade», which
he was able to explore in details and create a piece of code that will combat the virus.
This incident gave birth to his new hobby. He started collecting viruses and, more
importantly, creating cures for them. This led to the creation of a reputation for
Kaspersky within the Information Technology (IT) sector and he was thus offered other
projects. One was from a software development company in Russia, which wanted to
include the anti-virus software inside their software package and asked Kaspersky to
do that. The task was successfully completed and the final result gave birth to the first
Ani-virus with Graphical User Interface (GUI), which had significant advantages in
comparison to the competitors. Another project was related to the installation of the
security packages on several computers, which were later sold to the end user. Both
the projects were well paid, and from these earning he was able to self-publish his
10 Source: Interview from http://www.forbes.ru/milliardery/257437-virus-kasperskogo-kak-biznes-kaspersky-lab-zakhvatil-200-stran-mira 11 Source: Kaspersky Lab, from Russia with Antivirus
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book. As Kaspersky mentioned in one of his interviews “…I did not earn much from
this book, however I still believe, that my decision was right. I invested in my name,
which eventually became a well-known brand”12
Eventually, the number projects increased and Eugene decided to move into
the corporate sector. He was employed by KAMI Information Technology Centre (a
Russian family owned IT firm specialising in IT security). At that time, KAMI was one
of the leaders in IT sector in Russia and anticipating computerisation of the post-Soviet
country and concentrated on providing IT security for both business and personal
users. This firm knew Kaspersky from his work at Scientific Research Institute and
decided to support his antivirus software project.
The work at KAMI provided the opportunity for Eugene to concentrate on the
creation of the product without any distractions. In 1994, the project, which was called
“AntiViral Toolkit Pro” (AVP), was almost finished. KAMI decided to send its software
for testing to Hamburg University and, after the testing, AVP was named number one,
as this software was able to detect and combat most viruses. This victory attracted
new international contracts from Italy and Switzerland where the software was
distributed by the local firms. One of the largest deals was signed with the F-Secure,
a Finnish IT security. However, the Finnish firm interest was in the use of the core
elements of the software. The success in attracting international contracts was also
possible due to the help of Natalia Kaspersky who joined KAMI in 1994 as a sales
representative. As the demand for the AVP was increasing, Kaspersky’s department
in KAMI was also growing in terms of employee numbers. He was joined by Aleksey
De-Monderik and Vadim Bogdanov, two IT specialists who contributed to the further
development of the product.
12 http://www.fba.kz/www/files/istoriya_uspeha_kasperskiy.pdf
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Apart from the firm’s support and belief in Eugene’s product, there was another
crucial factor that influenced the further professional and personal development of
Kaspersky, which was his increasing awareness of the international environment in
the IT sector. First of all, during his work at KAMI, Eugene was given the opportunity
to travel abroad. His first trip was to the largest international computer expo CeBIT
(Centrum der Büro- und Informationstechnik) in Hanover, which took place in 1992,
just one year after he joined KAMI. In the book “The Principle of Kaspersky: The
Bodyguard of the internet” by Dorofeev and Kostileva (2010), which is based on
several interviews directly with Eugene Kaspersky and his top management team
(TMT), the author confirms this event influenced Kaspersky in two ways. Firstly, such
international event provided him with an opportunity to develop a professional network
development and search for new international partners and contracts for the firm, as
almost all the largest multinational IT firms were present at the expo. Secondly,
Kaspersky could see a clear distinction between western IT security firms and Russian
/ Post-Soviet firms. The former group of companies were more technologically
developed while the later did not even have a complete product.
After the Hanover conference, in the same year (1992), Kaspersky was invited
by the UK firm “Sophos” who offered collaboration with KAMI. The actual collaboration
between the Sophos and KAMI was based on the fact the English firm was forwarding
different viruses to the Kaspersky’s team. They were then analysed, “healed”, by KAMI
and the cure was sent back to the UK. At that time, this partnership was the main
source of funds for KAMI. As a side effect of this cooperation, Kaspersky was able to
make submit several articles in the western journal “Virus Bulletin”.
Despite Kaspersky’s product achievements in the international environment,
securing several international contracts in 2016, the firm’s main market focus was still
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Russia. However, although there was an increased demand for antivirus software due
to an increase in cybercrime and the computerisation of the Russian market, the
economy between 1992 and 1997 was going through the turmoil of restructuring from
a communist to a market economy. As a result, there was no regulatory framework in
the IT sector and despite KAMI’s attempts to sell the antivirus software though their
partners network the level of piracy and illegal distribution from user to user created
shortfalls in sales for Eugene’s department. At the same time, there was a
disagreement within KAMI between the owners, which caused an overall decrease in
performance and, consequently, its profitability. At that time, several KAMI’s
department decided to split form the main company and open their own firms. In 1997,
Kaspersky and 3 other KAMI employees (Natalia Kaspersky, Aleksey De-Monderik
and Vadim Bogdanov) decided to follow this example and start their own company.
Establishment of the frim
The idea to name the company after the AVP anti-virus software creator was
initially proposed by Natalia Kaspersky, who became the Managing Director of the new
firm. The main reason for this was Kaspersky’s reputation in the IT security sector in
domestic and international markets, which allowed the firm to spend less on marketing
and branding13. The two main roles within the company were distributed equally
between Eugene, who was responsible for the technical development and innovation,
and Natalia, who dealt with sales, human resources, marketing, general strategy and
the future development of the firm.
13 http://www.forbes.ru/milliardery/257437-virus-kasperskogo-kak-biznes-kaspersky-lab-zakhvatil-200-stran-mira
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Leaving KAMI and creating an independent firm had advantages and
disadvantages for Kaspersky Lab. As Natalia Kaspersky mentioned in one of her
interviews “One of the main advantages was the freedom of decision making, while
the drawback of being an independent company is to build your own distribution
network almost from scratch”. Due to the lack of resources, the owners decided to
focus on international markets and partners who stayed with them after splitting from
KAMI. However, the drawback of such a strategic decision was that the top
management team did not have significant knowledge of the foreign environment and
were not sufficiently proficient the English language to create and promote a complete
product for the foreign market (Dorofeev & Kostilova, 2010). Consequently, the foreign
partners were more interested in the actual technology rather than a final product.
Based on that interest, Kaspersky lab was able to sign two licencing contracts
for its technology (the core of the antivirus software) to two foreign firms within the first
year. The first one was with G-DATA, a German IT security company. The German
company contacted Kaspersky Lab direct and signed the contract during the CeBIT
international computer expo. The second was with F-Secure, a major player in the
antivirus software market. As one of the leading industry firms, they were able to
dictate the strict terms and conditions. As Kaspersky stated “The contract with F-
secure was the technology slavery. As the contract stated that we were not allowed to
licence our core of the antivirus software to anybody else apart from the previously
signed contracts, to develop antivirus internet solutions and the Finish firm was
granted all the rights to our technologies and their source codes” (Dorofeev &
Kostilova, 2010). These conditions were accepted by Kaspersky Lab, as there was no
alternative and the firm required the cash flow for further development.
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Even though the contract placed tough restrictions on the firm, the fact that 70%
of firm’s profit was coming from technology licencing and all the clients were from
Europe played a crucial role in 1998. This was the period of the financial crisis in
Russia and, by being an export oriented firm, and receiving its profit in US dollars, it
allowed Kaspersky Lab to prosper in such a challenging economic environment. The
difference in the exchange rate, which resulted from the strong devaluation of Russian
Rouble, provided the firm with extra fixed assets. Secondly, during the financial crisis
the there was an increase in unemployment and the labour market was overwhelmed
with skilled labour from different economic sectors. Kaspersky lab, were able to use
this opportunity and started to improve the corporate structure by hiring a financial
director and chief technology officer.
First stage of internationalisation (1997 -2000)
As mentioned by Kaspersky in an interview “If you just stay in the home market,
eventually you will be swallowed by large multinationals”. With such vision, the
international expansion was started from the inception of the company. The first
international office was established in Cambridge (United Kingdom) in 1999. However,
the decision to open the branch in the United Kingdom was not supported by any
business oriented logic. The main reason for establishing the new office in Cambridge
and starting the international expansion from the United Kingdom was the fact that
Eugene Kaspersky had visited the UK several times. The first time he went there as
KAMI’s employee, and later he went to attend the UK conference “Virus Bulletin” as
an entrepreneur and simply liked the country (Dorofeev & Kostilova, 2010). In 1999,
the market for IT security in the UK was divided between Symantec and McAfee, and
covered most of the consumer market (Dorofeev V. J. & Kostilova T.P. 2010), which
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by default created large barriers for entry, especially for a new start-up from the country
with no reputation in the IT industry.
The strategy was to find the local Russian manager, who had knowledge of the
UK market and would be willing to promote the product in this new market. Kaspersky
and his team found the person interested in starting and leading the new branch,
Vladimir Freidin - a Russian immigrant who had lived in the United Kingdom for 20
years and who agreed to work for the IT software firm as a sales representative14.
Together with another employee, Liza Klensy, both were trying to approach large and
small distributors across the UK. The main target at that time was Dixons (IT and
electronics retailer network in the United Kingdom) who currently had a 90% share of
the retail market in that industry, however all the negotiations were unsuccessful. The
main problem was the brand being unrecognised by the UK’s consumer and an
inability to spend a large amount on marketing and brand awareness in the new
market. The only thing that kept the UK’s office operating was the small level of IT
software piracy in the market, which meant that consumers preferred to buy the
original IT software from the developer, rather than finding free or illegal options.
Through direct sales to UK consumer, Kaspersky Lab was able to stay in the market,
however, that presence was more like survival as Eugene Kaspersky himself
acknowledged15.
Parallel to the establishment of the UK office, the managing director Natalia
Kaspersky was trying to enter Germany and Finland. However, the main difference
was the actual entry strategy. This time senior managers concentrated on the creation
of partners’ network and technology licencing, rather than developing a physical
14 http://www.forbes.ru/milliardery/257437-virus-kasperskogo-kak-biznes-kaspersky-lab-zakhvatil-200-stran-mira 15 http://tv.russia.ru/video/tinkov_10135/
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presence. In Germany, the brand Kaspersky had a much better reputation in
comparison to the UK. All the technical exhibitions and IT software lab tests, in which
Eugene participated as part of the KAMI firm, had a positive effect on brand
awareness, as anti-virus software from Kaspersky was receiving top reviews and
awards from local experts. Those recommendations allowed the firm to start to form a
partners’ network, who began distributing the product across Europe.
Nonetheless, overall the firm’s first physical presence outside the domestic
market was perceived as the failure. Kaspersky Lab’s management highlighted
several reasons for that outcome. First was the conservatism of the British consumer
market and their unwillingness to change their IT security software provider even if it
had a cheaper price than the leading brands on the market (Dorofeev & Kostilova
2011). Second was the high concentration of the retail sector in the IT industry, which
creates a lack of competition and made it harder for the firm to negotiate good terms
and conditions for the product. Thirdly was prioritising the UK market rather than
adopting an international strategy. This was particularly relevant to the products that
were coming from emerging markets, which are known for their lack of transparency
and the high degree of piracy, in terms of computer software.
Nonetheless, the experience from the UK market did have some positive effects
on internationalisation strategy for further expansion. Firstly, it encouraged the firm’s
senior management to decide that the physical presence was an important part for the
improvement of brand awareness and reputation. However, the lack of capital at this
initial stage foiled this objective. The solution came from their experience in other
European markets (Germany and Finland), which was successfully based on
licencing. The second main positive change was related to the corporate structure of
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the firm, where the senior managers decided to move away from the idea of employing
Russian top managers in their foreign offices to build trust and brand awareness.
Even though internationalisation was one of the core ideas of business
development for Kaspersky Lab, several factors were restricting the firm to a limited
numbers of internationalisation strategies. One significant obstacle was the contract
with the Finish firm F-secure. Not only was the Finish firm squeezing the profits of
Kaspersky, but in 2000, they were also trying to acquire Kaspersky Lab. At the time of
the dot-com bubble, F-secure launched an IPO and managed to raise a large amount
of capital. The priority of the firm was quick expansion into other markets and
improvement of their technology through M&A and Kaspersky Lab was one of their
targets, however the acquisition proposal was refused.
In the same year, another difficulty emerged within the company itself, which
was the first corporate crisis. The core of the problem was a misunderstanding
between the senior management team and employees (particularly IT engineers). The
top management team hired during the financial crisis in Russia came from a
management background but were unable to integrate into the technological process.
As a result of vague communication between employees and the top management
team, the new version of antivirus software, which was released for the Russian
market in 2000, was very technical, slowed down personal computer speed and was
not user friendly, therefore reducing the cash flow and damaging reputation.
Consequently, the firm’s technical and marketing director had to resign.
The founders started to look for top managers who would be oriented towards
internationalisation of the business. However, they soon realised that at that time there
was a lack of Russian managers with either international experience or international
awareness. As a result, Kaspersky Lab started extended their search for top managers
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to western countries. Firstly, they hired a German manager, who worked in the team
for just 4 months and (in the same year) an English manager was fired within the same
timeframe. The causes for the sacking in both cases were the same. First, employees
were complaining about the different approaches proposed by the new managers and,
due to difficulties in the communication process between the top management team
and employees, these were even harder to address in comparison to the Russian
managers. Secondly, managers from outside the firm were chasing commercial
benefits rather than the ideology of the founders, which was to build the best antivirus
software through innovation. The conclusion Kaspersky came to at that time was to
start training top management team personnel from within the firm’s employees.
Corporate restructuring within the firm helped Kaspersky Lab in several ways.
First, they were able to create a product that was easy to use for general PC users
and had more advanced settings for the experts. Secondly, besides improving the
main product, the new top management team, who were IT engineers, were able to
develop new diversified products, separating corporate and household users. The final
factor was the development of a 24hour support line, which was a unique service for
the Russian market at that time, and the daily update of the antivirus database, which
was a unique feature of the antivirus software worldwide.
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Second stage of internationalisation (2000-2006)
After corporate restructuring within the firm, the new trajectory was clear. The
two main objectives were to increase the share of corporate users and to increase the
firm’s share in foreign markets. Thus, the second stage of internationalisation started
with massive expansion across all continents.
At the beginning of the millennium, the focus of Kaspersky’s Lab expansion was
focused on Europe. The firm was preparing to start selling their product into European
markets as soon as the contract with F-secure expired, as this was the only factor
restricting them from selling the anti-virus directly to European consumers. The last
attempt by F-secure to take over Kaspersky Lab was in 2003. They proposed a merger
between the two companies with a 60% stake belonging to F-secure and 40% to
Kaspersky Lab. That offer was refused, as two others had also been, because, as
Eugene suggested “… in the next three years we would be the one who would offer
you to merge, buying off 80% of your company” (Dorofeev & Kostilova, 2011).
While they were still under the contract, Kaspersky Lab started its preparation
for international expansion. In 2000, at the CeBIT expo, Kaspersky had several
successful negotiations on establishing and strengthening cooperation with large
software distributors from the Netherlands, Sweden, Greece, Brazil, France, Iceland,
Switzerland, Spain, Hungary and Austria16. The year 2002 marked the establishing of
the first international office after the corporate crisis, which was opened in France
(“Sophia-Antipolis” – Technology Park on the south of France). Most of the products’
instructions were translated into French, as this market was about 20% of the firm’s
16 Source: https://www.kaspersky.ru/about/press-releases/2007_laboratorija-kasperskogo-otkryvaet-predstavitelstvo-v-shvecii
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European sales at that time17. The following year, Kaspersky Lab opened its
European antivirus research centre in Paris (France)18 to improve their ties with
international partners and to start their support line for European customers. As
managing director, Kaspersky Lab appointed one of the leading French experts in
computer viruses in Europe – Marc Blanchard.
The second major European market for Kaspersky was Germany. Sales of
Kaspersky product under its own name started in Germany in 2003 and the
geographical location of the new office did not have any influence on the decision at
that time. The German office was opened in Ingolstadt solely because Natalia
Kaspersky was able to find Andreas Lamm (Dorofeev & Kostilova 2011), a good
German manager who previously worked in a leading position at maxiBIT, Trusted
Information Systems and Network Associates, as well as at Articon-Integralis AG,
where he served as Technical Director.19
After developing its European offices, Kaspersky started to move into Asia and
the USA. Japan was the second largest market in the world for computer security at
that time, which was valued at around 500 million USD.20 As stated in Natalia’s
Kaspersky interview (Dorofeev & Kostilova 2011) the approach to enter Japan was
exactly the same in regards to the general product and general marketing strategy as
in Europe. They were attending different IT conferences and had long negotiations
with the Japanese potential distributors. However, this did not provide any positive
17 https://www.kaspersky.ru/about/press-releases/2002_laboratorija-kasperskogo-otkryvaet-predstavitelstvo-vo-francii 18 https://www.kaspersky.ru/about/press-releases/2003_laboratorija-kasperskogo-otkryvaet-evropejskij-centr-antivirusnyh-issledovanij 19 https://www.kaspersky.com/about/press-releases/2011_andreas-lamm-1966-2011 20https://www.kaspersky.ru/about/press-releases/2003_laboratorija-kasperskogo-otkryvaet-predstavitelstvo-v-japonii
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results, even though Kaspersky technology was already being used by several firms,
which operated in Japan. As Eugene Kaspersky stated in one of his interviews, the
Japanese market was very similar to the UK in terms of its conservatism and the
unwillingness of consumers to purchase a new product. After several failed attempts
to sell the Russian product directly to Japanese distributors the company decided to
search for a Japanese manager and found Daizo Yamaoko who had lived and worked
in Moscow for 17 years and, in 2003, a new joint venture with Japanese firm iMEX.Co
Ltd was created in Tokyo21.
Based on the internationalisation experience from the first Asian market
(Japan), Kaspersky lab was looking to appoint a Chinese manager in China, where
the office was opened in 2004. In fact, the candidate for this position contacted
Kaspersky directly and offered his services in China. This was Harry Cheung who in
2003 was the President of Information Security One (China), and was recognised as
one of the top providers of information security in China. The result of such a decision
based on the previous experienced helped the company with successful
internationalisation.
The largest market for IT security and Software innovation was the USA and
Kaspersky Lab was trying to enter this market almost from its inception. The first
attempt to start selling the product (at that time the AVP antivirus) was as early as
1998-1999. Natalia Kaspersky found a representative in USA (Kit Peer)22 who
registered the AVP brand in the USA two days prior to Moscow office in USA and
created a website (www.avp.com). This move allowed the American representative to
21https://www.kaspersky.ru/about/press-releases/2003_laboratorija-kasperskogo-otkryvaet-predstavitelstvo-v-japonii 22 http://www.forbes.ru/milliardery/257437-virus-kasperskogo-kak-biznes-kaspersky-lab-zakhvatil-200-stran-mira
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purchase the product from Kaspersky with huge discounts and keep most of the profit
to himself. In one of the interviews Natalia Kaspersky mentioned that “…out of 2 million
USD per year only 300 000 USD was Kaspersky’s Lab profit”. As a result, the
agreement with Kit was terminated in 1999. However, even at this stage there was a
difficulty, as the contract did not account for any termination clauses. However, after
a number of legal proceedings and fines the contract was finally terminated.
The second attempt to enter the market was not made through direct sales of
the final product but through the licensing of the technology, as this method had proved
successful in Europe. To strengthen the chances of success, the management team
decided to establish an office in Silicon Valley and appointed a manager from its
Moscow’s office (Vladimir Chernyavskij) to promote Kaspersky’s technology in the
USA. The lack of international experience and knowledge of American market in
particular was slowing down the promotion of Kaspersky’s technology and was the
result of inefficient resource allocation. “We had a profit of $20,000, but spent
$800,000 in a year” Natalia Kaspersky confirmed later23. As a result the office was
closed in 2002 and all the contracts were transferred to the control of the head office
in Moscow.
The third attempt to enter the American market took place after the completion
of first corporate restructuring, which helped Kaspersky Lab to formulate their
objectives and marketing strategy. The new search for a qualified manager in America
took place among the IT security firms in the US. As a result, Peter Laakkonen, the
top manager of F-secure (Finish Firm) in the US, was appointed as the new director
of the US office in 2004. His main objective was to sell the licensed technology to the
US IT firms. However, as the main target was to enter the American retail market with
23
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the complete product, Natalia Kaspersky started looking for a second person. The
second manager was Steve Orenberg, and in the spirit of Kaspersky Lab at that time,
they opened the second office in Boston in 2005, where Steve lived at that time. In
2004, when Orenberg resigned from his job and accepted Kaspersky’s Lab proposal,
he was unable to work for them immediately due to the non-compete clause of his
contract, but for the next year he was working on a strategy and building the team.
One of the core players hired by Orenberg as marketing director in Boston’s
office was Randy Dravas. He brought some radical marketing strategies for the US
software security retail market. One of them was not to start a price war by entering
the market with the lowest price, but to be the most expensive product on the shelf
(Dorofeev & Kostilova, 2011). At that time, the market was divided between Symantec
and McAfee. Both were American brands from California. The idea that Randy
proposed to American distributors was that by putting the price of Kaspersky Anti-virus
higher than Symantec and McAfee they would not steal clients and therefore the profit
of the distributor, but would attract new clients as Kaspersky product is much more
advanced and was favoured by IT specialists. The second idea provided by Randy,
which helped to attract other consumers to the antivirus-software, was to allow
different payments methods. At the beginning of that approach, the product was given
for free and if after 6 months the client did not want to continue to use the product, he
was cut off from the anti-virus database updates and support. However, if there was
no formal cancellation, money was deducted from the credit card that the customer
gave at the beginning of the trial period. As the practice showed, only 5% of the
customers decided to cancel the subscription (Dorofeev & Kostilova 2011). By using
this marketing approach, in 2006 Kaspersky anti-virus was distributed by 200 retail
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stores in the U.S. and Canada and, by 2008, about 15,00024. In 2010, Kaspersky
became the top retail seller of antivirus software in America (see Fig 2.1)25. However,
by 2007 the company had experienced significant growth and become one of the
major players in anti-virus software on several international markets.
Figure 2-1.Share of Kaspersky Lab in the US Market in 2008
Company Sales in the US market (October
2008)* Share of the market
Symantec $12.6 million 48.70%
Kaspersky Lab $5.1 million 19.80%
Trend Micro $4.0 million 15.70%
McAfee $2.2 million 8.70%
Microsoft $600,000 2.30%
* = approximate
Source: The NPD Group
Parallel to the successful internationalisation, the pressure of a new corporate
crisis was building in Kaspersky lab. The growth of its international distribution network
together with international offices around the globe, once again began to draw
attention to the corporate structure, which was unable to handle the large firm and, as
a result, was bringing inefficiency into the firm’s financial performance (Dorofeev &
Kostilova, 2011). The commercial interest of rapid internationalisation had set aside
the innovation and, as a result, versions Kaspersky 4.0 and 5.0 were repeating the
issues experienced during 2000. Another problem was the inefficiency of decision
making and the speed of these decisions due to the hierarchical structure of the large
corporation where the final decision was being made by a single person.
24 https://usatoday30.usatoday.com/money/companies/management/profile/2008-11-23-kaspersky-lab-pc-security_N.htm 25 http://www.forbes.ru/milliardery/257437-virus-kasperskogo-kak-biznes-kaspersky-lab-zakhvatil-200-stran-mira
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The solution the company introduced was the establishment of a board of
directors in the year 200726. There were 9 directors with 3 international directors
appointed from the firm’s foreign offices. The new managing director became Eugene
Kaspersky, replacing Natalia Kasperskaja in this post (however Natalia still was a
board member). Other board members included were Aleksey De-Moderik, Vitalij
Bezrodnih, Eugene Bujakin, Harry Kondakov, Andreas Lamm, Steve Orenberg and
Harry Cheung. Such restructuring helped the firm’s management team to keep up with
its fast-international growth and, as a result, the company managed to go through the
financial crisis without suffering a decrease in revenue. In 2008 the global revenue
almost doubled in comparison to the previous year. However, in 2009 the company
felt the effect of the global financial crisis and global revenues increased by only
40%27. From early 2009, the company started to look for the additional capital to
maintain its fast expansion and started to think about an IPO.
Third Stage of internationalisation (2007 – 2016)
The third and final stage of internationalisation started straight after the board
of directors was established and this was the decision of the board to build regional
hubs to encourage easy and quick operations. In 2008, 3 regional offices were
established, a North American Hub in the USA, a Middle eastern lab in Dubai, and an
Asian Lab in Malaysia. As Eugene Kaspersky describes, this was an active expansion
strategy, as the firm continued to build subsidiaries in the foreign markets. The hubs
were continuously growing and eventually five regional divisions were established.
26 https://www.kaspersky.ru/about/press-releases/2007_laboratorija-kasperskogo-moderniziruet-strukturu-korporativnogo-upravlenija 27 https://www.forbes.ru/milliardery/257437-virus-kasperskogo-kak-biznes-kaspersky-lab-zakhvatil-200-stran-mira
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These were in Western Europe (Austria, Benelux, France, Germany, Italy, Poland,
Portugal Spain Sweden, Switzerland, the UK); Eastern Europe, Middle East and Africa
(Kazakhstan, Romania, Russia, South Africa, Turkey, Ukraine, United Arab Emirates,
Latvia); North and South Americas (USA, Canada, Latin America countries); Asia
Pacific (Australia, China, India, South Africa), and Japan was a stand-alone country.
This time the expansion was proceeding in parallel with the corporate
restructuring, and there were number of things that changed in the corporate structure
during that period of internationalisation. Firstly, the firm was thinking about the IPO
and there were two main reasons for that. Initially, Kaspersky lab considered the
external capital could help with the rapid expansion in the third phase. However, at the
same time, as Natalia Kasperskaya moved away from the managing position, she was
looking for the opportunity to sell her 20% of the company to some external buyers.
This was due to the internal conflict of interest that happened between her and the
new board of directors (Dorofeev & Kostilova, 2011). In 2011, the 20% was bought by
the General Atlantic. Such turn of events created a potential threat to the Kaspersky
decision making process in terms of its global strategy as General Atlantic got a seat
at the board of directors. The threat can be viewed from the perspective that the
American company (General Atlantic) can sell these shares to some other American
firms that are direct competitors of Kaspersky Lab in America. The board was also
considering the benefits of such change, as this potentially opens the corporate market
for the Kaspersky Lab. However, within the years’ Kaspersky bought back the share
from General Atlantic28
28 https://www.kaspersky.ru/about/press-releases/2012_laboratoriya-kasperskogo-obyavlyaet-ob-izmenenii-struktury-akcionernogo-kapitala
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Furthermore, after the creation of the board of directors, the firm looked into the
value of building the corporate culture, taking into the account that not only the revenue
of the firm was steadily growing, but also the number of employees across the globe.
For that purpose, Kaspersky lab hired the HR firm Heidrick and Struggles to create
and implement a formal corporate culture across its global offices, which in 2008
employed 2400 employees.29 The process took several years and was finished in
2010. The main goal of such action was aligning the vision and ideas across the firm’s
division. Such action prevents the cases that happened earlier in the firm’s history,
where there was misunderstanding between the teams (for example sales and R&D),
which lead to the technical and corporate crisis.
It can be concluded that Kaspersky’s major internationalisation phase was
finished by the year 2012. After that, the board of director was restructuring in
accordance with the strategic objectives of the firm (Figure 2.5). During the third phase
of internationalisation the firm focused on the transparency and disclosure
mechanisms. As a result of this objective the new head office in the UK was
established in 201330. The idea behind the introduction of new transparency and
disclosure mechanisms was to show the stable development of the firm and earn trust
in the corporate sector. For that reason, Kaspersky Lab began to publish their reports
in the IFRS standards and publicly announced the press-releases of these reports on
their webpage (example31). At the same time the firm started to provide an annual
report which included the independent audit reports32.
29 https://www.pro-personal.ru/article/383692-razrabotka-korporativnyh-tsennostey 30 https://www.kaspersky.ru/about/press-releases/2013_laboratoriya-kasperskogo-otkryivaet-novyiy-evropeyskiy-ofis-hab-v-londone 31 https://www.kaspersky.ru/about/press-releases/2018_kaspersky-lab-revenues-grow-8-to-698-million-in-2017 32 https://beta.companieshouse.gov.uk/company/04249748/filing-history
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Between 2012 and 2017, only two additional foreign offices were opened, one
in Singapore and a research lab in Dublin. One reason for this was that all the strategic
markets were already conquered by the Kaspersky lab, and there was no need for
further expansions. In addition, in 2014 the political situation that occurred between
Russian and the Western countries that evolved was not in the favour of Russian firms.
As a result of this political conflict, some of the major Russian firms were placed under
the European and US sanctions. In 2017, Kaspersky lab itself was also involved in
litigation with Microsoft and in the same year received a ban from the US government
on its products to be used by governmental departments or firms. Both of these factors
were related to the tight relationship between the Russian government and the security
firm, however the proof of that link was not established33. The most recent interaction
between the Kaspersky Lab and Russian Federation is the fact that Kaspersky won
the government contract to run all cybersecurity efforts at the 2014 Winter Olympics
in Sochi (Russia). Both factors had a negative influence on the operation and its
revenue in the US market which was followed by partial withdrawal from the US
market34. To mitigate the negative influence that Kaspersky Lab faced during the year
2017, they proposed to launch the Global Transparency Initiative (GTI),35 the main aim
of which was to open the source code to the products and engage the expert
community in the field of cybersecurity to ensure the integrity and reliability of the
company's products, internal processes and business operations. The GTI program
33 https://www.wsj.com/articles/russian-hackers-scanned-networks-world-wide-for-secret-u-
s-data-1507743874
34 https://wccftech.com/kaspersky-closing-washington-office/
35 https://www.kaspersky.ru/about/press-releases/2017_kaspersky-lab-global-transparency-initiative
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started with the reallocation of its data processing facilities from Russia into the
Switzerland and continues to open independent offices around the globe36
Discussion and Conclusion
As can be seen from the company’s history, it can be classified as the
international new venture based on the definition of McDougal & Oviatt (1994). From
the inception of the company, its managers saw internationalisation as the primary
objective for the firm’s growth. However, managerial incompetence together with poor
strategic decisions led to the failures in the internationalisation process in certain
foreign markets. These failures were followed by partial or complete withdrawal from
foreign markets and the restructuring of the business. This process can be directly
link to the theoretical framework presented by Nummela et.al (2016) (Figure 2.2).
36 https://www.kaspersky.ru/blog/transparency-status-updates/21211/
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Figure 2-2: Theoretical framework of dynamic Internationalisation of INV (Nummela,
Saarenketo & Loane, 2016)
The beginning of the internationalisation process of Kaspersky Lab can be linked
to the traditional Uppsala model. The firm started their internationalisation through
licencing and exporting of their technology and selling of their products into the
neighbouring countries. During that period the company did not experience significant
growth resulting in minor changes in the managerial system of the firm. That phase of
the internationalisation did not require any adjustments in the corporate governance
structure of the firm. This chain of events shows that the exporting phase of
internationalisation would not necessarily require business restructuring or
introduction of corporate governance mechanisms.
The first poor strategic decision regarding internationalisation process was to open
a foreign subsidiary in the UK market. The entry method that was chosen by Kaspersky
together with the targeting market itself revealed the managerial incompetence and
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lack of international experience in the firm. As a result Kaspersky Lab faced the partial
withdrawal from the UK market, in which they could not be successful from the
beginning. At the same time the growth in the number of employees in the domestic
office required additional layers of management which were hired, however the lack
of instruments to align the interests of the owners and the top management teams lead
to the first corporate crisis. The conclusion that can be drawn that both of these factors
(internationalisation by establishing the foreign subsidiary and growth in the size of the
company in the domestic market) lead to corporate restructuring.
The second phase of internationalisation was a massive expansion into different
regions (Europe, Asia, North America). Based on the historical timeline presented in
the case study, it is possible to conclude that when the firm entered eastern European
countries, such as Poland, Ukraine, Kazakhstan they did not experience difficulties in
reaching the main consumers or confront complications in the internationalisation
process regardless of the company’s growth. The primary reason for that is the cultural
proximity between Russia and eastern European countries. That factor allowed
Kaspersky Lab to reallocate Russian managers who were able to efficiently manage
the new offices. Such reallocation At the same time the level of corporate governance
in the eastern European countries is similar to the Russian market. As a result none
of the corporate governance instruments were enforced on Kaspersky.
The internationalisation into Western Europe together with Asia and North
America regions, required different approach. Primarily, Kaspersky lab was looking
to hire the regional managers to lead the foreign offices. The decision making
process, however, was locked on the managing director of the firm at that moment
(Natalia Kasperskaya), which reduced the speed and efficiency of the crucial
strategic decisions. The geographical diversification of the firm, as the result of
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internationalisation, increased the complexity of Kaspersky Lab and required
adjustment in the corporate structure for the efficient performance. The result was
the establishment of a board of directors with international directors appointed from
the firm’s foreign offices. Such restructuring helped the firm’s management team to
keep up with its fast-international growth and, as a result, the company managed to
go through the financial crisis without suffering a decrease in revenue.
Further expansion in the third phase of internationalisation was also followed by
the restructuring of corporate board. The decision of the board to look into the IPO as
an instrument for additional financing of their international expansion, resulted in the
expansion of the board of directors prior to the potential IPO. The new board member
was the second largest stakeholder in the company. This change, however, was
temporary, as the firm realised that dispersed ownership will slow down their decision
making process. The result was the buyback of the shares by Eugene Kaspersky from
General Atlantic. After that the board composition did not experience major changes
and consisted of 7-8 execute directors out of which 2-3 were international directors .
At the same time during the third phase of internationalisation the firm focused on
their global image and implemented the transparency and disclosure corporate
governance mechanisms to assist with that strategic task. They started to apply the
international financial reporting standards to increase the transparency and disclosure
and to perform a yearly independent audit . However, further actions to improve their
transparency and disclosure were linked primarily to the external factors (sanctions
of the Russian firms in 2014, conflict with Microsoft in 2017, conflict with the US
government in 2017) rather than internationalisation. For example as result of the US
scandal, Kaspersky lab launched global transparency initiative.
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Plotting the events that are linked to the change in the corporate governance
structure and internationalisation on the same timeline show the correlation between
the adjustment and implementation of corporate governance mechanisms and the
successful internationalisation process (Appendix A.2.1). From the graph, the
internationalisation was followed by the organisational restructuring of the firm, which
emphasised the importance of corporate restructuring when the company is growing.
At the same time, the company did not experience the separation of ownership and
control, as the main controlling group of the firm stayed almost unchanged though the
time. Indeed, the same group of owners were managing the daily activity and setting
the global objectives for the firm. However, when the firm expanded globally in the
second phase of internationalisation, the hierarchical structure of the firm with the
single executive director became inefficient and resulted in a technical and corporate
crisis. To mitigate both, Kaspersky Lab established a board of directors and included
their regional foreign senior managers on the board to distinguish between the global
objectives and daily business operations. However the This case study example
provides the ground for the first 2 hypothesis of this thesis.
Hypothesis 1:
Firm’s internationalisation, which occurs through opening a subsidiary or foreign
acquisition in the foreign market, will be positively correlated with the number of
corporate governance mechanisms.
Hypothesis 2
Increase in the geographical diversification of the firm will be positively correlated
with the share of foreign directors represented on the board.
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It is also important to mention that corporate governance restructuring was not only
influenced by internationalisation. The family disputes between Natalia Kaspersky and
Eugene Kaspersky forced the Kaspersky Laboratory to change the corporate structure
of the board as Natiala sold her shares to the third party prior to the IPO . At the same
time several mechanisms of transparency and disclosure were applied in order to
retain reputation of the firm on the global stage after the scandals with Microsoft and
the ban from the US government. Or due to the growth of the company such as annual
reports with the independent auditor’s reports.
125
Appendix A. Figure 2-3.The roadmap of Kaspersky Lab internationalisation process and changes in the corporate governance structure.
126
Figure 2-4 Financial performance of Kaspersky Laboratory by region37
Total Revenue (in million dollars)
2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Total 388 538 612 639 667 711 619 644 698 726
EEMEA Region 283 349 379 386 380 412 461 429 493 563
North and South America Region 79 134 174 193 223 231 106 156 143 98
Asia-Pacific region 26 55 59 60 64 68 52 59 62 65
37 Authors calculation based on the available financial information of Kaspersky Lab
(Source: https://www.tadviser.ru/). Underlined figures were interpolated based on the original
data.
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Figure 2-5 Restructuring of the corporate board38
38 Structure of the Board of Directors (BOD) through time. Source: Annual reports available
online at: https://beta.companieshouse.gov.uk/company/04249748/filing-history
Year Changes in the structure of the board of directors
Comment
2007 9 Directors out of which: 6 Russian Directors | 3 Foreign Directors 1 Female director 9 Executive directors
Establishment of the board
2008 9 Directors out of which: 6 Russian Directors | 3 Foreign Directors 1 Female director 9 Executive directors
2009 9 Directors out of which: 6 Russian Directors | 3 Foreign Directors 1 Female director 9 Executive directors
2010 9 Directors out of which: 6 Russian Directors | 3 Foreign Directors 1 Female director 9 Executive directors
2011 9 Directors out of which: 6 Russian Directors | 3 Foreign Directors 1 Non - Executive director
Restructuring of the board in the preparation to the IPO
2012 8 Directors out of which: 5 Russian Directors | 3 Foreign Directors 1 Non - Executive director
Restructuring of the board due to the internal conflict between Natalia Kasperskaya and Eugeme Kaspersky
2013 5 Directors out of which: 4 Russian Directors | 1 Foreign Director 5 Executive Directors
Restructuring of the board due to the buyback of the shares from the external directors.
2014 6 Directors out of which: 4 Russian Directors | 2 Foreign Directors 6 Executive Directors
Restructuring of the board due to the objectivate to increase foreign sale
2015
6 Directors out of which: 4 Russian Directors | 1 Foreign Director 6 Executive Directors
2016 7 Directors out of which: 6 Russian Directors | 1 Foreign Director 7 Executive Directors
2017 5 Directors out of which: 4 Russian Directors | 1 Foreign Director 5 Executive Directors
2018 6 Directors out of which: 5 Russian Directors | 1 Foreign Director 6 Executive Directors
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Questionnaire for the first interview
1. In which markets KL operates at the moment?
2. What are the current international objectives of the firm?
3. What was the first foreign market in which the firm started to operate?
4. What was the main reason for internationalisation?
5. In your opinion, what influenced the main strategic decisions of the firm during
internationalisation?
6. Why the firm decided to use Join Ventures and subsidiaries as primary tools for
internationalisation?
7. Did internationalisation change the organisational structure of the firm?
8. In what way internationalisation changed the organisational structure of Kaspersky
laboratory?
9. From your perspective, what was the toughest market to enter, and why?
10. In your opinion, what was the main problems in the internationalisation process?
11. How these problems were resolved?
12. Does the company has a plan for the future geographical diversification?
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Questionnaire for the second interview.
1. How would you describe the organisational structure of the firm in the early
establishment?
2. In your opinion, when the organisational structure of the firm started to change? (In
what way?)
3. From your perspective, what was the main reason for the organisational changes?
4. Was the new organisational structure efficient?
5. Why the firm decided to create the board of directors? What was the main reason
behind this action?
6. From your opinion was this the right decision? Why?
7. Was the board actions transparent?
8. How many board meetings are held during the year? Was the firm planing to go
public (IPO?), what was the reason for that?
9. Did the sanctions against Russia in 2014 influence the firm in any way?
10. Why the firm decided to disclose their accounting in the IFRS format?
11. Why the firm started to disclose annual reports?
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Chapter 3 Internationalisation and strategic decisions on corporate governance
The extensive literature has focused on the causal relationship between the
corporate governance of a firm and its internationalisation, suggesting that the former
will determine the success of the later. For example, having an international director
with experience and knowledge of the foreign market on the BoD (board of directors)
will ease the process of entering that market (Lu, Xu, and Liu 2009; Chen 2014; Rivas
2012; Oxelheim et al., 2013). At the same time, good protection of minority
shareholders could attract the attention of foreign investors, therefore increasing the
capital of the firm and providing it with a financial opportunity to start operating outside
its market of origin (Jiraporn et al., 2006).
However, based on the agency theory, monitoring mechanisms of corporate
governance, such as BoD, transparency and disclosure mechanisms, and protection
of minority shareholders, is required only when there is a separation of ownership and
control (Berle and Means, 1932), which can occur in two situations. The first situation
is when there is an increase in asymmetric information within the company due to an
increase in size. That is applicable if we think of a company that is continuously
growing in terms of its employees, assets and branches that are distributed across
different geographical areas of the domestic market.
Secondly, conflict can arise if the firm requires external capital. The two options
that are viable for firms are financing through debt or equity. If the capital is obtained
from investors (equity financing), it may lead to dispersed ownership and thus will
require corporate governance control mechanisms to mitigate the rising conflict
between the principal and the agent. At the same time, debt financing may also require
certain corporate governance mechanisms to decrease the information asymmetry
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(and increase transparency) between the debt provider (bank) and the firm. The
literature suggests following the pecking order theory (Myers & Majluf, 1984): if the
firm is unable to finance itself internally through retained earnings, it should try and
finance itself through debt first, before financing itself through the issuing of equity.
This hypothesis is interlinked with agency costs that would depend on the capital
structure that the firm selects. Internal financing will require a minimum number of
corporate governance mechanisms, while financing through debt or equity will lead to
the implementation of additional corporate governance mechanisms (Vivek, Young &
Myungsoo, 2012). Therefore, it can be concluded that for small- and medium-sized
firms to introduce the monitoring of corporate governance mechanisms will depend on
the firm’s capital structure.
At the same time, both factors (size and external capital) may vary in relation
to the firm’s sector of performance. If we compare the inception stages of a
manufacturing firm to those of an information and communication (IT) software
company in terms of labour and capital, the first will require a larger amount of both.
Following that, the set of initial corporate governance mechanisms between two firms
may also vary due to industry characteristics. Combining these factors, it is reasonable
to assume that if a company is operating only in the home market, does not require
external capital from its inception, and operates in an industry that has low set up
costs, it will not need to monitor corporate governance mechanisms.
As this thesis focuses on internationalisation and corporate governance, it is
reasonable to assume that all the firms within the framework see internationalisation
as their main objective at some stages of their development. Consequently, for the
company that does not need to monitor corporate governance mechanisms, strategic
development can progress in two ways. The first way is to continue its growth in the
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home market to a certain level and then penetrate any other market. That procedure
is the first stage of the original Uppsala model of internationalisation (Johanson and
Vahlen, 1977). The second way is to start operations in the foreign market from
inception (international new ventures theory, McDougal and Oviatt, 1994). That
strategic decision will depend on several factors, such as competition intensity in the
home market in comparison to the foreign market, demand for a product/service
between the home market and foreign market, whether an actual physical presence in
the foreign market is required, etc.
Therefore, let us compare two firms, one of which can be international from
inception and the one that prefers stage development prior to international activity. As
has been observed from the existing literature, when a firm expands outside its country
of origin, it will lead to higher complexity and increase information asymmetry (Sanders
and Carpenter, 1998; Michael and Pearce 2004; Lee et al., 2008), making it more
difficult and costly to monitor top management teams’ (TMT) performance (Zajac and
Westphal, 1994), leading to a typical agency problem. That leads to a conclusion that
an international firm will have to adopt additional or new corporate governance
mechanisms, increasing its level of corporate governance, which will be higher in
comparison to the firm that is operating only on the domestic market39.
39 It is important to highlight that the literature points out the bi-directional relationship between corporate governance and internationalities based on the development path that the firm will select. One of the strategies for international expansion is firstly to grow in the domestic market, receive additional financing through debt or capital, then adjust the corporate governance structure in accordance to the level of complexity that the firm is facing to mitigate the agency problem, and then start the internationalisation process. The other strategy, which is the key focus of this thesis, is to start the internationalist expansion from the inception of the firm (become a ‘born global’ firm), which will increase the complexity of the firm and should be accompanied by the changes in the corporate governance structure to mitigate any failure in the internationalisation process.
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Apart from information asymmetry, some external factors can influence the
corporate governance of international firms. As different countries have different rules
and regulations, the structure of corporate governance mechanisms and their
application will differ as well. Typical examples include accounting standards across
different markets (IFRS standard or GAAP standard), board structure (one or two tier
board), rules and regulations about minority shareholder protection (voting rights), or
the type and amount of disclosed information. If those regulations are different
between the home market of the firm and the international market, an international
firm will be obliged to adopt certain government practices. Consequently, it is possible
to conclude that if an international firm emerges from a market where the general
standards of corporate governance are poor40 in comparison to the market of entry, it
will be forced to introduce some new or additional corporate governance mechanisms,
thus increasing and developing the overall number of corporate governance
mechanisms, in contrast with a firm that operates only in the domestic market.
As soon as such a firm starts its operation in the foreign market, and adopts the
corporate governance mechanisms which are required within that market, it engages
with other market actors (i.e.: suppliers, distributors, customers, etc.) and starts
building new relationships within the industry production network, hence absorbing
new practices. Based on such experiential learning (Kolb 1984) within the network, an
40 The poor corporate governance on a country level refers to the low enforcement of corporate
governance mechanisms. Countries with weak enforcement experience low protection of
minority shareholders’ interests, have weak financial auditing and accounting standards, and
non-transparent regulation of securities exchanges, which are subject to excessive government
influences. Public institutions in developed capital markets are perceived to provide a superior
framework of corporate governance than in emerging market economies (Cornelius, 2005).
136
international company may implement best practices, among which can be new
corporate governance mechanisms, thus establishing an additional channel through
which the overall corporate governance structure can be improved.
Hence, for a firm that sees internationalisation as one of the main objectives,
does not require external capital, and is originally from a market with a poor corporate
governance framework in comparison to the market of entry, it is possible to envisage
the following development path of corporate governance mechanisms, represented
below:
This graph represents the change in the number of corporate governance
mechanisms (y-axis) with respect to time (x-axis). The period of time from t to t+1
represents the establishment of the company in the home market. Based on the laws
and corporate governance framework in the domestic market, that company might be
t t +1 t +2
Number of corporate governance mechanisms (CG) of the firm
Time t +3 (0,0)
ΔCG1
ΔCG2
A1
B1
C1
A1
B1
C1
Figure 3-1.Internationalisation and corporate governance
137
obligated to introduce certain corporate governance mechanisms, or, due to the
industry specifications (i.e. manufacturing firm), which can lead to information
asymmetry, the company would require particular control mechanisms from inception.
Therefore, some corporate governance mechanisms may exist in any company from
inception.
Starting from t+1, the firm will enter a new international market, and as
discussed above, there are three factors that would lead to an increase in the number
of corporate governance mechanisms which emerge from the internationalisation
process. Area ‘A1’ represents a fixed increase in the number of corporate governance
mechanisms due to the laws and regulations of the new market. Area ‘B1’ shows
exponential growth of corporate governance mechanisms through time due to
experiential learning. Area ‘C1’ characterises an increase through time due to the
growth of the company (increase of information asymmetry within the company). For
example, a company can open an additional branch in a new geographical region of
the same foreign market. The overall level of corporate governance mechanisms will
increase by ‘ΔCG1’ when a company enters its first international market.
Starting from the period t+2, a firm may enter another international market, and
if all the assumptions are met, the firm can still absorb and implement new corporate
governance mechanisms (Areas A2, B2, C2). However, if first and second
international markets are similar in their corporate governance laws and overall
business environments (for example, Germany and Austria; United Kingdom and
United States), then that means that internationalisation into the second market can
yield some increase of corporate governance (if any); however, it will be in smaller
proportions in comparison to the first international market (ΔCG1> ΔCG2). Thus, when
the company enters some markets ‘n’ in the period t+n, that will mean that ΔCGn = 0.
138
At this point, the firm may not introduce any additional corporate governance
mechanisms, but it may restructure the existing ones, depending on the strategic
decisions.
On the other hand, if the firm’s first market of entry has the same corporate
governance framework as the firm’s domestic market, the change to the corporate
governance mechanisms can be minimal. For example, if the corporate governance
code in the foreign market is just a set of guidelines rather than a set of rules (for
example, the Russian code of corporate governance and the CIS regions), this will
imply that the increase of firm’s corporate governance due rules and regulations (area
A1 on Figure1) would be equal to 0. Adoption of corporate governance mechanisms,
which comes from experiential learning in the foreign market (Area B1), can also be
equal to 0 if firms, which already operate in the foreign market with a low level of
corporate governance, have no incentive to introduce any corporate governance
mechanisms. Thus, the only effect of internationalisation on corporate governance will
occur due to the increase in firm’s overall complexity (C1), which increases information
asymmetry.
Therefore, the following conclusion can be drawn from the above discussion:
internationalisation of a firm from a country with a low level of corporate governance
into a country with a high level of corporate governance will be correlated with the
restructuring of corporate governance mechanisms.
.
Cost function of implementing corporate governance mechanisms.
Following the discussion from the previous section, corporate governance may
play a vital role in sustainable international expansion. The new international market
will require additional corporate governance mechanisms to accompany the
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successful internationalisation process (as can be seen from Chapter 2). The
establishment of these new corporate governance mechanisms will have a direct
impact on the cost for the firm41. On the one hand, an investment into the restructuring
of the board of directors by adding additional non-executive, independent or foreign
directors, and introducing transparency and disclosure mechanisms or minority
shareholder protection mechanisms, should lead to an increase in firm’s performance
(Baysinger and Butler, 1985; Rosenstein and Wyatt, 1990; Brickley et al., 1994;
Durchin et al., 2009). This therefore suggests the existence of a positive linear
relationship between corporate governance mechanisms and a firm’s performance.
However, spending too much on corporate governance mechanisms may lead
to another extreme of the agency problem. Such “over-monitoring” generates costs,
harms managerial initiative, and, as a result, board members tend to make decisions
that lead to the increase in the size of the firm beyond its optimal level, or maintain
unutilized resources for increasing personal utility of status, power, compensation, and
prestige (Jensen et al., 1976; Stulz, 1990; Masulis, Wang, and Xie, 2007; Hope &
Thomas, 2008). Eventually, this will escalate the conflict between managers and
owners and will lead to corporate governance failures, which in turn will be negatively
correlated with the firm’s performance.
This introduces an important concept, that to mitigate the agency problem, the
firm should choose its corporate structure optimally in terms of its cost versus
profitability. Therefore, it is important to consider what would be the cost function of
implementing new corporate governance mechanisms when entering new
international markets.
41 Additional costs may be related to the restructuring of the corporate boards, which will correlate with the salaries and remunerations, or to the establishment of auditing and monitoring mechanisms.
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When viewed from the perspective that each additional international market that
has a higher level of corporate governance (developed economy) than a firm’s
domestic market (emerging market) will require some corporate governance
improvement or adjustments (Figure 3.1), it is possible conclude that as soon as a firm
enters its first international market, the cost of the implementation of new corporate
governance mechanisms will also increase. This positive relationship between cost
and a firm’s profitability will reach the optimal point at which the firm’s cost of
implementing additional corporate governance mechanisms will not yield any
additional benefit to the firm’s performance. The time interval during the optimization
will vary between firms and will depend on the firm’s characteristics and experience.
After the initial stage of internationalisation, the firm may continue with
geographical expansion and may enter another foreign market in which the corporate
governance mechanisms differ from the set of the corporate mechanisms that already
exist in the entrant’s firm. If these additional corporate governance mechanisms are
compulsory by the rules and regulations of the second foreign market, or the
complexity of the entrant’s firm increases due to geographical expansion, the
additional corporate governance mechanisms should be implemented by the entrant
firm and will once again increase the cost of introducing new corporate governance
mechanisms.
Following this explanation, it is possible to conclude that the cost for the
implementation of new corporate governance mechanisms is positively correlated with
internationalisation. The cost will start increasing from slow and steady implementation
of corporate governance mechanisms from the domestic market if the firm is operating
in a country with a poor level of corporate governance, followed by a steep acceleration
after the first international entry, and then followed by an increase at a decreasing rate
141
with each additional international market. Such a relationship between the cost and
the additional or new corporate governance mechanisms can be represented by cubic
function42.
42 It is important to state that the cost functions may be of three main types: linear cost functions, quadratic cost functions, and cubic cost function. The core difference among these types is the rate at which the cost changes, given the input variable (in the case of this thesis, this would be corporate governance mechanisms). If the cost function is linear, variable cost increases at a constant rate, which means that the quadratic cost function will have a diminishing return to the variable factor, while the cubic cost function will have both an increasing return to the variable factor in the beginning, the point at which the rate is constant (the inflection point), and, at the same time, a decreasing return to the variable factor. Different firms may adopt different cost functions based on their production functions, depending on their sector of production and firm structure. However, regardless of the cost function type, the increase in the variable factor will always increase the cost. Therefore, the introduction of new corporate governance mechanisms will increase the cost for the firm, regardless of its cost function. At the same time, each firm, regardless of its cost function, will go through an optimisation exercise. The academic literature acknowledges that this is positive, but the overall results that CG matters for a firm’s performance are robustly established in the literature.
Figure 3-2.Cost function of investment into corporate governance and its relationship
with profit maximization.
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The cost function represented in Figure 3.2 follows the logic from the previous
section. As soon as a firm enters a new international market with a higher level of
corporate governance in relation to its domestic market, it should improve its own
corporate governance structure beyond the fixed cost (a). This cost increase will
continue up to a certain point (flex point of the cubic function), at which the firm will
maximise its profit from the international market. And only by entering an additional
foreign market, will the cost restart its growth. The graph in Figure 3.2 represents the
equilibrium between the cost of implementing new corporate governance mechanisms
and the maximum profit that could be achieved by a firm that is using these corporate
governance instruments. Based on the graph, it can be clearly seen that overspending
and underspending on corporate governance mechanisms will not lead to profit
maximisation.
At the same time, the literature mentions that homogeneous firms use different
corporate governance mechanisms and still maximise their firm’s performance
(Hermalin,1994; Gibbons and Roberts, 2013). This suggests that a detailed corporate
structure will be individual, based on the firms’ objectives and structure. At the same
time, the national corporate governance codes that provide firms with the best
practices of good corporate governance and enforce certain corporate governance
mechanisms, will establish certain similarities between the firms that operate on the
same markets.
This indicates that the strategic decision that the entrant firm faces is to
establish an optimal level of corporate governance mechanisms that are required to
accompany successful (profitable) internationalisation. This strategic decision should
be based on costs associated with the introduction of new corporate governance
mechanisms, which in turn relate to the corporate governance standards of a foreign
143
country, the number of corporate governance mechanisms of the competitors43 that
are operating in this market, and the initial set of corporate governance mechanisms
that the entrant firm processes prior to the internationalisation process.
Methodology
To analyse that strategic decision on an optimal level of corporate governance
investment for the entrant firm, it is better to look at this decision-making process from
a game theory perspective. Game theory is a model for decision-making under
varying unpredictable conditions (uncertainty). Games are characterised as strategic
interactions between players. The strategy is a complete plan of actions, that includes
all possible options together with the outcome preferences (Dixit, Nalebuff, 2008). In
the academic literature the strategy that would predict the outcome of the game is
usually called a solution (Salkind, 2012) and the purpose of the game theory approach
is to explore and analyse different solutions, which are available for players in the
game. To justify the best possible solution the game theory modelling is using the
concept of ‘utility’, which refers to the preferred outcomes that may be different among
different players. The objective of such analysis is to identify the solution that would
maximise the utility of the player (Dixit, Skeath, Reiley, 2015). If the players are able
to solve the game is such a way that they optimise their utilities and none of the players
have an incentive to deviate from this solution that is called the equilibrium state. The
rest of this chapter will focus on identifying all the possible solutions (under perfect
and imperfect information) that the firms (players) will face and to establish, which
solutions will bring the companies towards the equilibrium state.
43 Homogeneous firms that are operating in the same sector and produce similar products / provide similar services.
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Low cost of corporate governance investment
I will start with a very simple game in which I assume that there are just two
firms: the entrant and the incumbent. Both firms are operating in the same sector and
produce homogeneous products. In the first game that I will analyse, I will assume that
both firms will decide at the same time (simultaneous game). The entrant firm has
already entered the market (the internationalisation has already occurred) and both
firms are competing purely on the level of corporate governance44 and thus have just
two strategies, either to set their corporate governance level “high” or “low”.
Before we analyse this game, it is important to highlight certain assumptions.
Firstly, I will assume that the game has perfect information, which means that both
firms are aware of each other’s strategies and the payoff structure is common
knowledge for both players prior to the game. This assumption simplifies the initial
steps of the analysis to find the Nash equilibrium in the first game. If we assume that
any player has doubts in terms of the information that he/she possesses this may
change the results of the analysis. If player one does not know the payoff structure of
the game, this fact should be made an integral part of the analysis and will change the
game to a game with asymmetric information45.
Secondly, we assume that they have the same cost of investment into
corporate governance mechanisms, which means that the cost functions in terms of
corporate governance mechanisms for both firms are identical and the cost of
investment into new corporate governance mechanisms is low.
44 The level of corporate governance will represent the set of corporate governance mechanisms that influence a firm’s profitability. The remaining of this chapter will refer to the firm with the higher level of corporate governance as the firm with the optimal set of corporate governance mechanisms, which are higher in comparison to the other firm. The low level of corporate governance will reflect the firm with the lower number of corporate governance mechanisms. 45 The game with asymmetric information will be discussed later in the analysis.
145
Thirdly, we assume that the market of entrance has the same corporate
governance level or lower than the domestic market of the entrant firm. This third
assumption will justify why the incumbent will have to make a decision on the
investment into corporate governance, because if the incumbent is operating in a
strong corporate governance market, that would force him to apply certain corporate
governance mechanisms and will make his corporate governance standards higher
than the entrant’s corporate governance. In this case, the entrant will have to catch up
with the incumbent to be competitive in the foreign market, regardless of the costs.
Fourthly, it is also important to highlight that both players of this game are
rational and determine to maximise their utility. The rationality assumption which is
widely applicable in the game theory assumes that the players are perfect calculators
and flawless followers of their best strategies. That means that a player has a
consistent set of payoffs over all the logically possible outcomes and calculates the
strategy that best services the player’s interest. From a strategic management
perspective, when the firm is facing a decision-making process (like
internationalisation), it will explore the vast number of available possibilities. After that
they will evaluate all the scenarios and will select the best possible outcome that they
can justify. In that case, it can be concluded that most of the time, the firm will act
rationally.
Taking into consideration the literature on corporate governance and a firm’s
profitability, it can be concluded that the increase in the number of corporate
governance mechanisms will increase the profitability of the firm. In the concept of
game theory, such a relationship can be represented in the form of payoffs46. The
46 The payoff will represent the value that is associated with each possible outcome. The higher the payoff, the better the outcome for the player. In the case of this chapter, the fact that corporate governance has a positive relationship with the firm’s profitability
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more a company invests into the establishment of corporate governance mechanisms,
the more profit (higher payoffs) it will receive. If the entrant firm matches the
incumbent’s decision of low investment into corporate governance, then they split the
profit equally (𝜋
2). If the entrant matches the decision of the incumbent of high
investment into corporate governance, then they will bear some cost of that investment
(c) but will still split the market. However, if the second firm does not match the decision
of the first, then the firm with higher corporate governance will be more competitive
and will have all the profit in the market for itself (), while the other firm will have a
negative impact on its performance and may even go out of the market in the long
term (𝛾)47, which means that 𝛾 < 0. The strategic form of the game is represented
below:
Figure 3-3. Simultaneous game under the low cost
Entrant
High Low
Incu
mb
en
t High 𝜋
2 -c ;
𝜋
2 -c 𝜋 − 𝑐 ; 𝛾
Low 𝛾 ; 𝜋 − 𝑐 𝜋
2 ;
𝜋
2
suggests that the higher the payoff, the higher the profit that the firm receives by making a certain strategic move. Later in the chapter, when the firm will face a decision-making process based on asymmetric information, this outcome will be weighted by the probability of that outcome, introducing the concept of expected payoff. To quantify the degree of preference that the firm will face in the game of asymmetric information, the game-theoretic modelling suggests using the utility function (Dixit, Skeath, Reiley, 2015). The game theory approach does not need to have a specific utility function; however, it will require a payoff structure that would be coherent with the fact that the increase in corporate governance mechanisms will represent higher payoffs. 47 In this case, the player who selects a low level of corporate governance, while his opponent chooses a high level of corporate governance, will lose some of his market share to the other player, which will be reflected as a negative payoff. In that sense, the incumbent firm may suffer from the internationalisation of the entrant.
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The payoff structure under the low cost of corporate governance investment is such
that:
𝜋 > 𝜋 − 𝑐 > 𝜋2⁄ > 𝜋
2⁄ − 𝑐 > 𝛾
The Nash equilibrium of this game would be for the incumbent to play “high”
and for the entrant to play “high”, which will yield a payoff of 𝜋
2− 𝑐 for both firms. In this
game, both players have a dominant strategy – “high” - and the payoff structure is
such that even by playing their dominant strategy, neither of the players will achieve
the most profitable outcome. This game is a typical prisoner’s dilemma. From the
perspective of corporate governance, this result supports the argument that if a firm’s
performance is positively correlated to a corporate governance level, then the safest
option for the entrant firm would be to adopt certain corporate governance
mechanisms, regardless of the competitor’s decision.
Let me now consider the scenario that such a game is not simultaneous but
sequential. In this case, the incumbent will move first and select the level of corporate
governance, either high or low. The entrant will have a second move and will also
select the level of his corporate governance at either high or low. All the assumptions
that were stated earlier will hold. Therefore, the entrant will know for sure if the
incumbent has selected a high corporate governance standard or a low corporate
governance standard in the first stage of the game. The payoff structure is also similar
to the simultaneous game. If the entrant firm matches the incumbent’s decision of low
investment into corporate governance (low, low), then they split the profit equally (𝜋
2).
If the entrant matches the decision of the incumbent of high investment into corporate
governance, then they will bear some of the cost of that investment (c), but will still
split the market (high, high). However, if the second firm does not match the decision
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of the first, then the firm with higher corporate governance will be more competitive
and will have all the profit in the market for itself (), while the firm with the low
corporate governance level will have a certain loss (𝛾) and vice versa. The extensive
form of this game, with the payoffs, is represented below.
The payoff structure is such that:
𝜋 > 𝜋 − 𝑐 > 𝜋2⁄ > 𝜋
2⁄ − 𝑐 > 𝛾
Using the backward induction, we can see that at the top decision node of the
entrant, he will choose strategy “high”. At the bottom node, he will also select strategy
Figure 3-4.Sequential game with perfect information under the low cost
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“high”. Knowing the payoff structure and all the strategies that are available for the
entrant, the incumbent will invest in high corporate governance. The rollback
equilibrium selects high corporate governance for the incumbent, and always selects
high corporate governance for the entrant. From Figure 3.4, we can see that for the
incumbent to stay competitive, he will need to introduce new corporate governance
mechanisms when a second player is entering the market, even though this will not
be the most profitable result for either firm, which is the case when the incumbent does
not invest into corporate governance (playing low), while the entrant matches his
action and also plays strategy low.
In both the simultaneous and consequential games represented above, given
perfect information where both players know each other’s payoffs and actions, it is
possible to draw the same conclusion. When the incumbent is initially operating in the
market with a low corporate governance level and the entrant comes from a similar
market, they will both choose to select a high level of corporate governance to stay
competitive, even though the better collective outcome would be not to introduce any
extra corporate governance mechanisms, therefore keeping the cost to a minimum
and sharing the maximum profit.
However, in a more realistic set-up, the entrant will not know for sure if the
incumbent has strong or weak corporate governance, therefore the assumption of
perfect information will not hold. In game theory terms, this will become a signalling
game and will change how the game tree will look.
Let us look at the following game. Firstly, its nature is going to decide the type
(𝑡 ∈ {𝑡1, 𝑡2}) of the incumbent with the certain probability (p for the type 1 and 1-p for
the second type). The first type (𝑡1) is the incumbent with strong corporate governance
standards. The second type (𝑡2) is when the incumbent’s corporate governance is
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weak. The incumbent knows for sure if he is type 1 or type 2, and after observing this
information, it will be the incumbent’s turn to select either a high corporate governance
standard or a low one. In the second stage of this game, it is for the entrant to choose
his strategy and either play strategy high or low. The payoff structure for this game
stays the same: 𝜋 > 𝜋 − 𝑐 > 𝜋2⁄ > 𝜋
2⁄ − 𝑐 > 𝛾, assuming that the cost for the
entrant to catch up with the incumbent’s corporate governance in not high. The game
tree for this updated scenario is represented in Figure 3.5.
Let us look at the right-hand side of the tree. Here, the incumbent, depending
on his type, will select a high level of corporate governance (H); however, the entrant
will not know if the incumbent’s corporate governance is actually high or low, which is
determined by nature in the first stage of the game. Therefore, if the incumbent
observes that he is a type 1, and then plays his strategy “high”, he is signalling to the
entrant that he actually has strong corporate governance. The opposite of that
scenario is that the incumbent will be type 2, but will behave as a firm with strong
Figure 3-5. Sequential game with imperfect information under the low cost
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corporate governance and will therefore be bluffing in order to push the entrant into
the strategy of not matching the incumbent’s corporate governance, and thus will
remain competitive in the market. At the same time, a firm signalling that it has high
corporate governance will have an extra cost, and therefore will reflect on the payoff
of the incumbents (𝐶𝐼(𝑚𝑖𝑚𝑖𝑐), 𝑤ℎ𝑒𝑟𝑒 0 < 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐) <𝜋
2). The important assumption here
is that for that bluff to be credible, the cost of the incumbent to mimic type 1 should be
less than the cost of the entrant (𝐶𝐸) to catch up with the incumbent’s corporate
governance (𝐶𝐼(𝑚𝑖𝑚𝑖𝑐) < 𝐶𝐸). If the incumbent mimics the action of the firm with the
high level of corporate governance while his corporate governance is actually low, he
will still receive some benefit of that move, represented by 𝜃. This reward is some
fraction of the market that he will receive based on his investment in corporate
governance. This reward is between 0 < 𝜃 <𝜋
2 and it should be subtracted from the
entrant’s payoff. As the entrant cannot truly distinguish between the types of the
incumbent, this is represented in the diagrams as “information set 1”.
On the left-hand side, the incumbent is playing strategy “low”, depending on his
type. When the incumbent initially has weak corporate governance (type 2) and is
playing “low”, it is possible to label this strategy as “honest”, meaning that the
incumbent will not lie about his type, and if he has weak corporate governance, he will
demonstrate low corporate governance investment. On the contrary, if nature will
determine that the incumbent is type 1 and has strong corporate governance, and the
incumbent will play action “low”, that means that he is hiding the real information and
trying to push the entrant into a trap. Hiding the true information will also come at a
cost for the incumbent (𝐶𝐼(𝑙𝑖𝑒), 𝑤ℎ𝑒𝑟𝑒 0 < 𝐶𝐼(𝑙𝑖𝑒) <𝜋
2). The trap here can be devastating
for the entrant, because if he follows the path in which nature determines that the
incumbent’s type is 𝑡1, the incumbent plays “low” and the entrant chooses to match
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the incumbent’s decision (to play low), that will lead to a payoff structure such that the
incumbent will remain as the monopolist (payoff of 𝜋 − 𝐶𝐼(𝑙𝑖𝑒)) and the entrant will be
unsuccessful in the market and will have the certain cost that can arise from
unsuccessful internationalisation (payoff of 𝛾 ). Once again, the entrant cannot directly
observe the type of the incumbent, and therefore we can see the second information
set on the left-hand side of the tree. It is also important to highlight that the incumbent’s
cost of hiding information is less than his cost of mimicking the actions of the firm with
the high level of corporate governance.
To solve this sequential game of incomplete information, it is important to
introduce a concept of beliefs. That means that the players of this game must not only
use their best strategies, given their information, but must also draw correct inferences
(update their beliefs via the Bayes rule when possible) by observing the actions of the
opponent. When the optimal decisions at all nodes will be
imposed, this will be a perfect Bayesian equilibrium (PBE).
Separating Equilibrium Subcase One (Low Cost)
A separating equilibrium comes with the assumption that each type of player 1
will choose a unique action, which means that the one type will choose one strategy,
while the other type will choose the opposite strategy. The second player observes
that action and, based on his belief, will be able to determine in which node of the tree
he is located. Therefore, if the incumbent plays a certain action, the entrant’s belief is
that this action can only be played by a certain type of incumbent. Based on this logic,
there are two potential cases in which the incumbent can select his actions. Case
number one is when the incumbent is “honest” and he plays action “high” when he is
type 1 and action “low” when he is type 2. The second case of the separating
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equilibrium that should be considered is when the incumbent is bluffing or hiding
information. In other words, he is playing “low” if he is type 1 and “high” if he is type 2.
Let us consider the first case and the incumbent’s strategy (𝜎𝐼) depending on
the type he is playing.
𝜎𝐼(𝑡) = {𝐻 𝑖𝑓 𝑡 = 𝑡1
𝐿 𝑖𝑓 𝑡 = 𝑡2
In this case, the entrant will update his beliefs based on the idea that only a certain
type of the incumbent will play this action, which means that the probability for the
incumbent being type 1 and playing strategy “high” is equal to 1 (p=1), and the
probability of the incumbent being type 2 and playing strategy “high” is equal to 0 (1-
p) and vice versa. Therefore, the beliefs could be updated via the Bayes rule:
𝜇1(𝑡1) = Pr(𝐻𝐼|𝑡1) ∗ Pr (𝑡1)
Pr (𝐻)=
Pr(𝐻|𝑡1) ∗ Pr (𝑡1)
Pr(𝐻|𝑡1) ∗ Pr(𝑡1) + Pr(𝐻|𝑡2) ∗ Pr (𝑡2)
Where: Pr(𝐻) = ∑ Pr(𝐻|𝑡𝑖) ∗ Pr (𝑡𝑖)𝑡=𝑖
𝑃𝑟(𝑡1) = 𝑝 and 𝑃𝑟(𝑡2) = 1 − 𝑝
Substituting the probabilities will yield:
𝜇1(𝑡1|𝐻) =1 ∗ 𝑝
1 ∗ 𝑝 + 0 ∗ (1 − 𝑝)= 1
Therefore: 𝜇1(𝑡1|𝐻) = 1; 𝜇1(𝑡2|𝐻) = 0
In the same way, it is possible to update the beliefs that type 2 will always play the
strategy “low” and type 1 will never play this strategy:
𝜇2(𝑡1|𝐿) = 0 ; 𝜇2(𝑡2|𝐿) = 1
Based on the beliefs of the entrant and the corresponding types of the incumbent, it is
possible to calculate the expected utility for the entrant 𝔼𝑈𝐸, when the incumbent is
playing action “high” and when he plays action “low”.
Identifying the best response for the entrant against strategy “high”:
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(1) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜇1(𝑡1|𝐻𝐼) ∗ 𝑈(𝐻𝐸|𝐻𝐼; 𝑡1) + 𝜇1(𝑡2|𝐻𝐼) ∗ 𝑈(𝐻𝐸|𝐻𝐼; 𝑡2)
(2) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝜇1(𝑡1|𝐻𝐼) ∗ 𝑈(𝐿𝐸 , 𝐻𝐼; 𝑡1) + 𝜇1(𝑡2|𝐻𝐼) ∗ 𝑈(𝐿𝐸|𝐻𝐼; 𝑡2)
Inputting the corresponding beliefs and payoffs will yield that:
(1)𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 1 ∗ (𝜋
2− 𝐶𝐸) + 0 ∗ (𝜋 − 𝜃−𝐶𝐸)
(1) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) =𝜋
2− 𝐶𝐸
(2) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 1 ∗ 𝛾 + 0 ∗ (𝜋
2− 𝜃)
(2) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝛾
Based on the expected utility and the payoff structure that was defined earlier, it is
possible to conclude that 𝑈𝐸(𝐻𝐸 , 𝐻𝐼) > 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼). Therefore, when the incumbent
plays strategy “high”, the entrant will choose to play “high” as well, based on the belief
that only the incumbent with strong corporate governance (type 1) will choose that
action. This best response can be written as follows:
𝐵𝑅𝐸(𝐻𝐼) = 𝐻𝐸
Now we need to calculate the expected utility and identify the best response for
the second player against strategy “low”:
(3) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜇2(𝑡1|𝐿𝐼) ∗ 𝑈(𝐻𝐸|𝐿𝐼; 𝑡1) + 𝜇2(𝑡2|𝐿𝐼) ∗ 𝑈(𝐻𝐸|𝐿𝐼; 𝑡2)
(4) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝜇2(𝑡1|𝐿) ∗ 𝑈(𝐿𝐸|𝐿𝐼; 𝑡1) + 𝜇2(𝑡2|𝐿𝐼) ∗ 𝑈(𝐻𝐸|𝐿𝐼; 𝑡2)
Inputting the corresponding beliefs and payoffs will yield that:
(3) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 0 ∗ (𝜋
2− 𝐶𝐸) + 1 ∗ (𝜋−𝐶𝐸)
(3) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋−𝐶𝐸
(4) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 0 ∗ 𝛾 + 1 ∗𝜋
2
(4) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝜋
2
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In this case the best response for the entrant will be to select strategy “high” as
𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) > 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼), if he believes that only a type 2 incumbent will play the
strategy “low”. Therefore, the best response for the entrant would be
𝐵𝑅𝐸(𝐿𝐼) = 𝐻𝐸
Based on the best responses which are calculated above, it can be concluded that the
entrant will have a dominant strategy of playing strategy “high”, regardless of the
incumbent’s actions. The strategies that we concluded based on the expected utilities
and beliefs are highlighted in red in the tree diagram below (Figure 3.6).
The final step to determine if that is the PBE is to check that the incumbent has
no incentive to deviate. First, we will look at a type 1 incumbent and compare his
payoffs of playing strategy “high”, knowing that the entrant will play “high”, and the
incumbent who will play “low” while the entrant chooses “high”. Comparing the payoffs,
we can identify that the incumbent will prefer to play “high” as his payoff is greater (
Figure 3-6. Separating equilibrium subcase 1 (Low Cost)
156
𝜋
2>
𝜋
2− 𝐶𝐼(𝑙𝑖𝑒) ). Thus, there is no incentive for the incumbent to deviate from the
equilibrium path.
We will now consider the type 2 incumbent who would choose strategy “low”
when the entrant selects “high”. In this scenario, by playing “low” the incumbent will
receive the payoff of 𝛾 and by playing the strategy “high” he will receive the payoff of
𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐). Therefore, there are two possible outcomes. Proposition one is that if the
incumbent’s reward for mimicking the action of the firm with strong corporate
governance is higher than the cost of this action, then there is an incentive to defect
from the equilibrium path (𝛾 < 0 < 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐)). Proposition two is that if the cost of
mimicking the actions of the firm with high corporate governance is high, then there is
no incentive to deviate under the condition that 𝛾 ≥ 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐).
As one of the assumptions is that the value of the reward is strictly between
zero and half of the potential market (0 < 𝜃 <𝜋
2 ), there is an incentive for the
incumbent to deviate, as proposition one will hold. Therefore, there is no perfect
Bayesian equilibrium in this case.
Separating Equilibrium Subcase Two (Low Cost)
The second case of separating the equilibrium that should be considered is when the
incumbent is bluffing or hiding information. In other words, he is playing “low” if he is
type 1 and “high” if he is type 2. Therefore, the strategy for the incumbent will be
𝜎𝐼(𝑡) = {𝐿 𝑖𝑓 𝑡 = 𝑡1
𝐻 𝑖𝑓 𝑡 = 𝑡2
In this case, the entrant will update his beliefs based on the idea that only a certain
type of incumbent will play this action, which means that the probability of the
incumbent being type 1 and playing strategy “low” is equal to 1 (p=1), and the
157
probability of being type 1 and playing strategy “high” is equal to 0 (1-p) and vice versa.
Therefore, the beliefs could be updated via the Bayes rule, in a similar manner to the
first case of separating equilibrium.
𝜇1(𝑡1|𝐻𝐼) = 0 ; 𝜇1(𝑡2|𝐻𝐼) = 1
𝜇2(𝑡1|𝐿𝐼) = 1 ; 𝜇2(𝑡2|𝐿𝐼) = 0
Knowing that only a certain type of incumbent will play strategy “high”, and another
type will play strategy “low”, with the corresponding belief for the entrant, it is possible
to calculate the entrant’s expected utility and identify the best responses. Firstly, I will
look at the right-hand side of the original tree, where different incumbent types will play
strategy “high”:
(5) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜇1(𝑡1|𝐻𝐼) ∗ 𝑈(𝐻𝐸| 𝐻𝐼; 𝑡1) + 𝜇1(𝑡2|𝐻𝐼) ∗ 𝑈(𝐻𝐸|𝐻𝐼; 𝑡2)
(6) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝜇1(𝑡1|𝐻𝐼) ∗ 𝑈(𝐿𝐸| 𝐻𝐼; 𝑡1) + 𝜇1(𝑡2|𝐻𝐼) ∗ 𝑈(𝐿𝐸|𝐻𝐼; 𝑡2)
(5)𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 0 ∗ (𝜋
2− 𝐶𝐸) + 1(𝜋 − 𝜃 − 𝐶𝐸)
(5)𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜋 − 𝜃 − 𝐶𝐸
(6) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 0 ∗ 𝛾 + 1 ∗ (𝜋
2− 𝜃)
(5) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) > (6) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
Therefore, the best response for the entrant against strategy “low” will be to play
strategy “high”, 𝐵𝑅𝐸(𝐻𝐼) = 𝐻𝐸
Now let us look at the left-hand side of the original tree, in which two different
types of the incumbent will play strategy “low”. Based on the beliefs that were defined
in the beginning of this subcase, the entrant will assume that only the second type of
incumbent would play strategy “low”. The expected utility for the second player is:
(7) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜇2(𝑡1|𝐿𝐼) ∗ 𝑈(𝐻𝐸| 𝐿𝐼; 𝑡1) + 𝜇2(𝑡2|𝐿𝐼) ∗ 𝑈(𝐻𝐸|𝐿𝐼; 𝑡2)
(8) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝜇2(𝑡1|𝐿𝐼) ∗ 𝑈(𝐿𝐸| 𝐿𝐼; 𝑡1) + 𝜇2(𝑡2|𝐿𝐼) ∗ 𝑈(𝐿𝐸|𝐿𝐼; 𝑡2)
158
(7) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 1 ∗ (𝜋
2− 𝐶𝐸) + 0 ∗ 𝜋 − 𝐶𝐸
(7) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋
2− 𝐶𝐸
(8) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 1 ∗ 𝛾 + 0 ∗𝜋
2
(8) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝛾
(7) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) > (8) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
Therefore, the best response for the second player (entrant) against strategy “low” will
be always to play strategy “high”. The tree diagram representing the beliefs, payoffs
and the best responses is represented below.
To identify if this set of sequential strategies and beliefs is indeed the perfect
Bayesian equilibrium, it is vital to check that the incumbent has no incentive to deviate
off the equilibrium path. Starting with the type 1 incumbent, his payoff along the
equilibrium path will be 𝜋
2− 𝐶𝐼(𝑙𝑖𝑒). If the type 1 incumbent deviates and selects strategy
“high” based on the best response of the entrant, the incumbent will have the payoff
Figure 3-7. Separating Equilibrium Subcase 2 (Low Cost)
159
of 𝜋
2. Therefore, the incumbent has the incentive to defect from his strategy “low” when
he is type 1, and play strategy “high”:
𝜋
2 >
𝜋
2− 𝐶𝐼(𝑙𝑖𝑒)
The type 2 incumbent, whose default strategy based on the beliefs would be to
play “high”, will receive the payoff of 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐). The potential deviation for the
incumbent of this type would be to play strategy “low”, and knowing that the entrant’s
best response in this case would be to play strategy “high”, the incumbent’s payoff
would be equal to 𝛾. Therefore, there are two potential outcomes depending on the
level of incumbent’s reward for mimicking the behaviour of the strong type (𝜃) and the
level of cost (𝐶𝐼(𝑚𝑖𝑚𝑖𝑐)). Proposition one is that if the incumbent’s reward for mimicking
the action of the firm with strong corporate governance is higher than the cost of this
action, then there is no incentive to defect from the equilibrium path (𝛾 < 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐)).
Proposition two is that if the cost of mimicking the actions of the firm with high
corporate governance is higher or equal to the reward that the incumbent can receive,
then there is no incentive to deviate as 𝛾 ≥ 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐). As 𝜃 is always greater than
0, it is possible to conclude that there is no incentive to defect from the equillibrium
path, and the type 2 incumbent will stick to the strategy “high”.
Conlcuding the analysis on the second subcase of seperating equilibrium, we can
state that the perfect Bayesian equilibrium does not exist, as the type 1 incumbent will
always have an incentive to defect.
160
Pooling Equilibrium Subcase Three (Low Cost)
In a pooling PBE, both types of incumbent will choose the same message, so
that they cannot be distinguished by the second player based on their behaviour.
Therefore, there are two potential cases in which the incumbent pools his actions: the
first is in the strategy “high”, regardless of his type, or the second case is when he
selects “low”, regardless of his type. Starting the analysis from the scenario when the
incumbent is pulling on strategy “high”, his strategy can be represented as:
𝜎𝐼(𝑡) = {𝐻 𝑖𝑓 𝑡 = 𝑡1
𝐻 𝑖𝑓 𝑡 = 𝑡2
Following the procedure to identify if the pooling equilibrium exists, the entrant’s beliefs
should be updated via the Bayes rule whenever possible. Considering the beliefs that
the entrant will have about the incumbent when observing his strategy “high”,
regardless of his type, the beliefs will be:
𝜇1(𝑡1|𝐻) = Pr(𝐻|𝑡1) ∗ Pr (𝑡1)
Pr (𝐻)=
Pr(𝐻|𝑡1) ∗ Pr (𝑡1)
Pr(𝐻|𝑡1) ∗ Pr(𝑡1) + Pr(𝐻|𝑡2) ∗ Pr (𝑡2)
𝜇1(𝑡2|𝐻) = Pr(𝐻|𝑡2) ∗ Pr (𝑡2)
Pr (𝐻)=
Pr(𝐻|𝑡2) ∗ Pr (𝑡2)
Pr(𝐻|𝑡2) ∗ Pr(𝑡2) + Pr(𝐻|𝑡1) ∗ Pr (𝑡1)
From the structure of the game we know that 𝑃𝑟(𝑡1) = 𝑝 and 𝑃𝑟(𝑡2) = 1 − 𝑝. And
based on the strategy of the first player, Pr(𝐻|𝑡1) = 1 and Pr(𝐻|𝑡2) = 1 . Therefore,
the beliefs will be
161
𝜇1(𝑡1|𝐻) = 𝑝
𝜇1(𝑡2|𝐻) = 1 − 𝑝
If, however, the incumbent will play strategy L (regardless of his type), which never
occurs along the equilibrium path, the Bayes’ rule will not apply because:
𝜇2(𝑡1|𝐿) ≠ Pr(𝐿|𝑡1) ∗ Pr(𝑡1)
Pr(𝐿)
𝜇2(𝑡2|𝐿) ≠ Pr(𝐿|𝑡2) ∗ Pr(𝑡2)
Pr(𝐿)
Where: Pr (𝐿) = 0
In this case, we reach arbitrarily assigned beliefs (Fudenberg & Tirole, 1991). It is not
possible at this point to know which, if any, beliefs regarding the equilibrium path
behaviour will sustain a pooling equilibrium. Therefore, for now, we assume that:
𝜇2(𝑡1|𝐿) = 𝜆
𝜇2(𝑡2|𝐿) = 1 − 𝜆
𝑊ℎ𝑒𝑟𝑒: 𝜆 ∈ [0,1]
Now we can start calculating the expected utility of the entrant when the incumbent is
pooling his types and playing action “high”:
(9) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜇1(𝑡1|𝐻𝐼) ∗ 𝑈(𝐻𝐸|𝐻𝐼; 𝑡1) + 𝜇1(𝑡2|𝐻𝐼) ∗ 𝑈(𝐻𝐸|𝐻𝐼; 𝑡2)
(10) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝜇1(𝑡1|𝐻𝐼) ∗ 𝑈(𝐿𝐸|𝐻𝐼; 𝑡1) + 𝜇1(𝑡2|𝐻𝐼) ∗ 𝑈(𝐿𝐸|𝐻𝐼; 𝑡2)
Substituting the beliefs and payoffs:
(9) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝑝 ∗ (𝜋
2− 𝐶𝐸) + (1 − 𝑝) ∗ ( 𝜋 − 𝜃 − 𝐶𝐸)
(9) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜋
2𝑝 − 𝐶𝐸𝑝 + 𝜋 − 𝜃 − 𝐶𝐸 − 𝜋𝑝 + 𝜃𝑝 + 𝐶𝐸𝑝
(9) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜋 −𝜋
2𝑝 − 𝐶𝐸 − 𝜃 + 𝜃𝑝
162
(10) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝑝 ∗ 𝛾 + (1 − 𝑝) ∗ (𝜋
2− 𝜃)
(10) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝑝 ∗ 𝛾 +𝜋
2− 𝜃 −
𝜋
2𝑝 + 𝜃𝑝
The best response (BR) for the entrant against the incumbent’s strategy “high” will
depend on which expected utility is higher. Therefore, there are three conditions:
𝐵𝑅𝐸(𝐻𝐼) = {
𝐻𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) > 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
𝐿𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) < 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
𝑝𝐻𝐸 + (1 − 𝑝)𝐿𝐸) 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
To find the best response of the entrant, we can start from the indifference condition:
(9) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = (10) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
(9) 𝜋 −𝜋
2𝑝 − 𝐶𝐸 − 𝜃 + 𝜃𝑝 = (10) 𝑝 ∗ 𝛾 +
𝜋
2− 𝜃 −
𝜋
2𝑝 + 𝜃𝑝
Knowing that the probability of 𝑝 ∈ [0,1], it is possible to approach this solution by
substituting the values of 𝛼 into the equation. Let us look at the first proposition that
𝑝 = 1 (proposition one):
(9) 𝜋 −𝜋
2− 𝐶𝐸 − 𝜃 + 𝜃 = (10) 𝛾 +
𝜋
2− 𝜃 −
𝜋
2+ 𝜃
(9) 𝜋
2− 𝐶𝐸 = (10) 𝛾
Therefore, the entrant would be indifferent as his payoff of 𝜋
2− 𝐶𝐸 will be equal to 𝛾.
However, taking into account the payoff structure that was defined at the beginning of
the analysis 𝜋 > 𝜋 − 𝑐 > 𝜋2⁄ > 𝜋
2⁄ − 𝑐 > 𝛾 the dominant strategy for the entrant
would be to play action “high”: 𝐵𝑅𝐸(𝐻𝐼) = 𝐻𝐸
The opposite case (proposition two) is when 𝑝 = 0.
(9) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = (10) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
(9) 𝜋 −𝜋
2𝑝 − 𝐶𝐸 − 𝜃 + 𝜃𝑝 = (10)𝑝 ∗ 𝛾 +
𝜋
2− 𝜃 −
𝜋
2𝑝 + 𝜃𝑝
163
(9) 𝜋 − 𝐶𝐸 − 𝜃 = (10) 𝜋
2− 𝜃
As 𝜃 is the constant that is the same on both sides, it can be removed, and the final
payoff for the indifference condition will be:
(9) 𝜋 − 𝐶𝐸 = (10) 𝜋
2
As in proposition one, for this statement to be true the entrant should face the high
cost of corporate governance. Based on the predefined payoff structure of the case,
the entrant’s strategy “high” will yield a higher payoff: (9) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) >
(10) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼), therefore the entrant’s best response would be to play action “high”:
𝐵𝑅𝐸(𝐻𝐼) = 𝐻𝐸.
Consequently, if the incumbent is pooling on strategy “high”, the best response for the
entrant would also be to set his corporate governance “high”.
Now it is important to look at the actions of the entrant off the equilibrium path,
which is to identify what would be the best response of the entrant in case of the type
1 incumbent playing strategy “low”.
(11) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜇2(𝑡2|𝐿𝐼) ∗ 𝑈(𝐻𝐸|𝐿𝐼; 𝑡1) + 𝜇2(𝑡2|𝐻𝐼) ∗ 𝑈(𝐻𝐸|𝐿𝐼; 𝑡2)
(12) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝜇2(𝑡2|𝐿𝐼) ∗ 𝑈(𝐿𝐸|𝐿𝐼; 𝑡1) + 𝜇2(𝑡2|𝐻𝐼) ∗ 𝑈(𝐿𝐸|𝐿𝐼; 𝑡2)
(11) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜆 ∗ (𝜋
2− 𝐶𝐸) + (1 − 𝜆) ∗ ( 𝜋 − 𝐶𝐸)
(11) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋 −𝜋
2𝜆 − 𝐶𝐸
(12) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝜆 ∗ 𝛾 + (1 − 𝜆) ∗𝜋
2
(12) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝜆 ∗ 𝛾 +𝜋
2−
𝜋
2𝜆
164
In this case, the best response (BR) for the entrant against the incumbent’s strategy
“low” will depend on which expected utility is higher. Therefore, there are 3 conditions:
𝐵𝑅𝐸(𝐿𝐼) = {
𝐻𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) > 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
𝐿𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) < 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
𝜆𝐻𝐸 + (1 − 𝜆)𝐿𝐸) 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
To find the best response of the entrant, we can start from the indifference condition:
(11)𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = (12)𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
Again, we will have to consider two different propositions based on the probability of
𝜆. Proposition one is that 𝜆 = 1
(11)𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋 −𝜋
2∗ 1 − 𝐶𝐸
(11)𝜋
2− 𝐶𝐸
(12)𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 1 ∗ 𝛾 +𝜋
2−
𝜋
2∗ 1
(12)𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝛾
The result for the incumbent under proposition one is that he will always play strategy
“high”, as 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) > 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
Under the second proposition, 𝜆 = 0:
(11)𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋 −𝜋
2∗ 0 − 𝐶𝐸
(11) 𝜋 − 𝐶𝐸
(12)𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 0 ∗ 𝛾 +𝜋
2−
𝜋
2∗ 0
(12)𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) =𝜋
2
165
As the entrant’s cost is low, playing high would once again be the dominant strategy
𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) > 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼). The equilibrium paths are shown in Figure 3.8.
To understand if the pooling equilibrium exists, we must now make sure that as
a result of the actions of player two (the entrant), the incumbent does not have the
incentive to deviate. Therefore, if the incumbent is pooling on his strategy “high” while
he is a type 1 player, he will end up with the payoff 𝜋
2. However, if he deviates from
that path and plays strategy “low” while being a type 1 player, his payoff based on the
best response of the entrant would be 𝜋
2− 𝐶𝐼(𝑙𝑖𝑒). Comparing these two payoffs, the
incumbent would be better off by staying on the equilibrium path, and therefore will
have no incentive to deviate.
If the incumbent is type 2 and is pooling on strategy high, his payoff, based on
the best response of the entrant, would be 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐). The alternative path for the
Figure 3-8. Pooling Equilibrium Subcase 3 (Low Cost)
166
type 2 incumbent would be to play strategy “low”, and, in this case, it would yield a
payoff of 𝛾. Therefore, it can be concluded that the pooling PBE will exist as:
𝛾 < 0 < 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐)
Pooling Equilibrium Sub-Case Four (Low Cost)
Let us now consider the second scenario of pooling equilibrium, in which the
incumbent is pooling on his strategy “low”:
𝜎𝐼(𝑡) = {𝐿 𝑖𝑓 𝑡 = 𝑡1
𝐿 𝑖𝑓 𝑡 = 𝑡2
Following the procedure to identify if the pooling equilibrium exists, the entrant’s beliefs
should be updated via the Bayes rule whenever possible. Starting from the beliefs that
the entrant will have about the incumbent when observing his strategy “low”,
regardless of his type, the beliefs will be:
𝜇2(𝑡1|𝐿) = Pr(𝐿|𝑡1) ∗ Pr (𝑡1)
Pr (𝐿)=
Pr(𝐿|𝑡1) ∗ Pr (𝑡1)
Pr(𝐿|𝑡1) ∗ Pr(𝑡1) + Pr(𝐿|𝑡2) ∗ Pr (𝑡2)
𝜇2(𝑡2|𝐿) = Pr(𝐿|𝑡2) ∗ Pr (𝑡2)
Pr (𝐿)=
Pr(𝐿|𝑡2) ∗ Pr (𝑡2)
Pr(𝐿|𝑡2) ∗ Pr(𝑡2) + Pr(𝐿|𝑡1) ∗ Pr (𝑡1)
From the structure of the game, we know that 𝑃𝑟(𝑡1) = 𝑝 and 𝑃𝑟(𝑡2) = 1 − 𝑝. Based
on the strategy of the first player, Pr(𝐿|𝑡1) = 1 and Pr(𝐿|𝑡2) =1. Therefore, the beliefs
will be
𝜇2(𝑡1|𝐿) = 𝑝
𝜇2(𝑡2|𝐿) = 1 − 𝑝
167
If, however, the incumbent plays strategy H (regardless of his type), which never
occurs along the equilibrium path, the Bayes’ rule will not apply, because:
𝜇1(𝑡1|𝐻) ≠ Pr(𝐻|𝑡1) ∗ Pr(𝑡1)
Pr(𝐻)
𝜇1(𝑡2|𝐻) ≠ Pr(𝐻|𝑡2) ∗ Pr(𝑡2)
Pr(𝐻)
Where: Pr (𝐻) = 0
In this case, we reach arbitrarily assigned beliefs. It is not possible at this point to know
which, if any, beliefs regarding the equilibrium path behaviour will sustain a pooling
equilibrium. Therefore, for now we assume that:
𝜇1(𝑡1|𝐻) = 𝜆
𝜇1(𝑡2|𝐻) = 1 − 𝜆
𝑊ℎ𝑒𝑟𝑒: 𝜆 ∈ [0,1]
Now we can start calculating the expected utility of the entrant when the incumbent is
pooling his types and playing action “low”:
(13) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜇2(𝑡2|𝐿𝐼) ∗ 𝑈(𝐻𝐸|𝐿𝐼; 𝑡1) + 𝜇2(𝑡2|𝐻𝐼) ∗ 𝑈(𝐻𝐸|𝐿𝐼; 𝑡2)
(14) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝜇2(𝑡2|𝐿𝐼) ∗ 𝑈(𝐿𝐸|𝐿𝐼; 𝑡1) + 𝜇2(𝑡2|𝐻𝐼) ∗ 𝑈(𝐿𝐸|𝐿𝐼; 𝑡2)
(13) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝑝 ∗ (𝜋
2− 𝐶𝐸) + (1 − 𝑝) ∗ ( 𝜋 − 𝐶𝐸)
(13) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋 −𝜋
2𝑝 − 𝐶𝐸
(14) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝑝 ∗ 𝛾 + (1 − 𝑝) ∗𝜋
2
168
(14) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝑝 ∗ 𝛾 +𝜋
2−
𝜋
2𝑝
In this case, the best response (BR) for the entrant against incumbent’s strategy “low”
will depend on which expected utility is higher. Therefore, there are three conditions:
𝐵𝑅𝐸(𝐿𝐼) = {
𝐻𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) > 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
𝐿𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) < 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
𝑝𝐻𝐸 + (1 − 𝑝)𝐿𝐸) 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
Similar to the first case of pooling equilibrium, it is important to consider two extreme
cases when 𝑝 = 1 and 𝑝 = 0. In the first proposition, let us consider that 𝑝 = 1
Under this condition, the best response of the entrant would be:
(13) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋 −𝜋
2∗ 1 − 𝐶𝐸
(13) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) =𝜋
2− 𝐶𝐸
(14) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 1 ∗ 𝛾 +𝜋
2−
𝜋
2∗ 1
(14) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝛾
Therefore, under proposition one, the entrant’s expected utility to play strategy “high”
is always greater than his expected utility to play strategy “low”. Thus, for the entrant,
“high” is the dominant strategy.
The second proposition is that 𝑝 = 0. Under this criterion, the expected utility of
playing strategy “high” and “low” for the entrant, while the incumbent is pooling on his
strategy “low”, would be:
(13) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋 −𝜋
2∗ 0 − 𝐶𝐸
(13) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋 − 𝐶𝐸
(14) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 0 ∗ 𝛾 +𝜋
2−
𝜋
2∗ 0
169
(14) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝜋
2
Based on the payoff structure that the cost implementation of new corporate
governance mechanisms is low ( 𝜋 > 𝜋 − 𝑐 > 𝜋2⁄ > 𝜋
2⁄ − 𝑐 > 𝛾), it can be
concluded that “high” is still the dominant strategy for the entrant. Therefore, the best
response for the entrant is always to play strategy “high”, while the incumbent is
pooling on his strategy “low”.
The next step to find the pooling equilibrium would be to consider the best
response actions of the entrant off the equilibrium path. In that case, the entrant would
assume that the incumbent is playing strategy “high”, regardless of his type.
(15) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜇1(𝑡1|𝐻𝐼) ∗ 𝑈(𝐻𝐸|𝐻𝐼; 𝑡1) + 𝜇1(𝑡2|𝐻𝐼) ∗ 𝑈(𝐻𝐸|𝐻𝐼; 𝑡2)
(16) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝜇1(𝑡1|𝐻𝐼) ∗ 𝑈(𝐿𝐸|𝐻𝐼; 𝑡1) + 𝜇1(𝑡2|𝐻𝐼) ∗ 𝑈(𝐿𝐸|𝐻𝐼; 𝑡2)
Substituting the beliefs and payoffs:
(15) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜆 ∗ (𝜋
2− 𝐶𝐸) + (1 − 𝜆) ∗ ( 𝜋 − 𝜃 − 𝐶𝐸)
(15) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜋
2𝜆 − 𝐶𝐸𝜆 + 𝜋 − 𝜃 − 𝐶𝐸 − 𝜋𝜆 + 𝜃𝜆 + 𝐶𝐸𝜆
(15) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜋 −𝜋
2𝜆 − 𝐶𝐸 − 𝜃 + 𝜃𝜆
(16) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝜆 ∗ 𝛾 + (1 − 𝜆) ∗ (𝜋
2− 𝜃)
(16) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝜆 ∗ 𝛾 +𝜋
2− 𝜃 −
𝜋
2𝜆 + 𝜃𝜆
The best response (BR) for the entrant against incumbent’s strategy “high” will depend
on which expected utility is higher. Therefore, there are three conditions:
𝐵𝑅𝐸(𝐻𝐼) = {
𝐻𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) > 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
𝐿𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) < 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
𝜆𝐻𝐸 + (1 − 𝜆)𝐿𝐸) 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
170
To find the best response of the entrant, we can start from the indifference condition:
(15) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = (16) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
(15) 𝜋 −𝜋
2𝜆 − 𝐶𝐸 − 𝜃 + 𝜃𝜆 = (16)𝜆 ∗ 𝛾 +
𝜋
2− 𝜃 −
𝜋
2𝜆 + 𝜃𝜆
Knowing that the probability of 𝜆 ∈ [0,1], it is possible to approach this solution by
substituting the values of 𝛼 into the equation. Let us look at the first proposition that
𝜆=1 (proposition one):
(15) 𝜋 −𝜋
2− 𝐶𝐸 − 𝜃 + 𝜃 = (16)𝛾 +
𝜋
2− 𝜃 −
𝜋
2+ 𝜃
(15) 𝜋
2− 𝐶𝐸 = (16) 𝛾
Taking into account the payoff structure that was defined at the beginning of
the analysis > 𝜋 − 𝑐 > 𝜋2⁄ > 𝜋
2⁄ − 𝑐 > 𝛾 , therefore the dominant strategy for the
entrant would be to play action “high”, 𝐵𝑅𝐸(𝐻𝐼) = 𝐻𝐸
The opposite case (proposition two) is when 𝜆 = 0.
(15) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = (16) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
(15) 𝜋 −𝜋
2𝜆 − 𝐶𝐸 − 𝜃 + 𝜃𝜆 = (16) 𝜆 ∗ 𝛾 +
𝜋
2− 𝜃 −
𝜋
2𝜆 + 𝜃𝜆
(15) 𝜋 − 𝐶𝐸 − 𝜃 = (16) 𝜋
2− 𝜃
As 𝜃 is the constant that is the same on both sides, it can be removed, and the final
payoff for the indifference condition will be
(15) 𝜋 − 𝐶𝐸 = (16) 𝜋
2
As in proposition one, based on the predefined payoff structure of the case, the
entrant’s strategy “high” will yield a higher payoff (15) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) > (16) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼),
therefore the entrant’s best response would be to play action “high” 𝐵𝑅𝐸(𝐻𝐼) = 𝐻𝐸.
171
Therefore, on the equilibrium path, the entrant would always play strategy “high”, as it
would be the dominant strategy. The tree diagram in Figure 3.9 represents the best
responses of the entrant.
The final step to identify if the pooling equilibrium will hold under the actions of
the second player would be to look at the incumbent’s payoff on and off the equilibrium
path, to determine if the incumbent has an incentive to deviate. If the incumbent is type
2 and is pooling on his strategy “low”, he will receive the payoff of 𝛾. On the other
hand, if the incumbent deviates from the equilibrium path and chooses strategy “high”
while he is a type 2 player, he would receive the payoff of 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐). In this case,
the incumbent will have an incentive to deviate 𝛾 < 0 < 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐).
In the scenario when the incumbent is a type one player and is pooling on the
strategy “low”, he will receive the payoff of 𝜋
2− 𝐶𝐼(𝑙𝑖𝑒). Taking the action off the
equilibrium path, and knowing the best response of the entrant on that path, the payoff
Figure 3-9. Pooling Equilibrium Sub-Case 4 (Low Cost)
172
for the incumbent would be 𝜋
2 , which will always be higher. Therefore, there is no
pooling equilibrium when the first player is pooling on his strategy “low”.
High cost and changes in the payoff structure
One of the key assumptions in the previous section of this chapter was that the
cost of investment into the corporate governance is low, and by investing into
corporate governance mechanisms, a firm would still be better off than not investing.
This section will consider the scenario when the cost on investment into corporate
governance is high, holding all the other assumptions the same as in the previous
section. The primary reason for that significant cost can be due to the fact that if the
entrant firm comes from a market with a low level of corporate governance into a
market where the corporate governance standards and regulations are high, then the
first market of entry will require a significant catch up in terms of corporate governance
mechanisms and therefore a significant investment, which will mean significant costs
for the entry firm. This assumption will change the payoff structure of the game and
the new payoff structure will be: 𝜋 > 𝜋2⁄ > 𝜋 − 𝑐 > 𝜋
2⁄ − 𝑐 > 𝛾.
As in the previous section, I will begin the analysis with the simple simultaneous
game (Figure 3.10), in which the entrant and the incumbent choose their strategy for
playing a high or low level of corporate governance at the same time.
173
Figure 3-10. Simultaneous game under the high cost of corporate governance
Entrant
High Low In
cu
mb
en
t High 𝜋
2 -c ;
𝜋
2 -c 𝜋 − 𝑐 ; 𝛾
Low 𝛾 ; 𝜋 − 𝑐 𝜋
2 ;
𝜋
2
Using the best response method, we can see that the entrant will play strategy
“high” when the incumbent is playing strategy “high”, and the entrant will play strategy
“low”, when the incumbent is playing strategy “low”. In this case, the game becomes
the coordination game, with two Nash equilibria (high, high) and (low, low). In this
scenario, unlike the previous case with the prisoner’s dilemma, there is no dominant
strategy. The players can achieve one of the Nash equilibria through cooperation, and
this becomes an assurance game in which the best results can be achieved if the
players use the same strategy.
Let us now consider the scenario that such a game is not simultaneous but
sequential (Figure 3.11). In this case, the incumbent will move first and select the level
of corporate governance at either high or low. The entrant will have a second move
and will also select his corporate governance investment at either high or low. All the
assumptions that were stated earlier will hold. Therefore, the entrant will know for sure
if an incumbent has selected a high corporate governance standard or a low corporate
governance standard in the first stage of the game. The payoff structure is also similar
to the simultaneous game. Using the backward induction method, it is possible to
conclude that the entrant will select the strategy “high” if he will end up in the upper
174
node (when the incumbent is playing high) and the entrant will select strategy “low”
when he ends up in the lower node (when the entrant is playing strategy “low”.)
Based on the assumption of perfect information and the rationality of the
players, the incumbent will know the payoffs of the entrant and, at the same time, will
assume that the entrant will select his actions based on the highest payoff at each
node. In this case, the incumbent will compare his payoffs of 𝜋
2− 𝐶 and
𝜋
2. Taking the
payoff structure into consideration ( 𝜋 > 𝜋2⁄ > 𝜋 − 𝑐 > 𝜋
2⁄ − 𝑐 > 𝛾) the higher
payoff for the incumbent in the sequential game would be (𝜋
2). Therefore, the rollback
equilibrium of this game would be for the incumbent to play strategy “low” and for the
entrant to play strategy “low” if the incumbent is playing strategy “low”, and to play
Figure 3-11. Sequential game with perfect information under the high cost
175
strategy “high” if the incumbent is playing strategy high. In comparison to the situation
in Figure 3.4., this time the perfect rollback equilibrium would occur when both players
play strategy “low”. This time the decision to cooperate and not to invest in corporate
governance would yield a higher possible payoff for both players.
Separating Equilibrium Subcase Five (High Cost)
Compared to the scenario with the low cost of corporate governance
investment, it is important to consider the imperfect information that occurs in the entry
game between the incumbent and the entrant under the assumption of high cost. Once
again, it is important to evaluate the outcomes of this game through the concepts of
separating and pooling equilibrium cases, and to determine if the Bayesian equilibrium
holds. All the assumptions and the sequence of actions in the game will remain the
same.
First, the game’s nature will decide the type (𝑡 ∈ {𝑡1, 𝑡2}) of incumbent with a
certain probability. The first type (𝑡1) is the incumbent with strong corporate
governance standards. The second type (𝑡1) is when the incumbent’s corporate
governance is weak. The incumbent knows for sure if he is type 1 or type 2, and after
observing this information, it will be incumbent’s turn to select either a high corporate
governance standard or a low one. In the second stage of this game, it is for the entrant
to choose either to match (select high if incumbent is high) or not to match the high
standards or low standards of the incumbent (select low if the incumbent selects high)
from the previous move. The only difference would be the payoff structure for this
game, which will be: 𝜋 > 𝜋2⁄ > 𝜋 − 𝑐 > 𝜋
2⁄ − 𝑐 > 𝛾 assuming that the cost for the
176
entrant to catch up with the incumbent’s corporate governance in high. The game tree
for this updated scenario is represented in Figure 3.12.
As the payoff’s outcome would stay identical to the previous case (Figure 3.5),
the expected payoffs of the entrant would be the same; however, the interpretation of
the best response functions would differ.
Let us consider the first case and the incumbent’s strategy (𝜎𝐼) depending on
the type he is playing.
𝜎𝐼(𝑡) = {𝐻 𝑖𝑓 𝑡 = 𝑡1
𝐿 𝑖𝑓 𝑡 = 𝑡2
In this sub-case, the entrant will update his beliefs based on the idea that only a certain
type of incumbent will play this action.
𝜇1(𝑡1|𝐻𝐼) = 1 ; 𝜇1(𝑡2|𝐻𝐼) = 0
𝜇2(𝑡1|𝐿𝐼) = 0 ; 𝜇2(𝑡2|𝐿𝐼) = 1
Therefore, the expected utility for the entrant would be:
Figure 3-12. Sequential game with imperfect information under the high cost
177
(1)𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 1 ∗ (𝜋
2− 𝐶𝐸) + 0 ∗ (𝜋 − 𝜃−𝐶𝐸)
(1) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) =𝜋
2− 𝐶𝐸
(2) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 1 ∗ 𝛾 + 0 ∗ (𝜋
2− 𝜃)
(2) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝛾
The best response for the entrant, when the incumbent is type 1 and plays his strategy
“high”, would be to play strategy “high” because (1)𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) > (2) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼).
Therefore: 𝐵𝑅𝐸(𝐻𝐼) = 𝐻𝐸
When the incumbent is type 2, he will always play strategy “low”, and, in this case, the
expected utility for the entrant would be:
(3) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 0 ∗ (𝜋
2− 𝐶𝐸) + 1 ∗ (𝜋−𝐶𝐸)
(3) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋−𝐶𝐸
(4) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 0 ∗ 𝛾 + 1 ∗𝜋
2
(4) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝜋
2
Under the assumption that the corporate governance investment has a high cost
associated with it and the payoff structure ( 𝜋 > 𝜋2⁄ > 𝜋 − 𝑐 > 𝜋
2⁄ − 𝑐 > 𝛾), this
time the best response for the entrant would be to play strategy “low” when the
incumbent is type 2, because: (3)𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) < (4) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼). 𝐵𝑅𝐸(𝐿𝐼) = 𝐿𝐸
The equilibrium paths for the players are represented in Figure 3.13 below:
178
To check if the separating equilibrium in subcase five will hold, it is important to analyse
if the incumbent will have an incentive to deviate from the equilibrium path. First,
consider when the incumbent is playing strategy “high” while being a type one (strong
corporate governance). In this situation, his payoff would be 𝜋
2. Playing the strategy off
the equilibrium path (strategy “low”, while being a type one player), he will end up with
the payoff of 𝜋−𝐶𝐼(𝑙𝑖𝑒). This action may be better under the condition that the cost of
the incumbent to lie (𝐶𝐼(𝑙𝑖𝑒)) and hide his actual type is small. This will lead to
𝜋−𝐶𝐼(𝑙𝑖𝑒) >𝜋
2 and, as a result, may lead to a profitable deviation. On the other hand, if
the cost of the incumbent to lie would be significant, then there is no incentive to defect
from the equilibrium action. Taking into consideration that 0 < 𝐶𝐼(𝑙𝑖𝑒) <𝜋
2, there is an
incentive for the incumbent to defect.
Looking at the incumbent’s payoff when he is a type 2 player and execute his
strategy ‘low’, the payoff would be 𝜋
2. The alternative for the incumbent is to play
strategy ‘high’, while he is a type 2 player, and receive the payoff of 𝜃−𝐶𝐼 (𝑚𝑖𝑚𝑖𝑐). Based
Figure 3-13.Separating Equilibrium Subcase 5 (High Cost)
179
on the assumptions that 0 < 𝜃 <𝜋
2 and 𝐶𝐼 (𝑚𝑖𝑚𝑖𝑐) > 0 it would be always better for the
incumbent to stay on the equilibrium path.
Therefore, separating the PBE equilibrium in subcase five under high cost
would not occur because the incumbent has an incentive to defect if he is hiding his
real type while being a type one player.
Separating Equilibrium Subcase Six (High Cost)
The second case of separating the equilibrium that should be considered is when the
incumbent is bluffing or hiding information. In other words, he is playing “low” if he is
type 2 and “high” if he is type 1. Therefore, the strategy for the incumbent will be:
𝜎𝐼(𝑡) = {𝐿 𝑖𝑓 𝑡 = 𝑡1
𝐻 𝑖𝑓 𝑡 = 𝑡2
In this case, the entrant will update his beliefs based on the idea that only a certain
type of incumbent will play this action:
𝜇1(𝑡1|𝐻𝐼) = 0 ; 𝜇1(𝑡2|𝐻𝐼) = 1
𝜇2(𝑡1|𝐿𝐼) = 1 ; 𝜇2(𝑡2|𝐿𝐼) = 0
Hence, the expected utility of the entrant would be:
(5)𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 0 ∗ (𝜋
2− 𝐶𝐸) + 1(𝜋 − 𝜃 − 𝐶𝐸)
(5)𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜋 − 𝜃 − 𝐶𝐸
(6) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 0 ∗ 𝛾 + 1 ∗ (𝜋
2− 𝜃)
Based on the payoff structure, equation (5) will be always greater than equation (6),
and therefore the best response would be 𝐵𝑅𝐸(𝐻𝐼) = 𝐻𝐸.
180
Now let us consider the scenario when the incumbent is type 2, and, based on
the beliefs that were defined in this sub-case, the expected utility of the entrant would
be:
(7) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 1 ∗ (𝜋
2− 𝐶𝐸) + 0 ∗ 𝜋 − 𝐶𝐸
(7) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋
2− 𝐶𝐸
(8) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 1 ∗ 𝛾 + 0 ∗𝜋
2
(8) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝛾
(7) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) > (8) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
Therefore, the best response for the second player (entrant) against strategy “low” will
be to play strategy “high”, 𝐵𝑅𝐸(𝐿𝐼) = 𝐻𝐸. The tree diagram representing the beliefs,
payoffs and the best responses is represented in figure 3.14
Figure 3-14. Separating Equilibrium Subcase 6 (High Cost)
181
To conclude, if separating equilibrium exists, it is important to check that the
incumbent has no incentive to deviate. Looking at the payoff of the incumbent when
he is type 2 and plays his strategy “high”, the payoff would be 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐). The
potential deviation for the incumbent of this type would be to play strategy “low”, and
knowing that the entrant’s best response in this case would be to play strategy “high”,
the incumbent’s payoff would be equal to 𝛾. Therefore, there are two potential
outcomes, depending on the level of the incumbent’s reward for mimicking the
behaviour of the strong type (𝜃) and the level of cost (𝐶𝐼(𝑚𝑖𝑚𝑖𝑐)). Proposition one is
that if the incumbent’s reward for mimicking the action of the firm with strong corporate
governance is higher than the cost of this action, then there is no incentive to defect
from the equilibrium path (0 < 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐)). Proposition two is that if the cost of
mimicking the actions of the firm with high corporate governance is higher or equal to
the reward that the incumbent can receive, then there is no incentive to deviate as
0 ≥ 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐). As 𝜃 is always greater than 0, it is possible to conclude that there is
no incentive to defect from the equilibrium path and the type 2 incumbent will stick to
the strategy “high”.
If the incumbent is type 1, he will play his strategy “low” and will end up with the
payoff of 𝜋
2− 𝐶𝐼(𝑙𝑖𝑒). If the type 1 incumbent deviates and selects strategy “high”, based
on the best response of the entrant, the incumbent will have a payoff of 𝜋
2. Therefore,
the incumbent has the incentive to defect from his strategy “low” when he is type 1,
and play strategy “high”. Thus, there will be no equilibrium reached in this sub-case.
𝜋
2 >
𝜋
2− 𝐶𝐼(𝑙𝑖𝑒)
182
The subcase five of separating the equilibrium under the high cost of corporate
governance investment is identical to sub-case two of separating the equilibrium under
the low cost of corporate governance. That fact suggests that if the entrant assumes
that his competitor (the incumbent) has a reputation of being a cheating player, the
entrant’s best strategy would be to select high corporate governance, regardless of
the cost and actions of the incumbent.
Pooling Equilibrium Sub-Case Seven (High Cost)
Starting the analysis from the scenario when the incumbent is pulling on strategy
“high”, his strategy can be represented as:
𝜎𝐼(𝑡) = {𝐻 𝑖𝑓 𝑡 = 𝑡1
𝐻 𝑖𝑓 𝑡 = 𝑡2
Updating the beliefs of the entrant that the incumbent will always pool on his strategy
“high” will give:
𝜇1(𝑡1|𝐻) = 𝑝
𝜇1(𝑡2|𝐻) = 1 − 𝑝
If, however, the incumbent plays strategy L (regardless of his type), which never
occurs along the equilibrium path, the Bayes’ rule will not apply. In this case, we reach
arbitrarily assigned beliefs. It is not possible at this point to know which, if any, beliefs
regarding the equilibrium path behaviour will sustain a pooling equilibrium. Therefore,
for now we assume that:
𝜇2(𝑡1|𝐿) = 𝜆
𝜇2(𝑡2|𝐿) = 1 − 𝜆
183
𝑊ℎ𝑒𝑟𝑒: 𝜆 ∈ [0,1]
Knowing the beliefs of the entrant, it is possible to calculate what the expected payoffs
would be like when pooling equilibrium subcase three (low cost):
(9) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝑝 ∗ (𝜋
2− 𝐶𝐸) + (1 − 𝑝) ∗ ( 𝜋 − 𝜃 − 𝐶𝐸)
(9) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜋
2𝑝 − 𝐶𝐸𝑝 + 𝜋 − 𝜃 − 𝐶𝐸 − 𝜋𝑝 + 𝜃𝑝 + 𝐶𝐸𝑝
(9) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜋 −𝜋
2𝑝 − 𝐶𝐸 − 𝜃 + 𝜃𝑝
(10) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝑝 ∗ 𝛾 + (1 − 𝑝) ∗ (𝜋
2− 𝜃)
(10) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝑝 ∗ 𝛾 +𝜋
2− 𝜃 −
𝜋
2𝑝 + 𝜃𝑝
The best response (BR) for the entrant against the incumbent’s strategy “high” will
depend on which expected utility is higher. Therefore, there are three conditions:
𝐵𝑅𝐸(𝐻𝐼) = {
𝐻𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) > 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
𝐿𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) < 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
𝑝𝐻𝐸 + (1 − 𝑝)𝐿𝐸) 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
To find the best response of the entrant, we can start from the indifference condition
and substitute the beliefs:
(9) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = (10) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
The first proposition would be that 𝑝 = 1
(9) 𝜋 −𝜋
2∗ 1 − 𝐶𝐸 − 𝜃 + 𝜃 ∗ 1 = (10) 1 ∗ 𝛾 +
𝜋
2− 𝜃 −
𝜋
2∗ 1 + 𝜃 ∗ 1
(9) 𝜋 −𝜋
2− 𝐶𝐸 − 𝜃 + 𝜃 = (10) 𝛾 +
𝜋
2− 𝜃 −
𝜋
2+ 𝜃
(9) 𝜋
2− 𝐶𝐸 = (10) 𝛾
Taking the payoff structure under the high cost scenario (𝜋 > 𝜋2⁄ > 𝜋 − 𝑐 > 𝜋
2⁄ −
𝑐 > 𝛾 ), the entrant has a strictly dominating strategy to play his action “high”.
Therefore, the best response is 𝐵𝑅𝐸(𝐻𝐼) = 𝐻𝐸.
184
The second proposition would investigate the case when 𝑝 = 0
(9) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = (10) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
(9) 𝜋 −𝜋
2𝑝 − 𝐶𝐸 − 𝜃 + 𝜃𝑝 = (10) 𝑝 ∗ 𝛾 +
𝜋
2− 𝜃 −
𝜋
2𝑝 + 𝜃𝑝
(9) 𝜋 − 𝐶𝐸 − 𝜃 = (10) 𝜋
2− 𝜃
(9) 𝜋 − 𝐶𝐸 = (10) 𝜋
2
In this case, the equation (10) would be always greater than (9), which means that the
best response of the entrant would be to play strategy “low”, 𝐵𝑅𝐸(𝐻𝐼) = 𝐿𝐸.
This result is different from the pooling equilibrium subcase three (low cost),
because now the entrant does not have the dominant strategy, and his best response
will vary based on the allocation of his beliefs about the incumbent’s type. If entrant
believes that the incumbent has a higher probability to be type 1 while pooling on his
strategy “high”, then the entrant’s best response would be to play strategy “high”. On
the other hand, if the entrant believes that the incumbent has a higher probability to
be type 1 while pooling on his strategy “high”, then the best response for the entrant
would be to play strategy “low”.
To make sure that all the possible entrant’s strategies are considered, the
analysis has to look at the entrant’s actions off the equilibrium path, which is to identify
what would be the best response of the entrant in case the type 1 incumbent is playing
strategy “low”.
(11) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜇2(𝑡1|𝐿𝐼) ∗ 𝑈(𝐻𝐸|𝐿𝐼; 𝑡1) + 𝜇2(𝑡2|𝐻𝐼) ∗ 𝑈(𝐻𝐸|𝐿𝐼; 𝑡2)
(12) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝜇2(𝑡1|𝐿𝐼) ∗ 𝑈(𝐿𝐸|𝐿𝐼; 𝑡1) + 𝜇2(𝑡2|𝐻𝐼) ∗ 𝑈(𝐿𝐸|𝐿𝐼; 𝑡2)
(11) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜆 ∗ (𝜋
2− 𝐶𝐸) + (1 − 𝜆) ∗ ( 𝜋 − 𝐶𝐸)
185
(11) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋 −𝜋
2𝜆 − 𝐶𝐸
(12) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝜆 ∗ 𝛾 + (1 − 𝜆) ∗𝜋
2
(12) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝜆 ∗ 𝛾 + 𝜋
2−
𝜋
2𝜆
In this case, the best response (BR) for the entrant against incumbent’s strategy “low”
will depend on which expected utility is higher. Therefore, there are three conditions:
𝐵𝑅𝐸(𝐿𝐼) = {
𝐻𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) > 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
𝐿𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) < 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
𝜆𝐻𝐸 + (1 − 𝜆)𝐿𝐸) 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
As in the equilibrium path estimations, there would be two propositions to consider.
Proposition one is that 𝜆 = 1
(11)𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋 −𝜋
2∗ 1 − 𝐶𝐸
(11)𝜋
2− 𝐶𝐸
(12)𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 1 ∗ 𝛾 +𝜋
2−
𝜋
2∗ 1
(12)𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝛾
The result for the incumbent under proposition one is that he will always play strategy
“high”, as 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) > 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼). Therefore, the best response is 𝐵𝑅𝐸(𝐿𝐼) = 𝐻𝐸.
Under the second proposition 𝜆 = 0:
(11)𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋 −𝜋
2∗ 0 − 𝐶𝐸
(11) 𝜋 − 𝐶𝐸
(12) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 0 ∗ 𝛾 +𝜋
2−
𝜋
2∗ 0
186
(12) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) =𝜋
2
The best response of the entrant would be to play strategy “low”. 𝐵𝑅𝐸(𝐿𝐼) = 𝐿𝐸. Once
again, the decision of the entrant will totally depend on the probabilities that he will
assign to the arbitrary beliefs.
To conclude, if there is a pooling equilibrium in this subcase, it is important to
consider four different scenarios. First, 𝑝 = 1 and 𝜆 = 1 and in this situation, the best
response of the entrant would be 𝐵𝑅𝐸(𝐻𝐼) = 𝐻𝐸, and 𝐵𝑅𝐸(𝐿𝐼) = 𝐻𝐸. Thus, the
incumbent will act in accordance to the pooling equilibrium in subcase three, and there
will be a pooling Bayesian equilibrium.
Second, when 𝑝 = 0 and 𝜆 = 0, the dominant strategy for the entrant would be
to play strategy “low”. This case has not been discussed yet, therefore it is important
to analyse if the incumbent has an incentive to deviate from the equilibrium path. The
graph in Figure 3.15 represents the equilibrium path of such actions.
Figure 3-15. Pooling Equilibrium subcase 7.2 (high cost) when p=0 and λ = 0
187
In this case, the incumbent will not have the incentive to deviate if he is type 1, and
the entrant is playing his strategy “low”, because his payoff would be lower if he
deviates. 𝜋 > 𝜋 − 𝐶𝐼(𝑙𝑖𝑒). If the incumbent is a type two player, knowing the best
response of the entrant, the incumbent’s payoff would be 𝜋
2+ 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐). The
deviation from strategy “high” by the incumbent will provide him with the payoff of 𝜋
2.
As a result, the weak Bayesian equilibrium can be always sustained if the 𝜃 −
𝐶𝐼(𝑚𝑖𝑚𝑖𝑐) = 0. If 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐) < 0, then the incumbent’s payoff after deviation would
be higher and there will be no equilibrium. On the other hand, the assumption that 𝜃 −
𝐶𝐼(𝑚𝑖𝑚𝑖𝑐) > 0 will sustain the strong Bayesian equilibrium.
Third, the p = 1 and λ = 0 condition under which the best response for the
entrant would be 𝐵𝑅𝐸(𝐻𝐼) = 𝐻𝐸 and 𝐵𝑅𝐸(𝐿𝐼) = 𝐿𝐸. The graph is represented in Figure
3.16.
Figure 3-16. Pooling Equilibrium subcase 7.3 (high cost) when p=0 and λ = 0
188
If the incumbent is a type 1 player, he will end up with the payoff of 𝜋
2. The alternative
payoff that he will receive if he deviates would be 𝜋 − 𝐶𝐼(𝑙𝑖𝑒). In this case, the deviation
from the equilibrium path would be beneficial only in the case when the incumbent’s
cost of hiding his actual information is not too high (𝜋 − 𝐶𝐼(𝑙𝑖𝑒) > 𝜋
2). If the incumbent is
a type 2 player, he will receive the payoff of 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐) and this will always be less
than the payoff from deviation (𝜋
2), because the (0 < 𝜃 <
𝜋
2). Therefore, there will be
no pooling equilibrium.
Fourth, p = 0 and λ = 1 with the entrant’s best response 𝐵𝑅𝐸(𝐻𝐼) = 𝐿𝐸 and
𝐵𝑅𝐸(𝐿𝐼) = 𝐻𝐸 respectively (Figure 3.17).
In this case, the incumbent will have no incentive to deviate as he will be worse off. If
he is type 1, then his payoff would be 𝜋. The deviation will yield a maximum payoff of
𝜋
2− 𝐶𝐼(𝑙𝑖𝑒), which is always smaller than 𝜋. If the incumbent is a type 2 player, then his
Figure 3-17. Pooling Equilibrium subcase 7.4 (high cost) when p=0 and λ = 1
189
payoff would be 𝜋
2+ 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐), which is always greater than 𝛾. Therefore, there will
always be a Bayesian equilibrium under the conditions that p = 0 and λ = 1 when the
incumbent is pooling on strategy “high”.
Pooling Equilibrium Sub-Case Eight (High Cost)
The last sub-case to consider, under the condition of high cost, is when the incumbent
is pooling on his strategy “low”.
𝜎𝐼(𝑡) = {𝐿 𝑖𝑓 𝑡 = 𝑡1
𝐿 𝑖𝑓 𝑡 = 𝑡2
Updating the beliefs via the Bayes rule where possible gives:
𝜇2(𝑡1|𝐿) = 𝑝
𝜇2(𝑡2|𝐿) = 1 − 𝑝
If, however, the incumbent plays strategy H (regardless of his type), which never
occurs along the equilibrium path, the Bayes’ rule will not apply, and, in this case, we
reach arbitrarily assigned beliefs. It is not possible at this point to know which, if any,
beliefs regarding off the equilibrium path behaviour will sustain a pooling equilibrium.
Therefore, for now we assume that:
𝜇1(𝑡1|𝐻) = 𝜆
𝜇1(𝑡2|𝐻) = 1 − 𝜆
𝑊ℎ𝑒𝑟𝑒: 𝜆 ∈ [0,1]
The expected utility of the entrant when the incumbent is pooling his types and playing
action “low” will be the same as in pooling equilibrium sub-case four (low cost).
(13) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜇2(𝑡2|𝐿𝐼) ∗ 𝑈(𝐻𝐸|𝐿𝐼; 𝑡1) + 𝜇2(𝑡2|𝐻𝐼) ∗ 𝑈(𝐻𝐸|𝐿𝐼; 𝑡2)
(14) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝜇2(𝑡2|𝐿𝐼) ∗ 𝑈(𝐿𝐸|𝐿𝐼; 𝑡1) + 𝜇2(𝑡2|𝐻𝐼) ∗ 𝑈(𝐿𝐸|𝐿𝐼; 𝑡2)
190
(13) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝑝 ∗ (𝜋
2− 𝐶𝐸) + (1 − 𝑝) ∗ ( 𝜋 − 𝐶𝐸)
(13) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋 −𝜋
2𝑝 − 𝐶𝐸
(14) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝑝 ∗ 𝛾 + (1 − 𝑝) ∗𝜋
2
(14) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝑝 ∗ 𝛾 +𝜋
2−
𝜋
2𝛼
In this case, the best response (BR) for the entrant against the incumbent’s strategy
“low” will depend on which expected utility is higher. Therefore, there are three
conditions:
𝐵𝑅𝐸(𝐿𝐼) = {
𝐻𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) > 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
𝐿𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) < 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
𝑝𝐻𝐸 + (1 − 𝑝)𝐿𝐸) 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼)
In the first proposition, let’s consider that 𝑝 = 1
(13) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋 −𝜋
2∗ 1 − 𝐶𝐸
(13) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) =𝜋
2− 𝐶𝐸
(14) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 1 ∗ 𝛾 +𝜋
2−
𝜋
2∗ 1
(14) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝛾
Equation (13) is always greater than (14) based on the payoff structure, therefore the
best response for the entrant is 𝐵𝑅𝐸(𝐿𝐼) = 𝐻𝐸.
In the second proposition let’s consider that 𝑝 = 0
(13) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋 −𝜋
2∗ 0 − 𝐶𝐸
(13) 𝔼𝑈𝐸(𝐻𝐸 , 𝐿𝐼) = 𝜋 − 𝐶𝐸
191
(14) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 0 ∗ 𝛾 +𝜋
2−
𝜋
2∗ 0
(14) 𝔼𝑈𝐸(𝐿𝐸 , 𝐿𝐼) = 𝜋
2
Equation (14) is always greater than (13) based on the payoff structure, therefore the
best response for the entrant is 𝐵𝑅𝐸(𝐿𝐼) = 𝐿𝐸.
Analyzing the best response actions of the entrant off the equilibrium path will
yield the following expected utility:
(15) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜇1(𝑡1|𝐻𝐼) ∗ 𝑈(𝐻𝐸|𝐻𝐼; 𝑡1) + 𝜇1(𝑡2|𝐻𝐼) ∗ 𝑈(𝐻𝐸|𝐻𝐼; 𝑡2)
(16) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝜇1(𝑡1|𝐻𝐼) ∗ 𝑈(𝐿𝐸|𝐻𝐼; 𝑡1) + 𝜇1(𝑡2|𝐻𝐼) ∗ 𝑈(𝐿𝐸|𝐻𝐼; 𝑡2)
Substituting the beliefs and payoffs:
(15) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜆 ∗ (𝜋
2− 𝐶𝐸) + (1 − 𝜆) ∗ ( 𝜋 − 𝜃 − 𝐶𝐸)
(15) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜋
2𝜆 − 𝐶𝐸𝜆 + 𝜋 − 𝜃 − 𝐶𝐸 − 𝜋𝜆 + 𝜃𝜆 + 𝐶𝐸𝜆
(15) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝜋 −𝜋
2𝜆 − 𝐶𝐸 − 𝜃 + 𝜃𝜆
(16) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝜆 ∗ 𝛾 + (1 − 𝜆) ∗ (𝜋
2− 𝜃)
(16) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼) = 𝜆 ∗ 𝛾 +𝜋
2− 𝜃 −
𝜋
2𝜆 + 𝜃𝜆
The best response (BR) for the entrant against the incumbent’s strategy “high” will
depend on which expected utility is higher. Therefore, there are three conditions:
𝐵𝑅𝐸(𝐻𝐼) = {
𝐻𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) > 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
𝐿𝐸 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) < 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
𝜆𝐻𝐸 + (1 − 𝜆)𝐿𝐸) 𝑖𝑓 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
To find the best response of the entrant, we can start from the indifference condition:
(15) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = (16) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
(15) 𝜋 −𝜋
2𝜆 − 𝐶𝐸 − 𝜃 + 𝜃𝜆 = (16) 𝜆 ∗ 𝛾 +
𝜋
2− 𝜃 −
𝜋
2𝜆 + 𝜃𝜆
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Knowing that the probability of 𝜆 ∈ [0,1], it is possible to approach this solution by
substituting the values of 𝛼 into the equation. Let us consider the first proposition that
𝜆=1 (proposition one):
(15) 𝜋 −𝜋
2− 𝐶𝐸 − 𝜃 + 𝜃 = (16) 𝛾 +
𝜋
2− 𝜃 −
𝜋
2+ 𝜃
(15) 𝜋
2− 𝐶𝐸 = (16) 𝛾
Taking into account the payoff structure 𝜋 > 𝜋2⁄ > 𝜋 − 𝑐 > 𝜋
2⁄ − 𝑐 > 𝛾, the
dominant strategy for the entrant would be to play action “high”, 𝐵𝑅𝐸(𝐻𝐼) = 𝐻𝐸.
The opposite case (proposition two) when 𝜆 = 0.
(15) 𝔼𝑈𝐸(𝐻𝐸 , 𝐻𝐼) = (16) 𝔼𝑈𝐸(𝐿𝐸 , 𝐻𝐼)
(15) 𝜋 −𝜋
2𝜆 − 𝐶𝐸 − 𝜃 + 𝜃𝜆 = (16) 𝜆 ∗ 𝛾 +
𝜋
2− 𝜃 −
𝜋
2𝜆 + 𝜃𝜆
(15) 𝜋 − 𝐶𝐸 − 𝜃 = (16) 𝜋
2− 𝜃
As 𝜃 is the constant that is the same on both sides, it can be removed, and the final
payoff for the indifference condition will be
(15) 𝜋 − 𝐶𝐸 = (16) 𝜋
2
Equation (16) is always greater than (15), hence the best response for the entrant is
to play strategy “low”, 𝐵𝑅𝐸(𝐻𝐼) = 𝐿𝐸.
Similar to the pooling equilibrium in subcase seven, there will be four different
scenarios in which it is important to check if the incumbent has an incentive to deviate.
If not, then the pooling equilibrium will hold, and vice versa.
First, 𝑝 = 1 and 𝜆 = 1 , which will lead to the following best responses by the
entrant: 𝐵𝑅𝐸(𝐿𝐼) = 𝐻𝐸; 𝐵𝑅𝐸(𝐻𝐼) = 𝐻𝐸. This is identical to the scenario in the pooling
193
equilibrium subcase four, and will lead to the similar conclusion that no pooling
Bayesian equilibrium will hold, as the incumbent will have an incentive to deviate.
Second, 𝑝 = 0 and 𝜆 = 0 with the best responses 𝐵𝑅𝐸(𝐿𝐼) = 𝐿𝐸 and 𝐵𝑅𝐸(𝐻𝐼) =
𝐿𝐸. This scenario is represented in Figure 3.18 below.
If the incumbent is a type 2 player while pooling on his strategy “low”, he will
receive a payoff of 𝜋
2. Diverging from his initial strategy “low” and playing strategy high
will lead to the payoff of 𝜋
2+ 𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐). Such a deviation will only be rational if the
𝜃 − 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐) > 0, based on the assumptions that the 0 < 𝜃 <𝜋
2 and that the cost of
mimicking is also 0 < 𝐶𝐼(𝑚𝑖𝑚𝑖𝑐) <𝜋
2 it can be concluded that there is also an incentive
to defect from the equilibrium path.
The incumbent’s payoff when he is staying on the equilibrium path, while being
a type 1 player, will be 𝜋 − 𝐶𝐼(𝑙𝑖𝑒). The deviation will yield a payoff of 𝜋, which is always
Figure 3-18. Pooling equilibrium subcase 8 (high cost) when p=0 and λ =0
194
better because the 𝐶𝐼(𝑙𝑖𝑒) > 0. Therefore, the equilibrium will not hold as the first player
has an incentive to deviate.
Third, 𝑝 = 1 and 𝜆 = 0 with the best responses 𝐵𝑅𝐸(𝐿𝐼) = 𝐻𝐸 and 𝐵𝑅𝐸(𝐻𝐼) =
𝐿𝐸, are represented in Figure 3.19 below.
It can be seen from the graph that in both cases, the incumbent will have an incentive
to deviate as his payoffs will be always higher in comparison to the payoffs that he
receives by staying on the equilibrium path. Therefore, the equilibrium will not hold.
Four, 𝑝 = 0 and 𝜆 = 1 with the best responses 𝐵𝑅𝐸(𝐿𝐼) = 𝐿𝐸 and 𝐵𝑅𝐸(𝐻𝐼) =
𝐻𝐸, are represented in figure 3.20. Here the type 1 incumbent will receive a payoff of
𝜋 − 𝐶𝐼(𝑙𝑖𝑒). The deviation will yield a payoff of 𝜋
2. If the cost of hiding the information
would be significantly higher, then the equilibrium will not hold (if 𝐶𝐼(𝑙𝑖𝑒) >𝜋
2). In other
words, there is no incentive to deviate. If the incumbent is a type 2 player, then his
payoff on the equilibrium path would be 𝜋
2. The deviation will lead to a payoff of 𝜃 −
Figure 3-19. Pooling equilibrium subcase 8 (high cost) when p=1 and λ =0
195
𝐶𝐼(𝑚𝑖𝑚𝑖𝑐), which will always be lower than 𝜋
2 because 0 < 𝜃 <
𝜋
2. Therefore, the
equilibrium will hold.
Looking beyond the duopoly game
So far, the analysis concentrated on the duopoly market with only two players,
but what if the number of firms is more than two? Let us now assume that the number
of firms in the foreign market is equal to “n”. Therefore, the larger the number of firms,
the less profit the entrant firm will be able to obtain ( 𝜋
𝑛 ). At the same time, investment
into corporate governance will mean that the entrant firm becomes more competitive
and will, therefore, have some share of the market (𝜃) from firms that decide not to
invest into corporate governance. In this case, the actual game will now depend on
these three parameters: the number of market participants (n), the cost of corporate
governance investment that the firms are facing (C) and the market share that the firm
would be able to receive as a result of investment into corporate governance
mechanisms.
Figure 3-20. Pooling equilibrium subcase 8 (high cost) when p=0 and λ=1
196
Based on the combinations of these factors, the game will be either the
prisoner’s dilemma, as discussed in the beginning of the theoretical chapter, or the
assurance game, and will follow one of the subcases discussed in this chapter. Four
possible outcomes can occur: (1) the number of market participants is small and the
cost of corporate governance is small; (2) the number of market participants is high
and the cost of corporate governance is small; (3) the number of market participants
is small and the cost of corporate governance is high; (4) the number of market
participants is high and the cost of corporate governance is high.
Figure 3-21. Simultaneous game with n number of players in the market
Entrant
High Low
Ma
rket
High 𝜋
𝑛 - c ;
𝜋
𝑛 -c
𝜋
𝑛− 𝑐 + 𝜃 ;
𝜋
𝑛− 𝜃
Low 𝜋
𝑛− 𝜃 ;
𝜋
𝑛− 𝑐 + 𝜃
𝜋
𝑛 ;
𝜋
𝑛
Figure 3.21 represents the general overview of the simultaneous game when the
entrant is playing in the market with n number of players. Looking at the payoff
structure, it can be seen that most important relationship would be between the market
concentration and the cost of the investment (𝜋
𝑛− 𝑐) in relation to the market share that
the firm will receive from that investment (𝜃). If (𝜋
𝑛− 𝑐 < 𝜃) that means that the cost is
197
low and the number of firms in the market is small, the overall payoff structure would
be 𝜋 >𝜋
𝑛− 𝑐 + 𝜃 >
𝜋
𝑛>
𝜋
𝑛− 𝑐 >
𝜋
𝑛− 𝜃. This payoff structure would lead to the prisoner’s
dilemma case and therefore will follow the solution as represented in subcases one to
four. The alternative is when the number of market participants is high and the cost of
investment into new corporate governance mechanisms is also high. For the entrant
firm, that means that the share of the market that he can obtain from the competition
is (𝜋
𝑛− 𝑐 > 𝜃). In this scenario, the payoff structure would change to 𝜋 >
𝜋
𝑛>
𝜋
𝑛− 𝑐 +
𝜃 >𝜋
𝑛− 𝑐 >
𝜋
𝑛− 𝜃 and the result of these change would be the assurance game, which
will lead to the same conclusions that are represented in the subcases five to eight.
Therefore, case number (1) with the small number of participants and the small
cost of corporate governance would be a prisoner’s dilemma where the dominant
strategy for the entrant firm would be to play his strategy high, regardless the actions
of the other players (Subcases 1-4). Case number (2), where the number of market
participants is high and the cost of corporate governance is small, and case number
(3) where the number of market participants is small and the cost of corporate
governance is high, will depend on the relationship between the market share reward
and the cost and concentration of the market, as described above. Case number (4)
is when the number of market participants is high and the cost of corporate governance
is high, which can be directly linked to the assurance game, where it would be better
for the entrant firm play in coordination with other players (Subcase 5-8).
The alternative strategy when the costs are greater than benefits is to stay out
of these markets in the beginning of internationalisation process to enter first into the
markets with a lower cost of corporate governance and gradually increase the number
of corporate governance mechanisms within the firm, and therefore reduce the overall
cost in the markets with a large number of market participants and high costs.
198
Discussion and Conclusion
Based on the results of the theoretical framework (figure 3.22), the entrant firm
will face different strategic decisions regarding the implementation of its corporate
governance mechanisms that will influence the future profits of the firm in the
international market. First, the decision will depend on the cost of introducing
additional corporate governance mechanisms. Under low costs, an example of which
is when the entrant firm is entering the market which is similar in terms of its corporate
governance practices in relation to the domestic market and therefore will not require
substantial corporate governance adjustments, the entrant firm will have a dominant
strategy. To try and take a substantial share of the new international market, the firm
should increase/improve its corporate governance mechanisms, regardless of the
strategy adopted by the incumbent. The result table (in the appendix of this chapter)
predicts that this will be the Nash equilibrium in simultaneous and sequential games,
given perfect information. The similar result is true for the scenario under the
assumption of imperfect information. In this case, the entrant will once again choose
to implement additional corporate governance mechanisms, assuming that his
competitor in the foreign market will do exactly the same, regardless of the actual type
of corporate governance in the foreign market.
If the firm from the emerging market enters the advanced market, where the
corporate governance standards together with the enforcement of these standards are
high, it will have to spend more on the development of new / additional corporate
governance mechanisms to catch up with the competitors on the foreign market.
Under high cost, the optimal strategy for the entrant firm would be to play a so-called
coordination game in which the entrant will benefit if his level of corporate governance
is similar to the competitors’ level. Under the assumption of perfect information, the
199
results of the theoretical framework predict that if the decision on the development of
corporate governance mechanisms would be taken simultaneously between the
entrant and the incumbent, then they will benefit if their strategy matches. In the
sequential game, if the incumbent has not developed his corporate governance
mechanisms yet, and the entrant knows for sure that this is the case (perfect
information), then it would be better for the incumbent to match the low corporate
governance standards, in which case, both firms would benefit from operating in the
market without additional costs and would therefore maximise their profits.
In the case of imperfect information in the sequential game (which was
represented in the successes 5-8), the strategic decisions that the entrant firm selects
will depend on the beliefs that the entrant firm has about the incumbent. In this
scenario the entrant will try to predict and analyse if the incumbent truly developed the
corporate governance mechanisms that differ substantially from the set of
mechanisms possessed by the entrant. If that is true, then the best option would be to
match the corporate structure of the incumbent. On the other hand, if the entrant
believes that the incumbent is mimicking the behaviour of the firm which has sufficient
corporate governance mechanisms, the entrant could invest in the development of his
corporate governance mechanisms, regardless of the incumbent’s actions.
This framework also considers the strategic decisions of the entrant firm when
the market concentration is high or low, together with the cost of the corporate
governance investment, and the overall benefits that the firm will achieve by entering
a particular foreign market. This was analysed in the last section of the chapter, where
the analysis moved away from the duopoly scenario. The market concentration should
be looked at as an additional factor that would influence the potential profits that the
firm can obtain from the geographical expansion. Looking at the result, the market
200
concentration will shift the game to either being a prisoner’s dilemma (subcases 1-4)
or coordination game (subcases 5-8). In theory, there would be a point at which the
market concentration and the cost of the implementation of new corporate governance
will make the entrant firm indifferent to improving the corporate governance
mechanisms or retaining them at the current level. Such results represent that the
extension of the model into the more complex and real scenarios did not change the
qualitative results, pointing to the robustness of the theoretical framework.
Overall, the market of entry will play a crucial role for the analysis of the strategic
decisions that should be taken by the entrant firm in relation to the corporate
governance restructuring. Therefore:
Hypothesis 3:
Internationalisation of the firm, from a country with low levels of corporate governance,
to a country with high levels of corporate governance, will be correlated with a
restructuring of corporate governance mechanisms.
This chapter explored the conceptual framework, to predict whether a firm (like
Kaspersky, for example) expanding outside its domestic market, should “strategically”
adopt new corporate governance mechanisms or, vice-versa, it could keep exploiting
the mechanisms already developed in the past inside the firm. Using this framework
as an additional tool for the analysis of the internationalisation process may provide a
complete strategy for the entrant firm during the internationalisation process by
entering the markets with a low level of corporate governance and a low number of
market participants first, and gradually entering additional foreign markets where the
cost of corporate governance investment is increasing, therefore resulting in foreign
expansion with a moderate increase in the cost of internationalisation.
201
Figure 3-22 Results of the game theory analysis
Case number Equilibrium Condition Case number Equilibrium Condition
Simultaneous game High , High Simultaneous game 2 nash equilibria (High, High and Low,Low)
sequential game High , High sequential game Low, Low
Subcase 1 (Seperating) No Equilibrium Subcase 5 (Seperating) No Equilibrium
Subcase 2 (Seperating) No Equilibrium Subcase 6 (Seperating) No Equilibrium
Subcase 3 (Pooling)Incumbent type 1 playing High, Entrant
playing high Subcase 7.1 (Pooling)
Incumbent type 1 playnig High; Entrant playing
High
Subcase 4 (Pooling) No Equilibrium Subcase 7.2 (Pooling) Incumbent type 1 plying high; Entrant playing Low
Subcase 7.3 (Pooling) No Equilibrium
Subcase 7.4 (Pooling)
Incumbent Pooling on strategy high; Entrant
playing High if incumbent is High and playing Low if
incumbent is low
Subcase 8.1 (Pooling) No Equilibrium
Subcase 8.2 (Pooling) No Equilibrium
Subcase 8.3 (Pooling) No Equilibrium
Subcase 8.4 (Pooling) No Equilibrium
Under Low-cost Under High Cost
The game of Perfect Information
The Game of imperfect information
202
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Chapter 4 Dataset for the analysis
Following the case study example from Chapter 2, which focused on a Russian
firm that went through an internationalisation process and changed its course from
failure to success due to the adjustment of its corporate structure, and the third
chapter, which aimed to generalise the framework for the strategic actions of corporate
restructuring that should be taken by the firm during internationalisation, Chapter 4
and 5 will focus on testing the hypotheses that are outlined earlier in the thesis.
As the geographical focus of the thesis is on Russian firms and the effect of the
internationalisation of these firms on their corporate governance, it was important to
create a dataset that would be unique in this field. To construct the exclusive dataset
for the empirical chapter, it was vital to overcome the shortcomings of the previous
studies in the related field. For that reason, the dataset exploited in this thesis has
been shaped based on three main criteria.
First of all, previous studies on Russian corporate governance concentrated
primarily on Russian public companies listed on the Moscow stock exchange. The
primary reason behind that was the amount of disclosed information (Ichiro, 2008;
Kuznecovs & Pal, 2011; Muravyev, 2017). To expand the thesis beyond publicly
available firms, the dataset focused on large companies, regardless of their public
status.
Secondly, earlier academic articles covered a small timespan, predominantly
the period between 2000 and 2012 (Naumova et al., 2003; Kuznecovs & Pal, 2011). The
sample of this thesis’ database covers 19 years, from 2000 to 2018. This timespan
includes two key events affecting corporate governance: the introduction of the first
205
corporate governance code in 2002, and the update of the corporate governance
practices code in 2014.
In several studies, a third empirical limitation (see also the literature review
chapter) has been the focus of analysis, namely the single “ready-to-use” database.
This thesis combined data from several databases and available sources: Bureau van
Dijk Amadeus (European firms’ level data), Bureau van Dijk Orbis (world firm-level
historical data), Interfax Spark (Russian firm-level database), Bureau van Dijk Zephyr
(mergers and acquisitions database), companies’ annual reports, and Moscow stock
exchange data. The merging of data from several sources has added value to the
existing literature.
To select the sample size, the analysis focused on three main criteria: operating
revenue greater than €350 million in 2016; total assets above €200 million in 2016;
fixed assets above €150 million in 2016. Applying these conditions to the Spark
database provided a dataset of the 300 largest companies in Russia. Out of 300
companies, three were liquidated during the process of data collection. At the same
time, as the base year for the sample was 2016, the firms that were established after
that year are not included in the sample.
Merging information from four different databases also allowed for a substantial
time span to be covered in the empirical analysis. The earliest observations in the
Interfax Spark and Historical BvD Orbis databases were 1995 and 1997 respectively;
however, the significant number of missing observations between 1995 and 2000
makes these years unreliable for the analysis. Therefore, the time span of the
empirical chapter will cover 19 years, from 2000 to 2018.
206
Figure 4-1 Total number of firms, average age and number of firms which were incorporated
during the time span of the analysis (by year)
Year Number of firms
Average age of the firms
Number of new firms
2000 184 22 -
2001 198 21 14
2002 208 21 10
2003 217 22 9
2004 237 21 20
2005 256 20 19
2006 264 21 8
2007 276 21 12
2008 283 21 7
2009 285 22 2
2010 288 23 3
2011 292 23 4
2012 292 24 0
2013 294 25 2
2014 296 26 2
2015 297 27 1
2016 297 28 0
2017 297 29 0
2018 297 30 0
Figure 4.1 represents the distribution of firms within the sample. The minimum
is 184 firms in the year 2000 and the maximum is 297 in the year 2018. On the one
hand, the average age of the firms has steadily increased from 22 to 30 years. On the
other, during this period, 113 new firms were established which became the largest
companies in Russia in 2016. There are several reasons for this. First, in the period
between 2000 and 2007, there was significant growth in total factor productivity and
capital intensity in industries which contributed to Russian economic growth (Andreff
W. and Andreff M., 2017). Secondly, as one of the key macroeconomic policies of that
time was to make the Russian market more transparent, the government introduced
the first code of corporate governance in 2002. That factor contributed to the growth
of foreign direct investment into Russia (Figure 4.2).
207
Based on the number of newly established firms within the timeframe of the
analysis before and after the crisis, the sample represents this boom and shows the
clear cut-off point of the growth. The pre-crisis number of firms that were established
between 2000 and 2007 was 92, which means that a third of the sample emerged
during the prosperous years of the Russian economy. On the other hand, the firms
that were established and became large successful companies after the financial crisis
only numbered 21.
It is also important to highlight that a certain proportion of newly emerged
companies in this dataset is the result of either vertical or horizontal integration of the
largest corporations which already existed, such as Gazprom and Lukoil, GAZ etc.
This explanation justifies how the newly emerged companies were able to grow at an
extraordinary rate and become the largest companies within a five year period.
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Foreign direct investment, net inflows (% of GDP)
Introduction of corporate
governance code
(2002)
Financial crisis
New release of
corporate
governance
guidelines (2014)
Figure 4-2. Foreign direct investment into Russia. Source: World Development Indicators.
208
Sectoral Distribution
Figure 4.3 represents the breakdown of the sample by sector of economic
activity. It can be seen that the largest portion of the sample (60.27%) is represented
by either manufacturing firms (33%), or firms which operate in the wholesale and retail
trade sector (27.27%). The dominant group is followed by firms in the mining and
quarrying sector (8.42 %), transportation and storage (7.42%), electricity, gas, steam
and air conditioning supply (7.41), and information and communication (4.71%).
Figure 4-3. Breakdown of the sample by sector of economic activity.
Nace Rev.2 Main Sector Number of Firms Percentage of
Firms
Total number of firms 297 100.00%
C. Manufacturing 98 33.00% G. Wholesale and retail trade; repair of motor vehicles and motorcycles 81 27.27%
B. Mining and quarrying 25 8.42%
H. Transportation and storage 25 8.42% D. Electricity, gas, steam and air conditioning supply 22 7.41%
J. Information and communication 14 4.71% M. Professional, scientific and technical activities 12 4.04%
F. Construction 9 3.03%
K. Financial and insurance activities 4 1.35%
L. Real estate activities 3 1.01%
A. Agriculture, forestry and fishing 2 0.67% I. Accommodation and food service activities 1 0.34% N. Administrative and support service activities 1 0.34%
Looking at the yearly breakdown (Figure 4.4), it is possible to conclude that
during the last 19 years, there was an increase in the share of the largest 297 firms in
the wholesale and retail trade sector from 20% to 27%; the share of electricity, gas,
steam and air conditioning supply sector rose from 2.72% to 7.41%; and the financial
sector from 0.54% to 1.35%. For the same period, the share of the manufacturing firms
209
in the sample decreased, which means that new firms that were established during
the last 19 years operated primarily in the least dominant sector of economic activity.
The other sectors, such as construction and information and communication, did not
experience significant changes in terms of major players in these sectors.
Figure 4-4 Percentage share of the sample by the sector of economic activity.
Considering that the sample of the thesis concentrates on the largest firms in
the Russian economy, their contribution to the overall GDP of the country should be
proportional to the percentage share of the firms represented in the thesis. Figure 4.5
represents the share of Russian GDP by sector of economic activity.
0.0
0%
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.00
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45
.00
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N. Administrative and support service activities
A. Agriculture, forestry and fishing
I. Accommodation and food service activities
K. Financial and insurance activities
L. Real estate activities
D. Electricity, gas, steam and air conditioning supply
F. Construction
M. Professional, scientific and technical activities
J. Information and communication
H. Transportation and storage
B. Mining and quarrying
G. Wholesale and retail trade; repair of motor vehicles…
C. Manufacturing
Percentage share of the sample by the sector of economic activity
2000 2007 2018
210
Figure 4-5 Share of GDP in Russia by sector of economic activity (2018)
48
Based on the Federal State Statistic Service, the largest contributor to the overall
economy is the manufacturing sector (14.3%), followed by wholesale and retail trade
(13.9%) and mining and quarrying (13.2%). This figure clearly shows that the
contribution of the top three sectors to the overall GDP figures is proportional to the
sector of economic activities of the firms that are presented in the sample. Therefore,
it can be concluded that on a sectoral level, the sample of this thesis is representative
of the country.
Regional Distribution of the Sample
The regional distribution of the dataset can be seen in Figure 4.6. The graph
indicates that the largest portion of the firms operates either in Moscow or the Moscow
region (Moscow Oblast). These two areas combined cover 54.21% of the dataset. The
next largest region is Saint Petersburg, with 7.41% of the sample being represented
by that region. Even though the highest proportion of the sample is concentrated in
48 Federal State Statistic Service (https://www.gks.ru/accounts)
211
the capital city of Russia, the rest of the sample is geographically dispersed in the
western part of Russia. Only four companies out of the sample (1.35% of the dataset)
are based in the eastern part of Russia. Overall, it can be concluded that most firms
have their headquarters in the western regions of Russia, leaving the eastern ones
without any major players in any sector.
Looking into the geographical distribution of Russian GDP (Figure 4.7), it is possible
to establish that the main contributor is the City of Moscow (19.90%), followed by
Tymen Oblast (8.10%), which is the largest Russian region for oil extraction and
production, and Saint Petersburg (4.94%) and Moscow Oblast (4.94%). Taking into
account that the major oil and gas companies in the sample have their headquarters
in Moscow (which is the variable for geographical location), it is clear why the main
region in the sample of the thesis is Moscow. At the same time, looking at the
139
3122
10 8 8 7 6 6 5 5 5 4 3 3 3 3 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 10
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Breakdown of the sample by geographical region
Figure 4-6. Geographical breakdown of the sample.
212
geographical distribution of the GDP by region, it is possible to notice a similar pattern
between the sample and the overall Russian economy by geographical region. Both
figures represent a high concentration in the western region of Russia, leaving the
eastern part aside.
Figure 4-7 Share of GDP by Geographical Region (2017)
Sectoral and Regional Concentration From the geographical and regional distribution of the sample, it is possible to
conclude that the Russian economy is highly concentrated in terms of these two
factors. Based on the sample, the majority of the largest Russian firms operate in either
manufacturing or the wholesale and retail sectors and are based in the western part
of Russia, Moscow Oblast and St. Petersburg Oblast. Such interactions between the
sectoral and regional parameters of Russian firms is well documented in the academic
literature.
213
The most important parameter for the economic development of the Russian
regions is the amount of natural resources that is available in the region (Rastvortseva
and Chentsova 2015). This is because Russia has an export-oriented economy49,
which means that the largest Russian companies, such as Gaszprom, Lukoil, and
Bashneft, will operate primarily in certain regions which are rich in natural resources
(the western part of Russia). Such a concentration of natural resources in certain
geographical areas creates an agglomeration effect, which contributes to the
concentration of manufacturing enterprises, service providers and skilled workers in
the region (Rastvortseva 2018).
Based on the overview of the sample, it can be concluded that the dataset
represents the largest 297 companies in Russia in 2016, dominated by the
manufacturing sector and wholesale and retail trade sectors, with 26% of the firms
listed on either domestic or foreign exchanges.
Control Variables in the Sample
The control variables that are used in the sample can be divided into two
groups. The first group is related to the size and age of the firm, and the second group
concerns the corporate structure of the firm. The first group includes the total number
of employees, total assets in thousands of rubles, total revenue in thousands of rubles,
total fixed assets in thousands of rubles, and total intangible assets in thousands of
rubles.
The histograms of the control variables (Appendix B) demonstrate that they
have a normal distribution on a yearly basis. The histograms also suggest that the
49 Figure 4.32 illustrates the Russian export of goods, with the main category consisting of mineral fuels/ oils and products of their distillations (61.6%)
214
density of the size variables (total assets, total fixed assets, total revenue, total
intangible assets) is increasing over time, which means that the groups in the sample
are converging in terms of these variables, rather than diverging. The age of the firm
was constructed using the establishment year of the corporation from the Amadeus
database. By subtracting the year of incorporation from the corresponding year of the
observation, the variable states the full number of years from the incorporation date.
The variable that represents the total number of employees was downloaded from the
Amadeus database; however, it included some missing observations. To fill the gaps
and to construct an accurate variable that measures the number of employees, the
Amadeus database was crosschecked with the Interfax Spark data. If neither of the
resources had the information, the publicly available documentation of the firm (i.e. the
annual report) was used where possible.
The second group of variables that should be controlled in the regression
analysis is the group of dummy variables that may have a relationship with the
corporate governance structure of the firm (state-owned enterprise, board existence,
and publicly quoted firm). All these variables are dummy variables.
As mentioned in the academic literature (Chapter 1), the state plays an
important role in the largest Russian companies. (Abramov et al., 2017; Grosman et
al., 2017). The state-owned enterprise variable has a value of one if Russian
government ownership of the firm is higher than 50.01%, and zero otherwise. In that
case, this variable accounts only for direct state ownership in the sample.50 The
ownership data was downloaded from the Amadeus database and varies over time.
50 The literature on the topic of state-owned enterprises in Russia points to the fact that it is not
possible to clearly identify the indirect ownership of the state due to the lack of information available (Abramov, Radygin, Chernova, 2017).
215
Figure 4.8 of the thesis clearly shows that from the year 2000, there was a
steady decrease in the number of state-owned enterprises in the largest Russian
corporations. Up to 2006, the share of SOE dropped from 38.05% to 13.13%.
After 2006, the share of the Russian state started to increase up to 21% in 2013, and
from that moment it began to increase at a decreasing rate. This trajectory is in line
with the IMF report on the Russian state’s size (2017).
Figure 4-8 Share of state-owned enterprises
The board existence variable demonstrates whether the firm has a board of
directors or not, and is equal to one when a firm announces the creation of a board of
directors. This variable was constructed based on the information from Interfax Spark.
The publicly quoted variable represents if the firm is listed on any domestic or
foreign exchanges. This variable is equal to one if the firm had an initial public offering
(IPO) during the year, and zero otherwise. Based on the academic literature, an IPO
“is the point of entry that gives firms expanded access to equity capital, allowing them
216
to merge and grow” (Fama & Fench, 2004). Financing through equity provides firms
with an opportunity to further develop their existing capabilities and can support
international expansion (Carpenter et al., 2003; Filatotchev & Piesse, 2009); therefore,
IPO can be seen as an initial step for future internationalisation processes.
On the other hand, initial public offerings will require the firms to set a certain
standard in corporate governance. For example, in the rules of the Moscow stock
exchange, the firm must establish the board of directors, an audit committee with the
independent director, and a compensation committee. Also, Russian law provides for
a two-tier board system in public companies. That means that prior to the IPO, the
firm’s corporate restructuring should take place, and therefore firms which have been
through an IPO should have a higher level of corporate governance in comparison to
other companies that are not listed on any exchanges, ceteris paribus. If a firm starts
to expand into the foreign markets after the IPO, the gap between two firms,
concerning the level of corporate governance will increase.
Hypothesis 4:
After the IPO of the firm there is a statistically significant relationship between the
internationalisation and its corporate governance restructuring.
Out of 297 firms in the sample, 62 firms are listed on an exchange. It can be
seen from Figure 4.9 that the number of listed firms against non-listed firms in the
sample is increasing at a decreasing rate from the year 2000 up to the year 2008. In
the post-crisis period, the number of firms that were listed on either domestic or foreign
exchanges was almost unchanged. The main exchange for listed firms in the sample
is the Moscow stock exchange.
217
Figure 4-9. Percentage of listed against non-listed firms.
The Dependent Variable
The dependent variable of this thesis will look at the corporate
governance board to determine how internationalisation phenomena do or do not
impact corporate governance structure. Even though the literature specifies three main
aspects of corporate governance that should be taken into consideration when
discussing the topic of corporate governance (board of directors, transparency and
disclosure, and minority shareholder protection), the strategic decision on
internationalisation is taken by the owners/entrepreneurs in SMEs or by directors on
the boards of multinational companies (Perks & Hughes, 2008; Nielsen, 2010;
Neubert, 2017; Neubert & Van Der Krogt, 2019). Even though this thesis will
concentrate on the board of directors as a focus of the analysis, it will allow for different
ways to measure corporate governance and a clear interpretative framework (see the
218
literature review chapter). The main reason to use the board of directors as a
dependent variable is that internationalisation may trigger the vital changes that should
be taken into consideration by the existing board during the process (e.g. hiring of non-
executive international directors). In some cases, the rapid international growth of
small and medium enterprises may require the board to be established to enter the
foreign market and to increase the chance of survival in the internationalisation
process (e.g. creation of a joint venture with the board of directors as a result of the
foreign representative on the board). Also, the strategic decision of becoming an
international firm may require the consideration of certain corporate governance
changes prior to the internationalisation process. For example, listing on a foreign
exchange may require the expansion of the board, or an increase in the number of
non-executive directors on the board, while the international operation in certain
sectors of economic activities (such as manufacturing) might require the firm to change
from a one-tier board system to two-tier board system.
To accurately analyse the changes in the structure of the board of directors, it
was important to consider the composition of the board. The following six
characteristics were investigated: the size of the board, age, gender diversity,
percentage of executive and non-executive directors on the board, share of foreigners
on the board, and board structure (one-tier or two-tier board)51.
51 The comparison between the two-tier board and one-tier board system is widely discussed in the literature (Tüngler, Grit T, 2000; Pillay 2013; Millet-Reyes et al., 2010; Van Camp et al. 2020. The “Anglo-American” model of a one-tier board structure is largely a reflection of the neoliberal norms of shareholder primacy and free-market capitalism. The German two-tier model is in many ways a reflection of stakeholder primacy, codetermination, and managerialism. In the two-tier board structure, a separate board of directors supervise the executive team and provides a recommendation to the executive team. In the one-tier board structure, the executive and non-executive or supervisors are all members of the same board, i.e. they collectively form one company body. The core differences between the boards lie in the segregation of roles, speed of the decision making process, role of the chairman and CEO.
219
To construct accurate and detailed board variables, this thesis investigated
three main sources. The first source was the database provided by Interfax Spark,
which has the firm-level data for all Russian firms, including the name of the director,
age, current position, position previously held, and the history of change in the board
of directors. Secondly, the Spark database was combined with the publicly available
information derived from the annual report as a complimentary source for data
accuracy and completeness. Thirdly, as some of the firms in the sample were listed
on the Moscow stock exchange, the available information on the directors of listed
firms was also used as an additional source for cross checks. The data was collected
and then reshaped for each firm individually by cleaning and merging the information
for each current director on the board and all the previous members. The data between
2000 and 2002 is less reliable as none of the sources above would show the complete
structure of the board.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Firms with the board of directors vs no board of directors
Board exist No Board
Figure 4-10. Share of the firms in the sample with the board of directors
220
Figure 4.10 represents the share of the firms with a board of directors against
those firms that do not have a board and are managed by either a single owner or
owned by other corporations who nominated the managing director, or a firm limited
by shares and which has several owners/partners. To construct this variable, two
sources were merged. The original data was gathered from the Interfax Spark
database, which has detailed firm-level data on the current and past board members
of Russian firms. If this information was absent, then the BvD Amadeus database was
checked for the same companies, and in all cases the companies that did not have
any information from Spark about the board of directors had a single owner/manager
(if they were controlled by other firms). The graph clearly shows that by 2007, at least
one-third of the firms had established a board of directors, and after that period the
number of firms which had a board of directors remained constant.
Out of firms with a board of directors, a slightly higher number of firms had a
two-tier board system compared to firms with a one-tier board system (Figure 4.11).
On average, 54% of the sample with a board chose the two-tier board system. To
construct this variable, the detailed company reports from BvD Amadeus were used.
These reports highlighted the members of the board of directors (supervisory board)
and executive board if it existed. If the executive board did not exist in the report, but
the report included the board members, it was assumed that the firm has a one-tier
board structure. The literature on the board structure emphasises the benefits of using
a one-tier or two-tier board structure, but it does not suggest that one is better than the
other, as the board structure should be firm-specific (Rouyer, 2013; Jungmann &
Carsten, 2007; Pellegrini & Sironi, 2017).
221
Figure 4-11. Corporate structure of the board, by year
Row Labels
No board of directors
1 -tier Board 2-tier board
Total Number of
firms
2000 184 - - 184
2001 195 2 1 198
2002 199 3 6 208
2003 193 12 12 217
2004 194 17 26 237
2005 194 26 36 256
2006 187 33 44 264
2007 188 38 50 276
2008 189 42 52 283
2009 198 44 53 295
2010 191 44 53 288
2011 194 44 54 292
2012 192 46 54 292
2013 193 47 54 294
2014 195 47 54 296
2015 196 47 54 297
2016 196 47 54 297
2017 197 46 54 297
2018 197 46 54 297
Board Size
The sample total coverage in 2018 was 924 directors. The board size varies
from the smallest board of four directors to the largest board on the sample, which
consists of 16 members. The average number of directors on the board has steadily
increased from 7.25 in the year 2003 to 9.15 in 2018. However, in terms of the board
of directors, the crucial difference lies between listed and non-listed firms (Figure
4.12).
222
Figure 4-12. Average board size in the sample, by year
Year
Average Board Size in
the sample
Average board size of
non-listed firms
Average board size of listed firms
2001 6.33 6.50 6.00
2002 7.22 6.50 7.43
2003 7.25 7.13 7.31
2004 7.88 7.50 8.11
2005 7.77 7.30 8.00
2006 7.66 6.50 8.13
2007 7.77 6.79 8.14
2008 7.84 6.18 8.35
2009 7.96 6.04 8.62
2010 8.16 6.16 8.85
2011 8.24 6.15 8.99
2012 8.50 6.11 9.38
2013 8.66 6.19 9.55
2014 8.75 6.23 9.61
2015 8.71 6.27 9.54
2016 8.86 6.44 9.65
2017 9.01 6.29 9.86
2018 9.15 6.42 10.25
Average 8.1 6.48 8.65
As can be seen from the graph, the average number of directors for non-listed firms is
on a fixed level of around 6.48 directors per board, while the average number of
directors of listed firms is around 8.65 for the whole period of 19 years. The data
indicate that after the introduction of the corporate governance code in 2002, both
listed and non-listed firms started to increase their board size; however, after 2005,
there was decoupling between the listed and non-listed companies and the average
gap between the two groups increased on a yearly basis.
223
Board Age
The average age of the board in the sample is 50.71 (Figure 4.13). One of the
reasons that the average age of directors is so low is the missing observations in the
early years of the sample. However, a report by Spencer Stuart on the Russian Board
Index (2017) suggests that that average age of the top 50 listed firms in 2017 was
54.3, while the sample of this thesis has 73 listed firms and the average age of the
board members is 54.7. The report also claims that the Russian boards remain the
youngest in Europe, ahead of Poland at 55.5 years; at 61.1 years, Swiss boards had
the highest average age in 2017. While the board size differs between the listed and
non-listed firms, the average age of the listed and non-listed firms has an insignificant
difference.
Figure 4-13. The average age of the board, by year.
Year Average age of the board
Average board age of
the non-listed
Average board age of
the listed firm
2001 42.52 40.69 46.17
2002 46.21 41.69 47.50
2003 46.14 45.34 46.53
2004 45.60 44.32 46.36
2005 46.50 45.82 46.82
2006 47.12 46.65 47.30
2007 47.51 47.25 47.60
2008 48.08 48.34 48.01
2009 48.96 49.08 48.92
2010 49.77 50.06 49.68
2011 50.41 50.35 50.43
2012 51.08 50.72 51.21
2013 51.52 51.14 51.66
2014 52.25 52.24 52.26
2015 52.98 52.77 53.05
2016 53.95 53.81 54.00
2017 54.77 54.97 54.71
2018 55.63 55.83 55.57
Average 50.71 50.27 50.86
224
Board Gender Diversity
The gender diversity in the represented sample is in line with the literature on
the corporate board diversity of Russian firms (Batayeva & Antonov, 2017; Garanina,
Tatiana, Muravyev & Alexander, 2018). The proportion of female board members
(Figure 4.14) is, unfortunately, very low, and on average is not greater than one (which
means that most of the boards of directors in the sample do not have a female director
on the board).
Figure 4-14. Board gender diversity in listed and non-listed firms
Year
Average number of male board
members
Average number of
female board
members
Average number of male board members in
the non-listed firms
Average number of
female board members in
the non-listed firms
Average number of
male board
members in the listed firms
Average number of
female board
members in the listed
firms 2001 6.33 0.00 6.50 0.00 6.00 0.00
2002 7.22 0.00 6.50 0.00 7.43 0.00
2003 7.17 0.08 7.00 0.13 7.25 0.06
2004 7.53 0.35 7.00 0.50 7.85 0.26
2005 7.45 0.32 6.95 0.35 7.69 0.31
2006 7.31 0.35 6.18 0.32 7.76 0.36
2007 7.40 0.38 6.38 0.42 7.78 0.36
2008 7.41 0.43 5.77 0.41 7.92 0.43
2009 7.47 0.49 5.56 0.48 8.12 0.49
2010 7.66 0.50 5.68 0.48 8.34 0.51
2011 7.67 0.58 5.58 0.58 8.41 0.58
2012 7.83 0.67 5.41 0.70 8.72 0.66
2013 7.90 0.75 5.44 0.74 8.79 0.76
2014 7.90 0.84 5.42 0.81 8.75 0.86
2015 7.83 0.87 5.38 0.88 8.67 0.87
2016 7.96 0.90 5.56 0.88 8.74 0.91
2017 8.09 0.92 5.38 0.92 8.94 0.92
2018 8.17 0.98 5.42 1.00 9.03 0.97
Average 7.57 0.52 5.95 0.53 8.12 0.52 The difference between the listed and non-listed firms indicates an interesting pattern
in that the non-listed firms had at least one female director on the board in 2018, while
the listed companies’ figure is slightly below one. One of the reasons for this is the fact
that these non-listed firms, which have a smaller number of board members on
225
average, can have a highly concentrated ownership, particularly in family-owned
businesses, in which the family members dominate the board.
Concerning the dynamics of the female board members of the listed firms
(Figure 4.15), we can see a steady increase from 2004 to 2014 and a period of
stagnation after 2014. During the construction of the sample, it was clear that in the
past four years, listed firms actively rotated the members on the board of directors
(from the management board to the executive board) without any significant changes
to the board composition.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Gender diversity of the board of listed firms
Share of female Directos Share of Male Directors
Figure 4-15. Gender diversity of the board of listed firms
226
Foreign Directors vs. Domestic Directors
Figure 4.16 represents the average number of foreign and Russian directors on the
board. The average number of foreign directors on the board is equal to 0.92, which
is equivalent to a 12.8% share in the average board of directors. The data between
2001 and 2004 suggests that the average number of foreign directors on the board
decreased from 1.33 to 0.79. However, this result may be misleading due to the large
number of missing observations in these years and the small number of firms that
reported their board structure. After the introduction of the first code of corporate
governance in Russia in 2002, it seems that the transparency and disclosure of the
information in large corporations began to improve, and from 2005 there was a steady
increase in the number of foreign directors on the board.
Figure 4-16. Average number of foreign and Russian directors on the board.
Average number of Russian
directors on the board
Average number of
foreign directors on
the board
Average number of Russian
directors on the board of non-listed
firms
Average number of
foreign directors on the board of non-listed
firms
Average number of Russian
directors on the board of listed firms
Average number of
foreign directors on the board of listed firms
2001 5.00 1.33 4.50 2.00 6.00 0.00
2002 6.11 1.11 4.50 2.00 6.57 0.86
2003 6.29 0.96 6.25 0.88 6.31 1.00
2004 7.09 0.79 6.94 0.56 7.19 0.93
2005 7.11 0.66 6.75 0.55 7.29 0.71
2006 6.95 0.71 6.05 0.45 7.31 0.82
2007 7.07 0.70 6.42 0.38 7.31 0.83
2008 7.11 0.73 5.82 0.36 7.50 0.85
2009 7.16 0.80 5.56 0.48 7.71 0.90
2010 7.37 0.80 5.64 0.52 7.96 0.89
2011 7.42 0.82 5.77 0.38 8.01 0.97
2012 7.60 0.90 5.52 0.59 8.36 1.01
2013 7.71 0.95 5.59 0.59 8.47 1.08
2014 7.75 0.99 5.62 0.62 8.49 1.12
2015 7.65 1.06 5.69 0.58 8.32 1.22
2016 7.76 1.10 5.88 0.56 8.38 1.27
2017 7.91 1.10 5.75 0.54 8.58 1.27
2018 8.05 1.10 5.88 0.54 8.73 1.27
Average 7.17 0.92 5.78 0.70 7.69 0.95
227
There is also a significant difference between the listed and non-listed firms in
the share of foreign directors represented on the board. On average, listed firms show
a clear positive growth rate after 2005 up until 2016. In 2016, the average remained
at the same level of 1.27 foreign directors per board of directors in the listed firms.
That increase may be linked to several factors. Firstly, the implementation of the
Russian corporate governance code impacted the listed firms in particular. Secondly,
the globalization of Russian multinationals, a certain proportion of which are listed on
the Moscow stock exchange, required the expertise of foreign directors for better
market entries and development of global strategies.
On the other hand, non-listed firms do not show any progression towards an
increase in the share of international directors on the board. This can be due to the
firm-specific characteristics and needs at a particular moment in time. For example, if
the non-listed firm is operating in a certain sector of economic activity that requires
international relations with the perspective of the foreign market, then this firm may
hire an international board member who can provide not only experience but also
valuable network connections for successful market entry.
Executive and Non-executive Members of the Board
The total number of non-executive directors on the board increased from 5.26%
in 2001 up to 19.7% in 2018 (Figure 4.17). On average, the board of directors in 2018
had 1.8 non-executive directors. The data indicates that over the last 19 years, the
average number of non-executive directors has steadily increased.
The average number of non-executive directors among the non-listed firms
follows the same pattern as the number of foreigners on the board for non-listed firms:
it has a constant number, with some insignificant changes between 0.7 and 0.8 non-
228
executive directors on the board, throughout the dataset period. This can be explained
by the ownership concentration that exists in the number of non-listed firms with a
board of directors, and that in these firms, directors are also the senior managers of
the firms. A major leap occurred between 2006 and 2007, from 0.45 to 0.75 non-
executive directors on the board.
Figure 4-17. Average number of executive and non-executive directors on the board.
Year
Average number of executive directors
Average number of
non-executive directors
Average number of executive
directors of non-listed firms
Average number of non-
executive directors of non-listed
firms
Average number of executive
directors of listed firms
Average number of
non-executive directors of listed firms
2001 6.00 0.33 6.00 0.50 6.00 0.00
2002 6.67 0.56 6.00 0.50 6.86 0.57
2003 6.58 0.67 6.75 0.38 6.50 0.81
2004 7.05 0.84 7.13 0.38 7.00 1.11
2005 6.82 0.95 6.65 0.65 6.90 1.10
2006 6.78 0.88 6.05 0.45 7.07 1.05
2007 6.81 0.97 6.04 0.75 7.09 1.05
2008 6.74 1.10 5.41 0.77 7.15 1.19
2009 6.85 1.11 5.28 0.76 7.38 1.23
2010 6.99 1.17 5.36 0.80 7.55 1.30
2011 7.01 1.23 5.35 0.81 7.60 1.38
2012 7.16 1.35 5.30 0.81 7.84 1.54
2013 7.19 1.47 5.44 0.74 7.81 1.73
2014 7.11 1.64 5.42 0.81 7.68 1.92
2015 7.03 1.68 5.46 0.81 7.57 1.97
2016 7.13 1.74 5.64 0.80 7.61 2.04
2017 7.24 1.77 5.58 0.71 7.75 2.10
2018 7.35 1.80 5.67 0.75 7.87 2.13
Average 6.92 1.18 5.81 0.68 7.29 1.35
In contrast, the average number of non-executive directors on the board of
listed firms has steadily increased, and in 2018 was equal to 2.13 non-executive
directors on the board. This suggests that the boards of the listed firms are becoming
more independent in comparison to the non-listed firms.
229
In regard to the board composition in the sample, it can be concluded that, on
average, 27% percent of the firms in the sample established a board of directors. The
crucial difference within these boards of directors exists between the listed and non-
listed firms. If a firm went through an initial public offering, the data suggests that it
would have a larger board size in comparison to a non-listed firm. At the same time,
the board would be more diversified in terms of the number of executive directors on
the board and the number of foreign directors on the board. However, the boards of
listed and non-listed firms seem to be almost identical in terms of the number of female
directors on the board and the average age of the boards.
Even though this data reflects a representative sample of a Russian board of
directors, some variables are missing. When corporate governance scholars analysed
the board compositions, they also focused their attention on the number of
independent directors on the board and the CEO duality. In the case of Russian
companies, the definition of ‘independent directors’ is very clear. The independent
directors are “persons who not only do not serve as members of the managerial board,
but are also independent from the officers of the company and their affiliated persons
and from major business partners of the company, and do not have any other relations
with the company that may affect the independence of their opinions”52. At the same
time, the CEO duality refers in the literature to the situation when the CEO of the
company is also the chairman of the board. Both of these mechanisms of corporate
governance are primarily used in the literature to mitigate the agency problem and
improve firms’ performance( Baysinger, 1985; Jensen and Murphy 1990; Boeker, and
Goodstein, 1991; Daily, and Dalton, 1993) . During the data collection exercise, the
databases did not provide this information for the non-listed companies, which
52 Russian corporate governance code 2002
230
represented two-thirds of the overall sample; therefore, these variables were
eliminated from the research in order to mitigate the issues arising from the large
number of missing observations.
Internationalisation Variables53
The definition of an international firm in this thesis stems from the idea
that an “international” company has to have a physical presence in a foreign market
through either subsidiary or joint ventures with another foreign company. For that
reason, two primary sources of data were used to construct such a variable: the
cumulative number of foreign and domestic subsidiaries in each year (using the BvD
Amadeus database), and the cumulative number of foreign and domestic mergers and
acquisitions in each year (using BvD Zephyr data). Both databases (Amadeus and
Zephyr) covered the entire period of the study, thus creating the time-variant variables
for the analysis.
Foreign and Domestic Subsidiaries
The BvD Amadeus database provides information about direct and indirect
subsidiaries of a given company, together with their percentage of ownership. This
relationship between the parent firm and all of its direct and indirect subsidiaries can
be unfolded or disentangled for up to ten levels in the company’s report file54. This
means that the firm-level data will show that parent firm A owns 100% of company B
53 As this thesis defines internationalisation as the operations of the foreign markets through
subsidiaries and acquisitions, the export-oriented variable, such as the number of foreign sales of the total value of exports, was not included in the dataset. Both, Interfax Spark and BvD Amadeus provide information about the total number of foreign sales; however, the number of missing observations for that variable is above 85%, which makes it unreliable. 54 As defined in the BvD Amadeus database, an entity is directly owned or part-owned by an individual or entity if the ownership link is direct and passes through no other individuals or entities. In the case of indirect ownership, a simple chain of two or more ownership links exists between an owned or part-owned entity, and an owning or part-owning individual or entity, via one or more intermediate entities.
231
(level one), and company B, in its turn, owns 60% of company C (level two); thus
company A directly owns company B and indirectly owns company C, which will be
shown as the level two relationship.
To construct the number of foreign and domestic subsidiaries, the following
methodology was applied. Firstly, the fully unfolded subsidiary data (on all levels) was
downloaded for each individual firm in the dataset. The subsidiary information included
the country of the subsidiary, subsidiary name, direct and indirect ownership, and the
level of the relationship to the parent company (from one to ten). The subsidiary
information provided in the BvD Amadeus database also included the total revenue,
total assets and number of employees for the last available year. However, the
financial information (total revenue, total assets, and total number of employees) for
the subsidiaries had a significant number of missing observations and did not include
any historical data (the data did not vary through time); it was therefore not included
in the dataset of this thesis.
Secondly, the subsidiary data was reduced to count only those subsidiaries that
are directly or indirectly controlled by the parent company at each level of
disaggregation. Based on the minimum value of ownership (0.01%) available in the
BvD Amadeus database, the assumption for the ownership threshold of the parent
company should be at least 50.01%, either directly or indirectly. In this case, the parent
company can participate in decision-making processes and change the corporate
structure.
Some of the ownership data had to be cleaned before applying the threshold
level. The data with the special codes had to be converted into the numeric values
where possible: “WO” (wholly owned) with 100%, “MO” (majority owned) with 50.01%
“CQP1” (50% plus one share) with 50.01%, “NG” (negligible) with 0.01%, “-” (not
232
significant) or “n.a.” (not available) with missing data. The special codes, such as the
± symbol, >= or <=, or % sign after the number, had to be replaced without changing
the actual number.
Thirdly, the data processing created a variable to distinguish between the
foreign and domestic subsidiaries, which was done based on an acronym of the
country of the subsidiary. If the acronym of the country of the subsidiary was different
to the acronym of the Russian Federation (RU), then the company would be counted
as foreign, and domestic otherwise. Summing up the number of subsidiaries with a
foreign acronym for each year by firm would provide the total number of foreign
subsidiaries of the parent firm from the sample for each year. On the contrary,
summing up the number of subsidiaries with a domestic acronym for each year would
give the total number of domestic subsidiaries of the parent firm from the sample for
each year.
The data had some limitations. At the time of the collection of this data, the BvD
Amadeus database provided information only up to the year 2016. The following years
had either a large amount of missing ownership information or duplicated the values
from the last available year of the information. For that reason, the number of
subsidiaries (either foreign or domestic) stayed constant after 2016. The other
limitation of the Amadeus database is that it covers only European companies, thus
the subsidiaries which are located beyond Europe were not always recorded.
Notwithstanding these limitations, the database remained extremely rich and
informative.
233
Looking at the descriptive statistics of the total number of foreign and domestic
subsidiaries, it can be concluded that from the beginning of the sample (the year 2000),
more than half of the firms were pursuing either domestic or international growth
(Figure 4.18). The percentage of firms with at least one recorded subsidiary steadily
increased from 53% in 2000 to 69% in 2018. For the firms that had at least one
domestic or foreign subsidiary, the average number of domestic subsidiaries was
23.05 while the average number of foreign subsidiaries was just 4.26 (Figure 4.19).
This shows that most of the largest Russian firms concentrated on the domestic
market rather than foreign expansion. At the same time, there were just three firms
(maximum four between the years 2005 and 2008) in the sample which only had
foreign subsidiaries. For both the total number of domestic subsidiaries and total
number of foreign subsidiaries, the distribution is skewed to the right, suggesting that
the larger number of firms had a smaller number of foreign and domestic subsidiaries
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Percentage of firms with and without subsidiaries
At least one subsidiary No subsidiaries
Figure 4-18. Percentage of firms with and without subsidiaries.
234
in relation to the mean, and, at the same time, the sample included some outliers like
Gazprom or Lukoil that had more than 250 subsidiaries.
Figure 4-19. Descriptive statistics of foreign and domestic subsidiaries.
Variable Obs. Mean Std. Dev. Min Max
Domestic Subsidiaries 3,218 23.055 49.78074 0 395
Foreign Subsidiaries 3,218 4.267557 16.87969 0 232
Total Number of Subsidiaries 3,218 27.32256 60.34797 1 444 Looking at the growth rate of foreign and domestic subsidiaries (Figure 4.20),
we can conclude that in the time span of the last 19 years, there were two major spikes
in the number of foreign subsidiaries among the top 297 Russian firms. The first
occurred after the introduction of the corporate governance code in Russia in 2002,
which was introduced as a set of guidelines from the world’s best practices for large
corporations. The second spike was in 2007, right before the financial crisis, and this
is also linked to the fact that Russia, as one of the emerging markets at that time, was
growing rapidly, and it provided good opportunities for the Russian firms to fortify their
positions in the European market.
235
The number of domestic subsidiaries is highly correlated with the number of
foreign subsidiaries throughout the last 19 years, which suggests that, in general, the
expansion phase of the firms in both domestic and foreign markets was occurring at
the same time. The only difference that is seen from the graph is the year 2015 to
2016. This difference arises from the change in the macroeconomic environment that
occurred after the year 2014 as a result of strict sanctions from the western countries.
The sectoral breakdown represented in Appendix B suggests that the largest
number of domestic subsidiaries in 2018 were established by firms operating in the
manufacturing sector (1012 domestic subsidiaries), closely followed by the companies
operating in information and communication (1010 domestic subsidiaries) sector of
economic activity. This highlights the rapid penetration of the domestic market by the
largest IT firms in Russia from early 2000 to the present time. However, the largest
growth rate was observed in the electricity, gas, steam and air conditioning supply
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Growth rate of foreign and domestic subsidiaries
Growth of Foreign Subsidiaries Growth of Domestic Subsidiaries
Figure 4-20. Growth dynamic of foreign and domestic subsidiaries.
236
sector, which resulted from the vertical integration of the largest energy companies
and their increased interest in the domestic market, from pure export-based strategy.
Looking at the breakdown of the international subsidiaries in 2018, the largest
number of them were established by firms operating in the sector of professional,
scientific, and technical activities. However, this result is “dragged” rightward by the
outlier, as the Russian oil firm “Lukoil” is registered in this sector, and its number of
foreign subsidiaries in the year 2018 was 232 out of the total 253. This suggests that
it would be more appropriate to count the firms operating in the transportation and
storage sector (202 foreign subsidiaries) as the leader in the number of foreign
subsidiaries in the year 2018. This sector is closely followed by the manufacturing
sector (174 foreign subsidiaries) and information and communication sectors (147
foreign subsidiaries).
Foreign and Domestic Merges and Acquisitions
To construct the full picture of a firm’s internationalisation, it is also important to
look not only at the subsidiaries, which are established by the parent firm itself, but at
the firms that were created as a joint venture with the foreign firm or through mergers
and acquisitions (M&As), after which the parent company gains control over the
foreign firm. In both cases, the parent firm would be able to take part in the managerial
decision-making processes or change the corporate structure of the newly created or
acquired firm. For this purpose, this thesis used the BvD Zephyr database, which
contains information on M&A, IPO, private equity and venture capital deals and
rumours globally, to construct the number of foreign M&As, number of domestic M&As
and the total number of M&As for each firm in the sample.
237
The Zephyr database provided the information about the acquirer firm (which is
the parent firm from the 297 companies) and the complete information about the target
firm (the firm that was acquired by the parent firm). This database also covered the
period up to the year 2018, which, to some extent, compensates for the limitation of
the subsidiaries variables which do not vary after 2016.
The following methodology was used to construct the required variables. First,
the initial download from the Zephyr database was reduced to 297 acquirer firms to
match the number of companies in the sample of this thesis. The total number of deals
that all these firms had over the period of 29 years was 6110. Secondly, the database
was filtered to use only a certain type of deals, the result of which would be that the
acquirer firm would own more than 50.01% of the target firm. Under these criteria, the
following deal types were included: acquisition deals with 50.01%+; acquisition
increase deals that led to the acquirer firm owning more than 50.01% of the target firm;
capital increase deals by more than 50.01%; joint venture deals in which the acquirer
owns more than 50%; mergers deals in which the acquirer owns more than 50%; and
minority stake increase deals in which the acquirer ended up with more than 50.01%
of the stake. The second cleaning filter was to count only those deals which were
completed. Thirdly, the deals were separated into foreign and domestic groups based
on the country of the target firm. If the country of the target firm was not Russia, then
this would count as a foreign M&A. If the country of the target firm was Russia, then it
would be counted as a domestic M&A.
Some of the M&A data had to be cleaned in the same way as subsidiary
ownership data. The data with the special codes had to be converted into the numeric
values where possible: “WO” (wholly owned) with 100%, “MO” (majority owned) with
50.01% “CQP1” (50% plus one share) with 50.01%, “NG” (negligible) with 0.01%, “-”
238
(not significant) or “n.a.” (not available) with missing data. If, at the end of the cleaning
process, the acquirer firm had a stake of less than 50.01% of a completed deal, such
a deal was dropped from the sample.
Figure 4-21. Descriptive statistics of foreign M&A and domestic M&A of the parent
company.
The descriptive statistics (Figure 4.21) represent that a much smaller number
of Russian firms in the dataset were using M&A as a method of geographical
expansion in domestic and foreign markets, in comparison to market expansion
through the establishment of new subsidiaries. The average number of M&A deals
which were completed and after which the parent company had a controlling stake in
the targeted firm is 8.09 for the whole period of 19 years. The number of domestic
M&A deals (7.02) is seven times higher in comparison to foreign M&A’s (1.07), which
also supports the idea that most firms pursue an increase in the share of the domestic
market before going international.
On the other hand, out of all the firms that had at least one M&A deal (either
foreign or domestic), the share of the firms that were using M&A deals as an instrument
for market growth increased steadily between 2000 and 2018 (Figure 4.22). Starting
from only 5% in 2000, almost half of the companies in the sample (49%) made at least
one M&A deal, which led to the control of the target company.
Variable Obs Mean Std. Dev. Min Max
Foreign M&As 1751 1.074814 2.630937 0 17
Domestic M&As 1751 7.024557 10.81882 0 85
Total M&As 1751 8.099372 12.7981 1 100
239
Similar to the growth rate of the subsidiaries, the growth rate of M&A deals
decreased after 2008. Figure 4.23 represents this decline, together with the very
strong correlation after 2008. There are several reasons for such a strong correlation
and for the steady increase, all of which are linked to the macroeconomic environment
that developed after the financial crisis. Firstly, the financial crisis itself decreased the
firm-level economic activity. Secondly, the sanctions from the western countries in
2014 restricted foreign activity, including the potential M&A deals.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Percentage of firms with and without M&A deals
At least one M&A deal No M&A Deals
Figure 4-22. Percentage of firms with and without M&A deals
240
The spike that can be seen on the graph in early 2000 to 2004 in the growth
rate of domestic M&A deals is the result of the initially low volume of M&A activity in
early 2000 (only 14 M&A deals). In that case, the largest companies in Russia were
able to double the initial amount almost on a yearly basis.
Looking at the sectoral breakdown of the foreign and domestic M&A activity
(represented in Appendix B), it is possible to conclude that the largest growing sector
of economic activity by domestic M&A deals was manufacturing (348 M&A deals),
followed by information and communication technology sector (199 M&A deals). This
represents the high correlation between the expansion approaches (own subsidiaries
or M&A activity) used by the largest Russian firms on the sectoral level of the domestic
market. The third largest sector in terms of the number of domestic M&A deals was
shared by the electricity, gas and steam industry, with a total of 192 M&A deals.
The foreign M&A deals breakdown by sector in 2018 was also led by the
manufacturing industry (57 M&A deals), followed by the information and
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
140.00%
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Growth Rate of Foreign and Domestic M&As
Growth of Foreign M&As Growth of Domestic M&As
Figure 4-23. Growth rate of foreign and domestic M&As
241
communication sector (38 M&A deals). This statistic indicates that the information and
communication technology sector experienced rapid growth both in the domestic and
foreign markets. The third largest number of foreign M&A deals (29) pertains to firms
operating in the wholesale and retail trade, followed by the financial sector (19 M&A
deals). This can indicate that the foreign M&A deals are primarily used as a tool to
increase market exposure during the internationalisation process.
Geographical Diversification
Another vital aspect of internationalisation in relation to corporate governance
is the geographical diversification of the internationalisation process; in other words,
the number of foreign markets in which the firm is operating. This may have a
significant effect on the corporate governance structure and, at the same time, will
justify if any corporate governance restructuring is necessary. For example, a firm from
Russia that is operating purely in the CIS (Commonwealth of Independent States)
region may require minimal adjustment to its corporate governance structure, in
comparison to a Russian firm that is operating in the United Kingdom or Germany.
For that reason, the dataset contains the variable that shows the number of
foreign markets in which the parent firm from the sample is operating. This variable
was constructed using the combined data from the number of subsidiaries and
mergers and acquisitions. The variable uniquely identifies each new foreign market on
a yearly basis. The average number of foreign markets for firms with international
activity (at least one foreign subsidiary or a single foreign M&A deal) is 5.7, with the
minimum of one and the maximum of 27 markets for a single firm (Figure 4.24). At the
same time, the increase in standard deviation (Figure 4.24) indicates that firms with
242
some degree of internationality have increased their operations in the foreign markets,
while the firms with no international activity pursue expansion on the domestic market.
Figure 4-24. Descriptive statistics of geographical diversification
year Mean of Foreign Markets
Std.Dev. of
Foreign Markets
Min Number Of
Foreign Markets
Max Number Of
Foreign Markets
2000 4.71 5.14 1 19
2001 4.97 5.18 1 20
2002 5.16 5.21 1 20
2003 5.75 6.07 1 21
2004 6.08 6.40 1 21
2005 5.88 6.40 1 21
2006 5.91 6.57 1 21
2007 5.71 6.62 1 22
2008 5.40 6.46 1 22
2009 5.42 6.34 1 22
2010 5.74 6.60 1 24
2011 5.82 6.76 1 25
2012 6.03 6.84 1 26
2013 6.06 6.87 1 27
2014 5.82 6.76 1 27
2015 5.88 6.75 1 27
2016 5.93 6.76 1 27
2017 5.93 6.76 1 27
2018 5.93 6.76 1 27
Total 5.76 6.49 1 27
Geographical Efficiency of the Board
To test the third hypothesis, that the internationalisation of a firm from a country
with a low level of corporate governance to a country with a high level of corporate
governance will be positively correlated with the positive corporate governance
change of that firm, it was important to construct a variable that would represent the
level of corporate governance at country level. For this purpose, the World Economic
Forum data was used. The variable that was used as a proxy was “efficiency of the
243
corporate board55” that has a value between one and seven, where one is poor and
seven is excellent. This data was collected on a yearly basis.
To create an accurate variable at firm level, it was important to construct the
index of the board efficiency based on the number of foreign markets and weighted by
the number of foreign subsidiaries and foreign acquisitions (separately) in that market.
For that purpose, I identified the total number of subsidiaries/acquisitions in each
market. After that, the weight of each market was calculated based on the ratio
between the number of the subsidiaries/acquisitions in the specific country and year
and the total number of foreign subsidiaries/acquisitions in a certain year. This weight
was multiplied by the country level board efficiency index and summed up to receive
a single index on a firm level.
The figures below represent the descriptive statistics for the index of the board
efficiency, weighted by the number of foreign acquisitions (Figure 4.25) and by the
number of foreign subsidiaries (Figure 4.26). The average index of the board efficiency
in Figure 4.25 shows that up to the year 2012, the index varied between 4.6 and 4.3.
After that period, we can see the steady increase in the index. This can be explained
by the fact that the M&A deals of the Russian firms, after which the Russian company
became the main owner, took place in the countries where the index of the board
efficiency is higher in comparison to the Russian market.
55 Definition of corporate board indicator from World Economic Forum: In your country, to what extent
is management accountable to investors and boards of directors? [1 = not at all; 7 = to a great extent]
244
Figure 4-25 Index of the board efficiency weighted by the number of foreign acquisitions.
Year
Average board efficiency
index
Std. dev. board
efficiency index
Min board efficiency
index
Max board efficiency
index
2000 4.57 0.25 4.30 4.80
2001 4.35 0.42 3.80 4.80
2002 4.30 0.34 3.80 4.80
2003 4.50 0.56 3.80 5.63
2004 4.55 0.45 3.80 5.57
2005 4.42 0.39 3.80 5.10
2006 4.53 0.43 3.79 5.09
2007 4.57 0.40 3.89 5.08
2008 4.60 0.37 3.77 5.30
2009 4.48 0.35 3.43 5.26
2010 4.37 0.33 3.64 5.19
2011 4.40 0.38 3.88 5.33
2012 4.37 0.44 3.73 5.53
2013 4.50 0.35 3.77 5.40
2014 4.62 0.36 3.87 5.36
2015 4.67 0.54 3.93 5.82
2016 4.77 0.60 3.97 6.12
2017 4.92 0.52 4.10 6.11
2018 4.92 0.52 4.10 6.11
Grand Total 4.59 0.47 3.43 6.12
Figure 4.26 illustrates the firm level index of the board efficiency weighted by the
number of foreign subsidiaries. Overall, between the year 2000 and 2018, the index
has an upward trend, during which there was a slight pullback after the year 2007,
from 4.99 to 4.70. The descriptive statistics also show that the standards deviation has
slightly increased over time, which could mean that some firms started to establish
subsidiaries in more advanced countries and not in CIS regions.
245
Figure 4-26 Index of the board efficiency weighted by the number of foreign subsidiaries.
Year
Average board efficiency index weighted by number of foreign subsidiaries
Std. Dev. board efficiency index weighted by number of foreign subsidiaries
Min board efficiency index weighted by number of foreign subsidiaries
Max board efficiency index weighted by number of foreign subsidiaries
2000 4.60 0.36 3.46 5.20
2001 4.58 0.35 3.50 5.20
2002 4.55 0.46 2.60 5.20
2003 4.66 0.49 2.68 5.37
2004 4.74 0.53 2.77 5.53
2005 4.79 0.61 2.85 5.70
2006 4.95 0.51 4.01 5.70
2007 4.99 0.51 4.13 5.92
2008 4.90 0.58 2.96 5.64
2009 4.77 0.52 2.94 5.44
2010 4.69 0.47 2.89 5.35
2011 4.69 0.46 3.11 5.33
2012 4.69 0.51 3.03 5.42
2013 4.78 0.45 3.77 5.48
2014 4.92 0.48 3.87 5.74
2015 5.14 0.59 3.98 6.01
2016 5.10 0.65 3.97 6.14
2017 5.10 0.65 3.97 6.14
2018 5.10 0.65 3.97 6.14
Grand Total 4.85 0.56 2.60 6.14
Graphical Analysis of Internationalisation and Corporate Governance
Since the focus of this thesis is internationalisation, it is important to graphically
assess its relationship with corporate governance variables. Figure 4.27 below
represents the average number of non-executive directors on the board for firms with
international activity (which either have one foreign subsidiary or one foreign
acquisition) and firms without international activity.
246
Figure 4-27 Comparison of the average number of non-executive directors on the board
between the firms with and without international activity
This graph illustrates that the average number of non-executive directors on the board
has steadily increased over time in firms with international activities. After the
intersection point of these two lines in 2002, when the Russian corporate governance
code was introduced, both types of firms increased the number of non-executive
directors on the board. However, after the year 2008, it is clear that firms with no
foreign subsidiaries or foreign acquisitions continued to introduce non-executive
directors at a decreasing rate. Figure 4.27 shows that internationalisation would have
a positive correlation with the number of non-executive directors on the board.
Figure 4.28 compared the number of firms that apply a one-tier board structure
between firms with international activity and firms without such activities. This graph
clearly shows that the one-tier board system prevails in the firms that do not operate
in foreign markets through subsidiaries or acquisitions. However, the graph also shows
that after the year 2013, there was a steady decrease in the number of firms that use
the one-tier board system. The primary reason for the decrease could be that firms
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Comparison of average number of non-executive directors on the board between the firms with and without international
activity
Firm with international activity Firm without international activity
247
changed their corporate structure to a two-tier board system due to IPO or to the fact
that the total number of shareholders became more than 50.
Figure 4-28 Comparison of 1-tier board system across firms with and without international
activity.
At the same time, Figure 4.29 represents a similar comparison, but across the firms
with a two-tier board structure. The pattern of these firms is different, and we can see
that the number of firms with the two-tier board structure was steadily increasing up to
the year 2000, regardless of internationalisation. In 2008, decoupling occurred and the
number of firms with foreign subsidiaries and acquisitions that used a two-tier board
in their corporate governance structure continued growing, while the number of firms
with no international activity started to decrease. This pattern can be justified by the
growing foreign direct investment in the Russian market between 2002 and 2008
(Figure 4.2). One of the ways to receive financing through equity would be to become
a public company and be listed on the Moscow stock exchange, and for that the board
0
5
10
15
20
25
30
35
40
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Comparison of 1-tier board system across firms with and wihtout international activity.
Firm With international activity Firm Without international activity
248
structure had to be changed from the one-tier board to the two-tier board system, or if
the firm did not have a board previously, to establish such a board. The decoupling
occurred at the same time as the FDI into Russia fell after the financial crisis of 2008,
and the trajectory of the two-tier board system among firms with or without
international activity was changed. As can be seen after 2008, there was a steady
decrease in the number of firms that used a two-tier board structure, and a continuation
of the growth in the number of firms with the two-tier board structure that operated on
the foreign markets through subsidiaries and acquisitions.
Figure 4-29 Comparison of the two-tier board system across firms with and without international activity.
Another important aspect of the corporate board that should have a positive
relationship with internationalisation is the number of foreign directors on the board.
Figure 4.30 represents the comparison of the average number of foreign directors on
the board, between firms with and without international activity. From 2002, when the
corporate governance code was introduced, we can see the spike in the number of
foreign directors on the boards of the firms with foreign subsidiaries and M&As.
0
5
10
15
20
25
30
35
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Comparison of 2-tier board system across firms with and without international activity.
Firm With international activity Firm Without international activity
249
However, a similar pattern can be seen in the firms without international activity, which
means that regardless of internationalisation, the corporate boards still hire foreign
directors. To support that statement, it is also important to look at the fact that the gap
between these two types of firms is almost unchanged after 2010. Therefore, the initial
spike in the number of foreign directors on the boards of firms with international
activities can be explained by the firms’ decision to be listed on the Moscow Stock
Exchange and to receive financing through equity, and, in this case, the foreign
director’s main role could be to represent the interest of foreign shareholders, rather
than playing a strategic role in the internationalisation process.
Figure 4-30 Comparison of the average number of international directors on the board between the firms with and without international activity
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Comparison of the average number of international directors on the board between the firms with and without international activity
Firm With international activity Firm Without international activity
250
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Rouyer E.,, (2013). "Company Performance and the Two-Tier Board Structure: Empirical Evidence from France," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 12(1), pages 45-58, June.
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252
Appendix B.
Number of
Foreign
Markets of
operation
Number of
Foreign
Subsidiaries
Number of
Domestic
Subsidiaries
Total
number of
Subsidiaries
Total
number of
M&A
Total
number of
Foreign
M&A
Total
number of
Domestic
M&A
board
structure =
1 if 1-tier
BoD, 2 if
Number of
directors on
the board
Avergae
age of the
board
Number of
male
directors on
the board
Number of
female
directors on
the board
Number of
executive
directors on
the boa
Number of
non-
executive
directors on
the
Number of
russian
directors on
the board
Number of
foreign
directors on
the board
Number of Foreign Markets
of operation 1
Number of Foreign
Subsidiaries 0.8082 1
Number of Domestic
Subsidiaries 0.7409 0.5385 1
Total number of Subsidiaries0.8328 0.7178 0.9732 1
Total number of M&A0.6396 0.581 0.2872 0.3958 1
Total number of Foreign
M&A 0.6051 0.4757 0.4848 0.5304 0.7339 1
Total number of Domestic
M&A 0.6376 0.5163 0.4674 0.5271 0.8165 0.9914 1
board structure = 1 if 1-tier
BoD, 2 if 0.3474 0.2411 0.3007 0.3142 0.3576 0.4695 0.468 1
Number of directors on the
board 0.3241 0.2293 0.2808 0.2946 0.3485 0.4574 0.456 0.9482 1
Avergae age of the board0.2745 0.2039 0.2341 0.2491 0.3156 0.406 0.4059 0.9242 0.9457 1
Number of male directors on
the board 0.3261 0.2327 0.275 0.2907 0.3505 0.4491 0.4493 0.9402 0.9925 0.9384 1Number of female directors
on the board 0.1498 0.0927 0.1814 0.1752 0.1618 0.2868 0.2749 0.532 0.5547 0.5258 0.4487 1Number of executive
directors on the boa 0.2976 0.2293 0.2507 0.2697 0.3372 0.4241 0.4255 0.9192 0.977 0.9367 0.9719 0.5266 1Number of non-executive
directors on the 0.2886 0.1407 0.2743 0.265 0.2518 0.3934 0.3829 0.6792 0.6908 0.6099 0.6779 0.4355 0.5208 1Number of russian directors
on the board 0.2911 0.194 0.2773 0.2821 0.293 0.4112 0.406 0.9144 0.976 0.9218 0.9687 0.541 0.9562 0.6652 1Number of foreign directors
on the board 0.2573 0.2302 0.1223 0.1638 0.3574 0.3619 0.3765 0.5004 0.4808 0.4594 0.477 0.2685 0.459 0.3686 0.2783 1
Figure 4-31. Correlation between the dependent and independent variables.
253
Figure 4-32. Distribution of Foreign and Domestic subsidiaries by sector of economic activities.
Sector of Economic Activity (NACE Rev.2)
Total number of Foreign
Subsidiaries (2000)
Total number of Domestic Subsidiaries
(2000)
Total number of Foreign
Subsidiaries (2007)
Total number of Domestic Subsidiaries
(2007)
Total number of Foreign
Subsidiaries (2018)
Total number of Domestic Subsidiaries
(2018)
M. Professional, scientific and technical activities 88 32 166 98 253 330
H. Transportation and storage 34 305 109 605 202 954
C. Manufacturing 56 282 88 556 174 1012
J. Information and communication 31 187 65 401 147 1010
K. Financial and insurance activities 16 74 87 340 143 677
F. Construction 18 115 40 225 74 424
G. Wholesale and retail trade; repair of motor vehicles and motorcycles 12 215 31 485 62 857
D. Electricity, gas, steam and air conditioning supply 5 50 25 508 61 932
B. Mining and quarrying 0 48 1 113 4 177
A. Agriculture, forestry and fishing 0 9 0 13 0 22
L. Real estate activities 0 5 0 11 0 18
254
Figure 4-33 Distribution of Foreign and Domestic M&A deals by sector of economic activities.
Sector of Economic Activity (Nace Rev.2) Total number
of Foreign M&As (2000)
Total Number of Domestic
M&As (2000)
Total number of Foreign
M&As (2007)
Total Number of Domestic
M&As (2007)
Total number of Foreign
M&As (2018)
Total Number of Domestic
M&As (20018)
C. Manufacturing 0 3 19 138 57 348
J. Information and communication 0 5 19 82 38 199
G. Wholesale and retail trade; repair of motor vehicles and motorcycles 0 0 5 20 29 87
K. Financial and insurance activities 0 0 5 42 19 87
M. Professional, scientific and technical activities 4 4 12 35 16 112
D. Electricity, gas, steam and air conditioning supply 0 1 0 16 7 192
H. Transportation and storage 0 1 0 18 7 48
B. Mining and quarrying 1 0 3 36 6 88
F. Construction 0 0 0 19 5 61
A. Agriculture, forestry and fishing 0 0 0 1 0 13
255
Figure 4-34. Histogram of log: Number of Employees
256
Figure 4-35. Histogram of log Total Assets in thousands of rubbles
257
Figure 4-36. Histogram of log” Total Fixed assets in thousands of rubbles
258
Figure 4-37. Histogram of log: Age of the firm
259
Figure 4-38. Histogram of log: Operating Revenue in thousands of rubbles.
260
Figure 4-39 What does Russia export? (2018)
56
56 Source: The Observatory of Economic Complexity https://oec.world/
261
Chapter 5 Regression analysis
This chapter of the thesis will focus on testing the four hypotheses previously
discussed in Chapter 2, Chapter 3 and Chapter 4. To test the first hypothesis,57 the
empirical analysis will focus on identifying the relationship between the dependent
variables measuring corporate governance and the independent variables measuring
foreign subsidiaries and foreign acquisitions. With regard to the second hypothesis58,
the analysis will focus on foreign markets, specifically examining whether the number
of foreign markets has a positive and significant effect on the number of foreign
directors on the board, and whether the geographical diversification of the firm leads
to a higher number of foreigners on the board. Next, to test the third hypothesis59, it is
important to focus on the index of board efficiency, a sophisticated measure weighted
by the relative importance of foreign subsidiaries and foreign acquisitions. In other
words, this hypothesis tests whether the internationalisation of the firm, from a country
with low levels of corporate governance, to a country with high levels of corporate
governance, will correlate with the restructuring of corporate governance mechanisms.
Finally, to test the fourth hypothesis,60 it is important to identify how corporate
governance mechanisms, measured by dependent variables, will vary due to
internationalisation in two groups of firms (listed and non-listed).
57 Hypothesis 1: Firm’s internationalisation, which occurs through opening a subsidiary or foreign acquisition in the
foreign market, will be positively correlated with the number of corporate governance mechanisms. 58
Hypothesis 2: Increase in the geographical diversification of the firm will be positively correlated with the share
of foreign directors represented on the board. 59
Hypothesis 3: Internationalisation of the firm, from a country with low levels of corporate governance, to a
country with high levels of corporate governance, will be correlated with a restructuring of corporate governance mechanisms.
60 Hypothesis 4: After the IPO of the firm there is a statistically significant relationship between the
internationalisation and its corporate governance restructuring.
262
Methodology
For this purpose, a panel database will be adopted and this choice has several
advantages for an empirical analysis. One of the main advantages is the possibility to
derive dynamic models (Maddala, 1993; Lee, 1998; Bond, 2002). Such dynamic
models can thus be used to determine the causal nexus between independent and
dependent variables.
The panel estimation model, for example, fully accounts for the existence of
time-invariant variables, not included in the model, correlated with explanatory
variables: correlation(X,e) different from zero, also called exogeneity assumption.
Such time-invariant omitted variables can be either observable, but not reported, or
unobservable, and hence missing by construction, and, therefore, might create biased
and inconsistent coefficients in traditional cross-section specification models. The
problem with observational data is that there are potentially an infinite number of such
unobserved variables, which could render the observed relationship endogenous (i.e.
a violation of the exogeneity assumption). This is the problem of so-called “unobserved
heterogeneity” (Green, 2002).
To resolve such drawbacks, academic literature proposes using the
fixed/random effects model which accounts for the unobserved heterogeneity. The
main assumption is that all these unobserved variables are time-invariant and they
could be potentially correlated with other regressors. In this case, the general form of
regression will be:
𝑌𝑖𝑡 = 𝛽1𝑋1,𝑖𝑡 + ⋯ + 𝛽𝑘𝑋𝑘,𝑖𝑡 + 𝛼𝑖 + 𝑢𝑖𝑡
Where 𝑌𝑖𝑡 is a dependent variable, 𝛽1 𝑢𝑝 − 𝑡𝑜 𝛽𝑘 are coefficients, 𝑋𝑘,𝑖𝑡 represents
independent variables, 𝛼𝑖 represents constant unobserved variables (also called “fixed
effect”) and 𝑢𝑖𝑡 which is an idiosyncratic error term.
263
All RHS and LHS variables are converted into natural logarithms. A log-log model
allows for easy interpretation of the effect of independent variables on the dependent
variables, in terms of elasticity.
For the robustness check, this thesis will also include a dynamic Generalised Method
of Moments model (GMM). The GMM method is particularly relevant when the panel
data have smaller numbers of years (T) in comparison to the number of groups (N),
which is the case in this data. The dynamic GMM model tests whether
internationalisation variables have a significant, positive effect on corporate board
mechanisms by lagging the internationalisation variables and considering them as
endogenous, as exemplified in the equation below:
𝑙𝑛𝑌𝑖𝑡 = 𝜑𝑙𝑛𝑌𝑖𝑡−1 + 𝛽𝑙𝑛𝑍𝑖𝑡−1 + 𝛾𝑋𝑖𝑡−1 + 𝑑𝑡 + 𝜀𝑖𝑡
Where 𝑙𝑛𝑌𝑖𝑡 is a dependent variable in logarithm; 𝑙𝑛𝑍𝑖𝑡−1 are endogenous variables
that are lagged by one year; 𝑋𝑖𝑡−1 are a set of control variables that are also lagged
by one year; 𝑑𝑡 is the time dummy; and 𝜀𝑖𝑡 is an error term.
Regression Results
Overall, there are eight dependent variables, with regard to the composition of
the board: the number of directors; the average age of board members; the number of
female directors; the number of male directors; the number of independent directors;
the number of executive directors; the number of foreigner directors; and the number
of Russian directors61. The control variables in the regressions include: the number of
61 Using the ratios too (e.g. % foreign directors), the results would be qualitatively very similar due to the granular
set of controls.
264
employees; total revenue; total assets; total fixed assets; total intangible assets;
dummy variable to identify whether the board exists; dummy variable to identify
whether the firm has the government as the main shareholder; the board dummy to
show whether the firm is listed on any stock exchange62; and the year dummies. The
categorical variable that determines the board structure (1-tier or 2-tier board) has
been omitted from the regression results having been perfectly determined by the
“board existence dummy” and the “publicly quoted” dummy. In other words, the effect
of the board structure is indirectly taken into account by using the publicly quoted
variable, which captures the effect of the firm having been listed on the exchange and,
therefore, using the 2-tier board.
The descriptive statistics for all variables used in the regressions are presented
in the appendix of this chapter, Figure 5.27. After running fixed effect and random
effect models, and performing the Hausman tests for each regression63, the best
model to use for this panel dataset would be fixed effect. The correlation matrix among
independent variables presented in Figure 5.1 does advise against the use of the
seven internationalisation variables within the same specification. In other words, the
high correlation between internationalisation variables warns against regressions with
all seven internationalisation variables all together (the so-called horse race) due to
multicollinearity. On a more general note, the full correlation table of all variables is
presented in Appendix C. The next section will investigate the regression results for
each dependent variable in turn.
62
This is not collinear with FE because it does change for some firms, which become listed in the 2000-2018 span. 63
Hausman tests to justify the use of the fixed regression model is provided in the appendix of this chapter.
265
Figure 5-1 Correlation matrix of independent variables
Variables
Log: Number of Foreign Markets
Log: Number of Foreign Subsidiaries
Log: Number of Domestic Subsidiaries
Log: Total number of Subsidiaries
Log: Total number of Acquisitions
Log: Number of Foreign Acquisitions
Log: Number of Domestic Acquisitions
Log: Number of Foreign Markets 1
Log: Number of Foreign Subsidiaries 0.9474 1
Log: Number of Domestic Subsidiaries 0.6471 0.6302 1
Log: Total number of Subsidiaries 0.7015 0.6922 0.9913 1
Log: Total number of Acquisitions 0.5991 0.5104 0.5804 0.6018 1
Log: Number of Foreign Acquisitions 0.6786 0.5623 0.3664 0.4123 0.7035 1 Log: Number of Domestic Acquisitions 0.5691 0.4938 0.5851 0.6023 0.9921 0.641 1
Board of Directors and Internationalisation
As can be seen from the regression results of the fixed effects model (Figure
5.2), the number of foreign subsidiaries has the greatest effect on the size of the board.
An increase of one percent in the number of subsidiaries leads to a 0.07% increase in
the size of the board. The second largest effect on board size is determined by the
number of domestic mergers and acquisitions, which indicates that a percentage
increase in the number of foreign mergers and acquisitions leads to a 0.056% increase
in the size of the board. The R-square, across all seven regressions, shows that
around 77% of variation in the board of directors can be explained by independent
variables. Controlling for listed and non-listed firms suggests that the former have a
greater effect on the size of the board of directors. The effect of the state on the board
size is also positive and significant. By examining the first two independent variables,
266
which represent the weighted index of the board efficiency at firm level (weighted by
the number of foreign subsidiaries and foreign mergers and acquisitions), it can be
concluded that they both have a significant and positive effect on board size. A one
percent increase in the index of board efficiency, weighted by the number of
subsidiaries, leads to a 0.028% increase in the number of directors on the board, while
a one percent increase in the index of board efficiency, weighted by the number of
mergers and acquisitions leads to a 0.014% increase in board size.
267
Figure 5-2. Regression results, dependent variable “size of the board of directors”
268
Overall, it can be concluded that expansion of the firm in domestic and foreign markets
leads to an increase in the number of board members.
Average Age of the Board
Based on the regression results in Figure 5.3, the average age of the board is
positively affected by variables measuring internationalisation and domestic growth.
All the independent variables in the model are highly significant.
Looking at the internationalisation variables, a one percent increase in the
number of foreign markets leads to an increase in the average age of the board by
0.029%. This is the highest coefficient out of all the independent variables related to
internationalisation. At the same time, a percentage increase in the number of
foreign/domestic subsidiaries (0.0268% / 0.0264% respectively) and the number of
foreign/domestic mergers and acquisitions (0.0248% / 0.0247% respectively) leads to
an increase in the average age of the board. The greater the board efficiency index,
based on the number of foreign subsidiaries and mergers and acquisitions, the higher
the average age of the board.
The explanatory power of all nine regressions is very high, with an average of
69% R-square. State-owned enterprises also have a higher average board age in
comparison to other firms. The crucial difference, however, is the dummy variable that
shows the difference between listed and non-listed firms. In this set of regressions,
the average age of the board of listed firms is not statistically different from non-listed
firms, ceteris paribus. Based on these results, it can be concluded that the
independent variables in the analysis have a positive and significant impact on the
average age of the firm.
269
Figure 5-2Regression results, dependent variable “age of the board of directors”
270
Number of Male Directors
Figure 5-3 Regression results, dependent variable “number of male directors on the board”
271
Examining the details of the regression results in Figure 5.4, it can be seen that
all the regressors have significant and positive coefficients. The main explanatory
variable is the number of foreign subsidiaries. A percentage increase in the number of
foreign subsidiaries leads to a 0.0644% increase in the number of male directors on
the board. This is followed by the number of foreign markets (0.056%) and total
number of foreign mergers and acquisitions (0.0326%). In contrast to board size and
board age, state-owned enterprises do not have a significant effect on the numbers of
male directors on the board. This could be because, following the OECD code of
corporate governance, state-owned enterprises have tried to maintain the proportion
of male and female directors on the board. Looking at the publicly quoted variable, it
can be seen that a listed firm has a much greater proportion of male directors on the
board compared to non-listed firms.
Number of Female Directors
Results of the regressions of independent variables on the number of female directors
on the board (Figure 5.5) differs when compared to the number of male directors on
the board. First, the impact that the independent variables have on the dependent
variables are, in some cases, higher. For example, a one percent increase in the
number of foreign mergers and acquisitions leads to a 0.119% increase in the number
of female directors on the board (in comparison to the previous figure 5.4) where the
percentage increase in the number of foreign mergers and acquisitions leads to an
increase of 0.0326%). Such a difference may arise from the difference between Russia
and advanced foreign countries, in terms of the percentage of female directors on the
boards.
272
Figure 5-4 Regression results, dependent variable “number of female directors on the
board”
273
Another opposing finding from the previous set of results, is that state-owned
enterprises have a significant and positive relationship on the number of female
directors on the board.
Even though all the internationalisation variables have a positive and significant
effect on the number of female directors on the board, the explanatory power of the
models represented in Figure 5.5 is significantly lower than those in Figure 5.4. The
largest R-squared in this set of regressions is 28.3%, for regression number 35, and
the lowest R-squared is 26.1%, in regression number 28.
Number of Executive Directors
Regression results in Figure 5.6 turn to the analysis of the number of executive
directors on the board. The variables index of board efficiency weighted by foreign
subsidiaries and foreign mergers and acquisitions, the number of foreign markets, the
number of foreign subsidiaries, and the number of foreign mergers and acquisitions
are not significant. This might indicate that internationalisation does not have an effect
on the number of executive directors on the board.
On the other hand, domestic expansion, measured by the number of domestic
subsidiaries and domestic mergers and acquisitions, has a positive and significant
effect on the number of executive directors.
274
Figure 5-5 Regression results, dependent variable “number of executive directors on the
board”
275
The R-square is around 66% in all regressions which means that more than
66% of variations on the number of executive directors on the board can be explained
by independent variables. The coefficients for state-owned enterprises are barely
significant, although positive in some cases (regression numbers 37, 39, 40, 43). The
publicly quoted variable shows that there is no statistical difference between listed and
non-listed firms.
Number of Independent Directors.
In the case of non-executive directors in Figure 5.7, it can be seen that
internationalisation variables are both positive and significant. The greatest effect on
the number of non-executive directors on the board is that of foreign subsidiaries,
where a rise of one percent increases the number of non-executive directors by
0.288%. This is followed by the number of foreign markets in which the firm is
operating (0.241%), showing that geographical diversification is positive and
significant. The third greatest effect on the number of non-executive directors on the
board is that of the number of foreign mergers and acquisitions: a one percent increase
leads to a 0.19% increase in the number of non-executive directors. This demonstrates
that, after a mergers and acquisitions deal, Russian firms may leave directors of an
acquired international firm as strategists in the foreign market without the execution of
day-to-day business. At the same time, it is important to highlight that state-owned
enterprise has a significant and positive effect on the number of non-executive
directors on the board. Being a listed firm also increases the number of non-executive
directors on the board.
276
Figure 5-6 Regression results, dependent variable “number of non-executive directors on the
board”
277
Number of Russian Directors on the Board
The internationalisation variables have a positive and significant impact on the
number of Russian directors on the board, except the board efficiency index, based
on the number of foreign mergers and acquisitions. This result reflects the fact that
internationalisation into foreign markets, where corporate governance levels are
higher in comparison to Russian markets, is not statistically significant for the number
of Russian directors on the board. The number of foreign subsidiaries indicates that a
one percent increase in the number of foreign subsidiaries leads to a 0.0751%
increase in the number of Russian directors on the board. This factor could be linked
to the overall growth of the company strategy; whereby Russian firms favour a majority
of Russian directors on the board.
State-owned enterprises have a higher number of Russian directors on the
board in comparison to other firms. Listed firms have more Russian directors on the
board in comparison with non-listed firms. The explanatory power of the models is
high and the adjusted R-squared shows that 74% of variation can be explained by the
model.
278
Figure 5-7 Regression results, dependent variable “number of Russian directors on the
board”
279
Number of Foreigners on the Board
Figure 5-8 Regression results, dependent variable “number of foreign directors on the
board”
280
In the last set of regressions, represented in Figure 5.9, most of the variables
linked to internationalisation have a positive and significant effect on the number of
foreign directors on the board. On the one hand, the dependent variable is most
influenced by the number of foreign subsidiaries, where a one percent increase in the
number of foreign subsidiaries leads to a 0.095% increase in the number of foreign
directors. On the other hand, the board efficiency index, weighted by the number of
foreign subsidiaries, has a positive but not significant coefficient. Such results can be
explained by the fact that most of the subsidiaries were established in countries with
similar levels of corporate governance to Russia (such as CIS or Eastern Europe). As
a result, even if Russian firms add foreign directors to their boards from these
countries, the index that represents board efficiency, weighted by the number of
subsidiaries, does not change dramatically.
Another interesting result is that the greatest positive coefficient is represented
by the number of domestic mergers and acquisitions. This is possible if a Russian firm
acquires another Russian firm which has a better international connection, in other
words, if it is a strategic decision for future internationalisation.
In contrast to all other regression results, the fact that the company is owned
by the state has a negative and significant effect on the number of foreign directors on
the board. This can be explained by the fact that state-owned enterprises dominate
the main strategic sectors of the Russian economy (such as oil and gas) and, as a
result, they favour a concentration of Russian directors on the board.
281
Robustness Checks
Running a fixed effects regression model in the section above highlights the
fact that internationalisation has a positive and significant effect on different aspects
of the board of directors. However, fixed effects regression models alone cannot
determine that improvements in corporate governance are driven by
internationalisation and not the other way around (reverse causality). To test whether
internationalisation has a causal impact on corporate governance mechanisms, it is
important to consider a different method, which should be applicable with the same
set of variables. For that purpose, this thesis will also include a dynamic Generalised
Method of Moments model (GMM).
The GMM method is particularly relevant when the panel data have smaller
numbers of years (T) in comparison to the number of groups (N), which is the case in
this data. The dynamic GMM model tests whether internationalisation variables have
a significant, positive effect on corporate board mechanisms by lagging the
internationalisation variables and considering them as endogenous, as exemplified in
the equation below:
𝑙𝑛𝑌𝑖𝑡 = 𝜑𝑙𝑛𝑌𝑖𝑡−1 + 𝛽𝑙𝑛𝑍𝑖𝑡−1 + 𝛾𝑋𝑖𝑡−1 + 𝑑𝑡 + 𝜀𝑖𝑡
Where 𝑙𝑛𝑌𝑖𝑡 is a dependent variable in logarithm; 𝑙𝑛𝑍𝑖𝑡−1 are endogenous variables
that are lagged by one year; 𝑋𝑖𝑡−1 are a set of control variables that are also lagged
by one year; 𝑑𝑡 is the time dummy; and 𝜀𝑖𝑡 is an error term.
282
Figure 5-9 Results of the GMM regression models
283
The specifications of the model used for the regressions follow. For each
regression, the dependent variable is one of the corporate governance variables,
regressed on the lag of the same variable (endogenous by construction). The
explanatory variables (all lagged) used in these regressions are the number of foreign
markets, number of foreign mergers and acquisitions, and number of foreign
subsidiaries. The control variables set includes the number of employees, operating
revenue, total assets, fixed assets, intangible assets, state-owned enterprise dummy,
board existence dummy, publicly quoted dummy. All control variables (apart from
dummy variables) were also lagged. The number of instruments used for each model
is shown in Figure 5.10 and varies between 92 and 96 and in all cases, this number is
smaller than the number of groups. The instruments also include the board efficiency
index weighted by the number of foreign subsidiaries and number of foreign mergers
and acquisitions. The GMM model in all eight regressions exploits a two-step robust
system GMM approach6465.
The results seen in Figure 5.10 confirm the findings from the fixed effects
regression models: the number of foreign subsidiaries and number of foreign
acquisitions have a positive and significant impact (at 5% significance level) on the
board structure. Considering the dependent variables one by one, it can be seen that
the size of the board is influenced by the number of foreign subsidiaries and foreign
acquisitions. A one percent increase in the number of foreign subsidiaries leads to a
0.138% increase in board size. A one percent increase in the number of foreign
acquisitions increases the board size by 0.0875%. The board size is negatively
64 The GMM model also touches on the problem of selection bias. Using a two-step robust system GMM will
attenuate selection bias. In other words, if there is some residual correlation between the errors and the independent variables (violation of orthogonality condition) the GMM model will precisely capture this effect via the IV strategy. 65
When excluding outliers (trimming, Winsorizing at the 1st and 99th percentiles the key variables), the main
results also remain unchanged. See Figure 5.30 in the appendix of the chapter.
284
correlated with the number of foreign markets in which the firm operates. This means
that geographical diversification of the firm reduces the board size, which is explained
by the fact that if the firm is entering additional foreign markets that are similar in terms
of economic environment, rules and regulations etc., it means that the firm does not
require any additional knowledge or specialisation that a new director could bring to
the firm. Therefore, the firm may not change the number of directors with an increase
in geographical diversification, or even reduce the number of directors, if the original
strategic decision of the firm was to use a specific director for a short period to facilitate
foreign market operations.66 The number of foreign acquisitions has a significant and
positive effect of the average age of the board and shows that an increase in the
number of foreign acquisitions leads to an increase in the average age of the board
by 0.0857%. The number of foreign subsidiaries and of foreign markets are, however,
not significant.67
The number of male and female directors on the board reflect very similar
results: both the number of foreign subsidiaries and the number of foreign acquisitions
have positive effects on the number of male and female directors on the board. The
only difference is that these coefficients are significant at 10% for the number of female
employees, while they are more significant (at 5% significance level) for the number
of male directors on the board. The number of foreign markets shows a negative
relationship between the independent and dependent variables. An increase in one
percent in the number of foreign markets leads to a decrease in the number of male
directors by 0.161% and a decrease in the number of female directors by 0.125%. 68
66
The Hansen test and the Arellano-Bond test for Autocorrelation (AR2) are both insignificant (p-value above
0.10), which means that the IV model is valid. 67
Furthermore, the Hansen test is highly significant (p-value below 0.10) meaning that the model is not passing
the “validity of the instruments” test. 68 Both tests (Hansen and AR2) are insignificant and validate the model.
285
If we turn to the number of executive directors and the number of non-executive
directors on the board as dependent variables, a different set of results is shown. While
the independent variables show the significant coefficients for the number of executive
directors on the board, they do not for the non-executive members. Internationalisation
does not have a significant effect on the number of non-executive directors on the
board. At the same time, the number of executive directors on the board increases by
0.109% if the number of foreign subsidiaries increases by one percent, and it
increases by 0.098% if the number of foreign acquisitions rises by one percent.69
The last set of regressions examines the relationship between
internationalisation and the number of Russian and foreign directors on the board.
Coefficients for both regressions are significant, however, they are in opposition to
each other. The effect of internationalisation on the number of Russian directors on
the board follows the same pattern as described above. There is a positive and
significant result when considering the number of foreign subsidiaries and
acquisitions, while the effect of foreign markets on the number of Russian members
on the board is negative. The number of foreign directors on the board is, however,
negatively correlated with the number of foreign acquisitions and foreign subsidiaries,
but positively correlated with the number of foreign markets. This highlights the
potential strategy of Russian companies that hire foreign directors along geographical
diversification. Such an approach could help Russian firms establish successful
operations in foreign markets.
69
Hansen test together with AR2 are insignificant for regressions 77 and 78.
286
Margin Analysis
As was mentioned earlier in the thesis, the IPO plays a vital role in the firm’s
internationalisation process and its corporate governance structure. The initial public
offering requires certain adjustments and, at the same time, can be an initial step for
foreign expansion. It is, therefore, important to understand if internationalisation after
the IPO of the firm has a positive effect on its corporate governance structure70.
To test the 4th hypothesis, it is appropriate to use the margin analysis that
represents two groups of firms (listed and non-listed). The analysis investigates the
effect of internationalisation (number of foreign markets, number of foreign
subsidiaries, number of foreign mergers and acquisitions) on the dependent variables
measuring corporate governance. The crucial step is to create the interaction between
the dummy that represents the (time-varying) status of listed and non-listed firms, and
the yearly dummies themselves. Such interaction compares the two categories of
firms in the analysis, implicitly taking into account, the year of the IPO for each
individual firm71. Fully-fledged fixed effects regression models, that were used at the
beginning of this chapter, together with the interaction term, will be used for margin
predictions.
70 At the same time predictive margins would be able to visually represent the relationship between the
internationalisation and corporate governance as a result of the timing of the IPO. 71
The year has not to be the same for all firms, but the interaction will allow to precisely account for pre vs. post
IPO CG performance. This a sort of post IPO natural experiment approach also teasing out causality and corroborating the previous analysis in chapter 5.
287
Board of Directors Figure 5-10 Margin analysis of the board size for listed and non-listed firms based on the
number of foreign markets
The graph in Figure 5.11 represents the expected size of the board of directors based
on the full factorial log-log model, which includes the independent variable (number of
foreign markets), the dummy that indicates the listed and non-listed firms, control
variables, the year dummies, the state-owned dummy variable, and, crucially, the
interaction between the publicly quoted dummy and year dummies.
The graph indicates that, based on the regression model, the expected size of
the board in listed firms constantly increases over the years. This decoupling process,
between listed and non-listed firms, started in 2002, which could be explained by the
introduction of the corporate governance code in Russia. At the same time, it is evident
that internationalisation also had a positive and significant effect on non-listed firms.
The graph shows that the predicted size of the board for non-listed firms increases
288
between 2000 and 2006, and, after that, remains almost constant for the rest of the
period.
Taking the exponent ( e(…) ) as the minimum value in the year 2000 for listed
firms gives the result of 0.79, while for non-listed firms the result is 1.02. This means
that for both groups of firms, internationalisation did not play any significant role before
the year 2002, while in 2018, the expected size of listed firms increased to 6.68 and
non-listed firms to 1.4. Such a low effect on the non-listed firm category can also be
explained by the fact that it includes firms that do not have a board of directors at all
(but are controlled for by the use of the “board presence” dummy).
Similar results can be seen for the effect of total number of foreign subsidiaries
(Figure 5.12) and total number of foreign mergers and acquisitions (Figure 5.13) on
the predicted size of the board.
Figure 5-11 Margin analysis of the board size for listed and non-listed firms based on the
number of foreign subsidiaries.
289
Figure 5-12Margin analysis of the board size for listed and non-listed firms based on the
number of foreign acquisitions
The Dominance of Russian Executive Male Directors on the Board
The graph that predicts the number of Russian directors on the board, based
on the number of foreign markets (Figure 5.14), looks very similar to the previous
graph in Figure 5.10. However, the margin predictions are slightly different (the full
table of all margin values can be found in the appendix of this chapter).
Internationalisation has a positive effect on both listed and non-listed firms, and the
effect of internationalisation on the number of Russian directors for listed and non-
listed firms is the same as for board size.
290
Figure 5-13 Margin analysis of the number of Russian directors for listed and non-listed
firms based on the number of foreign markets
Such results are mostly driven by the extremely high correlation between the
size of the board and the number of male directors on the board (the correlation of
0.9982). At the same time, looking at the detailed correlation matrix of the dependent
variables (Figure 5.15), together with the margin results (represented in the appendix
of this chapter), it can be concluded that similar results regarding the impact of
internationalisation will be observed for the number of executive directors on the
board, and the number of male directors on the board.
291
Figure 5-14 Correlation matrix of the dependent variables
Board Size
Board Age
Number of Male
directors
Number of
Female directors
Number of
Executive directors
Number of Non-
executive directors
Number of
Russian directors
Number of
Foreign directors
Board Size 1
Board Age 0.9903 1
Number of Male directors
0.9982 0.9875 1
Number of Female directors
0.5806 0.5663 0.5344 1
Number of Executives directors
0.9936 0.9854 0.9924 0.5666 1
Number of Non-executive directors
0.7153 0.6768 0.7113 0.5017 0.643 1
Number of Russian directors
0.9914 0.9806 0.9896 0.5761 0.9857 0.7037 1
Number of Foreign directors
0.5232 0.5065 0.523 0.3176 0.513 0.4415 0.4222 1
This suggests that internationalisation of Russian firms will lead to a restructuring of
the board of directors. In all cases, the predictive margins for listed firms will be higher
in relation to non-listed firms. The margin table (Appendix A), taking the exponent of
these values, suggests that the predicted average number of Russian male executives
on the board of directors in the year 2018 for listed firms was equal to 6.61, while for
non-listed firms, the average number of Russian male executives on the board of
directors was 1.3. The predictive model, therefore, suggests that non-listed firms, that
do not have a board of directors but operate in the foreign market, would be better off
if they established a board of directors.
292
Average Age of the Board
The predictive model for the average age of the firm based on the
internationalisation variables, shows a different pattern. (Figure 5.16)
Figure 5-15 Margin analysis of the average age of the board for listed and non-listed firms
based on the number of foreign markets.
Graph 5.16 indicates that the internationalisation of listed and non-listed firms has no
statistically differential effect on the average age of the board, up to the year 2013.
After that period, we see a slight decoupling in the average age of the board between
listed and non-listed firms. It seems that the number of foreign markets in which the
firm is operating, has a greater effect on non-listed firms in comparison to listed firms.
Other independent variables (number of foreign subsidiaries and number of foreign
mergers and acquisitions) demonstrate a similar pattern and are represented in
293
Figures 5.17 and 5.18 respectively. Once again, this similarity is due to the high
correlation between internationalisation variables.
The exponent of the log margin values suggests that, in the year 2018, the
average predicted board age for listed firms, based on the level of internationalisation,
is around 55.4 years. For non-listed firms it is around 57.62 years, thus demonstrating
not much difference.
Figure 5-16 Margin analysis of the average age of the board for listed and non-listed firms
based on the number of foreign
294
Figure 5-17 Margin analysis of the average age of the board for listed and non-listed firms
based on the number of foreign M&As
Number of Foreign Directors on the Board
Figure 5.19 represents the expected number of foreign directors on the board
based on the full factorial log-log model. Similar to the structure of the Russian
directors on the board, the model predicts decoupling in the number of foreign
directors in listed and non-listed firms, due to the internationalisation process. The
point of interaction between the two categories is the year 2002, when the corporate
governance code was introduced. The growth in the expected value of foreigners on
the boards of listed firms can be grouped into two periods. The first is between the
years 2003 and 2007, and the second is between 2010 and 2015. The expected
number of foreign directors on the board of listed firms in 2018 is 1.4.
295
On the other hand, the internationalisation of non-listed firms did not affect the
expected number of foreign directors on the board, suggesting marginal influence of
internationalisation on the number of foreign directors on the board of non-listed
companies. The expected number of foreign directors for non-listed firms is almost
constant and varies between 1.04 and 1.07 foreign directors. This suggests that non-
listed firms, operating outside of the domestic market, should have at least one foreign
director.
Figure 5-18 Margin analysis of the average number of foreign directors on the board for
listed and non-listed firms based on the number of foreign markets
Similar patter can be seen the other independent variables (number of foreign
subsidiaries and number of foreign mergers and acquisitions)
296
Figure 5-19 Margin analysis of the average number of foreign directors on the board for
listed and non-listed firms based on the number of foreign subsidiaries.
Figure 5-20 Margin analysis of the average number of foreign directors on the board for
listed and non-listed firms based on the number of foreign M&As.
297
Number of Female Directors on the Board
The expected value of the number of female directors on the board also shows
a decoupling effect between listed and non-listed firms. The model predicts that the
expected number of female directors on the board, based on the number of foreign
markets, constantly increases for listed firms up to the year 2014, after which growth
continues at a decreasing rate. The predicted number of female directors on the board
for listed firms in the year 2018 is equal to 1.61.
The expected value of the number of female directors on the board for non-
listed firms steadily increases from the year 2003 until 2014, after which it remains
almost unchanged in the region of 1.067 per board. Comparing the effect of
internationalisation on the number of female directors of listed and non-listed firms,
suggests that firms who are operating outside of the domestic market have at least
one female representative on the board of directors.
Figure 5-21 Margin analysis of the average number of female directors on the board for
listed and non-listed firms based on the number of foreign markets
298
The graphs that are based on the number of foreign subsidiaries (figure 5.23) and the
number of foreign mergers and acquisitions (figure 5.24) have a similar form and
meaning due to the strong correlation of independent variables
Figure 5-22 Margin analysis of the average number of female directors on the board for
listed and non-listed firms based on the number of foreign subsidiaries.
299
Figure 5-23 Margin analysis of the average number of female directors on the board for
listed and non-listed firms based on the number of foreign M&As.
Number of Non-Executive Directors on the Board
The expected value for the number of non-executive directors on the board,
based on internationalisation, shows that listed firms, once again, demonstrate a sharp
increase in prediction value in comparison to non-listed firms. The graph in Figure 5.25
shows the two intervals during which the prediction value increased (2000 till 2007
and 2011 till 2014), and the two periods of either slow growth (2007-2010) or
stagnation (2014-2018). Such patterns directly correlate with the macroeconomic
environment in Russia during these periods (the financial crisis in 2007 and Western
sanctions on the largest companies in 2014). This implies that internationalisation,
during these periods, did not necessitate additional non-executive directors.
The margin analysis also suggests that there was a steady decrease in the
expected number of non-executive directors in non-listed firms after the year 2014.
300
Such an outcome suggests that an increase in the number of independent directors at
these firms did not bring additional value during the internationalisation process. In the
year 2018, the model predicts that the average number of non-executive directors is
around 1.02. Such a decrease could be the result of experiential learning during initial
internationalisation phases. In other words, outside directors, who were guiding non-
listed firms in the internationalisation process in the year 2000, shared knowledge with
executive directors, who were later able to proceed with further successful
internationalisation without non-executive directors.
Figure 5-24 Margin analysis of the average number of non-executive directors on the board
for listed and non-listed firms based on the number of foreign markets
Due to the high correlation of independent variables, the graphs based on the number
of foreign subsidiaries and number of foreign mergers and acquisitions will have a
similar shape and interpretation.
301
Figure 5-25 Margin analysis of the average number of non-executive directors on the board
for listed and non-listed firms based on the number of foreign subsidiaries.
Figure 5-26Margin analysis of the average number of non-executive directors on the board
for listed and non-listed firms based on the number of foreign M&As
302
Discussion and conclusion
Through examining the set of fixed effects regressions, dynamic GMM
regressions, and margin analysis based on post-IPO corporate governance
restructuring, it can be concluded that the variables measuring internationalisation, in
general, have a positive and significant effect on the extent and intensity of “corporate
governance” in general, and specifically on the “mechanism of implementation of such
corporate governance” in almost all specifications. The detailed analysis also shows
that there is a clear role played by the number of foreign subsidiaries and foreign
acquisitions. They exert a positive and significant impact on the size of the board, the
number of male directors on the board, the number of executive directors on the board,
and the number of Russian directors on the board, across virtually all methods of
analysis. Internationalisation occurring through opening a subsidiary or acquisition in
the foreign market, will be positively correlated with the number of new corporate
governance mechanisms and this correlation can be interpreted causally.
Russian firms’ board structures are changing via the internationalisation
process, for example by increasing the board size (a positive outcome), or by
increasing the concentration of male Russian executive directors (a less positive
outcome). With regard to the latter example, such a high concentration of male
Russian executive directors has its roots in the characteristics of the transition period
within the Russian economy, which has not changed much over the past 15 years. Of
all the characteristics that could diversify/restructure the board (such as the number of
female directors on the board, or the number of non-executive and foreign directors),
only the number of female directors is affected by the number of foreign subsidiaries
and mergers and acquisitions.
303
The total number of foreign markets represents the geographical diversification
of the firm. The fixed effects regression model shows that this independent variable is
positive and significantly correlates with corporate governance. The GMM method also
supports the result of the fixed effect regression models. The two methods, show
similar results in terms of the number of foreign directors on the board. Both fixed
effects and GMM methods show that the number of foreign markets has a positive and
significant effect on the number of foreign directors on the board. As a result, the
analysis supports the hypothesis that geographical diversification of the firm will be
positively correlated with the share of foreign directors represented on the board and,
therefore, operations in foreign markets should be accompanied by the appointment
of foreign directors.
Another set of interesting results relates to the number of non-executive
directors on the board. The fixed effects regression model shows a positive
relationship between internationalisation variables (in particular, the number of foreign
markets, the number of foreign subsidiaries and the number of foreign acquisitions)
and corporate governance restructuring. The GMM model did not, however, show that
there was any significance between internationalisation and non-executive directors.
This could be justified by the fact that the non-executive directors on Russian boards
have the primary role of mitigating principal-agent conflicts and, therefore, play the
role of a monitoring mechanism rather than participating in the international strategic
decisions of firms.
The board efficiency index, weighted by the number of foreign subsidiaries and
number of foreign acquisitions, stays significant and positive across most
specifications with different dependent variables as proxies of corporate governance.
This means that when Russian firms have subsidiaries or make acquisitions in foreign
304
markets with a higher level of corporate governance in relation to their domestic
market, this will have a positive effect on the number of corporate mechanisms that
should be implemented on the board of directors. The restructuring of mechanisms
could be enhanced by either external factors (for example the rules and regulation of
the foreign country) or internal factors (such as expanding the board with new directors
from the acquired firm).
Furthermore, expansion outside the market of origin of Russian firms owned by
the government, has a positive and significant effect on most corporate governance
mechanisms. The only exception is the number of foreign directors on the board. As
shown by the fixed effects regression model, state-owned enterprise has a negative
relationship with the number of foreign directors on the board. Taking into account that
the Russian state owns most strategic sectors of the Russian economy that contribute
the most to the Russian GDP, it seems appropriate that the policy of state-owned
enterprise is to appoint Russian directors to the board.
Looking at internationalisation among listed and non-listed firms, it is evident
that the former has a greater positive effect on corporate board mechanisms, based
on marginal analysis. After the IPO of the firm, there is a statistically significant
relationship between internationalisation and corporate governance restructuring.
Even though the expected value of all dependent variables (apart from age, as
expected) is always higher for the listed firms in comparison to non-listed firms, the
analysis indicates that these firms will have, on average, a large board of around seven
board members, with a high concentration of Russian male executive directors on the
board. Such a conclusion highlights the underlying question of the effectiveness of
such a board during the internationalisation process.
305
The analysis also, however, indicates that non-listed firms will also benefit from
an adjustment of the board structure during internationalisation. Results suggest that
internationalisation should be accompanied by a board structure that considers gender
diversity, increasing the independence of the board, and the inclusion of a foreign
director on the board, by the minimum possible (one female director, one non-
executive director, and one foreign director).
306
Appendix C. Figure 5-27 Descriptive statistics of the key variables.
Variable Obs Mean Std. Dev. Min Max
Dependent Variable
Board Size 5,058 2.322262 3.953074 0 16
Board Age 5,058 14.09497 22.85595 0 67
Number of Male Directors on the board
5,058 2.145314 3.680384 0 14
Number of Female Directors on the board
5,058 0.1769474 0.5414648 0 5
Number of Executive Directors on the board
5,058 1.950376 3.348121 0 16
Number of Non-Executive Directors on the board
5,058 0.3718861 0.9871111 0 7
Number of Russian Directors on the board
5,058 2.071965 3.608698 0 16
Number of Foreign Directors on the board
5,058 0.2502966 0.8963623 0 8
Independent Variable
Number of Foreign Markets 5,643 1.09215 3.596201 0 27
Number of Foreign Subsidiaries
5,058 2.715105 13.61873 0 232
Number of Domestic Subsidiaries
5,058 14.66805 41.22495 0 395
Total number of Subsidiaries 5,058 17.38316 49.89575 0 444
Index of board efficiency weighted by foreing subsidiaries
5,643 0.7753555 1.791814 0 6.138008
Number of Foreign M&As 5,058 0.3513246 1.526815 0 17
Number of Domestic M&As 5,058 2.426255 7.171712 0 83
Total Numebr of M&As 5,058 2.77758 8.332553 0 93
Index of board efficiency weighted by foreing M&As
5,643 0.4307222 1.347181 0 6.124218
Control Variables
Number of Employees 4,293 7211.882 40626.09 1 969662
Age of the firm squared 5,058 1635.756 7426.517 1 99225
Operating Revenue in Th. Rubles
4,958 6.01E+07 1.30E+08 12 2.07E+09
Total Assests in Th. Rubles 4,934 8.16E+07 2.77E+08 104 6.26E+09
Fixed Assets in Th. Rubles 4,933 5.42E+07 2.42E+08 1 5.90E+09
Intangible Assets in Th. Rubles 4,388 320919 1803487 1 3.54E+07
State Owned enterprise (dummy)
5,643 0.2195641 0.413988 0 1
Board Existance (dummy ) 5,643 0.2502215 0.4331789 0 1
Publicly quoted (dummy) 5,058 0.2360617 0.4247025 0 1
307
Number of
Foreign
Markets of
operation
Number of
Foreign
Subsidiaries
Number of
Domestic
Subsidiaries
Total
number of
Subsidiaries
Total
number of
M&A
Total
number of
Foreign
M&A
Total
number of
Domestic
M&A
board
structure =
1 if 1-tier
BoD, 2 if
Number of
directors on
the board
Avergae
age of the
board
Number of
male
directors on
the board
Number of
female
directors on
the board
Number of
executive
directors on
the boa
Number of
non-
executive
directors on
the
Number of
russian
directors on
the board
Number of
foreign
directors on
the board
Number of Foreign Markets
of operation 1
Number of Foreign
Subsidiaries 0.8082 1
Number of Domestic
Subsidiaries 0.7409 0.5385 1
Total number of Subsidiaries0.8328 0.7178 0.9732 1
Total number of M&A0.6396 0.581 0.2872 0.3958 1
Total number of Foreign
M&A 0.6051 0.4757 0.4848 0.5304 0.7339 1
Total number of Domestic
M&A 0.6376 0.5163 0.4674 0.5271 0.8165 0.9914 1
board structure = 1 if 1-tier
BoD, 2 if 0.3474 0.2411 0.3007 0.3142 0.3576 0.4695 0.468 1
Number of directors on the
board 0.3241 0.2293 0.2808 0.2946 0.3485 0.4574 0.456 0.9482 1
Avergae age of the board0.2745 0.2039 0.2341 0.2491 0.3156 0.406 0.4059 0.9242 0.9457 1
Number of male directors on
the board 0.3261 0.2327 0.275 0.2907 0.3505 0.4491 0.4493 0.9402 0.9925 0.9384 1Number of female directors
on the board 0.1498 0.0927 0.1814 0.1752 0.1618 0.2868 0.2749 0.532 0.5547 0.5258 0.4487 1Number of executive
directors on the boa 0.2976 0.2293 0.2507 0.2697 0.3372 0.4241 0.4255 0.9192 0.977 0.9367 0.9719 0.5266 1Number of non-executive
directors on the 0.2886 0.1407 0.2743 0.265 0.2518 0.3934 0.3829 0.6792 0.6908 0.6099 0.6779 0.4355 0.5208 1Number of russian directors
on the board 0.2911 0.194 0.2773 0.2821 0.293 0.4112 0.406 0.9144 0.976 0.9218 0.9687 0.541 0.9562 0.6652 1Number of foreign directors
on the board 0.2573 0.2302 0.1223 0.1638 0.3574 0.3619 0.3765 0.5004 0.4808 0.4594 0.477 0.2685 0.459 0.3686 0.2783 1
Figure 5-28. Correlation matrix between the dependent and independent variables
308
Figure 5-29 winsorizing results of the GMM
1 2 3 4 5 6 7 8
VARIABLES
LN Board
Size
LN Board
Age
LN Board
male
LN Board
Female
LN Board
Executive
LN Board Non-
Executive
LN Board
Russian
LN Board
Foreing
0.148**
(0.0650)
0.00253
(0.0187)
0.151**
(0.0706)
0.934***
(0.0379)
0.169**
(0.0705)
0.910***
(0.0252)
0.380***
(0.111)
0.960***
(0.0297)
-0.188** -0.109 -0.138* -0.110** -0.173** -0.0536 -0.246** 0.135**
(0.0769) (0.0698) (0.0744) (0.0531) (0.0855) (0.0848) (0.113) (0.0596)
0.136** 0.0515 0.0949* 0.0746* 0.0989 0.0368 0.161** -0.0826**
(0.0581) (0.0463) (0.0531) (0.0382) (0.0635) (0.0584) (0.0788) (0.0397)
0.0833** 0.0853** 0.0833** 0.0388 0.0878** 0.0273 0.0956* -0.0557*
(0.0399) (0.0378) (0.0349) (0.0272) (0.0366) (0.0377) (0.0541) (0.0299)
0.0670* 0.0720** 0.0649** 0.0338 0.0610* 0.0701** 0.0791 -0.0360
(0.0365) (0.0291) (0.0313) (0.0329) (0.0356) (0.0314) (0.0495) (0.0251)
-0.0537* -0.00246 -0.0574** -0.0104 -0.0108 -0.00998 -0.0766 -0.000678
(0.0280) (0.00848) (0.0272) (0.00978) (0.00981) (0.00681) (0.0587) (0.00535)
-0.0806 -0.0451** -0.0302** -0.0294 -0.0279 -0.0370 0.0119 0.0266
(0.0520) (0.0179) (0.0126) (0.0287) (0.0174) (0.0341) (0.0563) (0.0344)
0.111 0.189*** 0.0980* 0.0506 0.0675 0.0732 -0.0115 -0.105
(0.0897) (0.0437) (0.0507) (0.0918) (0.0668) (0.0989) (0.0960) (0.0819)
-0.0486 -0.151*** -0.0761* -0.0147 -0.0547 -0.0502 -0.0110 0.0839
(0.0440) (0.0369) (0.0406) (0.0595) (0.0550) (0.0490) (0.0589) (0.0521)
-0.000436 -0.00253 -0.00157 -0.00210 -0.000163 -0.00209 -0.00403 -0.0113
(0.00304) (0.00307) (0.00276) (0.00224) (0.00213) (0.00215) (0.00360) (0.00887)
0.00943 0.0209 0.0278 -0.0130 0.0212 -0.0298 0.0566 -0.00281
(0.0287) (0.0275) (0.0205) (0.0201) (0.0219) (0.0273) (0.0366) (0.0142)
1.707*** 3.918*** 1.642*** 0.0312 1.610*** 0.0566* 1.187*** 0.0377
(0.118) (0.0717) (0.141) (0.0358) (0.146) (0.0313) (0.184) (0.0274)
0.215*** -0.0154 0.241*** -0.0246 0.0846* -0.0150 0.236 0.0163
(0.0457) (0.0279) (0.0516) (0.0271) (0.0491) (0.0278) (0.160) (0.0251)
Year Y*** Y*** Y*** Y*** Y*** Y*** Y*** Y***
0.0541 0 -0.105 -0.297 -0.169 -0.248 0.0689 0.372
(0.492) (0) (0.211) (0.403) (0.238) (0.447) (0.788) (0.362)
Observations 3,564 3,564 3,564 3,564 3,564 3,564 3,564 3,564
Number of ID 277 277 277 277 277 277 277 277
Arellano-Bond test for AR(1) 0.0118 0.0216 0.0190 6.26e-09 0.0143 7.21e-09 0.00163 9.26e-05
Arellano-Bond test for AR(2) 0.131 0.553 0.126 0.585 0.361 0.342 0.190 0.0326
Sargan test 0.00425 0 0.662 0 0.609 0.000244 0.240 6.75e-05
Hansen 0.682 0.0109 0.698 0.0279 0.771 0.388 0.407 0.268
Number of Instruments 94 95 95 92 96 95 92 95
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
bod_dummy
publicly-quoted
Constant
L.ln_firm_age_sq
L.ln_op_rev_thRUB
L.ln_tt_assets_thRUB
L.ln_fa_assets_thRUB
L.ln_int_assets_thRUB
state-owned
Lagged LN Board Russian
Lagged LN Board Foreing
Lagged Log number of
goreing markets
Lagegd log numebr of
foreign subs
Lagged log numebr of
foreing M&As
L.ln_empl
Lagged LN Board Size
Lagged LN Board Age
Lagged LN Board male
Lagged LN Board Female
Lagged LN Board Executive
Lagged LN Board Non-
Executive
309
Figure 5-30. Margin results for the size of the board.
(1) (2) (3)
Board Size
Number of Foreign Markets
Number of Foreign
Subsidiaries
Number of Foreign M&As
Listed in year 2000 -0.223** -0.226** -0.227**
Listed in year 2001 -0.144** -0.146** -0.152**
Listed in year 2002 0.106 0.102 0.0991
Listed in year 2003 0.546*** 0.543*** 0.540***
Listed in year 2004 1.095*** 1.092*** 1.087***
Listed in year 2005 1.456*** 1.456*** 1.446***
Listed in year 2006 1.750*** 1.750*** 1.741***
Listed in year 2007 1.852*** 1.853*** 1.845***
Listed in year 2008 1.894*** 1.895*** 1.883***
Listed in year 2009 1.957*** 1.960*** 1.946***
Listed in year 2010 1.971*** 1.973*** 1.962***
Listed in year 2011 1.976*** 1.980*** 1.967***
Listed in year 2012 2.000*** 2.005*** 1.992***
Listed in year 2013 2.008*** 2.013*** 1.998***
Listed in year 2014 2.013*** 2.018*** 2.004***
Listed in year 2015 2.006*** 2.011*** 1.998***
Listed in year 2016 2.001*** 2.005*** 1.994***
Listed in year 2017 1.975*** 1.979*** 1.968***
Listed in year 2018 1.989*** 1.992*** 1.979***
Non-Listed in year 2000 0.0202 0.0179 0.0198
Non-Listed in year 2001 0.0834** 0.0812** 0.0843**
Non-Listed in year 2002 0.0733** 0.0715** 0.0730**
Non-Listed in year 2003 0.129*** 0.128*** 0.129***
Non-Listed in year 2004 0.195*** 0.193*** 0.195***
Non-Listed in year 2005 0.277*** 0.277*** 0.277***
Non-Listed in year 2006 0.275*** 0.275*** 0.274***
Non-Listed in year 2007 0.305*** 0.305*** 0.306***
Non-Listed in year 2008 0.295*** 0.294*** 0.297***
Non-Listed in year 2009 0.303*** 0.301*** 0.305***
Non-Listed in year 2010 0.308*** 0.307*** 0.312***
Non-Listed in year 2011 0.315*** 0.314*** 0.319***
Non-Listed in year 2012 0.326*** 0.326*** 0.330***
Non-Listed in year 2013 0.318*** 0.318*** 0.323***
Non-Listed in year 2014 0.318*** 0.317*** 0.322***
Non-Listed in year 2015 0.317*** 0.317*** 0.322***
Non-Listed in year 2016 0.317*** 0.316*** 0.322***
Non-Listed in year 2017 0.313*** 0.312*** 0.318***
Non-Listed in year 2018 0.314*** 0.313*** 0.319***
Observations 4,285 4,285 4,285
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
310
Figure 5-31. Margin Results for the average age of the board
(4) (5) (6)
Board Age
Number of Foreign Markets
Number of Foreign Subsidiaries
Number of Foreign M&As
Listed in year 2000
Listed in year 2001
Listed in year 2002 3.813*** 3.816*** 3.813***
Listed in year 2003 3.815*** 3.816*** 3.814***
Listed in year 2004 3.823*** 3.824*** 3.823***
Listed in year 2005 3.842*** 3.842*** 3.842***
Listed in year 2006 3.858*** 3.859*** 3.858***
Listed in year 2007 3.876*** 3.877*** 3.876***
Listed in year 2008 3.891*** 3.891*** 3.891***
Listed in year 2009 3.910*** 3.911*** 3.910***
Listed in year 2010 3.923*** 3.923*** 3.923***
Listed in year 2011 3.938*** 3.938*** 3.938***
Listed in year 2012 3.953*** 3.954*** 3.953***
Listed in year 2013 3.962*** 3.962*** 3.961***
Listed in year 2014 3.974*** 3.975*** 3.974***
Listed in year 2015 3.990*** 3.990*** 3.989***
Listed in year 2016 4.006*** 4.007*** 4.005***
Listed in year 2017 4.019*** 4.020*** 4.019***
Listed in year 2018 4.035*** 4.036*** 4.035***
Non-Listed in year 2000
Non-Listed in year 2001
Non-Listed in year 2002 3.810*** 3.808*** 3.810***
Non-Listed in year 2003 3.818*** 3.816*** 3.816***
Non-Listed in year 2004 3.822*** 3.819*** 3.820***
Non-Listed in year 2005 3.844*** 3.842*** 3.844***
Non-Listed in year 2006 3.863*** 3.860*** 3.864***
Non-Listed in year 2007 3.871*** 3.869*** 3.872***
Non-Listed in year 2008 3.898*** 3.897*** 3.899***
Non-Listed in year 2009 3.916*** 3.915*** 3.916***
Non-Listed in year 2010 3.928*** 3.926*** 3.928***
Non-Listed in year 2011 3.940*** 3.937*** 3.940***
Non-Listed in year 2012 3.953*** 3.951*** 3.953***
Non-Listed in year 2013 3.967*** 3.965*** 3.968***
Non-Listed in year 2014 3.985*** 3.983*** 3.986***
Non-Listed in year 2015 3.995*** 3.994*** 3.996***
Non-Listed in year 2016 4.019*** 4.017*** 4.019***
Non-Listed in year 2017 4.039*** 4.037*** 4.039***
Non-Listed in year 2018 4.054*** 4.052*** 4.055***
Observations 1,227 1,227 1,227 Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
311
Figure 5-32. Margin Results for the number of male directors on the board
(7) (8) (9)
Number of Male directors
Number of Foreign Markets
Number of Foreign Subsidiaries
Number of Foreign M&As
Listed in year 2000 -0.217** -0.220** -0.221**
Listed in year 2001 -0.162** -0.164** -0.168**
Listed in year 2002 0.0925 0.0880 0.0856
Listed in year 2003 0.525*** 0.522*** 0.519***
Listed in year 2004 1.070*** 1.067*** 1.063***
Listed in year 2005 1.433*** 1.433*** 1.425***
Listed in year 2006 1.711*** 1.712*** 1.704***
Listed in year 2007 1.813*** 1.814*** 1.808***
Listed in year 2008 1.839*** 1.842*** 1.831***
Listed in year 2009 1.900*** 1.904*** 1.892***
Listed in year 2010 1.905*** 1.909*** 1.899***
Listed in year 2011 1.904*** 1.909*** 1.898***
Listed in year 2012 1.922*** 1.928*** 1.917***
Listed in year 2013 1.920*** 1.926*** 1.915***
Listed in year 2014 1.916*** 1.923*** 1.911***
Listed in year 2015 1.909*** 1.915*** 1.905***
Listed in year 2016 1.902*** 1.908*** 1.899***
Listed in year 2017 1.878*** 1.884*** 1.875***
Listed in year 2018 1.889*** 1.895*** 1.884***
Non-Listed in year 2000 0.0225 0.0195 0.0208
Non-Listed in year 2001 0.0888*** 0.0859*** 0.0883***
Non-Listed in year 2002 0.0784** 0.0759** 0.0769**
Non-Listed in year 2003 0.134*** 0.133*** 0.133***
Non-Listed in year 2004 0.196*** 0.194*** 0.195***
Non-Listed in year 2005 0.273*** 0.273*** 0.273***
Non-Listed in year 2006 0.272*** 0.271*** 0.270***
Non-Listed in year 2007 0.300*** 0.299*** 0.300***
Non-Listed in year 2008 0.290*** 0.289*** 0.291***
Non-Listed in year 2009 0.295*** 0.293*** 0.296***
Non-Listed in year 2010 0.301*** 0.299*** 0.303***
Non-Listed in year 2011 0.304*** 0.304*** 0.307***
Non-Listed in year 2012 0.312*** 0.311*** 0.315***
Non-Listed in year 2013 0.305*** 0.304*** 0.308***
Non-Listed in year 2014 0.303*** 0.303*** 0.307***
Non-Listed in year 2015 0.301*** 0.301*** 0.305***
Non-Listed in year 2016 0.302*** 0.301*** 0.306***
Non-Listed in year 2017 0.298*** 0.297*** 0.302***
Non-Listed in year 2018 0.298*** 0.298*** 0.302***
Observations 4,285 4,285 4,285
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
312
Figure 5-33. Margin Results for the number of female directors on the board
(10) (11) (12)
Number of Female Directros
Number of Foreign Markets
Number of Foreign Subsidiaries
Number of Foreign M&As
Listed in year 2000 -0.0776 -0.0777 -0.0782
Listed in year 2001 0.0542 0.0537 0.0504
Listed in year 2002 0.0429 0.0431 0.0413
Listed in year 2003 0.0635* 0.0643* 0.0617*
Listed in year 2004 0.121*** 0.122*** 0.118***
Listed in year 2005 0.133*** 0.132*** 0.126***
Listed in year 2006 0.194*** 0.192*** 0.186***
Listed in year 2007 0.188*** 0.184*** 0.180***
Listed in year 2008 0.248*** 0.244*** 0.237***
Listed in year 2009 0.269*** 0.264*** 0.256***
Listed in year 2010 0.296*** 0.291*** 0.284***
Listed in year 2011 0.329*** 0.322*** 0.315***
Listed in year 2012 0.363*** 0.355*** 0.348***
Listed in year 2013 0.415*** 0.407*** 0.399***
Listed in year 2014 0.471*** 0.462*** 0.454***
Listed in year 2015 0.479*** 0.467*** 0.461***
Listed in year 2016 0.502*** 0.489*** 0.484***
Listed in year 2017 0.495*** 0.482*** 0.477***
Listed in year 2018 0.515*** 0.502*** 0.496***
Non-Listed in year 2000 0.00566 0.0106 0.0110
Non-Listed in year 2001 -0.00685 -0.00220 -0.000999
Non-Listed in year 2002 -0.00810 -0.00323 -0.00311
Non-Listed in year 2003 -0.00841 -0.00404 -0.00421
Non-Listed in year 2004 0.00958 0.0136 0.0140
Non-Listed in year 2005 0.0222 0.0264 0.0258
Non-Listed in year 2006 0.0208 0.0246 0.0237
Non-Listed in year 2007 0.0334** 0.0374** 0.0374**
Non-Listed in year 2008 0.0290* 0.0319** 0.0333**
Non-Listed in year 2009 0.0368** 0.0394** 0.0411***
Non-Listed in year 2010 0.0377*** 0.0403*** 0.0427***
Non-Listed in year 2011 0.0479*** 0.0499*** 0.0522***
Non-Listed in year 2012 0.0612*** 0.0629*** 0.0654***
Non-Listed in year 2013 0.0593*** 0.0604*** 0.0634***
Non-Listed in year 2014 0.0640*** 0.0650*** 0.0679***
Non-Listed in year 2015 0.0670*** 0.0678*** 0.0709***
Non-Listed in year 2016 0.0650*** 0.0654*** 0.0690***
Non-Listed in year 2017 0.0649*** 0.0653*** 0.0687***
Non-Listed in year 2018 0.0670*** 0.0675*** 0.0707***
Observations 4,285 4,285 4,285
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
313
Figure 5-34. Margin Results for the number of foreign directors on the board
(13) (14) (15)
Number of Foreign directors
Number of Foreign Markets
Number of Foreign Subsidiaries
Number of Foreign M&As
Listed in year 2000 -0.175*** -0.177*** -0.177***
Listed in year 2001 -0.0689* -0.0703* -0.0718*
Listed in year 2002 0.0316 0.0292 0.0280
Listed in year 2003 0.0867*** 0.0854** 0.0834**
Listed in year 2004 0.174*** 0.173*** 0.170***
Listed in year 2005 0.200*** 0.200*** 0.197***
Listed in year 2006 0.219*** 0.218*** 0.216***
Listed in year 2007 0.208*** 0.206*** 0.207***
Listed in year 2008 0.238*** 0.237*** 0.236***
Listed in year 2009 0.253*** 0.251*** 0.251***
Listed in year 2010 0.253*** 0.252*** 0.252***
Listed in year 2011 0.278*** 0.277*** 0.277***
Listed in year 2012 0.290*** 0.289*** 0.291***
Listed in year 2013 0.311*** 0.309*** 0.312***
Listed in year 2014 0.329*** 0.327*** 0.330***
Listed in year 2015 0.354*** 0.350*** 0.355***
Listed in year 2016 0.358*** 0.353*** 0.360***
Listed in year 2017 0.353*** 0.348*** 0.355***
Listed in year 2018 0.353*** 0.348*** 0.354***
Non-Listed in year 2000 0.0473*** 0.0487*** 0.0452***
Non-Listed in year 2001 0.0593*** 0.0606*** 0.0578***
Non-Listed in year 2002 0.0454*** 0.0471*** 0.0435**
Non-Listed in year 2003 0.0457*** 0.0477*** 0.0443***
Non-Listed in year 2004 0.0543*** 0.0559*** 0.0531***
Non-Listed in year 2005 0.0657*** 0.0679*** 0.0645***
Non-Listed in year 2006 0.0578*** 0.0597*** 0.0564***
Non-Listed in year 2007 0.0655*** 0.0674*** 0.0644***
Non-Listed in year 2008 0.0658*** 0.0668*** 0.0654***
Non-Listed in year 2009 0.0690*** 0.0696*** 0.0686***
Non-Listed in year 2010 0.0705*** 0.0714*** 0.0709***
Non-Listed in year 2011 0.0616*** 0.0625*** 0.0624***
Non-Listed in year 2012 0.0754*** 0.0760*** 0.0762***
Non-Listed in year 2013 0.0727*** 0.0729*** 0.0737***
Non-Listed in year 2014 0.0715*** 0.0718*** 0.0726***
Non-Listed in year 2015 0.0706*** 0.0707*** 0.0719***
Non-Listed in year 2016 0.0712*** 0.0712*** 0.0728***
Non-Listed in year 2017 0.0691*** 0.0690*** 0.0706***
Non-Listed in year 2018 0.0689*** 0.0689*** 0.0703***
Observations 4,285 4,285 4,285
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
314
Figure 5-35. Margin Results for the number of Russian directors on the board
(16) (17) (18)
Number of Russian Directros
Number of Foreign Markets
Number of Foreign Subsidiaries
Number of Foreign M&As
Listed in year 2000 -0.184** -0.187** -0.188**
Listed in year 2001 -0.108 -0.110 -0.115*
Listed in year 2002 0.115* 0.111* 0.108
Listed in year 2003 0.518*** 0.515*** 0.512***
Listed in year 2004 1.057*** 1.055*** 1.050***
Listed in year 2005 1.409*** 1.408*** 1.399***
Listed in year 2006 1.698*** 1.697*** 1.689***
Listed in year 2007 1.801*** 1.802*** 1.795***
Listed in year 2008 1.823*** 1.825*** 1.813***
Listed in year 2009 1.884*** 1.887*** 1.874***
Listed in year 2010 1.903*** 1.906*** 1.895***
Listed in year 2011 1.899*** 1.903*** 1.890***
Listed in year 2012 1.921*** 1.927*** 1.914***
Listed in year 2013 1.921*** 1.926*** 1.912***
Listed in year 2014 1.920*** 1.925*** 1.911***
Listed in year 2015 1.897*** 1.902*** 1.890***
Listed in year 2016 1.891*** 1.894*** 1.885***
Listed in year 2017 1.872*** 1.875*** 1.866***
Listed in year 2018 1.886*** 1.889*** 1.877***
Non-Listed in year 2000 0.0189 0.0166 0.0182
Non-Listed in year 2001 0.0744** 0.0721** 0.0750**
Non-Listed in year 2002 0.0665** 0.0648** 0.0661**
Non-Listed in year 2003 0.122*** 0.121*** 0.121***
Non-Listed in year 2004 0.181*** 0.180*** 0.182***
Non-Listed in year 2005 0.260*** 0.259*** 0.259***
Non-Listed in year 2006 0.259*** 0.259*** 0.259***
Non-Listed in year 2007 0.288*** 0.287*** 0.288***
Non-Listed in year 2008 0.277*** 0.276*** 0.279***
Non-Listed in year 2009 0.284*** 0.283*** 0.286***
Non-Listed in year 2010 0.287*** 0.286*** 0.290***
Non-Listed in year 2011 0.295*** 0.295*** 0.299***
Non-Listed in year 2012 0.297*** 0.297*** 0.301***
Non-Listed in year 2013 0.290*** 0.290*** 0.294***
Non-Listed in year 2014 0.290*** 0.289*** 0.294***
Non-Listed in year 2015 0.289*** 0.289*** 0.294***
Non-Listed in year 2016 0.289*** 0.288*** 0.294***
Non-Listed in year 2017 0.285*** 0.285*** 0.290***
Non-Listed in year 2018 0.286*** 0.286*** 0.291***
Observations 4,285 4,285 4,285
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
315
Figure 5-36. Margin Results for the number of executive directors on the board
(19) (20) (21)
Number of Executive directors
Number of Foreign Markets
Number of Foreign Subsidiaries
Number of Foreign M&As
Listed in year 2000 -0.241*** -0.242*** -0.242***
Listed in year 2001 -0.195*** -0.196*** -0.200***
Listed in year 2002 0.0468 0.0452 0.0435
Listed in year 2003 0.459*** 0.458*** 0.456***
Listed in year 2004 0.981*** 0.979*** 0.977***
Listed in year 2005 1.316*** 1.316*** 1.309***
Listed in year 2006 1.605*** 1.606*** 1.598***
Listed in year 2007 1.707*** 1.708*** 1.700***
Listed in year 2008 1.741*** 1.743*** 1.731***
Listed in year 2009 1.801*** 1.805*** 1.790***
Listed in year 2010 1.815*** 1.817*** 1.806***
Listed in year 2011 1.819*** 1.823*** 1.808***
Listed in year 2012 1.837*** 1.842*** 1.826***
Listed in year 2013 1.826*** 1.831*** 1.814***
Listed in year 2014 1.813*** 1.818*** 1.800***
Listed in year 2015 1.800*** 1.806*** 1.788***
Listed in year 2016 1.797*** 1.804*** 1.785***
Listed in year 2017 1.772*** 1.779*** 1.760***
Listed in year 2018 1.787*** 1.793*** 1.773***
Non-Listed in year 2000 -0.00750 -0.0103 -0.00482
Non-Listed in year 2001 0.0581* 0.0554* 0.0615*
Non-Listed in year 2002 0.0536* 0.0510 0.0561*
Non-Listed in year 2003 0.113*** 0.110*** 0.115***
Non-Listed in year 2004 0.180*** 0.178*** 0.182***
Non-Listed in year 2005 0.255*** 0.253*** 0.257***
Non-Listed in year 2006 0.257*** 0.255*** 0.258***
Non-Listed in year 2007 0.294*** 0.292*** 0.296***
Non-Listed in year 2008 0.276*** 0.275*** 0.279***
Non-Listed in year 2009 0.286*** 0.285*** 0.289***
Non-Listed in year 2010 0.294*** 0.292*** 0.298***
Non-Listed in year 2011 0.302*** 0.301*** 0.306***
Non-Listed in year 2012 0.317*** 0.316*** 0.321***
Non-Listed in year 2013 0.312*** 0.312*** 0.316***
Non-Listed in year 2014 0.313*** 0.312*** 0.316***
Non-Listed in year 2015 0.313*** 0.313*** 0.317***
Non-Listed in year 2016 0.314*** 0.314*** 0.318***
Non-Listed in year 2017 0.311*** 0.310*** 0.314***
Non-Listed in year 2018 0.312*** 0.311*** 0.315***
Observations 4,285 4,285 4,285
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
316
Figure 5-37. Margin Results for the number of non-executive directors on the board
(22) (23) (24)
Number of Non-executive Directors
Number of Foreign Markets
Number of Foreign Subsidiaries
Number of Foreign M&As
Listed in year 2000 0.0512 0.0448 0.0444
Listed in year 2001 0.180*** 0.175*** 0.170***
Listed in year 2002 0.201*** 0.193*** 0.189***
Listed in year 2003 0.309*** 0.304*** 0.298***
Listed in year 2004 0.457*** 0.454*** 0.445***
Listed in year 2005 0.554*** 0.553*** 0.544***
Listed in year 2006 0.590*** 0.588*** 0.582***
Listed in year 2007 0.566*** 0.562*** 0.563***
Listed in year 2008 0.595*** 0.594*** 0.589***
Listed in year 2009 0.629*** 0.628*** 0.625***
Listed in year 2010 0.631*** 0.630*** 0.629***
Listed in year 2011 0.649*** 0.648*** 0.648***
Listed in year 2012 0.683*** 0.683*** 0.687***
Listed in year 2013 0.764*** 0.762*** 0.767***
Listed in year 2014 0.830*** 0.828*** 0.834***
Listed in year 2015 0.840*** 0.835*** 0.848***
Listed in year 2016 0.837*** 0.827*** 0.847***
Listed in year 2017 0.848*** 0.839*** 0.858***
Listed in year 2018 0.855*** 0.845*** 0.862***
Non-Listed in year 2000 0.0818*** 0.0835*** 0.0739***
Non-Listed in year 2001 0.0729*** 0.0744*** 0.0668***
Non-Listed in year 2002 0.0565*** 0.0592*** 0.0493***
Non-Listed in year 2003 0.0469*** 0.0508*** 0.0415**
Non-Listed in year 2004 0.0523*** 0.0550*** 0.0474***
Non-Listed in year 2005 0.0746*** 0.0796*** 0.0699***
Non-Listed in year 2006 0.0608*** 0.0651*** 0.0556***
Non-Listed in year 2007 0.0629*** 0.0668*** 0.0586***
Non-Listed in year 2008 0.0583*** 0.0600*** 0.0564***
Non-Listed in year 2009 0.0537*** 0.0540*** 0.0515***
Non-Listed in year 2010 0.0467*** 0.0483*** 0.0472***
Non-Listed in year 2011 0.0379*** 0.0396*** 0.0398***
Non-Listed in year 2012 0.0396*** 0.0405*** 0.0415***
Non-Listed in year 2013 0.0315** 0.0315** 0.0343***
Non-Listed in year 2014 0.0275** 0.0279** 0.0308**
Non-Listed in year 2015 0.0278** 0.0276** 0.0314**
Non-Listed in year 2016 0.0269** 0.0264** 0.0317**
Non-Listed in year 2017 0.0210 0.0205 0.0255*
Non-Listed in year 2018 0.0202 0.0197 0.0242*
Observations 4,285 4,285 4,285
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
317
Figure 5-38 Hausman Test for fixed effect and random effects models with Board Size as a
dependent variable
(b) (B) (b-B) sqrt(diag(V_b-
V_B))
Fixed Effects Random Effects Difference S.E.
ln_sub_bod~w -0.0009622 0.001743 -0.0027051 0.0045443
ln_acq_bod~w -0.0239181 -0.0308891 0.006971 0.0032307
ln_foreign~s -0.0406808 -0.0132871 -0.0273937 0.0066489
ln_sub_for~n 0.0475095 0.0116278 0.0358816 0.0110073
ln_sub_dom~c -0.106679 -0.0599629 -0.0467161 0.0289359
ln_num_of_~b 0.1259354 0.0737927 0.0521427 0.0284506
ln_acq_for~n 0.0783618 0.0750695 0.0032923 0.0075822
ln_acq_dom~c 0.1407973 0.1228277 0.0179696 0.0090133
ln_num_of_~s -0.0928587 -0.075496 -0.0173627 0.0088259
ln_empl 0.0055613 0.0046516 0.0009098 0.0009018
ln_op_rev_~B 0.000751 0.0009365 -0.0001855 0.0005021
ln_firm_ag~q -0.0202905 -0.0130071 -0.0072834 0.0017984
ln_tt_asse~B -0.0107904 -0.008752 -0.0020384 0.0009449
ln_fa_asse~B -0.0000917 -0.0012729 0.0011813 0.000928
ln_int_ass~k -0.0004562 -0.000816 0.0003598 0.0001464
1.soe 0.0091742 0.0155355 -0.0063613 0.0017588
1.bod_dummy 2.067668 2.064872 0.0027958 0.002099
1.pub_quoted 0.0552763 0.0922975 -0.0370212 0.004349
2001 -0.0039934 -0.0077878 0.0037944 .
2002 -0.0034795 -0.0093451 0.0058656 .
2003 -0.0052964 -0.0139071 0.0086107 .
2004 0.0064648 -0.0035018 0.0099666 0.0003954
2005 0.0132021 0.001027 0.0121752 0.0013087
2006 0.0198566 0.0068763 0.0129803 0.0018293
2007 0.0235208 0.0087442 0.0147765 0.0022805
2008 0.0203705 0.0045165 0.015854 0.0026506
2009 0.0276885 0.0117253 0.0159632 0.0029123
2010 0.0327337 0.0157805 0.0169532 0.0031049
2011 0.0388312 0.0213764 0.0174547 0.0033807
2012 0.0496269 0.0310628 0.0185641 0.0036102
2013 0.0568711 0.0375077 0.0193634 0.0038425
2014 0.0623119 0.0423625 0.0199494 0.00403
2015 0.0622849 0.0417736 0.0205113 0.0042432
2016 0.0681173 0.0471348 0.0209826 0.0045704
2017 0.0730523 0.0512614 0.0217909 0.00473
2018 0.0804706 0.0578142 0.0226564 0.0048728
b = consistent under Ho and Ha; obtained from xtreg
B inconsistent under Ha, efficient under Ho; obtained from xtreg
Test: Ho difference in coefficients not systematic
chi2(36) = (b-B)'[(V_b-V_B)^(-1)](b-B)
chi2(36) = 223.21
Prob>chi2 = 0.0000
(V_b-V_B is not positive definite)
318
Figure 5-39Hausman Test for fixed effects and random effects models with the Age of the
board as a dependent variable
(b) (B) (b-B) sqrt(diag(V_b-V_B))
Fixed Effects Random Effects Difference S.E.
ln_sub_bod~w -0.0009622 0.001743 -0.0027051 0.0045443
ln_acq_bod~w -0.0239181 -0.0308891 0.006971 0.0032307
ln_foreign~s -0.0406808 -0.0132871 -0.0273937 0.0066489
ln_sub_for~n 0.0475095 0.0116278 0.0358816 0.0110073
ln_sub_dom~c -0.106679 -0.0599629 -0.0467161 0.0289359
ln_num_of_~b 0.1259354 0.0737927 0.0521427 0.0284506
ln_acq_for~n 0.0783618 0.0750695 0.0032923 0.0075822
ln_acq_dom~c 0.1407973 0.1228277 0.0179696 0.0090133
ln_num_of_~s -0.0928587 -0.075496 -0.0173627 0.0088259
ln_empl 0.0055613 0.0046516 0.0009098 0.0009018
ln_op_rev_~B 0.000751 0.0009365 -0.0001855 0.0005021
ln_firm_ag~q -0.0202905 -0.0130071 -0.0072834 0.0017984
ln_tt_asse~B -0.0107904 -0.008752 -0.0020384 0.0009449
ln_fa_asse~B -0.0000917 -0.0012729 0.0011813 0.000928
ln_int_ass~k -0.0004562 -0.000816 0.0003598 0.0001464
1.soe 0.0091742 0.0155355 -0.0063613 0.0017588
1.bod_dummy 2.067668 2.064872 0.0027958 0.002099
1.pub_quoted 0.0552763 0.0922975 -0.0370212 0.004349
2001 -0.0039934 -0.0077878 0.0037944 .
2002 -0.0034795 -0.0093451 0.0058656 .
2003 -0.0052964 -0.0139071 0.0086107 .
2004 0.0064648 -0.0035018 0.0099666 0.0003954
2005 0.0132021 0.001027 0.0121752 0.0013087
2006 0.0198566 0.0068763 0.0129803 0.0018293
2007 0.0235208 0.0087442 0.0147765 0.0022805
2008 0.0203705 0.0045165 0.015854 0.0026506
2009 0.0276885 0.0117253 0.0159632 0.0029123
2010 0.0327337 0.0157805 0.0169532 0.0031049
2011 0.0388312 0.0213764 0.0174547 0.0033807
2012 0.0496269 0.0310628 0.0185641 0.0036102
2013 0.0568711 0.0375077 0.0193634 0.0038425
2014 0.0623119 0.0423625 0.0199494 0.00403
2015 0.0622849 0.0417736 0.0205113 0.0042432
2016 0.0681173 0.0471348 0.0209826 0.0045704
2017 0.0730523 0.0512614 0.0217909 0.00473
2018 0.0804706 0.0578142 0.0226564 0.0048728
b = consistent under Ho and Ha; obtained from xtreg
B inconsistent under Ha, efficient under Ho; obtained from xtreg
Test: Ho difference in coefficients not systematic
chi2(36) = (b-B)'[(V_b-V_B)^(-1)](b-B)
chi2(36) = 774.74
Prob>chi2 = 0.0000
(V_b-V_B is not positive definite)
319
Figure 5-40 Hausman Test for fixed effects and random effects models with the number of
male directors on the board as a dependent variable
(b) (B) (b-B) sqrt(diag(V_b-
V_B))
Fixed Effects Random Effects Difference S.E.
ln_sub_bod~w -0.006041 -0.0114577 0.0054167 0.0051994
ln_acq_bod~w -0.0436257 -0.048779 0.0051533 0.0037637
ln_foreign~s 0.0075552 0.0447555 -0.0372003 0.0076653
ln_sub_for~n -0.0074937 -0.0276652 0.0201715 0.0125275
ln_sub_dom~c -0.2834655 -0.1556891 -0.1277764 0.0329061
ln_num_of_~b 0.2953284 0.1682236 0.1271048 0.0323647
ln_acq_for~n 0.0718918 0.0709775 0.0009143 0.0086999
ln_acq_dom~c 0.0887677 0.0853339 0.0034338 0.0104624
ln_num_of_~s -0.0554576 -0.0537845 -0.0016731 0.0102706
ln_empl 0.0048325 0.0049019 -0.0000694 0.0010376
ln_op_rev_~B -0.0015193 -0.0017845 0.0002652 0.0005923
ln_firm_ag~q -0.0164248 -0.0103947 -0.00603 0.0020516
ln_tt_asse~B -0.0071938 -0.0056266 -0.0015672 0.0011137
ln_fa_asse~B -0.0005738 -0.001383 0.0008092 0.0010752
ln_int_ass~k -0.0002416 -0.0006198 0.0003782 0.0001746
1.soe 0.0070605 0.012611 -0.0055504 0.0020632
1.bod_dummy 1.991211 1.985138 0.0060728 0.002456
1.pub_quoted 0.0697723 0.1072022 -0.0374298 0.0050012
2001 -0.0037869 -0.0075658 0.0037789 .
2002 -0.0025353 -0.0080428 0.0055075 .
2003 0.0000346 -0.0079425 0.0079771 .
2004 0.0142268 0.0047121 0.0095147 0.0008505
2005 0.0245444 0.0129364 0.011608 0.001662
2006 0.0313052 0.0190481 0.0122571 0.002212
2007 0.0369769 0.0228918 0.0140851 0.0027046
2008 0.0304226 0.0152995 0.0151231 0.0031147
2009 0.0357252 0.0201092 0.0156161 0.0034018
2010 0.0409917 0.0251009 0.0158909 0.0036122
2011 0.0440036 0.0271508 0.0168528 0.0039218
2012 0.0501362 0.0321045 0.0180317 0.0041798
2013 0.0546507 0.0359054 0.0187453 0.0044415
2014 0.0565215 0.0372796 0.0192419 0.0046535
2015 0.0554565 0.0358275 0.019629 0.0048948
2016 0.0622464 0.0413809 0.0208655 0.0052626
2017 0.0675099 0.0459326 0.0215773 0.0054431
2018 0.0731263 0.0508564 0.02227 0.0056054
b = consistent under Ho and Ha; obtained from xtreg
B inconsistent under Ha, efficient under Ho; obtained from xtreg
Test: Ho difference in coefficients not systematic
chi2(36) = (b-B)'[(V_b-V_B)^(-1)](b-B)
chi2(36) = 170.23
Prob>chi2 = 0.0000
(V_b-V_B is not positive definite)
320
Figure 5-41 Hausman Test for fixed effects and random effects models with the number of
female directors on the board as a dependent variable
(b) (B) (b-B) sqrt(diag(V_b-
V_B))
Fixed Effects Random Effects Difference S.E.
ln_sub_bod~w 0.039243 0.0728554 -0.0336125 0.0109749
ln_acq_bod~w 0.1034003 0.0864874 0.0169129 0.0085312
ln_foreign~s -0.2608771 -0.2768677 0.0159906 0.0167621
ln_sub_for~n 0.274825 0.1830972 0.0917278 0.0257834
ln_sub_dom~c 0.6720292 0.3644223 0.3076069 0.0676165
ln_num_of_~b -0.6250772 -0.3543322 -0.270745 0.0666488
ln_acq_for~n 0.0980842 0.0715248 0.0265594 0.0186843
ln_acq_dom~c 0.3931701 0.284179 0.1089911 0.0234667
ln_num_of_~s -0.3403878 -0.2250024 -0.1153854 0.023231
ln_empl 0.0098837 0.0043316 0.005552 0.0022603
ln_op_rev_~B 0.0016498 0.0058336 -0.0041837 0.001389
ln_firm_ag~q -0.0195465 -0.0130765 -0.00647 0.0042995
ln_tt_asse~B -0.0100479 -0.0081333 -0.0019146 0.0026099
ln_fa_asse~B 0.0019954 0.0002411 0.0017543 0.0023998
ln_int_ass~k -0.0010124 -0.0011313 0.0001189 0.0004194
1.soe 0.028306 0.0344211 -0.0061151 0.0047719
1.bod_dummy 0.3157212 0.3309536 -0.0152324 0.005614
1.pub_quoted -0.0313243 -0.0153553 -0.015969 0.0108483
2001 -0.001486 -0.0030685 0.0015826 .
2002 -0.0059507 -0.009543 0.0035922 .
2003 -0.0247597 -0.031114 0.0063543 0.0020234
2004 -0.0281495 -0.0343233 0.0061737 0.0031192
2005 -0.0400181 -0.0477616 0.0077435 0.0043477
2006 -0.0394281 -0.0477625 0.0083345 0.0053183
2007 -0.0474547 -0.0560224 0.0085677 0.0062459
2008 -0.0367441 -0.0453567 0.0086126 0.0070431
2009 -0.0294912 -0.0358286 0.0063375 0.0075766
2010 -0.0335357 -0.0437919 0.0102562 0.0079771
2011 -0.0180879 -0.025975 0.0078871 0.0085966
2012 0.0027522 -0.0049095 0.0076616 0.0091158
2013 0.0174108 0.00943 0.0079808 0.0096443
2014 0.0378908 0.0297361 0.0081547 0.0100781
2015 0.042473 0.0336448 0.0088282 0.0105727
2016 0.0428581 0.0378445 0.0050136 0.0112985
2017 0.0429552 0.0374719 0.0054833 0.0116675
2018 0.0528358 0.0463542 0.0064816 0.0120059
b = consistent under Ho and Ha; obtained from xtreg
B inconsistent under Ha, efficient under Ho; obtained from xtreg
Test: Ho difference in coefficients not systematic
chi2(36) = (b-B)'[(V_b-V_B)^(-1)](b-B)
chi2(36) = 98.16
Prob>chi2 = 0.0000
(V_b-V_B is not positive definite)
321
Figure 5-42 Hausman Test for fixed effects and random effects models with the number
executive directors on the board as a dependent variable
(b) (B) (b-B) sqrt(diag(V_b-
V_B))
Fixed Effects Random Effects Difference S.E.
ln_sub_bod~w 0.0039996 -0.0176254 0.021625 0.005089
ln_acq_bod~w -0.0396637 -0.0487834 0.0091197 0.0033356
ln_foreign~s -0.0423744 -0.0010269 -0.0413475 0.0072116
ln_sub_for~n -0.0368218 -0.0281073 -0.0087145 0.0125877
ln_sub_dom~c -0.1459612 -0.1107805 -0.0351807 0.0331933
ln_num_of_~b 0.1759207 0.1390024 0.0369183 0.0325963
ln_acq_for~n 0.0484064 0.0578502 -0.0094438 0.0083939
ln_acq_dom~c -0.007879 -0.0086651 0.0007861 0.0094735
ln_num_of_~s 0.0376668 0.0344891 0.0031776 0.0091639
ln_empl -0.0024445 -0.0005364 -0.0019081 0.0009874
ln_op_rev_~B 0.0010366 0.0011894 -0.0001528 0.0004842
ln_firm_ag~q -0.0135995 -0.00817 -0.0054296 0.0020381
ln_tt_asse~B -0.0236311 -0.0214739 -0.0021572 0.0009158
ln_fa_asse~B 0.0041697 0.003562 0.0006077 0.0009839
ln_int_ass~k 0.0011736 0.0010821 0.0000915 0.000132
1.soe 0.0088472 0.0121932 -0.003346 0.0017512
1.bod_dummy 1.95376 1.950185 0.003575 0.0021175
1.pub_quoted -0.0014466 0.0396687 -0.0411153 0.0047698
2001 0.0005227 -0.0035327 0.0040554 .
2002 0.0051326 -0.0010208 0.0061534 .
2003 0.0092136 0.0002642 0.0089494 .
2004 0.0267184 0.0158861 0.0108323 .
2005 0.0292844 0.0160251 0.0132593 0.0002552
2006 0.0392094 0.0247158 0.0144936 0.0014641
2007 0.053283 0.0364946 0.0167883 0.0021193
2008 0.0423062 0.0232817 0.0190245 0.0026061
2009 0.0503367 0.0304289 0.0199078 0.0029585
2010 0.0587166 0.039074 0.0196426 0.0032212
2011 0.065636 0.0442831 0.0213529 0.0035574
2012 0.0775572 0.0544053 0.0231519 0.0038347
2013 0.0808011 0.0565078 0.0242933 0.0041129
2014 0.0810696 0.0560118 0.0250579 0.004334
2015 0.0797092 0.0536765 0.0260327 0.0045845
2016 0.0854073 0.0581518 0.0272555 0.0049783
2017 0.090531 0.062592 0.027939 0.0051665
2018 0.0976335 0.0689757 0.0286578 0.0053311
b = consistent under Ho and Ha; obtained from xtreg
B inconsistent under Ha, efficient under Ho; obtained from xtreg
Test: Ho difference in coefficients not systematic
chi2(36) = (b-B)'[(V_b-V_B)^(-1)](b-B)
chi2(36) = 4139.69
Prob>chi2 = 0.0000
(V_b-V_B is not positive definite)
322
Figure 5-43 Hausman Test for fixed effects and random effects models with the number of
non-executive directors on the board as a dependent variable
(b) (B) (b-B) sqrt(diag(V_b-
V_B))
Fixed Effects Random Effects Difference S.E.
ln_sub_bod~w -0.0156487 0.0389849 -0.0546336 0.0092776
ln_acq_bod~w -0.0122973 -0.0050419 -0.0072554 0.0063673
ln_foreign~s 0.0005728 -0.0284042 0.028977 0.0131516
ln_sub_for~n 0.2255277 0.1138429 0.1116848 0.022822
ln_sub_dom~c 0.0770706 0.1195927 -0.0425221 0.0593108
ln_num_of_~b -0.0850677 -0.1479645 0.0628967 0.0581136
ln_acq_for~n 0.2514909 0.2194785 0.0320124 0.0150656
ln_acq_dom~c 0.6484404 0.6045971 0.0438433 0.0176424
ln_num_of_~s -0.5653779 -0.5156675 -0.0497104 0.0172484
ln_empl 0.026265 0.0212714 0.0049936 0.0017614
ln_op_rev_~B 0.0004248 0.0013216 -0.0008967 0.0010027
ln_firm_ag~q -0.0345511 -0.0248697 -0.0096814 0.0035931
ln_tt_asse~B 0.022703 0.0246529 -0.0019499 0.0018709
ln_fa_asse~B -0.0094487 -0.0129576 0.0035089 0.0018115
ln_int_ass~k -0.005447 -0.0061503 0.0007033 0.0002971
1.soe 0.0116908 0.0215658 -0.0098751 0.0034723
1.bod_dummy 0.3929459 0.4000883 -0.0071423 0.0042027
1.pub_quoted 0.2655577 0.2616547 0.003903 0.008569
2001 -0.0179451 -0.0184275 0.0004824 .
2002 -0.0297741 -0.0313228 0.0015488 .
2003 -0.0434196 -0.0462613 0.0028417 0.0008038
2004 -0.0464153 -0.0489931 0.0025778 0.0021512
2005 -0.0262672 -0.0299262 0.0036591 0.0032958
2006 -0.0302352 -0.0332625 0.0030273 0.004187
2007 -0.0527562 -0.055773 0.0030168 0.0050079
2008 -0.0510064 -0.0516268 0.0006203 0.0057069
2009 -0.045354 -0.0442129 -0.0011411 0.0062045
2010 -0.053645 -0.0552314 0.0015863 0.006524
2011 -0.0524267 -0.0513545 -0.0010721 0.0070645
2012 -0.0402556 -0.0381279 -0.0021277 0.0075103
2013 -0.0202437 -0.0176709 -0.0025728 0.0079658
2014 -0.0004688 0.0022022 -0.0026709 0.0083334
2015 0.0057249 0.0089683 -0.0032435 0.0087527
2016 0.0090513 0.0144069 -0.0053556 0.0094251
2017 0.0118459 0.0163528 -0.0045069 0.0097347
2018 0.0168391 0.0203283 -0.0034892 0.0100112
b = consistent under Ho and Ha; obtained from xtreg
B inconsistent under Ha, efficient under Ho; obtained from xtreg
Test: Ho difference in coefficients not systematic
chi2(36) = (b-B)'[(V_b-V_B)^(-1)](b-B)
chi2(36) = 86.09
Prob>chi2 = 0.0000
(V_b-V_B is not positive definite)
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Figure 5-44 Hausman Test for fixed effects and random effects models with the number of
Russian directors on the board as a dependent variable
(b) (B) (b-B) sqrt(diag(V_b-
V_B))
Fixed Effects Random Effects Difference S.E.
ln_sub_bod~w 0.0125534 0.018235 -0.0056816 0.007547
ln_acq_bod~w -0.0653038 -0.0684345 0.0031307 0.0058761
ln_foreign~s -0.0071693 -0.0085491 0.0013798 0.0114946
ln_sub_for~n 0.0356066 0.0186309 0.0169757 0.0177477
ln_sub_dom~c 0.0687899 0.1244896 -0.0556997 0.0464438
ln_num_of_~b -0.0291939 -0.0995296 0.0703356 0.0457524
ln_acq_for~n 0.0718659 0.0612856 0.0105803 0.0127913
ln_acq_dom~c -0.0574479 -0.0799078 0.0224599 0.016117
ln_num_of_~s 0.0904968 0.1152309 -0.0247341 0.0159708
ln_empl 0.0076853 0.0062666 0.0014187 0.0015434
ln_op_rev_~B -0.000817 -0.000777 -0.00004 0.0009651
ln_firm_ag~q -0.0145252 -0.0079125 -0.0066127 0.0029402
ln_tt_asse~B -0.0035404 -0.0005717 -0.0029687 0.0018099
ln_fa_asse~B -0.0093258 -0.0110477 0.0017219 0.0016452
ln_int_ass~k 0.0014072 0.0009736 0.0004336 0.0002937
1.soe 0.0392576 0.0478563 -0.0085987 0.0033001
1.bod_dummy 1.940588 1.938192 0.0023962 0.0038923
1.pub_quoted 0.0873747 0.1165047 -0.02913 0.007423
2001 -0.007127 -0.0099709 0.0028439 .
2002 -0.0076088 -0.0119597 0.0043509 0.0009631
2003 -0.0088322 -0.0153948 0.0065626 0.0018828
2004 0.0045079 -0.0028036 0.0073115 0.0024845
2005 0.015761 0.0071619 0.0085991 0.0032376
2006 0.0249214 0.0162303 0.0086912 0.00386
2007 0.0305684 0.020556 0.0100124 0.0044666
2008 0.0215903 0.0110143 0.010576 0.004995
2009 0.0267677 0.0165089 0.0102588 0.0053458
2010 0.0292017 0.0178274 0.0113743 0.0055963
2011 0.0317421 0.0206772 0.0110648 0.0060126
2012 0.0327994 0.0211015 0.0116978 0.0063614
2013 0.0380029 0.0257689 0.0122341 0.0067177
2014 0.0405643 0.0280573 0.012507 0.0070109
2015 0.0354408 0.0226511 0.0127897 0.0073455
2016 0.0372934 0.0249133 0.0123801 0.00784
2017 0.0441888 0.0310374 0.0131513 0.0080889
2018 0.0511491 0.0371651 0.013984 0.0083179
b = consistent under Ho and Ha; obtained from xtreg
B inconsistent under Ha, efficient under Ho; obtained from xtreg
Test: Ho difference in coefficients not systematic
chi2(36) = (b-B)'[(V_b-V_B)^(-1)](b-B)
chi2(36) = 59.69
Prob>chi2 = 0.0078
(V_b-V_B is not positive definite)
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Figure 5-45 Hausman Test for fixed effects and random effects models with the number of
foreign directors on the board as a dependent variable
(b) (B) (b-B) sqrt(diag(V_b-
V_B))
Fixed Effects Random Effects Difference S.E.
ln_sub_bod~w -0.0661288 -0.0541753 -0.0119535 0.0082783
ln_acq_bod~w 0.1304676 0.1197997 0.0106679 0.0057176
ln_foreign~s -0.086671 -0.0539395 -0.0327315 0.0117094
ln_sub_for~n 0.1495398 0.0601702 0.0893696 0.0203614
ln_sub_dom~c -0.2993072 -0.3721759 0.0728686 0.0526719
ln_num_of_~b 0.2732513 0.3537467 -0.0804954 0.0515685
ln_acq_for~n 0.0499778 0.0902944 -0.0403166 0.0133742
ln_acq_dom~c 0.736062 0.7584386 -0.0223766 0.0157605
ln_num_of_~s -0.6690783 -0.6935665 0.0244882 0.0154372
ln_empl 0.0023149 0.0011914 0.0011235 0.0015603
ln_op_rev_~B 0.0051934 0.00505 0.0001434 0.0009125
ln_firm_ag~q -0.0309493 -0.0223313 -0.008618 0.0031765
ln_tt_asse~B -0.0083349 -0.0092223 0.0008875 0.0016984
ln_fa_asse~B 0.0103969 0.0110186 -0.0006217 0.0016147
ln_int_ass~k -0.0010483 -0.0012911 0.0002428 0.0002734
1.soe -0.0669483 -0.0688464 0.0018981 0.0031372
1.bod_dummy 0.2616596 0.2687167 -0.0070571 0.0037991
1.pub_quoted -0.0262393 0.0027063 -0.0289456 0.007603
2001 0.0107688 0.0071676 0.0036012 .
2002 0.0162746 0.0098336 0.006441 .
2003 0.0124788 0.0031101 0.0093687 0.0015253
2004 0.0162027 0.004788 0.0114147 0.0023313
2005 0.0147387 0.0000176 0.0147211 0.0032155
2006 0.0128018 -0.0040166 0.0168184 0.0039489
2007 0.0038363 -0.014701 0.0185373 0.0046414
2008 0.0124438 -0.0074403 0.0198841 0.0052407
2009 0.0210301 0.0004896 0.0205404 0.005664
2010 0.0288198 0.0081191 0.0207007 0.0059232
2011 0.0352579 0.0133299 0.021928 0.006394
2012 0.0537918 0.0307025 0.0230893 0.0067816
2013 0.0603143 0.03619 0.0241243 0.0071789
2014 0.0670641 0.0419969 0.0250672 0.0075005
2015 0.0768685 0.0511009 0.0257676 0.0078678
2016 0.0848501 0.0583565 0.0264936 0.0084609
2017 0.0836933 0.0562237 0.0274696 0.0087304
2018 0.0867834 0.0584891 0.0282942 0.0089722
b = consistent under Ho and Ha; obtained from xtreg
B inconsistent under Ha, efficient under Ho; obtained from xtreg
Test: Ho difference in coefficients not systematic
chi2(36) = (b-B)'[(V_b-V_B)^(-1)](b-B)
chi2(36) = 68.79
Prob>chi2 = 0.0008
(V_b-V_B is not positive definite)
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Chapter 6
Conclusion In using a multi-method approach, this thesis identifies the gap in the literature,
provides a real case study of the relationship between internationalisation and
corporate governance, and provides empirical evidence of such a relationship.
Examining traditional theories of internationalisation (Johanson & Vahlne, 1977;
McDougal & Oviatt, 1994; Malhorta & Hinings, 2010) and corporate governance (Berle
& Means, 1932; Fama & Jensen, 1983; Freeman, 1984; Donaldson & Davis, 1991),
the thesis demonstrates that the literature does not address, in full, the important
strategic decisions that SME firms are faced with in the process of rapid
internationalisation, especially if the firm comes from a developing country and is
looking to expand to a developed country. Mainstream literature focuses on strategic
decisions, made by managers, who are also the owners of the SMEs, around issues
such as entry modes into foreign markets (Ripollés & Blesa, 2017), operational
strategies (Bell, Crick & Young, 2004; Crick & Spence, 2005; Martin & Javalgi, 2016),
and growth and performance beyond the inception stage (Ghannda & Ljungquist,
2005; Li et al, 2017). The literature overlooks the quick international expansion of
small- and medium-sized firms. These firms display no separation of ownership and
control, thus concealing the problem of unchanged corporate structure, because as
the corporate governance literature points out, this issue primarily relates to large firms
with separation of ownership and control. The managerial incompetence of owners
can lead to a decrease in the profitability of a business in foreign markets, or may even
result in partial or full business closure. However, internationalisation is a dynamic
process and firms may have opportunities to re-enter the same foreign market after
certain corporate restructuring.
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An example of this rapid internationalisation was presented in this thesis in
Chapter 2. The chapter examined the real case example of the Kaspersky Lab, which
transitioned from a small Russian IT software company, into a multinational
corporation, and managed to overcome the hidden threat of unchanged corporate
governance structures along the internationalisation path. The detailed analysis of the
development path of Kaspersky Laboratory, based on an in-depth interview, confirmed
that when a firm’s internationalisation occurs through opening a subsidiary or foreign
acquisition in the foreign market, it will be followed by the creation of corporate
governance mechanisms (such as a board of directors). The corporate restructuring
of the Kaspersky Laboratory, after aggressive internationalisation, allowed the firm to
change its trajectory from failure to success. Findings from the Kaspersky case study
emphasise that an increase in geographical diversification of a firm will positively
correlate with the share of foreign directors represented on the board.
This case study was the initial step in constructing a general theoretical
framework that considered the strategic decision of corporate governance adjustment,
through the lens of game theory. The main objective of the framework was to predict
whether a firm expanding outside its domestic market, should strategically adopt new
corporate governance mechanisms, or if it could keep exploiting pre-existing internal
mechanisms.
The results of the theoretical chapter suggest that internationalisation of a firm
from a country with low levels of corporate governance, to a country with higher levels
of corporate governance, should correlate with a restructuring of corporate
governance mechanisms. The critical parameters that would determine the action of
the firm entering the foreign market, are the cost of investment into corporate
governance mechanisms, and the concentration of the foreign market. Both
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parameters relate to the potential profit that a firm could achieve as a result of
internationalisation. These parameters would, therefore, directly affect the strategic
decisions of the entrant firm, determining whether it is worth investing in new corporate
governance mechanisms, regardless of the actions of other firms, or aligning with
other market participants for the most profitable outcome.
Both the case study and theoretical framework point to the existence of a
relationship between internationalisation and corporate governance. To check
empirically if such a relationship exists, the thesis examined a sample of 300 Russian
firms, based on a proprietorial level panel database, fully described in Chapter 4. Using
the fixed effects regression model, together with the GMM as the robustness check,
empirical analysis provided the evidence that a firm’s internationalisation process,
when occurring through opening a subsidiary or foreign acquisition in the foreign
market, is positively correlated with the number of corporate governance mechanisms
they exhibit. The regression results also confirm that an increase in the geographical
diversification of the firm is positively correlated with the share of foreign directors
represented on the board. Following the theoretical framework, the empirical results
confirm the existence of a positive relationship between internationalisation of the firm,
from a country with low levels of corporate governance, to a country with higher levels
of corporate governance, and the restructuring of its corporate governance
mechanisms.
To support the final hypothesis, the empirical analysis exploits the fixed effects
regression model, based on a pseudo post IPO natural experiment approach. The
evidence suggests that internationalisation, in terms of the number of foreign
subsidiaries and number of foreign merger and acquisition deals, has a positive and
significant effect on several aspects of corporate board structure, particularly on the
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number of independent directors on the board and the number of foreign directors on
the board. The regression analysis also indicates that listed firms (i.e. post-IPO) are
more influenced by the number of foreign and domestic subsidiaries, and by the
number of foreign and domestic mergers and acquisitions, when compared with non-
listed firms. Further evaluation, using the margin analysis, denoted a clear decoupling
effect between listed and non-listed firms. The main result of the margin analysis
indicates that internationalisation impacts listed firms much more than non-listed firms,
in terms of changes in corporate governance. The analysis also suggests that non-
listed firms will benefit from an adjustment of the board structure during
internationalisation.
This thesis contributes to the existing field of strategic management in three
main ways. First it provides the evidence for the existence of a relationship between
internationalisation and corporate governance for small and medium emerging
markets firms that are internationalising. Acknowledgement of such a relationship
provides a foundation for future research around emerging markets and points to the
different strategic decisions that could be taken by emerging markets firms during the
process of internationalisation.
Secondly, the theoretical framework of this thesis provides vital evidence that
corporate governance adjustments are necessary for successful internationalisation.
This, therefore, provides an analytical framework which is relevant to small and
medium firms pursuing rapid internationalisation. This framework could provide senior
managers and owners of businesses with a robust plan of action for corporate
governance restructuring, that should be taken during the internationalisation process,
while also considering the market of entry, market concentration and the current
development stage of the entrant firm. Based on the Kaspersky case study, this
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research proves that the application of the theoretical framework could change the
trajectory of internationalisation from failure to success.
Thirdly, the unique representative panel dataset of Russian firms from 2000 and
2018 contributes to the existing literature on corporate governance and
internationalisation of Russian firms, through the fact that the dataset focuses not only
on listed firms but also on non-listed firms. At the same time, the dataset of this thesis
covers 19 years, which captures the effect of external events such as financial crises,
the introduction of a corporate governance code in 2002, and the update of corporate
governance practices code in 2014. The dataset also combines several sources while
the merging exercise itself has been a valuable addition to the existing literature.
This thesis has potential limitations. Even though this research contributes
significantly to the scarce empirical academic literature on the topic of
internationalisation and corporate governance of Russian firms, and although it used
a unique proprietorial dataset for the analysis, the sample size could still be larger in
terms of the number of firms, to improve the analysis. At the same time, the poor data
availability for Russian companies between 1995 and 2002 has a certain bias towards
misinterpretation of the effect of internationalisation on corporate board structure.
Another limitation resides within the theoretical framework. The framework is too
narrow and focuses on a single question regarding the implementation of new
corporate governance mechanisms, during the rapid process of internationalisation.
Such a narrow approach allows one to analyse the effect of internationalisation on
corporate governance in detail. It also, however, sets aside other important strategic
decisions, and the costs that are related to these decisions, could potentially lead to
misjudgement with regards the final choice on corporate governance investment.
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To overcome these limitations, future research could focus on several aspects.
It should extend the sample size of the current thesis using the same methodology of
combining and refining several databases. Such an exercise will improve the
significance of the analysis and could shed light on other aspects of
internationalisation that could lead to changes in corporate governance of firms. At the
same time, there is evidence in the academic literature that economic activity can play
an important role in determining the strategies of internationalisation. Therefore, using
a similar theoretical framework to that which is presented in the thesis, further research
could concentrate on the effect of the internationalisation process on corporate
governance structures among firms from different sectors of economic activity.
Additionally, future research could investigate the theoretical framework itself and
expand it further. An updated theoretical framework could also examine the strategic
decisions that firms are faced with after the decision to invest in corporate governance
mechanisms. Questions could include: what should the structure of the board be and
how should particular firms select the set of mechanisms that would be optimal in their
context? One potential idea is also to look into the production function of the firm
experiencing rapid internationalisation. The production function would indicate
whether the firm is capital intense, labour intense or resource dependent. In turn, these
three aspects of production function could be linked to aspects of corporate
governance such as shareholder protection, transparency and disclosure, board of
directors, and future theoretical research could focus on the link between these
factors.