corporate effects and core competencies: the …
TRANSCRIPT
The Pennsylvania State University
The Graduate School
College of Health and Human Development
CORPORATE EFFECTS AND CORE COMPETENCIES: THE INFLUENCE OF
CORPORATE STRATEGIES ON THE PERFORMANCE OF HOTELS
A Thesis in
Hotel, Restaurant and Institutional Management
by
Qu Xiao
Copyright 2007 Qu Xiao
Submitted in Partial Fulfillment of the Requirements
for the Degree of
Doctor of Philosophy
December, 2007
The thesis of Qu Xiao was reviewed and approved* by the following:
John W. O’Neill Associate Professor of Hospitality Management Thesis Adviser Chair of Committee Anna S. Mattila Associate Professor of Hospitality Management Professor-in-Charge of Graduate Programs in School of Hospitality Management Daniel J. Mount Associate Professor of Hospitality Management Donald C. Hambrick Professor of Management and Organization
*Signatures are on file in the Graduate School
ABSTRACT
The purpose of this empirical study is to examine the corporate effects in the
lodging industry from a hotel owner’s perspective. Linking the concepts of corporate
strategy and core competence, eight corporate strategies are proposed relating to hotel
property financial performance and contributing to hotel owner’s core competence. Based
on a three-year sample provided by Smith Travel Research, four hypotheses are tested
with regard to the effects of hotel owner’s corporate strategies and core competencies.
The findings strongly support the existence of corporate effects and the influences of
corporate strategies on hotel financial performance. Based on the relative importance of
the eight strategies, a hotel owner’s expertise in implementing superior strategies
regarding segment, brand, operator, location (i.e., MSA), brand diversification, and
location (i.e., MSA) specialization are identified as the core competencies of the best-
performing owners. The results reveal that a hotel owner’s core competencies may
influence its hotels differently. This study also suggests that the collective influence of
multiple corporate strategies may have a strong impact on a hotel’s financial performance.
iii
TABLE OF CONTENTS
List of Tables viAcknowledgements viiDedication viii Chapter I: INTRODUCTION 1
Objective of the Study 2 Research Questions 3 Significance of the Study 4 Organization of the Dissertation 6 Definition of Terms 7
Chapter II: LITERATURE REVIEW 9
Corporate Effects 9 Corporate Strategy and Core Competence 12 Diversification Strategy 16 Corporate Strategy in the U.S. Lodging Industry 19 Diversification and Specialization Strategies of Hotel Owners 26 Strategy and Core Competence in the Field of Hospitality Management 30 Summary of Literature 34
Chapter III: METHODOLOGY 36
Research Questions 36Hypotheses 37Sample 38Variables and Measures 40Statistical Procedures 47Data Analysis 49Summary 56
Chapter IV: RESULTS 58 Sample Characteristics 58 Effects of Owner 62 Effects of Corporate Strategy 66 Determination of Top and Bottom Hotel Owners 71 Core Competencies of Hotel Owners 73 Effects of Core Competence 78
Chapter V: DISCUSSIONS AND CONCLUSION 97 Summary of Major Findings 97 Discussions 101 Conclusion 115 Theoretical Implications 116
iv
Managerial Implications 118 Limitations and Recommendation for Future Research 121 References 126
v
LIST OF TABLES
Table 1. Data Analysis Procedures 57Table 2. Descriptive Statistics of Sample 1-A and Sample 1-B 59Table 3. Correlation Matrix for Continuous Variables 60Table 4. Mean RevPAR and NOIPAR by Segment 61Table 5. Brand Comparison within Segment 62Table 6. Effects of Owner - General Linear Model 63Table 7. Effects of Owner – Variance Components Analysis 63Table 8. Effects of Owner (Controlling for Location, Segment, Brand, and
Operator) – General Linear Model 64
Table 9. Effects of Owner (Controlling for Location, Segment, Brand, and Operator) – Variance Components Analysis
66
Table 10. Effects of Corporate Strategies - General Linear Model 68Table 11. Effects of Corporate Strategy – Variance Components Analysis 70Table 12. RevPAR and NOIPAR Ranking of Hotel Owners 72Table 13. Core Competence of Hotel Owners –General Linear Model 74Table 14. Core Competence of Hotel Owners – Variance Components Analysis 76Table 15. Effects of Core Competence – Top Six Hotel Owners 79Table 16. Effects of Core Competencies – Hotel Owner One 82Table 17. Effects of Core Competencies – Hotel Owner Two 86Table 18. Effects of Core Competencies – Hotel Owner Three 88Table 19. Effects of Core Competencies – Hotel Owner Four 90Table 20. Effects of Core Competencies – Hotel Owner Five 92Table 21. Effects of Core Competencies – Hotel Owner Six 95Table 22. Comparison of Best-Performing and Under-Performing Hotel Owners 107
vi
ACKNOWLEDGMENTS
First of all, I would like to express my deepest gratitude to my academic advisor
and dissertation chair, Dr. John W. O’Neill, for his constant guidance, tremendous
encouragement, and extraordinary support in every step along the way of completing my
Ph.D. study at Penn State. The expertise, leadership and professionalism I have learned
from him will permeate throughout my career as well as life.
My sincere appreciation also goes to Dr. Anna S. Mattila, Dr. Daniel J. Mount,
and Dr. Donald C. Hambrick. Their support, guidance, and theoretical and practical
insights are not only essential for the completion of this dissertation, but also invaluable
throughout my doctoral education. It was the opportunities of working with them that
made me realize the joy of researching and teaching.
Very special thanks go to Mr. Mark V. Lomanno and his team at Smith Travel
Research. This study would not have been possible without their significant contributions
of data and industry insights.
Finally, I would like to thank the faculty, staff and friends at Penn State for their
help and friendship that made my four years at Happy Valley one of the most enjoyable
memories of my life.
vii
DEDICATION
This dissertation is gratefully dedicated to my beloved grandma, grandpa, mom,
dad, wife, and daughter. It is their unconditional love, constant encouragement, unceasing
sacrifices and everlasting belief in me that always enable me to follow my dream.
viii
Chapter I
INTRODUCTION
Literature regarding strategic management typically distinguishes between
business and corporate strategies. Business strategy deals with the ways in which a
single-business firm, or an individual business-unit of a large firm, competes within a
particular industry or market, while corporate strategy deals with the ways in which a
corporation manages a set of businesses together (Bowman & Helfat, 2001). The relative
importance of business-unit factors in determining performance differences of business-
units between firms has been widely documented, and the literature has revealed that
industry plays a critical role in affecting business-unit profitability. However, previous
research has produced mixed results on the influence of corporate-parent, or corporate
effects, on business-unit performance. Most studies find significant corporate effects,
while they range widely from approximately one percent to eighteen percent of the
variance of business-unit profitability that can be explained by the corporate-level factors.
Such a wide variety among recorded corporate effects suggests the influence of
corporations on business-units may vary in different industries. However, little empirical
research has been conducted to examine the magnitude and the sources of corporate
effects within specific industries.
Strategy research in hospitality management is still in its embryonic stages.
Previous studies on corporate-level strategies have primarily focused on topics of
branding, franchising, internationalization, and leadership, while little attention has been
1
given to the perspective of hotel owners. Industry practitioners have long argued that
hotel owners play critical roles in the lodging industry, and they implement different
strategies in order to improve the performance of their hotels. It is believed that hotel
owners make significant strategic decisions in choosing the location(s) and segment(s) in
which they would like to possess hotels, the brand(s) with which they would like their
hotels to affiliate, and the operator(s) by whom they prefer their hotels to be managed.
Despite a large number of articles and discussions on the importance of hotel
owners found in the trade magazines and industry conferences, little has been studied
with regard to the effects of hotel owner’s corporate-level strategies on property-level
performance. Specifically, whether or not corporate effects exist in the lodging industry,
how hotel owners’ corporate-level strategies affect property-level performance, and how
corporate strategies contribute to the core competencies of hotel owners remain unknown.
Answers to these questions are of great importance because they can improve our
understanding regarding the role of hotel owners in the lodging industry. Consequently,
hotel owners’ corporate strategies are worthy of empirical analysis.
Objectives of the Study
The objective of this research is to complement existing research in corporate
effects and hospitality strategic management by studying the corporate effects in the
lodging industry from a hotel owner’s perspective. The specific objectives of this study
are:
2
(1) To examine the existence of corporate effects in the lodging industry,
(2) To investigate the effects of corporate strategies in determining hotel property
financial performance, and
(3) To explore the core competencies of hotel owners in terms of influencing
hotel property financial performance.
Research Questions
Specifically, this study addresses the following research questions:
(1) Do corporate effects exist in the lodging industry?
(2) Can a hotel owner’s corporate effects on property financial performance be
attributed to the owner’s strategic decisions regarding hotel location, segment,
brand, and operator, as well as corporate specialization strategies regarding
hotel location, segment, brand, and operator?
(3) What are the core competencies of the best-performing hotel owners?
(4) For a particular hotel owner, do its core competencies influence all the hotels
of this owner equally? Or, do the effects of the owner’s core competencies
influence some hotels more or less than other hotels? If the answer to the
second question is yes, then, how do the effects of the core competencies vary
among this particular owner’s hotels?
3
Significance of the Study
This research makes important contributions to the literature of general strategic
management. First, it expands the literature on corporate effects by examining the
existence and magnitude of corporate effects in an interesting but unstudied industry,
namely the lodging industry. Studying corporate effects, a concept primarily drawn from
manufacturing industries, within a service industry helps to improve the validity of the
theory of corporate effects. In addition, focusing on only one single industry avoids the
risk that the corporate effects found in previous research may be caused by industry
characteristics. Second and more importantly, this study investigates the underlying
sources of corporate effects, an important topic that has been only generally discussed but
not fully tested. Specifically, the following strategies are proposed as the sources of
corporate effects: hotel owner’s strategic decisions regarding hotel location, segment,
brand, and operator (management company), as well as the degree of specializations of
these factors. The statistical results of this research reveal which of these candidates are
indeed significant sources of corporate effects. Third, this study not only identifies the
core competencies of the best-performing hotel owners, but also goes one step further to
explore the influences of the identified core competencies on the hotels of a particular
hotel owner. In the literature of strategic management, whether the effects of a firm’s
core competencies on some business-units are more or less than on some other business-
units and what type(s) of business-units benefit most from the firm’s core competencies
are rarely explored questions, and consequently, the answers can add significant value to
the concept of corporate effects.
4
This study is particularly valuable to hospitality management research. Literature
suggests a significant gap between strategic management research in general business
administration and in the hospitality industry (Tse & Olsen, 1999). As a relatively new
notion, research on strategy has suffered two major limitations in the field of hospitality
management (Tse & Olsen, 1999). First, previous studies on hospitality corporate
strategy has focused primarily on the constructs related to environmental scanning,
strategic planning, strategy formulation, and leadership, while little has been researched
regarding implemented strategies and the linkage between strategy and financial
performance. Second, survey and case studies were commonly applied methodologies,
and consequently the results were generally descriptive or only relate to strategic
perceptions rather than realized strategies. Moreover, it has been suggested that, due to
the significant differences between manufacturing industries and service industries, many
strategic theories and models, which were primarily developed from studies on
manufacturing industries, should be re-studied because they may not be valid in the field
of hospitality management (Olsen, 2004; Tse & Olsen, 1999). This dissertation seeks to
compensate for the limitations of previous research by introducing corporate effects, a
relatively new theory to hospitality research, studying the relationship between strategy
and property financial performance, and implementing a large-sample and rigorous
research design.
Furthermore, this study has significant empirical contributions to the lodging
industry. First, the findings of this research can help to qualify/disqualify the popular but
untested notions regarding hotel location, segment, brand, and operator strategies in the
5
hotel investment community. In addition, the results reveal important sources and reasons
for firm strengths and weaknesses, and consequently can assist the strategic analysis of
hotel companies in general, and hotel owners in particular. Through identifying and
improving their respective core competencies, hotel owners could become more effective
in assessing future development, acquisition and/or divestiture opportunities. Finally, for
investors of publicly owned hotel ownership companies, such as Real Estate Investment
Trusts (REITs), this study can assist their evaluation of the companies’ performance.
Although not perfectly correlated, a publicly owned hotel company’s performance in the
stock market is clearly and closely related to the value of the company’s underlying
properties (e.g., Capozza & Seguin, 1999). An investor who understands the company’s
strengths and weaknesses in terms of its influence on property performance can better
evaluate whether the company’s acquisition and/or divestiture activities are value-adding
or value-decreasing.
Organization of the Dissertation
This dissertation is organized into five chapters. Chapter I provides a brief
background regarding corporate effects and hospitality strategy research, as well as
research objectives and research questions. Significance of the study and definition of
terms are also presented. In Chapter II, relevant literature regarding corporate effects,
corporate strategy, and core competence are provided, and the corporate strategies in the
lodging industry are discussed as well. Hypotheses are presented based on the literature.
In Chapter III, a description of methodology is provided and the data analysis procedure
6
is discussed. Results and findings of the study are offered in Chapter IV. Finally, in
Chapter V, the discussions, conclusion, theoretical and managerial implications, and
limitations and recommendations for future research are provided.
Definition of Terms
To assist in interpreting this study more clearly, the following definitions are
offered:
Corporate Effects: the effects of corporate-level factors on the performance of a
business-unit. In this study, corporate effects are measured as the variance of the hotel
property-level financial performance that can be explained by the different owners of the
hotels.
Core Competence: the organizational resources that enable a firm to differentiate itself
from competitors and to achieve competitive advantage. These resources can include a
firm’s assets, capabilities, organizational processes, personnel, finance, knowledge, etc.
In this study, a firm’s capability of implementing performance-improving strategies is
regarded as a core competence of the firm. Such strategies include a firm’s decisions in
choosing hotel location, segment, brand affiliation, and operator.
Hotel Property Financial Performance: Revenue Per Available Room (RevPAR) and
Net Operating Income Per Room (NOIPAR) of a hotel property.
7
Hotel Owner: an individual or institution who is a legal possessor of the realty or realties
of a hotel or a group of hotels, but is not actively involved in the daily operational
activities of the hotel(s).
Hotel Operator: a management company or individual who is responsible for daily
operations of the hotel(s) for a hotel owner and obtains a management fee from the owner.
Hotel Segment: a classification scheme of hotels. Following Smith Travel Research
(2006), in this study, there are six hotel segments: economy, midscale without food &
beverage (F&B), midscale with F&B, upscale, upper upscale, and luxury.
8
Chapter II
LITERATURE REVIEW
This chapter explores and organizes the relevant literature on several key topics
and concepts of strategic management and hospitality management, and attempts to
integrate the findings. Specifically, this chapter reviews the following six major areas:
• Corporate Effects
• Corporate Strategy and Core Competence
• Diversification Strategy
• Corporate Strategy in the U.S. Lodging Industry
• Diversification and Specialization Strategies of Hotel Owners
• Strategic Management Research in the Field of Hospitality Management
Each of these headings is discussed in detail accordingly and hypotheses are
provided following the most relevant literature. A summary of literature is provided at the
end of the chapter.
Corporate Effects
Financial performance of a firm or the business-unit of a firm has been one of key
dependent variables in strategic management research (e.g., Olsen, 1999; 2004).
Literature regarding strategic management typically distinguishes between business and
9
corporate strategies. Business strategy deals with the ways in which a single-business
firm or an individual business-unit of a large firm competes within a particular industry
or market, while corporate strategy deals with the ways in which a corporation manages a
set of businesses together (Bowman & Helfat, 2001). Strategic management researchers
have sought to assess the relative importance of business-unit, corporate, and industry
factors in determining performance differences of business-units between firms. Much
research has emphasized the relative roles that corporate, industry, and business-unit
effects play on outcomes at the business-unit-level. While industry and business-unit
effects have been widely documented as major factors explaining large portions of the
variance in business-unit profitability, previous research has produced mixed results on
the effects of the corporate-parent.
Stimulated by Schmalensee’s (1985) research, in which significant business-unit
and industry effects but zero corporate effects were found, a large number of studies
have reported the relative importance of corporate effects (e.g., McGahan & Porter, 1997;
Rumelt, 1991; Roquebert, Phillips, & Westfall, 1996). In general, previous research uses
accounting measures, such as return on assets, to measure individual business-unit
performance, and shows a wide range of estimated corporate effects. While Rumelt (1991)
reports a small corporate effect of zero to 1.6 percent using variance component analysis,
Roequbert et al. (1996) show a 17.9 percent corporate effect with the same statistical
method. Measuring business-unit performance with market share, the study of Chang and
Singh (2000) also indicates that corporate effects can change from 2.4 percent to 7.6
percent for the same sample, which is primarily comprised of manufacturing industries.
10
Among the factors suggested that lead to the inconsistency of estimated corporate
effects, researchers have found that the effects of the corporate parent differ for
companies in different industries. McGahan and Porter (1997) report that corporate
parent effects are substantially larger for non-manufacturing companies (e.g., agriculture,
transportation, services) than for manufacturing companies that were analyzed in the
studies of Rumelt (1991) and Schmalensee (1985). In addition, literature shows that the
definition of industry and business in previously studied samples, primarily based on the
3- or 4-digit SIC levels, may also contribute to inaccurate estimates of corporate
influence on profitability (Chang & Singh, 2000; Bowman & Helfat, 2001). Due to the
considerable limitations of prior studies, researchers suggest that most results of
corporate effects studies should only be interpreted strictly within the context of their
samples (Bowman & Helfat, 2001). Consequently, more research is needed to disclose
the specific corporate effects of companies in unstudied industries, such as the lodging
industry.
Literature in strategic management has suggested a number of corporate-level
factors that affect profitability, including scope of the firm, core competencies,
organizational structure, organizational climate, planning and control systems, and
corporate strategies (Bowman & Helfat, 2001). Specifically, Bowman and Helfat (2001)
suggest that, theoretically, corporate strategy is a subset of total corporate effects on
profitability, and corporate strategies that affect these corporate-level factors are believed
to influence the firm’s profitability. The concept of strategy and a specific type of
corporate strategy, namely diversification strategy, will be discussed in detail in the
11
following two sections. However, prior research, while suggesting non-negligible
corporate effects, has not provided direct evidence of the potential sources of such
corporate effects, nor has the research revealed how corporate strategies function as
underlying sources of corporate effects.
Corporate Strategy and Core Competence
As a core concept of strategic management, strategy was defined by Chandler
(1962) as the determination of long-term goals of an organization, and the allocation of
resources and the adoption of actions to achieve goals. A number of different definitions
have also been presented by other researchers since (e.g. Andrews, 1971; Ansoff, 1965;
Hofer & Schendel, 1978; Miles & Snow, 1978; Porter, 1980, 1996). Although Chandler’s
(1962) definition is not completely supported by all strategic management researchers, it
serves as the basis for the concept of strategy and for most other studies, which generally
accept that strategy can be viewed as a pattern in the organization’s important decisions
and actions, and strategy is composed of two aspects: formulation and implementation
(e.g., Miles & Snow, 1978; Taylor, 2002). Mintzberg (1978) further distinguishes
between deliberate, emergent, realized and unrealized strategies. By his definitions,
realized strategies are patterns in a stream of decisions, and deliberate strategies are the
intended strategies that become realized (Mintzberg, 1978). Most recently, Hambrick and
Fredrickson (2005) define strategy as an integrated overarching concept of how the
business will achieve its objectives.
12
Literature indicates that, to compete in the market, firms are consistently engaged
in seeking strategies that are most effective in building competitive advantage, based on
their core competencies (Olsen, Tse, & West, 1998; Pearce & Robinson, 1997).
Consequently, obtaining competitive advantage has been a focus of strategic management
research. Kay (1993) defines competitive advantage as the advantage one firm has over
its competitors, while Hofer and Schendel (1978) define competitive advantage as the
unique position a firm develops through its patterns of resource deployment. Although
there is no consensus regarding the exact definition of competitive advantage among
researchers, most studies relate competitive advantage to the firm’s strategy (e.g., Hofer
& Schendel, 1978; Kay, 1993; Porter, 1985, 1996).
Strategic management researchers agree that strategies are the results of the
strategic analysis of an organization, which systematically investigates the organization’s
external environment and its internal context (e.g., David, 2001; Harrison, 2003;
Mintzberg, 1990). Therefore, the strategic analysis, generally referred to as SWOT
(strengths, weaknesses, opportunities, and threats) analysis, is essential for an
organization to develop and execute sound strategies, which aim to achieve long-term
organizational goals through matching an organization’s internal strengths and
weaknesses with its external opportunities and threats. Two important streams in the
literature of strategic management, Porter’s (1980) Five-Forces framework and the
resource-based view (RBV) of the firm, shaped the focuses of strategic analysis and
competitive advantage.
13
First, Porter’s (1980) Five-Forces model directly examines the firm’s external
environment and provides the framework to assess the structure of an industry and to
conduct competition analysis. According to Porter (1980), competitive advantage is
related to positioning, through which the firm obtains a competitive position in its
industry and builds and defends its market share. Specifically, the collective effects of the
five forces (industry competitors, bargaining power of buyers, bargaining power of
suppliers, potential entrants, and substitutes) determine the ability of firms to position and
compete in an industry. Porter (1980) proposes that three generic strategies (overall cost
leader, differentiation, and focus) can be applied by organizations to cope with the
competitive forces.
Second, on the other hand, RBV focuses on the firm’s resources in determining
how to gain competitive advantage (Barney, 1986). RBV considers corporate strategies
from an internal perspective, and explains the differences in firm performance that can
not be attributed to differences in industry and/or competition conditions (e.g., Barney,
1991; Collis & Montgomery, 1995; Peteraf, 1993). From an RBV of strategy research,
previous studies have revealed that analysis of internal resources can enable firms to
determine their potential or realized sources of competencies and capabilities, and a firm
can achieve competitive advantage if its resources are inimitable by its competitors (e.g.,
Amit & Schoemaker, 1993; Peteraf, 1993; Nelson, 1994; Wernerfelt, 1984). According to
Barney (1991), firm resources include all assets, capabilities, organizational processes,
knowledge, etc. that are possessed by a firm and can enable a firm to develop and
implement strategies that improve performance. In addition, Hofer and Schendel (1978)
14
suggest six major categories of resources, including financial, physical, human,
technological, reputation, and organizational, and other researchers use core
competencies (e.g., Prahalad & Hamel, 1990) and capabilities (e.g., Stalk, Evans, &
Schulman, 1992) to suggest firm resources that could generate competitive advantage.
Literature has clearly revealed that RBV is closely linked with core competence, a
key concept in strategic management that addresses the question of “What a firm does
best” (Taylor, 2002). Prahalad and Hamel (1990) view a firm as a portfolio of
competencies and suggest that a firm should organize around its core competencies,
which are its critical resources. According to Leonard-Barton (1992, p.111), “capabilities
are considered core if they differentiate a company strategically.” More specfically,
Coyne, Hall, and Clifford (1997) define core competencies as complementary skills and
knowledge that result in superior performance. Moreover, Henderson and Cockburn
(1994) propose two broad classes of competence: component competence, “the local
abilities and knowledge that are fundamental to day-to-day problem-solving,” and
architectural competence, “the ability to use theses component competencies to integrate
them effectively and to develop fresh component competencies” (p.65). Regardless of
different defintions that have been introduced in the liteature, researchers generally agree
that only those resources that enable a firm to differentiate itself from competitors can be
regarded as the firm’s core competencies (e.g., Harrison, 2003; King, Fowler, & Zeithaml,
2001).
15
Different types of resources are suggested as candidates of core competencies. For
instance, Harrison and Enz (2005) suggest that core competencies could come from
financial, human, physical, knowledge, and/or general organizational resources. Dev,
Erramilli, and Agarwal (2002) propose that core competencies develop/evolve as firms
develop resources to improve performance. Specifically, it is suggested that corporate
strategies, when developed and implemented appropriately, can be important resources of
the firm’s core competencies (Aharoni, 1993; Peteraf, 1993). Stalk et al. (1992) suggest
that, to achieve long-term success, firms identify their key business process strategies,
manage them centrally, and invest in them heavily. While there are a large number of
studies on the resources of core competencies, the effects of a firm’s core competencies
on business-unit performance has not been fully explored in the strategic management
research. Particularly, little is known about whether or not a firm’s core competencies
influence its business-units equally or differently.
Diversification Strategy
As a corporate strategy, diversification has been an important growth tool for
corporations, and consequently its effects on firm performance have been recognized as
one of the central topics in strategic management research (Ramanujam & Varadarajan,
1989). In manufacturing industries, diversification is generally defined as firm expansion
to make/sell products that have no market interaction with the firm’s other products
(Rumelt, 1982). Since Rumult (1974) first tied diversification strategy to financial
performance, the effects of diversification on the performance of firms have been
16
intensively investigated. Previous studies basically have focused on the extent/degree
(more or less), direction (relateness or unrelateness), and mode (internal or acquisition-
based) of diversification. Since Rumult (1974), the degree of diversification has become a
widely used operationalization of corporate strategy, and the measure of the degree of
diversity is based primarily on SIC codes (Ramanujam & Varadarajan, 1989). Rumult’s
(1974) classification on the degree of diversification has also been adopted in a large
number of studies, and the four major categories include single-product firm (over 95
percent of its revenue from one single product), dominant-product firm (70-94 percent of
its revenue from one single product), related-product firm (less than 70 percent of
revenues from a single-product domain and the rest of its revenues from related
businesses), and unrelated-product firm (its revenues from unrelated businesses). The
later three categories all have subcategories.
Some studies have linked diversification strategy directly to corporate effects.
Chang and Singh (2000) suggest a relationship between the size of corporate effects and
the degree of diversification. Specifically, Roequbert, Phillips, and Westfall (1996) find
that corporate effects increase as firms are less diversified. Moreover, Rumelt (1974,
1982) indicates that firm diversification is closely related to its core competencies,
because the best performances are normally enjoyed by the firms that diversify primarily
into the areas that drew on some common core competencies. Bettis (1981) suggests that
related firms and unrelated firms differ significantly by their advertising and research and
development (R&D) expenditures, and that R&D might be part of the core competencies
that Rumult (1974, 1982) implies.
17
However, more recent research reports an overall negative relationship between
diversification strategy and business value and/or performance, and suggests that it is
specialization rather than diversification that benefits the organization (e.g., Berger &
Ofek, 1995; Lang & Stulz, 1994; Montgomery, 1994). A notable study by Wernerfelt and
Montgomery (1988) examines the corporate specialization strategy by operationalizing
corporate effects as focus effects (i.e., the effects of the degree of a firm’s specialization
in one industry or a few industries). The results suggest that the effects of specialization
are positive and explain about 2.5 percent of the variance of the corporate performance,
which is measured by “Tobin’s q,” calculated as the capital market value of the firm
divided by the replacement value of the firm’s asset (Wernerfelt & Meontgomery, 1988).
Ramanujam and Varadarajan (1989), after reviewing a large number of studies on the
relationship between diversification/specialization strategy and business performance,
indicate that such a relationship may be confounded and/or moderated by many plausible
factors, such as industry and/or risk effects. Lang and Stulz (1994) suggest that, although
diversification is found to negatively associate with performance, whether or not
diversification strategy hurts performance may be still questionable. Alternatively, firms
in industries with poor growth prospects may be more inclined to diversify. Therefore, a
possibility is that diversification is not the cause of poor performance, but poor
performance in the underlying line of business may be causing diversification (Lang and
Stulz, 1994). Regardless of the large number of previous studies, they have examined
only the effects on the overall corporate performance but not on the performance of
individual business-units or individual diversification projects (Capozza & Seguin, 1999;
Ramanujam & Varadarajan, 1989).
18
Corporate Strategy in the U.S. Lodging Industry
In the hotel industry, the importance of business-unit (i.e., property) strategies and
corporate strategies are well recognized. Hotels represent over ten percent of all
commercial real estate in the United States (Corgel, 2005). However, unlike other
commercial real estate such as office, apartment, and retail, which are usually rented on
annual or multi-year bases, hotels compete on a nightly occupancy basis, and thus have a
high level of uncertainty in occupancy. Due to the uncertainty of the hotel market, hotels
demand more ongoing marketing efforts and are most vulnerable to local, regional, and
national economic downturns. Consequently, hotels require the highest level of
management expertise. Therefore, at the property-level, the effectiveness of the
competing strategies formulated and implemented by the hotel’s management team, such
as marketing, pricing, human resources, and service strategies, is a critical factor to the
success of the hotel in its local market (e.g., Corgel, 2005; Hayes & Ninemeier, 2007;
Imperiale, 2002; Mueller & Anikeeff, 2001).
In addition, there are different corporate players in the lodging industry, such as
franchisors, management companies, and hotel owners (individual or institutional). In
many cases, those who invest in hotels are not the operators who manage the hotels.
While most hospitality research related to strategic management has focused on the
strategies of either properties or franchisors and management companies, such as
branding, franchising, and internationalization (e.g., Dev et al., 2002; Tse & Olsen, 1999;
Olsen, 2004), little attention was given to the corporate strategies of the hotel owners. As
19
a group owning over ten percent of all commercial real estate in the United States, hotel
owners and investors are among the most essential and active stakeholders in the lodging
industry (Corgel, 2005). After a substantial decline in hotel acquisition and development
activities due to decreased hotel value in 2001-2002, hotel owners’ buying and
developing trends have started to recover considerably since 2003. A recent report shows
that the volume of U.S. hotel transactions has increased from 12.8 billion dollars in 2004
to 21 billion dollars in 2005, and is expected to exceed 30 billion dollars in 2006 (Simon,
2006).
Similar to the owners of other types of commercial real estate, hotel owners are
suggested to concern about the performance of their hotels, because the market value of a
hotel is closely, although not perfectly, related to its operating performance (e.g.,
Capozza & Lee, 1995; Corgel, 2005). Although the role of hotel owners in influencing
the performance of their properties remains unknown, literature regarding other types of
commercial real estate suggests that corporate offices can affect property-level
performance (Capozza & Seguin, 1998). Therefore, Hypothesis 1 is proposed to study the
effects of hotel owners on their hotels and answer Research Question 1 presented in
Chapter I:
Research Question 1: Do corporate effects exist in the lodging industry?
Hypothesis H1: The financial performance of hotels owned by certain owners is
superior to the financial performance of hotels owned by other owners.
20
As a profit-driven entity, hotel owners buy/sell/develop hotel properties to seek
acceptable return on investment. The link between a hotel property’s market value and
the hotel’s financial performance indicators, including ADR, occupancy rate, and net
operating income (NOI), has been well established (e.g., O’Neill, 2004). Therefore, it is
reasonable for non-operating hotel owners, both individual and institutional, to
implement relevant strategies to maximize the financial performance of hotel properties.
Specifically, from a hotel owner’s perspective, a non-operating hotel owner can generally
make significant, corporate-level strategic decisions regarding: (1) at which
location(s)/market(s) to possess a property/properties, (2) which type(s) of hotels to
possess, (3) whether to affiliate with hotel brand(s), that is, whether to obtain brand(s) for
their properties, and with which brand(s) to affiliate, and (4) which operator(s)
(management company/companies) will be retained to operate the property/properties.
While the effects of a superior hotel location on the profitability have been well
recognized by hotel owners for a long time (e.g., Imperiale, 2002), previous research has
also suggested the performance of different hotel types may vary in different time periods.
In the lodging industry, properties are categorized into different types based on price and
service level, such as luxury, upscale, mid-scale, and economy (Stutts, 2001); full-service,
mid-scale, economy, all-suites with food and beverage (F&B), and all-suites without
F&B (O’Neill & Lloyd-Jones, 2002); and even more detailed categories such as luxury,
upper upscale, upscale, mid-scale with F&B, mid-scale without F&B, and economy
(Smith Travel Research, 2006). It has been reported that among the lodging REIT
companies, a group of hotel owners who own approximately 19 percent of the hotel
21
rooms in the United States, the ones concentrating on luxury and upscale full-service
hotels had experienced highest return rates during the REIT booming years including
1996 and 1997, because upscale full-service hotels had higher revenue per available room
(RevPAR) and occupancy rate than the mid-scale and economy properties did (Poutasse,
1997). Brady and Conlin’s study (2004) during 1991-1998 supports Poutasse’s
conclusion by revealing that hotels owned by REITs outperformed non-REIT hotels
because most of them were mid-scale and upscale ones. Gordon and McCarthy (1998)
also suggest that REIT companies focusing on luxury and upscale hotels might have the
least risk due to the least possibility of an overbuild problem compared to other hotel
types such as midscale without F&B and limited-service segments. However, during the
economic downturn exacerbated by September 11th, luxury hotels suffered the greatest
losses in revenue and market value, while economy hotels were affected less in 2001 and
2002 (O’Neill & Lloyd-Jones, 2002).
The performance differences across hotel types have caused more and more hotel
investors and owners to formulate appropriate strategies regarding investing in their
respectively favorite hotel type(s) (e.g., Kidd, 2006; Kish, 2006). It is suggested that
limited-service hotels are less affected by unfavorable economic environment than full-
service hotels because of their relatively lower fixed costs; while in a favorable economic
environment, limited-service hotels can be affected more quickly by the new supply than
full-service properties, because the development cycle of limited-service hotels is much
shorter (Imperiale, 2002). A recent study conducted by O’Neill and Mattila (2006)
supports this argument by revealing that the most profitable hotel type in 2003 was the
22
economy segment. Based on the findings in the literature, one could argue that, some
aggressive hotel owners seeking return maximization may like to acquire luxury and
upscale hotels if they foresee promising economic growth, some owners seeking risk
minimization may tend to acquire limited-service properties if they expect economic
downturns, while other owners may diversify their hotels in different segments to seek
balanced return and risk in the long-term. However, research is lacking for the topic of
hotel owner’s strategic decisions on their favorite hotel type(s).
Moreover, Corgel (2002) reported that, in the hotel investment community, the
conventional wisdom holds that superior return on hotel investment cannot occur without
brand affiliation and superior management. Among a number of benefits of brand
affiliation is the positive influence on hotel sales and profitability (e.g., Hayes &
Ninemeier, 2007). Literature also suggests a link between brand and hotel value
indicators such as ADR, occupancy, RevPAR, NOI, and hotel sale price (e.g., O’Neill &
Mattila, 2006; O’Neill & Xiao, 2006). However, the only empirical study focusing on the
effects of brand affiliation and hotel operator does not reveal a significant relationship
between investment return and the combination of management and brand affiliation
(Hanson, 1991). Hanson’s (1991) study on 65 mid-size full-service hotels concludes that
affiliating with a chain and engaging a management company did not lead to a significant
difference in hotel investment return, measured by the ratio of operating income to
replacement cost.
23
Furthermore, it is well agreed that the financial success of a hotel depends, in
large measure, on the quality and skill of its onsite operator (e.g., Green, 2006; Hayes &
Ninemeier, 2007; Higley, 2006). Hotel operators, or management companies, can be
classified in different ways. A common classification is first-tier and second-tier
operators, which also refers to branded managers and non-branded managers (e.g., Hayes
& Ninemeier, 2007; Sandman, 2003; Stutts, 2001). The first-tier operators, or branded
managers, are the hotel companies that operate hotels for owners using their respective
hotel brands, while the second-tier operators operate hotels but do not have a recognized
hotel brand. In the latter case, while most hotel owners choose to flag a franchisor’s
brand, a few hotel owners may elect to keep their hotels as independent (e.g., Beals &
Denton, 2004; Hayes & Ninemeier, 2007).
While hotel operators were created to satisfy the need for improving management
efficiencies by separating the ownership from operation, the interests of hotel owners and
the operators are not always consistent. A major cause of serious conflicts between the
two parties is the different financial criteria by which they assess the hotel’s performance:
While the hotel owners focus more on profitability, management companies concentrate
more on revenues, on which primary management fees are based (e.g., Eyster, 1997;
Hayes & Ninemeier, 2007). Historically, the management contracts between hotel owners
and operators heavily favored management companies. However, since the mid-1980s,
relative bargaining power began to shift to favoring the owners due to increasing
competition among operators, increasing owner sophistication and experience in the hotel
24
business, and consequently increasing transparency of operating information (e.g., Beals
& Denton, 2004; Eyster, 1996, 1997; Higley, 2006).
According to Beals and Denton (2004), and Eyster (1996, 1997), current trends on
owner’s influences on the operators can be reflected in the following two major aspects.
First, hotel owners are more actively engaging in asset management. It has been
recognized that the role of hotel asset managers is not only developing investment
strategies, but also selecting affiliated brands and operators, and monitoring ongoing
operation performance of the hotels. Although it is still the operator’s exclusive job of
running daily operations of the hotel, owners or their asset managers have gained
significant input in two major areas of operations: budgeting and personnel. Today, hotel
owners and their asset managers request regular financial reports from the operators,
evaluate and approve periodic budgeting and capital expenditure plans, have frequent
meetings with hotel general managers and other executives, constantly evaluate
properties’ marketing actions, and have the right to approve, disapprove, and even
request replacement of the hotel’s executive members. Second, the management-fee
structures in the management contracts are changing to favor hotel owners: Basic fee
percentages continue to decline, the emphasis on the incentive-fee portion has increased,
and the bases for incentive fees have shifted from being based on levels of income to
achieving a more challenging cash-flow level that reflects owner’s debt service needs and
return on equity. From the perspective of owner-operator relationship, hotel owners can
influence their hotels’ operators significantly through different asset management skills,
and many hotel owners have explicitly claimed that such capability of monitoring the
25
operators is an important core competence (e.g., Kidd, 2006; Strategic Hotel Capital,
2006).
To summarize, although hotel owners may not operate their hotels directly, they
can influence their properties indirectly through various strategies in choosing location(s),
segment(s), brand(s), and operator(s). Therefore, Hypothesis 2a is proposed to answer the
first part of Research Question 2:
Research Question 2 (partial): Can a hotel owner’s corporate effects on property
financial performance be attributed to the owner’s strategic decisions regarding
hotel location, segment, brand, and operator?
Hypothesis H2a: The financial performance of a hotel is associated with its owner’s
strategies regarding (1) location, (2) segment, (3) brand affiliation, and (4)
operator.
Specialization and Diversification Strategies of Hotel Owners
Since various alternatives regarding hotel location, type, brand, and operator are
available, hotel owners can choose to specialize in certain location(s), type(s), brand(s),
and/or operator(s), or to achieve diversification within the lodging industry. It has been
revealed that diversifying geographically and across the property types are the most
common diversification strategies in the commercial real estate market, including the
26
lodging industry (Brueggeman & Fisher, 2005; Kish, 2006). A real estate industry survey
indicates nearly 91 percent of investors who make systematic efforts to diversify their
portfolios vary the geographic locations of properties (Nelson & Nelson, 2003). Previous
studies on other types of commercial real estate have shown, however, geographic
diversification may reduce the value of publicly owned hotel owner companies. Bers and
Springer (1997) suggest that, when a real estate owner chooses to diversify, its average
costs may increase. More specifically, Capozza and Seguin (1999) find that the value
reduction is not because of diversified owners’ poor managerial performance, but due to
higher management, administrative, and interest expenses. In contrast, a geographical
focus or specialization strategy has been suggested to generate economies of scale,
because geographic concentration may allow certain real estate owners to dominate
others by achieving information efficiencies through a relatively larger market share than
the competition (Ambrose, Ehrlich, Hughes, & Wachter, 2000).
No research has been conducted specifically on the effect of lodging companies
and hotel owners’ geographic specialization/diversification strategies, in spite of the
suggestion that owning hotels in different locations may be beneficial (e.g., Berke, 2003;
Corgel & deRoos, 1997; Carl, 2006). However, Woods (2006) argues that owning hotels
in different locations may not be an effective diversification strategy. Instead,
diversifying hotel portfolio in different types of locations is the key for a successful
diversification strategy. It is suggested that the type of location can be classified based on
the population of the market, such as the top 25 markets, the second 25 markets, and the
other markets (Woods, 2006).
27
In addition, diversifying by hotel type is found in a number of hotel owners’
portfolios (Corgel & deRoos, 1997; Gordon & McCarthy, 1998). As previously discussed,
the performance of different hotel types may vary in different time periods, and
consequently hotel owners may choose to focus on certain type(s) of hotels or to diversify
across several hotel types based on their judgments regarding economic trends and
internal needs. However, remaining unknown is whether the corporate strategy regarding
the degree of hotel-type specialization/diversification influences the individual hotel’s
financial performance. Since different types of hotels may be affected by the external
environment to different degrees, it raises the question of whether the degree of a
corporate parent’s (i.e., a hotel owner’s) hotel-type specialization/diversification affects
the individual hotel’s financial performance.
Literature also suggests that hotel owners and investors may diversify brand and
operator in hotel properties. However, the relationships between
specialization/diversification strategy and brand affiliation and operator choice have not
been rigorously studied. While some REITs and private hotel owners claim that
specializing in certain brand(s) enables the hotels to gain competitive advantage, others
prefer to have a portfolio of different brands (e.g., Artusio, 2006; Baldo, 1994; Berke,
2003; Carl, 2006; Host Hotels and Resorts, 2006; Kidd, 2006; Kish, 2006). Similarly,
hotel owners’ preferences of the choice of hotel operator are mixed. Some hotel owners
believe that the operators have different strengths and weaknesses that fit different
locations and properties; consequently they prefer to have multiple, unrelated
management teams, each of which is chosen specifically for a particular hotel. However,
28
other owners favor working with a limited number of operators managing multiple
properties to reduce the administrative complexity and overhead costs (e.g., Artusio,
2006; Beals & Arabia, 1998; Eyster, 1997; Green, 2006; Higley, 2006; Kidd, 2006).
Regardless of the mixed opinions found in a large number of trade magazines and
conference presentations, the degree of the corporate-parent’s brand affiliation and
management company specialization/diversification strategies remain unknown. Hanson
(1991) suggests that the insignificant relationship between hotel investment return and
brand affiliation and management company engagement in his study may be caused by
limited sample size (65 hotels) and single hotel type (full-service), and consequently
further research on the linkage between hotel performance and brand affiliation and
management is needed.
In summary, literature suggests that hotel owners do choose to focus or diversify
their hotel portfolios by location, segment, brand and operator. However, there is no
consensus on whether specialization or diversification benefits or hurts the hotels. Since
both specialization and diversification strategies regarding hotel location, segment, brand,
and operator are common practices in the hotel investment community, a worthy
investigation is how these specialization/diversification strategies affect the hotel
properties. Taking a stance with the majority of the industry practitioners who suggest
that diversification rather than specialization benefits the performance of the hotels,
Hypothesis 2b is developed to answer the second part of Research Question 2:
29
Research Question 2: Can a hotel owner’s corporate effects on property financial
performance be attributed to the owner’s strategic decisions regarding hotel
location, segment, brand, and operator, as well as corporate specialization
strategies regarding hotel location, segment, brand, and operator?
Hypothesis H2b: The financial performance of a hotel is negatively related to its
owner’s degree of specialization regarding (1) location, (2) segment, (3) brand,
and (4) operator.
Strategy and Core Competence in the Field of Hospitality Management
As service industries started growing rapidly in the 1980s, studies regarding
strategies of hospitality organizations began to emerge. However, strategy and strategic
management are relatively new notions in hospitality research (Tse & Olsen, 1999).
Although several strategic issues including franchising have been partially studied in the
context of strategy, a review of major strategic management studies in the hospitality
industry indicates that most previous studies have focused on environmental scanning,
strategic planning, strategy formulation, and strategy-structure relationship, while there is
a lack of research on strategy implementation or realized strategies (Tse & Olsen, 1999).
Most importantly, little hospitality strategy research has been conducted on one of the
most important dependent variables of strategic management – financial performance
(Okumus, 2002; Tse & Olsen, 1999). Among 31 major strategy related articles in the
hospitality management field, most are descriptive or case studies; only four studies
30
adopted a survey approach, and none used financial data as a dependent variable (Tse &
Olsen, 1999).
Literature has pointed out that a significant gap exists between strategic
management research in general business administration and in the hospitality industry
(Okumus, 2002; Olsen, 2004; Tse & Olsen, 1999). It is suggested that, because service
industries are fundamentally different from manufacturing industries, many strategic
theories and models, which were primarily developed from studies on manufacturing
industries, may not hold in the field of hospitality management, and consequently may
mislead practitioners in the hospitality industry (Tse & Olsen, 1999; Olsen, 2004).
Therefore, re-studying the key strategic management concepts in the hospitality industry
and developing appropriate theories for hospitality strategic management are crucial.
In addition, core competencies have been studied by a few hospitality researchers.
Olsen, West, and Tse (1998) indicate that core competencies of a hospitality organization
are its processes, skills, and assets that enable it to achieve competitive advantage. Due to
the complex service-product mix of hotels, it is revealed that various sources may
contribute to the core competencies of hotel firms (Olsen et al., 1998). Specifically,
literature has suggested a number of hotel property-level and company-level
characteristics and capabilities as sources of hotel firm’s core competencies, such as
location, brand, facilities, employee, customer loyalty, market coverage, market share,
service quality, technology, leadership, systems and procedures, and organizational
culture (e.g., Dev et al., 2002; Olsen et al., 1998; Taylor, 2002). However, as criticized by
31
Olsen (2004) and Tse and Olsen (1999), hospitality research on the topic of core
competencies have suffered two significant limitations. First, the primary focus on core
competencies is on leadership and managerial capabilities but not on strategies, and
second, such research was drawn from either case-based or survey studies of industry
leaders. Consequently the results are primarily descriptive and survey-oriented
perceptions of industry leaders and/or the researchers, while no attempts have been made
to assess the relationships between core competencies and other strategy constructs, such
as financial performance. Therefore, there is a clear lack of rigorous and large-sample
research on strategy and its financial impact on hospitality organizations. Specifically,
Tse and Olsen (1999, p.368) propose that “it is believed that systematic, longitudinal
research on strategy and its impact on financial performance, as well as a larger sample,
may show some significant differences in hypothesis testing.”
A few recent studies have sought to compensate for some of the limitations. For
instance, based on relatively large sample sizes, several studies have revealed that hotel
firms’ and/or owners’ strategies regarding branding, franchising, and service may have
significant effects on hotel financial performance at both the corporate-level and the
property-level (O’Neill & Mattila, 2004; 2006; O’Neill, Mattila, & Xiao, 2006; O’Neill
& Xiao, 2006). However, there is no known comprehensive research that incorporates
and focuses exclusively on multiple hotel strategy and/or competence constructs.
As previously discussed, based on the RBV, corporate strategies may be
important resources of a firm’s core competencies. Therefore, this study proposes that the
32
hotel owner’s strategies related to hotel location, segment, brand affiliation and operator
can also be the candidates for the owner’s core competencies. To answer Research
Question 3 and to identify the core competencies of the owners whose hotels achieved the
best financial performance, Hypothesis 3a and 3b are developed:
Research Question 3: What are the core competencies of the best-performing hotel
owners?
Hypothesis H3a: The superior financial performance of the hotels owned by the best-
performing owners is associated with these owners’ strategies regarding (1)
location, (2) segment, (3) brand affiliation, (4) and operator.
Hypothesis H3b: The superior financial performance of the hotels owned by the best-
performing owners is negatively related to these owner’s degree of specialization
regarding (5) location, (6) segment, (7) brand, and (8) operator.
Moreover, to further investigate the effects of core competence, answers for
Research Question 4 are needed. Consequently, Hypothesis 4 is developed:
Research Question 4: For a particular hotel owner, do its core competencies
influence all the hotels of this owner equally? Or, do the effects of the owner’s
core competencies influence some hotels more or less than other hotels? If the
33
answer to the second question is yes, then, how do the effects of the core
competencies vary among this particular owner’s hotels?
Hypothesis H4: For a particular hotel owner, if this owner’s core competence is
identified as related to its superior strategy regarding hotel location, segment,
brand, or operator, such core competence has different effects on the financial
performance of the owner’s hotels with different (a) locations, (b) segments, (c)
brands, or (d) operators.
Summary of Literature
Upon examination of the related literature in this chapter, the following
conclusions are formed:
• Although corporate effect is an important theoretical concept in strategic
management, further research is needed to assess its existence and magnitude in
different industries.
• Corporate strategy is proposed to contribute to corporate effects, while there are
no established theories regarding the underlying sources of corporate effects.
Little research has been conducted in this regard.
34
• While financial performance at both the corporate-level and the business-unit-
level is a core dependent variable in strategic management research, hospitality
strategy research has failed to study the relationship between strategy and
financial performance. Rigorous, systematic, and large-sample research regarding
the concepts of strategy and core competencies is also lacking.
• In the hotel industry, conflicting views exist regarding the effects of hotel owner’s
specialization and diversification strategies about location, segment, brand
affiliation, and operator. However, no rigorous research has been conducted in
this regard.
• Based on the literature, eight corporate-level strategies have been identified as
potential sources of corporate effects and core competencies (location strategy,
segment strategy, brand strategy, operator strategy, location specialization
strategy, segment specialization strategy, brand specialization strategy, and
operator specialization strategy). To address the four research questions outlined
in Chapter I, these eight strategies are adopted as the focal independent variables
to develop the hypotheses regarding corporate effects and core competence in the
context of the lodging industry.
35
Chapter III
RESEARCH METHODOLOGY
This chapter first presents the research questions and hypotheses of this study.
The descriptions of the sample and the variables are then discussed. Finally, statistical
procedures and steps of data analysis are provided.
Research Questions
As discussed in Chapter I, this study seeks to address the following research
questions:
(1) Do corporate effects exist in the lodging industry?
(2) Can a hotel owner’s corporate effects on property financial performance be
attributed to the owners’ strategic decisions regarding hotel location, segment,
brand, and operator, as well as corporate specialization strategies regarding
hotel location, segment, brand, and operator?
(3) What are the core competencies of the best-performing hotel owners?
(4) For a particular hotel owner, do its core competencies influence all the hotels
of this owner equally? Or, do the effects of the owner’s core competencies
influence some hotels more or less than other hotels? If the answer to the
second question is yes, then, how do the effects of the core competencies vary
among this particular owner’s hotels?
36
Hypotheses
To address the above research questions, the following hypotheses are developed
and tested in this study:
H1: The financial performance of hotels owned by certain owners is superior to the
financial performance of hotels owned by other owners.
H2a: The financial performance of a hotel is associated with its owner’s strategies
regarding (1) location, (2) segment, (3) brand affiliation, and (4) operator.
H2b: The financial performance of a hotel is negatively related to its owner’s degree
of specialization regarding (1) location, (2) segment, (3) brand, and (4) operator.
H3a: The superior financial performance of the hotels owned by the best-performing
owners is associated with these owners’ strategies regarding (1) location, (2)
segment, (3) brand affiliation, (4) and operator.
H3b: The superior financial performance of the hotels owned by the best-performing
owners is negatively related to these owners’ degree of specialization regarding
(5) location, (6) segment, (7) brand, and (8) operator.
H4: For a particular hotel owner, if this owner’s core competence is identified as
related to its superior strategy regarding hotel location, segment, brand, or
operator, such core competence has different effects on the financial performance
37
of the owner’s hotels with different (a) locations, (b) segments, (c) brands, or (d)
operators.
Sample
The sample of the study is provided by Smith Travel Research (STR). STR is the
only organization that tracks hotel unit-level performance throughout the country, and it
is believed that most major hotel owners, if not all, provide information regarding
property financial performance to STR. Therefore, STR data are the most comprehensive
available in the industry.
The overall time frame of the study covers a three-year period between 2003 and
2005. These years are selected because they represent the most current data available. In
addition, this period has shown a significant recovery in hotel financial performance, and
compared to single year data, conducting the study over three years is expected to control
for the time/year factor.
To effectively test the proposed hypotheses, annual data regarding the following
variables is required for each hotel between 2003 and 2005: RevPAR, NOI, hotel age,
room price level, location (region, state, MSA, market), segment, brand affiliation,
operator, and owner (all these variables are discussed in the following section). While
STR’s original data set consisted of over 25,000 hotels, most lacked information
regarding one or more of these variables. Only a total of 2,012 hotels provided data
38
regarding RevPAR, number of rooms, hotel age, room price level, location (region, state,
MSA, market), segment, brand affiliation, operator, and owner in year 2003, 2004, and
2005. These 2,012 hotels (6,036 cases) form the base sample – Sample 1-A for this study.
Among the 2,012 hotels, 684 hotels also provided NOI information. To use the largest
available sample, Sample 1-B includes these 684 hotels (2,052 cases). Sample 1-B is used
to test the models in which the dependent variable is NOI per available room (NOIPAR)
(details regarding the variables and statistical models are provided in the following
sections of this chapter). Because this study involves analyses at multiple stages, different
data sets are created based on the 2,012 hotels and are used to test the hypotheses at
different stages. Details are provided in the data analysis section.
It should be noted that, to ensure confidentiality, the information regarding owner,
brand, and operator was coded by STR by assigning a unique number to each owner,
brand, and operator, while the actual names were not disclosed. However, STR provided
the specific information regarding segment, state, and region for this study. Since the
main interest of this study is on the overall effects of owner, brand, operator, and location
rather than on any specific owners, brands, operators, or locations, such a coding scheme
is believed to satisfy the purpose of this research.
Moreover, this research only focuses on the branded hotels in the United States
and does not include independent properties. It is reported that branded hotels represent
almost 75 percent of the lodging market, while independent properties represent the
remaining 25 percent (Turkel, 2006). Independent hotels are not be included in this study
39
because STR classifies all independent hotels as one single hotel segment, namely
“independent,” and technically treats them as one single brand. Previous research
suggests that classifying independent properties as a “brand of one” or a “segment of
one” without considering those properties’ actual prices and quality levels may influence
the effects of the other segments and brands on the financial performances of hotels
(O’Neill & Xiao, 2006). Since this study can only be feasible with data from STR,
excluding independent properties from the study is believed to improve the accuracy of
the statistical results.
Variables and Measures
Hotel financial performance
In this study, hotel property financial performance is operationalized as two
separate measures: RevPAR and NOIPAR. RevPAR data is provided by STR. As a
function of two important top-line financial indicators - average daily rate (ADR) and
occupancy rate (RevPAR = ADR x occupancy rate), RevPAR is a crucial performance
measure guiding the operating and investment decisions of hotel managers, investors and
owners (e.g., Corgel, 2002; Singh & Schmidgall, 2002). Consequently, RevPAR is the
most widely used indicator in recent studies on hotel performance (e.g., Canina, Enz, &
Harrison, 2005; Chung & Kalnins, 2001; Corgel, 2002; Ismail, Dalbor, & Mills, 2002;
Kalnins, 2005; Kim, Kim, & An, 2003). However, these studies, as well as most previous
research on hotel property performance in the literature of strategic management, have
40
examined only top-line financial indicators (e.g., ADR, occupancy rate, and/or RevPAR)
but not bottom-line indicators. Therefore, this study aims to compensate for this
limitation by examining the hotels’ operating performance with not only revenue
indicator (i.e., RevPAR) but also profit measure – NOI. NOI data is provided by STR,
and NOI per available room (NOIPAR) was calculated by dividing a hotel’s NOI by its
number of rooms. Similar to that RevPAR is favored over total rooms revenue to
represent a hotel’s revenue performance, NOIPAR is chosen to measure a hotel’s profit
performance when taking into consideration the hotel size, because larger hotels tend to
have higher revenues and NOIs than smaller hotels.
Overall corporate effects and ownership
Overall corporate effects are examined based on the ownership of the hotels. STR
provides the ownership information of the hotels. While the actual names of the hotel
owners are not available due to the strict confidentiality policy of STR, each hotel owner
is assigned a unique code so that it can be differentiated from the others. In the base
sample (Sample 1-A) consisting of 2,012 hotels, there are a total of 159 hotel owners,
including 106 owners among the 684 hotels that also provided NOI information.
Hotel Location
STR provides information regarding hotel location including (1) region, (2) state,
(3) Metropolitan Statistical Area (MSA) where a hotel is located, and (4) the market type
41
(whether a hotel is located in the top-25 markets, second-25 markets, or the other
markets). The 2,012-hotel base sample (Sample 1-A) includes 256 MSAs, 50 states and
Washington, DC, and nine regions as defined by STR, including New England, Middle
Atlantic, South Atlantic, East North Central, East South Central, West North Central,
West South Central, Mountain, and Pacific. It should be noted that, for the purpose of
classification, STR identifies Washington, DC in the scale of state, and therefore there are
a total of 51 states in the data. All four location classifications are examined in this study.
Hotel Segment
Because the chain scale developed by STR is well recognized and well regarded
in the industry, and this study relies on the data from STR, hotel segment is determined
based on the STR classifications. Specifically, according to STR, all hotels are
categorized into one of the following six hotel segments that are determined by hotel
brands’ system-wide average daily rate (ADR):
• Luxury: the brands whose system-wide ADRs are more than $195
• Upper Upscale: the brands whose system-wide ADRs are between $120
and $195
• Upscale: the brands whose system-wide ADRs are between $90 and $120
• Midscale with F&B: the brands that have F&B facilities and system-wide
ADRs are less than $90
42
• Midscale without F&B: the brands that do not have F&B facilities and
system-wide ADRs are greater than $60
• Economy: the brands that have system-wide ADRs less than $60
In the 2,012-hotel base sample (Sample 1-A), 250 are economy hotels, 664 are
midscale without F&B hotels, 282 are midscale with F&B hotels, 482 are upscale hotels,
291 are upper upscale hotels, and 43 are luxury hotels.
Brand Affiliation
Information regarding brand affiliation is provided by STR. Similar to the
ownership information, each individual hotel’s brand in the sample is represented by a
unique number but not the actual brand name. The base sample (Sample 1-A) represents
a total of 90 brands, including 52 brands of which at least one hotel also provided NOI
information.
Hotel Operator
Information regarding the operator of each hotel is also provided by STR in the
form of coded numbers but not the actual operators’ names. The base sample represents a
total of 195 operators, including 121 operators of which at least one hotel also provided
NOI information.
43
Specialization of Location, Segment, Brand, and Operator
Following Capozza and Seguin (1999), the measures of specialization adopt the
concept of Herfindahl indices and are developed based on hotel location, segment, brand,
and operator. As explained below, the higher levels of index scores indicate higher levels
of specialization or lower levels of diversification, while lower scores in the index show
lower degrees of specialization or higher degrees of diversification.
Location specialization: location is examined with four different variables (region,
state, MSA, and location type) in this study. For example, because the hotels in the base
sample are in 256 MSAs, I compute , where is the proportion of an owner’s
hotel rooms in each of the identified MSAs. Higher levels of specialization by MSA lead
to higher levels of scores in the index. For instance, if an owner only has a hotel(s) in one
MSA, this variable would be one or 100 percent, which indicates perfect specialization or
no diversification; if an owner equally diversifies all hotel rooms among the 256 MSAs,
this variable would be 0.0039 or 0.39 percent (equal to one divided by 256). Similarly,
the lowest possible degree of the state specialization variable is 0.0196 or 1.96 percent
(equal to one divided by 51), and the lowest possible degree of the region specialization
variable is 0.111 or 11.1 percent (equal to one divided by nine). In addition, following
Woods’ (2006) notion of classifying hotels into three location types (top-25 markets,
second 25-markets, and the other markets), the lowest possible degree of the market type
specialization is 0.333 or 33.3 percent (equal to one divided by three).
2256
1 llS∑ = lS
44
In the base sample, the region specialization degree ranges from 13.7 percent to
100 percent; the state specialization degree ranges from 5.59 percent to 100 percent; the
MSA specialization degree ranges from 2.80 percent to 100 percent, and the market type
specialization degree ranges from 34.27 percent to 100 percent.
Segment specialization: To measure hotel segment specialization, I
compute , where is the proportion of an owner’s hotel rooms in each of the six
hotel segments as defined by STR. Likewise, higher levels of specialization by hotel
segment lead to higher levels in the index. The degree of the segment specialization in the
base sample ranges from 20.27 percent to 100 percent.
26
1 ssS∑ = sS
Brand specialization: To measure hotel brand specialization in the base sample, I
computed , where is the proportion of an owner’s hotel rooms in each of the 90
brands. The degree of brand specialization in the base sample ranges from 9.23 percent to
100 percent.
290
1 bbS∑ = bS
Operator specialization: Similarly, to measure hotel operator specialization, I
compute , where is the proportion of an owner’s hotel rooms managed by each
of the 195 operators. The degree of the operator specialization in the base sample ranges
from 21.36 percent to 100 percent.
2195
1 ooS∑ = oS
Core Competence
45
Core competence is not an independent variable in the statistical models that are
presented in the data analysis section. Instead, in this study, a hotel owner’s strategies
regarding location, segment, brand affiliation, operator, location specialization, segment
specialization, brand specialization, and operator specialization are proposed as
candidates for the owner’s core competencies. The actual core competencies are
identified based on the statistical results related to these eight strategies. The details
regarding the identified core competences are presented in Chapter IV.
Control Variables
In addition to the previously discussed independent variables, literature has
suggested several other factors that may affect hotel financial performance, and
consequently, they need to be controlled in this study. First, strategic management
research indicates business-unit performance may vary by year (Bowman and Helfat,
2001). In the lodging industry, also widely recognized is that the performance of hotels
may be affected by owner size (measured as the number of rooms of the owner), hotel
size (measured as number of rooms of the hotel), and hotel age. Moreover, a hotel owner
may have concern for a hotel’s relative performance compared to the other hotels in a
particular market, and may favor investment in hotels at certain room price level(s) than
the ones at other price level(s). Consequently, the owner’s corporate strategies may be
affected by such preference. According to STR, each hotel is compared to the
competitors in its respective market and then is classified into one of the five price levels
based on this hotel’s actual ADR:
46
• Luxury: top 15 percent within the market
• Upscale: second 15 percent within the market
• Mid-Price: middle 30 percent of the market
• Economy: next 20 percent within the market
• Budget: lowest 20 percent within the market
To summarize, the effects of the following factors were controlled in this study:
year, owner size, hotel age, hotel size, and room price level.
Statistical Procedures
To answer the research questions and test the hypotheses, the following statistical
procedures are used with the SAS Package Version 8. First, literature has established that
variance components analysis (VCA) is the most appropriate statistical method to
examine corporate effects (Bowman & Helfat, 2001). As a technique used to apportion
variance in a continuous dependent variable across a number of independent variables,
VCA is commonly used in strategic management research involving comparisons of the
relative influence of various factors on firm performance (e.g., Ander & Helfat, 2003;
Chang & Hong, 2002; Chang & Singh, 2000; Crossland & Hambrick, 2007; McGahan &
Porter, 1997; Roquebert et al., 1996; Schmalensee, 1985; Rumelt, 1991). While previous
VCA studies employed either fixed-effect models (e.g., Schmalensee, 1985), or random-
effect models (e.g., Chang & Singh, 2000; Rumelt, 1991), or both (e.g., Crossland &
Hambrick, 2007; McGahan & Porter, 1997), this study employs random-effect models
47
estimated with the restricted maximum likelihood technique. This approach is suggested
to avoid potentially confounding effects caused by the order of entry of the independent
variables, which may associate with fixed-effect models and other estimation techniques
such as least squares (e.g., Chang & Hong, 2002; Crossland & Hambrick, 2007;
Roquebert et al., 1996).
Second, while random-effect VCA approach estimates the variances attributable
to the independent variables, it does not disclose whether each independent variable is
statistically significant. Therefore, several notable studies on corporate effects also
adopted fixed-effect models, in which the independent variables were alternatively
treated as fixed factors, to supplement the random-effect VCA models and to estimate the
statistical significances of the independent variables (e.g., McGahan & Porter, 1997;
Rumelt, 1991). Similarly, this study employs the procedure of fixed-effect General Linear
Model (GLM) to study the significance of the eight proposed corporate strategies. As
further explained in the following sections, the results of this statistical analysis show the
existence of corporate effects on the hotels owned by different owners.
In addition, because this research involves individual “case studies” on several
best-performing hotel owners, nonparametric Kruskal Wallis Tests are adopted to
compare the hotels of one single hotel owner, and Tukey’s Multiple Comparison Tests
are followed in the cases where statistical significances were detected among the hotels
of the hotel owner. The following section provides further explanations regarding how
48
the previously discussed statistical procedures were employed at the different stages of
the data analysis.
Data Analysis
To test the four hypotheses of the study, data was analyzed in the following five
steps:
Step One
Hypothesis H1 aims to answer the question of whether systematic corporate
effects exist among the hotels owned by different owners. Therefore, the following
Model (1) and (2) are tested with GLM and VCA procedures to show the existence and
the degree of importance of the effects of owners on the financial performance of hotels.
In these two models, R, the owner affiliation, is the focused main effect:
εμ ++++++= Rznaypr (1)
εμ ++++++= Rznaypn (2)
where is the hotel RevPAR, rp
is the hotel NOIPAR, np
u is the constant,
y is the year effects,
a is the hotel age effects,
n is the hotel size effects,
49
z is the room price level effects,
R is the owner affiliation, and
ε is the error term.
Sample 1-A, the base sample that consists of 6,036 cases (2,012 hotels) is used to
test Model (1), in which RevPAR is the dependent variable. Sample 1-B including 2,052
cases (684 hotels) is used to test Model (2) with NOIPAR as the dependent variable. It
should be noted that, because the control variable “owner size” is indeed a characteristic
of the owner and consequently its effects should be reflected by the overall owner effects,
owner size is not tested in this model for model simplification. However, it will be
included in the following statistical models.
Step Two
Hypotheses H2a and H2b explore whether or not the previously determined eight
strategies of the hotel owners contribute to the corporate effects of the owners. The
following Model (3) and (4) are tested with GLM and VCA procedures. The results of
this step reveal, among the eight corporate strategies, which strategies are the sources of
corporate effects of the hotel owners. That is, among the eight independent variables, the
ones showing statistical significance (from the GLM procedure) are identified as the
sources of corporate effects, and will also be proposed as potential candidates for firm
core competencies. Moreover, the strength and magnitude of each source of corporate
50
effects are precisely estimated in the results of the VCA procedure as the variance
percentage values associated with the respective independent variables.
εμ ++++++++++++++= DoDbDsDlobslzmnaypr (3)
εμ ++++++++++++++= DoDbDsDlobslzmnaypn (4)
where is the hotel RevPAR, rp
is the hotel NOIPAR, np
u is the constant,
y is the year effects,
a is the hotel age effects,
n is the hotel size effects,
m is the owner size effects,
z is the room price level effects,
l is the location strategy effects,
s is the segment strategy effects,
b is the brand strategy effects,
o is the operator strategy effects,
Dl is the location specialization strategy effects,
Ds is the segment specialization strategy effects,
Db is the brand specialization strategy effects,
Do is the operator specialization strategy effects, and
ε is the error term.
51
Similar to Step One, Model (3) with RevPAR as the dependent variable is tested
with Sample 1-A, and Model (4) with NOIPAR as the dependent variable is tested with
Sample 1-B.
Step Three
While the statistical results of Step Two propose the candidates for core
competencies for all hotel owners, this study aims to identify which of these candidates
are indeed the actual core competencies of the best-performing hotel owners. Therefore,
it is necessary to first identify, among all the hotel owners, which owners are the best and
which ones are the “worst” in terms of their hotels’ financial performance.
Due to the fact that hotel segments (i.e., economy, midscale without F&B,
midscale with F&B, upscale, upper upscale, and luxury) are classified based on brands’
system-wide ADRs, hotel segment is clearly related to a hotel’s ADR and consequently
RevPAR (which is shown in the descriptive statistical results presented in Chapter IV).
Moreover, literature indicates that segment is associated with NOI as well (e.g., O’Neill
& Mattila, 2006). Consequently, since most hotel owners have hotels in more than one
segment, direct RevPAR and NOI comparisons between hotels in different segments
would not be appropriate. Therefore, to make the financial performance of the hotels
owned by all hotel owners comparable, the values of RevPAR and NOIPAR are
standardized by owner, and the standardized mean value of each hotel owner indicates
the overall performance of all hotels owned by this particular owner.
52
Based on the standardized mean scores, two rankings are established: one on
RevPAR and the other on NOIPAR. However, the two ranks are not identical: some hotel
owners have hotels only with superior RevPAR levels, while the hotels of some other
owners only achieved superior NOIPAR levels. Therefore, this study uses a combination
of both “RevPAR” and “NOIPAR” as the selection criteria for identifying the best-
performing hotel owners. That is, only the hotel owners whose hotels perform well in
both RevPAR and NOIPAR are chosen as members of the best-performing group.
Specifically, the hotel owners of the top 25 percent of each ranking list are first identified.
The two lists are then matched, and only the hotel owners that are in both lists are chosen.
Such procedure results in a total of sixteen best-performing owners, which have a total of
156 hotels (468 cases).
A similar procedure is repeated to identify the “worst” hotel owners, which are
also measured by the standardized mean values of their hotels’ RevPAR and NOIPAR.
Sixteen “under-performing” hotel owners are selected by matching the bottom 25 percent
of the RevPAR and NOIPAR ranking lists. These sixteen hotel owners have a total of 137
hotels (411 cases). .
To identify the core competencies of the best-performing hotel owners, a sub-
sample – Sample 2 is created to include the sixteen best-performing owners and the
sixteen under-performing owners identified previously. Consequently, Sample 2 consists
of a total of 32 hotel owners with 293 hotels (879 cases). All hotels in Sample 2 provided
both RevPAR and NOIPAR information.
53
Step Four
Hypotheses H3a and H3b are tested on Models (3) and (4), in which RevPAR or
NOIPAR are the dependent variables, and the proposed eight strategies are the
independent variables. Similar to Step Two, GLM and VCA procedures are employed on
Sample 2. The results of GLM reveal which of the eight independent variables are
statistically significant, and the results of VCA procedure indicate the respective
percentage of the total variance explained by these independent variables. Because all the
better-performing hotels in this sub-sample are owned by the best sixteen owners, the
independent variables that explain a significant portion of the total variance are deemed
as core competencies of these sixteen owners. The details regarding the identified core
competences are presented in Chapter IV.
Step Five
After the core competencies of the top sixteen hotel owners are identified, this
study goes one step further to investigate whether the identified core competencies of the
owners influence all hotels of a particular owner equally or differently. Particularly, when
the owners’ core competencies are identified as being related to specialization (or
diversification) strategies (i.e., location specialization/diversification strategy, segment
specialization/diversification strategy, brand specialization/diversification strategy,
and/or operator specialization/diversification strategy), the interpretations of these core
competencies would be straightforward based on the t values of these continuous
54
variables: the owners’ core competencies are their superior capabilities of specializing in
or diversifying across certain locations, segments, brands, and/or operators. However, if a
hotel owner’s core competence is its expertise in choosing specific location(s),
segment(s), brand(s), and/or operator(s) for its properties and t values are not informative
for these categorical variables, then as proposed in Research Question 4, an important
and interesting question would be whether such core competencies have equal or
different effects on all hotels owned by this particular owner.
To answer Research Question 4, Hypotheses H4 is tested to investigate whether
or not an owner’s expertise in choosing location(s), segment(s), brand(s), and/or
operator(s) benefits all hotels of this owner equally. Specifically, the top six best-
performing hotel owners (measured in both RevPAR and NOIPAR as previously
discussed) are chosen, and six sub-samples (Sample 3 – 8) are created, each of which
consists of only the hotels of one hotel owner. Then, the following procedures are
repeated on the hotels of each of the six best-performing owners (Sample 3 – 8):
First, nonparametric Kruskal Wallis Tests are conducted based on the identified
core competencies. Each core competence identified in Step Four serves as the
independent variable, and RevPAR and NOIPAR is the respective dependent variable.
The results, shown as the Chi-square scores, reveal whether this core competence (the
owner’s expertise in choosing segment, location, brand, and/or operator) has equal
influences on all hotels of this particular owner. The Kruskal Wallis Test is repeated on
each identified core competence.
55
Second, if significant differences are detected by the Kruskal Wallis Tests,
Tukey’s Multiple Comparison Tests are followed to investigate the exact differences –
between which groups (the levels of the identified core competencies, i.e., segments,
locations, brands, and operators) are the differences. The results disclose how the
particular hotel owner’s core competencies in choosing segment(s), location(s), brand(s),
and/or operator(s) have different influences on different segment(s), location(s), brand(s),
and/or operator(s). Detailed explanations and results are fully presented in Chapter IV.
Summary
This study examines corporate effects on hotel financial performance with a
secondary data provided by STR. In this chapter, research questions and hypotheses are
presented, sample and variables are described, and data analysis techniques and
procedures are outlined. Because this study aims to answer four research questions at
different levels, four hypotheses were tested with a five-step data analysis procedure. To
avoid the potential confusion due to different techniques employed in different data
analysis steps, Table 1 summarizes the relative research questions, hypotheses, and
statistical techniques in each of the five steps.
56
Table 1. Data Analysis Procedures
Step Research Question
Hypothesis Purpose Sample Statistical Methods
1
Research Question 1
H1
Examining the existence of owner effects – systematic corporate effects among hotel owners
Sample 1-A and Sample 1-B
GLM and VCA
2 Research Question 2
H2a and H2b
Testing which of the eight strategies are the sources of corporate effects
Sample 1-A and Sample 1-B
GLM and VCA
3 ---- ---- Identifying the top- and bottom hotel owners to form a new sample consisting of only the top- and bottom-ten-percent hotel owners
Sample 1-A and Sample 1-B
----
4 Research Question 3
H3a and H3b
Iidentifying the core competencies of the sixteen best performing owners
Sample 2 GLM and VCA
5 Research Question 4
H4 Investigating (1) whether or not the identified core competencies of a particular owner influence all of its hotels equally or differently; and (2) if differently, how do the effects of the core competencies vary among this owner’s hotels
Sample 3-8 Kruskal Wallis Tests and Tukey’s Multiple Comparison Tests
57
Chapter IV
RESULTS
This chapter presents results and findings of the statistical analyses performed to
investigate the four research questions of the study. Following the five data analysis steps
discussed in Chapter III, this chapter is divided into six sections:
• Sample characteristics
• Effects of owner – Testing Hypothesis H1
• Effects of corporate strategies – Testing Hypothesis H2
• Determination of the top and bottom hotel owners
• Core competencies of hotel owners – Testing Hypothesis H3
• Effects of core competencies – Testing Hypothesis H4
Sample Characteristics
As discussed in Chapter III, a total of 2,012 hotels in the STR database provided
data regarding RevPAR and all independent variables and control variables (i.e., hotel
sizes, hotel age, room price level, location [region, state, MSA, market], segment, brand
affiliation, operator, and owner) in years 2003, 2004, and 2005. Therefore, they are
selected to form the base sample (Sample 1-A), which consists of 6,036 cases. In addition,
Sample 1-B, a sub-sample of Sample 1-A, is created to include only the 684 hotels (2,052
cases) that also provided NOI information. Descriptive statistics for Sample 1-A and 1-B
58
are presented in Table 2, and the correlations among the continuous independent
variables are shown in Table 3.
Table 2. Descriptive Statistics of Sample 1-A and Sample 1-B
Sample 1-A Sample 1-B N N Owner 159 106 Hotel 2012 684 Independent Variable
Segment 6 6 Brand 90 68 Operator 195 121 Region 9 9 State 51 49 MSA 256 186 Market type 3 3 Mean S.D. Mean S.D. Segment Specialization 0.57 0.17 0.55 0.19 Brand Specialization 0.34 0.19 0.33 0.21 Operator Specialization 0.84 0.23 0.88 0.19 Regional Specialization 0.34 0.23 0.49 0.30 State Specialization 0.23 0.23 0.33 0.29 MSA Specialization 0.16 0.18 0.22 0.21 Market Type Specialization 0.53 0.18 0.57 0.20
Dependent variable
RevPAR 58.20 30.51 67.57 38.58 NOIPAR 10754.38 9219.84 10754.38 9219.84
59
60
In addition, because segment information is provided by STR and hotel RevPAR
and NOIPAR vary significantly by segment, Table 4 presented the mean RevPAR and
NOIPAR values by segment. Since Sample 1-B only consists of all hotels that provided
NOI data in Sample 1-A, the NOIPAR values are identical for both samples.
Table 4. Mean RevPAR and NOIPAR by Segment
Sample 1-A Sample 1-B Segment Hotel RevPAR NOIPAR
Hotel RevPAR NOIPAR
Luxury 43 147.60 29,179.42
34 155.44 29,179.42
Upper Upscale 291 82.35 14,955.62
173 86.48 14,955.62
Upscale 482 67.82 9,955.33
151 68.01 9,955.33
Midscale w/ F&B 282 48.58 7,907.86
70 55.75 7,907.86
Midscale w/o F&B 664 49.66 7,215.06
220 48.94 7,215.06
Economy 250 30.07 3,910.09
36 29.94 3,910.09
Total 2,012 58.20 10,754.38
684 67.57 10,754.38
Moreover, since hotel segment is classified by STR based on brands’ system-wide
ADRs, each hotel brand can only be included in one segment. While brand names are not
available as discussed previously, the brands within each segment do differ by RevPAR
and NOIPAR. Table 5 presents the comparisons between the brands with the highest and
lowest average RevPAR and NOIPAR values of each segment.
61
Table 5. Brand Comparison within Segment
Sample 1-A Sample 1-B Brand RevPAR Hotel Owner NOIPAR Hotel Owner
Luxury Brand 1 271.30 5 2 64497.97 3 2Brand 2 91.95 1 1 4872.97 1 1
Upper Upscale Brand 1 113.38 30 11 24212.35 24 9Brand 2 66.97 24 13 8102.43 13 7
Upscale Brand 1 78.08 58 33 13729.81 7 12Brand 2 62.28 5 5 4541.14 1 1
Midscale w/ F&B Brand 1 76.64 3 1 12470.75 3 1Brand 2 45.53 10 7 905.45 2 2
Midscale w/o F&B Brand 1 65.64 38 24 10185.89 8 7Brand 2 30.18 5 5 2404.64 2 2
Economy Brand 1 40.63 20 4 6138.08 8 3Brand 2 21.33 3 2 1241.23 2 1
Note: 1. Brand 1 represents the brand with the highest RevPAR and NOIPAR within its
respective segment, and Brand 2 represents the brand with the lowest RevPAR and NOIPAR within its respective segment.
2. Due to the different sizes of Sample 1-A and Sample 1-B, the brand with the highest/lowest average RevPAR may not necessarily be the same brand with the highest/lowest NOIPAR within the segment.
Effects of Owner
Testing Hypothesis H1: The financial performance of hotels owned by certain owners
is superior to the financial performance of hotels owned by other owners.
The purpose of Hypothesis H1 is to explore whether the hotel owner is an
important factor influencing the financial performance of their hotels. Hypothesis H1 is
62
tested on Sample 1-A (RevPAR as the dependent variable) and Sample 1-B (NOIPAR as
the dependent variable). Results of fixed-effect GLM procedure are presented in Table 6,
which clearly show that the owner is a statistically significant factor in both samples
(F=13.27, p<0.001; F=3.28, p<0.001). Moreover, the results of the random-effects VCA
procedure, presented in Table 7, reveal that the owner explains the largest portion of
variance in hotel RevPAR and NOIPAR (71.54 percent and 40.74 percent, respectively).
Therefore, Hypothesis H1 is supported.
Table 6. Effects of Owner - General Linear Model
Sample 1-A Sample 1-B
Model (1) a b
DV = RevPAR Model (2) DV = NOIPAR
Variable df F df F Year 2 97.55*** 2 14.74*** Hotel Age 1 8.42** 1 10.25** Hotel Size 1 4.92* 1 38.62*** Room Price Level 4 304.73*** 4 59.98*** Owner 158 13.27*** 105 3.28***
Note: * p<0.05; ** p<0.01; *** p<0.001.
Table 7. Effects of Owner – Variance Components Analysis
Sample 1-A Sample 1-B DV = RevPAR DV = NOIPAR Variable Variance Percentage Variance Percentage Year 1.10% 0.93% Age 4.83% 20.11% Hotel Size 7.14% 23.77% Room Price Level 5.62% 2.58% Owner 71.54% 40.74% Error 9.77% 11.86% Total 100.00% 100.00%
63
In addition, Table 8 presents the results of an additional GLM procedure, in which
the influence of the owner is re-examined after taking into consideration of the effects of
the hotel location, segment, brand and operator. It is not surprising that all these four
additional variables are statistically significant because, as discussed earlier, they are
important strategies adopted by hotel owners. Because STR classifies hotel segment
based on brands’ system-wide ADRs, each hotel brand can only be included in one
segment. Therefore, the independent variable “brand” is nested within hotel segment in
both statistical models.It should be noted that,because the variable “location” has four
different measures (region, state, MSA, and market type), the model is repeatedly tested
four times with only one location variable included in the model each time.
Table 8: Effects of Owner (Controling for Location, Segment, Brand, and Operator) - General Linear Model Sample 1-A Sample 1-B
Model (3) a
DV = RevPARModel (4) b
DV = NOIPARVariable df F df F Segment 5 157.92*** 5 34.14*** Brand (nested within Segment) 73 11.93*** 52 9.95*** Operator 182 6.77*** 112 1.98***
Location Variable Region 8 82.29*** 8 20.55*** State 50 33.42*** 48 9.63*** MSA 255 7.70*** 179 3.53*** Market-Type 2 26.50*** 2 5.78**
Owner 158 10.68*** 104 7.31*** Control Variable Year 2 158.87*** 2 20.14*** Age 1 31.01*** 1 22.20*** Hotel Size 1 8.46** 1 80.01*** Room Price Level 4 133.86*** 4 28.54***
Note: * p<0.05; ** p<0.01; *** p<0.001.
64
The results of the corresponding VCA procedure, presented in Table 9, clearly
show that, a hotel owner’s strategies regarding its hotels’ location, segment, brand, and
operator do contribute to the owner’s corporate effects because they all explain some
variance in hotel RevPAR and NOIPAR. Moreover, it is indicated that additional
strategies of the owner may also have influence on the performance of its hotels, because
these four strategies could not fully explain the variances in RevPAR and NOIPAR
attributable to the owner, although such variances are reduced from 71.54 percent and
40.74 percent (when these four strategies are not taken into consideration) to 21.39
percent and 18.68 percent (after taking into account these four strategies), respectively.
These results support the notion in the lodging industry that hotel owners do implement
multiple strategies to influence their hotels. The results presented in the next section show
how a hotel owner’s corporate strategies with regard to hotel location, segment, brand,
operator, and the degrees of specialization regarding location, segment, brand, and
operator could collectively affect its hotels’ financial performance.
65
Table 9. Effects of Owner (Controlling for Location, Segment, Brand, and Operator) – Variance Components Analysis Sample 1-A Sample 1-B DV = RevPAR DV = NOIPARVariable Variance Percentage Variance Percentage
Segment 33.23% 19.96% Brand (nested in Segment) 11.21% 26.52% Operator 5.60% 3.92%
Location Variable Region 3.66% 4.30% State 1.19% 2.51% MSA 2.28% 3.18% Market Type 0.61% 0.44%
Owner 21.39% 18.68%
Control Variable Year 0.64% 0.73% Age 0.91% 0.92% Hotel Size 1.28% 0.88% Room Price Level 4.81% 5.23% Error* 17.27% - 21.32% 18.86% - 22.72% Total 100.00% 100%
Note: *Error varies due to different variances attributed to different location variables.
Effects of Corporate Strategies
Testing Hypotheses H2a and H2b:
H2a: The financial performance of a hotel is associated with its owner’s strategies
regarding (1) location, (2) segment, (3) brand affiliation, and (4) operator.
H2b: The financial performance of a hotel is negatively related to its owner’s degree of
specialization regarding (1) location, (2) segment, (3) brand, and (4) operator.
66
Hypotheses H2a and H2b are formulated to investigate whether the owner effects
on property financial performance can be attributed to the hotel owners’ strategic
decisions regarding hotel location, segment, brand, and operator, as well as corporate
specialization strategies regarding hotel location, segment, brand, and operator.
Sample 1-A is tested with RevPAR as the dependent variable, and Sample 1-B is
tested with NOIPAR as the dependent variable. The results of the GLM analysis are
presented in Table 10. Seven of the eight proposed strategies are statistically significant
in both samples. The only insignificant factor in both samples is the location (state)
specialization strategy (F=0.3, p>.05; F=0.43, p>.05). This suggests that neither
diversifying across states nor focusing on certain states have effects on hotel financial
performance. In addition, specialization by region is not significantly related to hotel
NOIPAR (F=1.63, p>0.05). Therefore, H2a - (1), - (2), - (3), and - (4) are fully supported.
Regarding H2b, H2b - (3) and - (4) are also supported because the t values of brand
specialization and operator specialization indicate negative relationships between the
degree of both specializations and hotel financial performance. However, the effects of
segment specialization as well as location (MSA) and location (market-type)
specializations are not in the expected direction. Their t values suggest that they are
negatively related to hotel financial performance: As a hotel owner specializes in less
segments/MSAs/market types, the RevPAR and NOIPAR of its hotels tend toincrease.
Therefore, an owner’s strategies of segment specialization and location (i.e., MSA and
market type) specialization actually benefit its hotels’ financial performance. H2b - (1)
and - (2) are not supported.
67
Table 10: Effects of Corporate Strategies - General Linear Model
Sample 1-A Sample 1-B
Model (3) a
DV = RevPARModel (4) b
DV = NOIPARVariable df F t df F t Segment 5 143.53*** 5 26.83*** Brand (nested within
Segment) 73 12.52*** 52 10.88*** Operator 182 6.82*** 112 2.18*** Segment Specialization 1 25.67*** 5.07 1 22.444*** 4.74 Brand Specialization 1 36.99*** -6.08 1 37.50*** -6.12 Operator Specialization 1 5.07* -2.25 1 4.97* -2.23 Location Variable Region 8 83.07*** 8 19.37*** State 50 36.33*** 48 10.18*** MSA 255 7.36*** 179 3.42*** Market-Type 2 28.57*** 2 4.88** Region Specialization 1 6.5* 2.55 1 1.63 1.28 State Specialization 1 0.3 -0.55 1 0.43 0.65 MSA Specialization 1 10.64** 3.26 1 5.99* 2.45 Market-Type
Specialization 1 74.36*** 8.62 1 19.89*** 4.46 Control Variable Year 2 147.69*** 2 19.37*** Age 1 17.94*** 1 6.73** Hotel Size 1 22.64*** 1 98.25*** Owner Size 1 0.44 1 0.09 Room Price Level 4 138.69*** 4 32.43***
Note: * p<0.05; ** p<0.01; *** p<0.001.
More importantly, Table 11 shows the relative importance of all these statistically
significant strategies with the results of the VCA procedure. Similarly, the model is
repeatedly tested four times with only one location variable is included in the model each
time, and their relative variance percentages are obtained accordingly when holding all
other variables consistent in the model.
68
The results show that segment explains the largest portion of variance in hotel
RevPAR (37.63 percent), followed by brand specialization (17.32 percent) and brand
(12.59 percent). Operator, location (region and MSA), location (market-type)
specialization, and the control variable “room price level” also contribute to explaining
the variance of RevPAR, while the other factors have little effects on RevPAR.
Regarding the effects on NOIPAR, segment, brand, and brand specialization are still the
three most important factors, but the order is changed: Brand specialization is the number
one predictor (27.27 percent), followed by brand (20.47 percent) and segment (16.98
percent). Except the location (market-type) specialization strategy and control variable
“price level,” the others contribute little to the variance in NOIPAR. Based on the
significance of the strategies, all eight strategies can be deemed as candidates for core
competencies of hotel owners, while their predicting power vary considerably.
69
Table 11. Effects of Corporate Strategy – Variance Components Analysis
Sample 1-A Sample 1-B DV = RevPAR DV = NOIPARVariable Variance Percentage Variance Percentage Segment 37.63% 16.98% Brand (nested in Segment) 12.59% 20.47% Operator 4.74% 1.92% Segment Specialization 1.77% 1.18% Brand Specialization 17.32% 27.27% Operator Specialization 0.11% 1.05% Location Variable Region 3.07% 2.32% State 1.21% 2.60% MSA 3.52% 2.96% Market Type 0.31% 0.28% Region Specialization 0.50% 0.00% State Specialization 0.00% 0.00% MSA Specialization 0.32% 2.38% Market Type Specialization 6.68% 10.08% Control Variable Year 0.70% 0.61% Age 0.00% 0.00% Hotel Size 0.00% 0.00% Owner Size 0.00% 0.00% Room Price Level 5.48% 6.09% Error* 12.68% - 18.46% 14.08% - 22.12% Total 100.00% 100%
Note: *Error varies due to different variances attributed to different location variables.
70
Determination of Top and Bottom Hotel Owners
To investigate which of the candidates for core competencies, as indicated in the
previous section, are indeed the actual core competencies of the best-performing hotel
owners, a new sample, Sample 2, is created. The hotel owners are ranked, based on the
standardized mean scores of RevPAR and NOIPAR of their hotels, and then the two
rankings are matched. The sixteen owners that are in both lists’ top 25 percent category
are identified, and these top sixteen owners whose hotels performed well (measured in
both RevPAR and NOIPAR) are selected to form the best-performing owner group,
which includes 156 hotels. Similarly, the sixteen owners that are in both rankings’ bottom
25 percent are chosen to form the under-performing owner group, which consists of 137
hotels, because the hotels of those sixteen owners had lowest standardized RevPAR and
NOIPAR values during the study period. By combining the top and bottom hotel owners,
Sample 2 is composed of a total of 32 hotel owners with 293 hotels (879 cases), all of
which provided both RevPAR and NOIPAR data. The average mean values of RevPAR
and NOIPAR of the top sixteen hotel owners are $80.15 and $14,430, respectively, which
are significantly higher than the RevPAR and NOIPAR of the bottom sixteen owners
($37.14 and $8,172, respectively). Table 11 shows the respective ranks of the 32 hotel
owners in the RevPAR and NOIPAR lists.
71
Table 12: RevPAR and NOIPAR Ranking of Hotel Owners
Owner ID Number of Hotels
Number of Cases
Rank of Standardized RevPAR
Rank of Standardized NOIPAR
1 8 24 2 1 2 5 15 3 21 3 10 30 4 6 4 8 24 5 2 5 11 33 10 9 6 8 24 11 20 7 14 42 13 7 8 5 15 14 16 9 3 9 15 12 10 30 90 16 5 11 8 24 18 15 12 11 33 19 4 13 5 15 20 25 14 8 24 22 19 15 14 42 26 22 16 8 24 29 23 Sub-total 156 468 17 18 54 118 91 18 3 9 121 106 19 9 27 134 96 20 6 18 135 92 21 25 75 140 100 22 6 18 143 94 23 5 15 145 105 24 11 33 148 103 25 3 9 149 97 26 8 24 150 90 27 4 12 151 93 28 14 42 152 102 29 9 27 153 95 30 5 15 155 98 31 5 15 157 101 32 6 18 159 104 Sub-total 137 411 Total 293 879
Note: 159 hotel owners provided RevPAR data, while NOI information is only available from 106 owners. Therefore the 159th rank is the lowest in the RevPAR list and the 106th rank is the lowest in the NOIPAR list.
72
Core Competencies of Hotel Owners
Testing Hypotheses H3a and H3b:
H3a: The superior financial performance of the hotels owned by the best-performing
owners is associated with these owners’ strategies regarding (1) location, (2)
segment, (3) brand affiliation, and (4) operator.
H3b: The superior financial performance of the hotels owned by the best-performing
owners is negatively related to these owners’ degree of specialization regarding
(1) location, (2) segment, (3) brand, and (4) operator.
Hypotheses H3a and H3b are tested in order to identify which of the eight
strategies are actual core competencies of the sixteen best-performing hotel owners in
Sample 2. As shown in Table 13, the results of fixed-effect GLM analysis on Sample 2
are similar to the results drawn from Samples 1-A and 1-B. All strategies except the
operator specialization have shown statistical significance, and the directions of the
specialization strategies are consistent with the results of Samples 1-A and 1-B: Negative
relationship is found between brand specialization and hotel RevPAR and NOIPAR,
while positive relationships exist between segment as well as location (region, state,
MSA, and market type) specializations and hotel financial performance. Therefore,
hypotheses H3a - (1), - (2), - (3), - (4), and H3b - (3) are supported, while H3b - (1), (2),
and - (4) are not supported.
73
Table 13: Core Competence of Hotel Owners –General Linear Model
Sample 2 Sample 2
Model (3) a
DV = RevPAR Model (4) b
DV = NOIPAR Independent Variable df F t df F t Segment 5 26.32*** 5 13.18*** Brand (nested in
Segment) 41 24.89*** 41 10.82*** Operator 49 10.86*** 49 6.00*** Segment Specialization 1 7.65*** 2.77 1 4.81** 2.19 Brand Specialization 1 12.50*** -3.54 1 11.99*** -3.46 Operator Specialization 1 0.05 0.22 1 0.37 -0.61 Location Variable Region 8 21.60*** 8 4.61*** State 39 10.27*** 39 3.39*** MSA 89 8.90*** 89 3.72*** Market Type 2 6.97*** 2 3.35** Region Specialization 1 4.46* 2.11 1 6.62*** 2.57 State Specialization 1 46.16*** 6.79 1 6.12*** 2.47 MSA Specialization 1 14.17*** 3.76 1 7.81*** 2.79 Market-Type
Specialization 1 32.83*** 5.73 1 9.04*** 3.01 Control Variable Year 2 49.09*** 2 18.89*** Age 1 36.09*** 1 11.40** Hotel Size 1 16.27*** 1 18.63*** Owner Size 1 1.17 1 0.96 Room Price Level 4 18.53*** 4 10.01***
Note: * p<0.05; ** p<0.01; *** p<0.001.
While the statistical significance of the eight strategies found in the GLM model
is expected, this study is more interested in the relative importance of these strategies.
Table 14 shows the variance percentages partitioned into each of the strategies through
the VCA procedure. Similar to the results drawn from Samples 1-A and 1-B, segment,
brand, and brand specialization are the three most important corporate strategies
74
influencing both hotel RevPAR and NOIPAR. However, two noticeable differences are
detected between the results of Sample 2 and Samples 1-A and 1-B. First, the variance in
hotel performance explained by operator has increased from 4.74 percent in Sample 1-A
to 10.76 percent in Sample 2 related to RevPAR, and increased from 1.92 percent in
Sample 1-B to 10.50 percent in Sample 2 related to NOIPAR. Second, most location-
related measures (i.e., region, state, MSA, region specialization, state specialization, and
MSA specialization) explain a much larger portion of the variance in hotel financial
performance in Sample 2 than in Samples1-A and 1-B. Most noticeably, the variances
attributable to the MSA and MSA specialization strategies have increased from 2.96
percent and 2.38 percent, respectively, in Sample 1-B to 10.14 percent and 10.46 percent
in Sample 2. These results suggest that the hotel performance differences associated with
the owners’ operator and location choices become more distinct in Sample 2.
75
Table 14. Core Competence of Hotel Owners – Variance Components Analysis Sample 2 Sample 2 DV = RevPAR DV = NOIPAR Variable Variance Percentage Variance Percentage Segment 32.59% 5.02% Brand (nested in Segment) 11.57% 21.74% Operator 10.76% 10.50% Segment Specialization 0.00% 0.01% Brand Specialization 22.86% 25.19% Operator Specialization 0.00% 0.00% Location Variable Region 3.76% 6.70% State 4.57% 7.55% MSA 5.23% 10.14% Market Type 0.33% 0.25% Region Specialization 1.40% 8.34% State Specialization 5.70% 9.12% MSA Specialization 4.24% 10.46% Market-Type Specialization 9.37% 9.30% Control Variable Year 0.86% 1.72% Age 0.00% 0.01% Hotel Size 0.00% 0.00% Owner Size 0.00% 0.00% Room Price Level 2.96% 6.72% Error* 8.70% - 13.24% 9.49% - 20.52% Total 100.00% 100%
Note: * Error varies due to different variances attributed to different location variables.
The primary task of the variance components analysis on Sample 2 is to identify
the core competencies of the best-performing hotel owners. Literature suggests that the
core competencies can be identified as the resources, including well implemented
strategies, that can differentiate a firm from the competitors (e.g., Aharoni, 1993;
Harrison, 2003; King et al., 2001). Following this notion, because Sample 2 is created in
76
a way to maximize the distinct performance difference between the best-performing and
under-performing hotel owners, such distinct differences are known and all “better”
hotels in Sample 2 are owned by the best sixteen owners. Therefore, the strategies that
explain significant portions of the total variance in performance are chosen as the core
competencies of these sixteen owners. Specifically, brand and brand specialization
strategies are definite core competencies of hotel owners because of their consistently
strong influences on both RevPAR and NOIPAR across samples. Segment is also
selected due to its significant impact on RevPAR in both samples. In addition, operator,
MSA, and MSA specialization strategies are identified as core competencies of hotel
owners because each of them explains more than ten percent of the variance in NOIPAR
in Sample 2. Consequently, a total of six corporate strategies are identified as the core
competencies of the hotel owners: segment, brand, operator, location (MSA), brand
specialization, and location (MSA) specialization strategies (bold in Table 11).
It is acknowledged that such process of core competence identification involves
subjectivity in the researcher and may be arguable. The choice of this method over the
others is due to that these six strategies collectively explain over 80 percent of variance in
both RevPAR and NOIPAR, and no other combinations of strategies can have more
explanation power without adding more factors. While an alternative and “safer” method
is to classify brand and brand specialization strategies as the only two core competencies
since their consistent importance in affecting hotel performance is most indisputable,
such an approach also has limitations because these two strategies together only account
for 34.43 percent of variance in RevPAR and 46.93 percent of variance in NOIPAR. As a
77
preliminary study on the core competencies of hotel owners pertaining to property
financial performance, inclusion of more reasonable factors is favored, not only because
of their relatively greater explanation power, but also because they may provide more
insights on the topic of core competence and consequently may contribute to building a
broader foundation for future research.
Effects of Core Competence
Testing Hypothesis H4: For a particular hotel owner, if this owner’s core competence
is identified as related to its superior strategy regarding hotel (a) location, (b) segment,
(c) brand, or (d) operator, such core competence has different effects on the financial
performance of the owner’s hotels with different (a) locations, (b) segments, (c) brands,
or (d) operators.
Hypothesis H4 further investigate how the core competencies of a particular
owner influence all the hotels of this owner: Do the owner’s core competencies influence
all hotels equally, or affect some hotels more or less than other hotels? In the previous
section, the expertise in implementing superior segment strategy, brand strategy, operator
strategy, location (MSA) strategy, brand specialization strategy, and location (MSA)
specialization strategy have been identified as the six core competencies of the best-
performing owners. For the two specialization strategies, because they are continuous
variables, their t values provide direct interpretations: an owner’s degrees of brand
specialization and location specialization are positively related to the financial
78
performance of this owner’s hotels. On the other hand, the core competencies regarding
choosing particular segment(s), brand(s), operator(s), and MSA(s) require further
investigation because they are categorical variables.
To examine the effects of the identified core competencies on the hotels of a
particular hotel owner, case studies on six hotel owners are conducted. As shown in Table
15, these six owners are chosen because all of them are ranked among the top ten percent
of both RevPAR and NOIPAR lists, and therefore, are regarded the best-performing hotel
owners among all 159 hotel owners studied in this research. Consequently, six sub-
samples (Samples 3 – 8) are created, each of which consists of only the hotels of one
hotel owner.
Table 15: Effects of Core Competence – Top Six Hotel Owners
Owner ID Sample ID
Number of Hotels
Number of Cases
RevPAR rank
NOIPAR Rank
1
3 8 24 2 1
2 4 10 30 4 6 3 5 8 24 5 2 4 6 11 33 10 9 5 7 14 42 13 7 6 8 30 90 16 5
Nonparametric Kruskal Wallis Test is repeated on each sample, and one of the
four core competencies serves as the independent variable in each test. Specifically, since
segment, brand, and operator strategies explain a large portion of variance of hotel
RevPAR, three Kruskal Wallis Tests are conducted, in which RevPAR is the dependent
variable, and segment, brand, or operator is the independent variable. Similarly, due to
79
that brand, operator, and MSA are the most important factors in explaining variance of
NOIPAR, three Kruskal Wallis Tests are performed with NOIPAR as the dependent
variable, and brand, operator, or MSA as the independent variable. Therefore, a total of
six Kruskal Wallis Tests are conducted for each sample.
Chi-square scores of the Kruskal Wallis Tests indicate whether a core competence
(the owner’s expertise in choosing segment, brand, operator, or MSA) has equal
influence on all hotels of this particular owner. When significant differences are detected,
Tukey’s Multiple Comparison Test is followed to explore further between which groups
(segments, brands, operators, or MSAs) were the differences lie. The results of each
sample are presented below. Because segment is the only known factor, brand, operator
and MSA are coded with a unique number for each hotel owner. However, such coding
does not carry across owners, therefore the same code for different owners are not
comparable. For instance, Brand 1 in the data of Owner 1 is not the same brand as Brand
1 in the data of Owner 2.
Hotel Owner One
Kruskal Wallis Tests are first conducted on the hotels of Hotel Owner One. As
shown in Table 16, the results indicate that the RevPAR performance of the hotels of
Hotel Owner One varies by segment, brand, and operator. Therefore, Tukey’s Multiple
Comparison Tests are performed and the results reveal that: (1) The mean RevPAR of
this owner’s upper upscale hotels is significantly higher than its upscale hotels, (2) the
80
mean RevPAR of Brand 1 hotels is significantly higher than Brand 2 and 4 hotels, and (3)
the mean RevPAR of the hotels managed by Operator 2 is significantly higher than the
hotels managed by Operator 1.
While no statistically significant differences are found in the NOIPAR
performance across the five brands and three operators, results of Kruskal Wallis Tests
show that mean NOIPAR varies by MSA. The follow-up Tukey’s Multiple Comparison
Test further reveals that the mean NOIPAR of the hotels in MSA 2 is significantly higher
than the hotels in MSA 1 and 3.
81
Table 16. Effects of Core Competencies – Hotel Owner One
Kruskal Wallis Tests Independent Variable Level DV = RevPAR DV = NOIPAR Segment 2 7.435** ---- Brand 5 14.988** 3.42 Operator 3 12.67** 3.41 MSA 3 ---- 7.740* Tukey’s Multiple Comparison Tests DV=RevPAR Segment Hotel Case Mean S.D. Minimum Maximum
Upper
Upscale 6 18 136.66(a) 42.90 75.40 269.60 Upscale 2 6 59.96(b,c) 6.90 52.80 66.60 Total 8 24 123.57 48.04 52.80 269.60 Brand 1 3 9 160.99(a) 50.85 115.20 269.60 2 1 3 58.66(b) 6.90 52.80 66.60 3 1 3 116.04 9.67 108.00 126.80 4 1 3 70.53(b) 6.82 65.70 75.40 5 2 6 120.69 8.60 109.00 134.40 Total 8 24 123.57 48.60 52.80 269.60 Operator 1 1 3 58.66(b) 6.90 52.80 66.60 2 5 15 144.87(a) 43.83 109.00 269.60 3 2 6 97.83 26.07 65.70 126.80 Total 8 24 123.57 48.60 52.80 269.60 DV=NOIPAR MSA Hotel Case Mean S.D. Minimum Maximum 1 3 9 32394.67(b) 3081.11 29141.03 37441.01 2 2 6 48477.31(a) 12820.67 35464.71 61097.00 3 3 9 33377.64(b) 4322.47 27062.63 41437.81 Total 8 24 36783.38 8150.15 27062.63 61097.00
Note: * p<0.05; ** p<0.01. a. Significantly larger value. b. Significantly smaller value. c. Value is smaller than the segment mean in the base sample
82
The results suggest that Hotel Owner One’s core competencies in terms of its
expertise in choosing hotel segments, brands, operators and MSAs do not have equal
effects on all of its hotels. Therefore, Hypothesis H4 is supported. The superior RevPAR
and NOIPAR performance of this owner’s hotels are not because all hotels performed
equally well. Indeed, the superior RevPAR was primarily attributable to the higher
RevPAR achieved by the hotels in the Upper Upscale segment, the hotels affiliated with
Brand 1, and the hotels managed by Operator 2. In addition, the superior NOIPAR was
primarily due to the hotels in MSA 2.
On the other hand, the mean NOIPAR of its hotels in MSA 1 and 3 is below the
average NOIPAR of Hotel Owner One. Moreover, the hotels in the upscale segment,
affiliated with Brand 2 and 4, and managed by Operator 1 have relatively lower
RevPARs than the mean value of this hotel owner. Specifically, while it is not surprising
that the mean RevPAR of the upscale hotels of Hotel Owner One is lower than the one of
upper upscale hotels, it should be noted that the mean RevPAR of the upscale hotels
($59.96) is even below the mean RevPAR of all upscale hotels studies in this research
(Sample 1-A). This suggests that the upscale hotels have a negative influence on the
overall RevPAR performance of this owner.
Hotel Owner Two
Table 17 presents the results of the Kruskal Wallis Tests and the follow-up
Tukey’s Multiple Comparison Tests. The RevPAR performance of the hotels of Hotel
83
Owner Two varies by brand, and the NOIPAR performance varies by MSA. Specifically,
the mean RevPAR values of this owner’s Brand 2, 3 and 4 hotels are significantly higher
than the one of Brand 5 hotels, and the mean NOIPAR values of the hotels in MSA 1, 2,
5, and 6 are significantly higher than the ones of hotels in MSA 3 and 4.
Because no statistically significant differences are found in the RevPAR and
NOIPAR performances across the two segments and seven operators, the conclusion
could be that no statistical evidence suggests Hotel Owner Two’s core competencies with
regard to its expertise in choosing hotel segments and operators influence its hotels
differently. However, the results suggest that this owner’s expertise in choosing hotel
brands and MSAs do not have equal effects on all of its hotels. Therefore, Hypothesis H4
is partially supported in the case of Hotel Owner Two. The superior RevPAR is primarily
due to the higher RevPAR achieved by the hotels affiliated with Brands 2, 3, and 4, while
the superior NOIPAR is primarily associated with the hotels in MSAs 1, 2, 5, and 6.
In addition, the results indicate that the mean RevPAR of Brand 5 hotels ($57.42)
is not only below the other hotels of Hotel Owner Two, but also less than the mean
RevPAR of all hotels studied in this research ($58.20). Similarly, the mean NOIPAR of
its hotels in MSA 4 is not only less than the other hotels of the owner, but also below the
average NOIPAR of the hotels of all hotel owners ($10,751). Therefore, while Hotel
Owner Two’s core competencies of implementing brand and location (MSA) strategies
have contributed to the superior financial performance of most of its hotels, such brand
84
strategy did not benefit the RevPAR for hotels affiliated with Brand 5, and the location
strategy did not contribute to the NOIPAR for hotels in MSA 4, either.
85
Table 17. Effects of Core Competencies – Hotel Owner Two
Kruskal Wallis Tests Independent Variable Level DV = RevPAR DV = NOIPAR Segment 2 0.97 ---- Brand 5 10.396* 6.421 Operator 7 9.651 1.684 MSA 6 ---- 8.566* Tukey’s Multiple Comparison Tests DV=RevPAR Hotel Case Mean S.D. Minimum Maximum Brand 1 1 3 103.87 2.87 100.70 106.20 2 3 9 120.14(a) 39.34 64.70 169.80 3 3 9 129.59(a) 13.09 105.10 148.80 4 2 6 130.68(a) 30.82 88.20 179.20 5 1 3 57.42(b,c) 7.05 51.00 65.00 Total 10 30 117.18 33.44 51.00 179.20 DV=NOIPAR Hotel Case Mean S.D. Minimum Maximum MSA 1 2 6 36007.56(a) 291.71 35773.92 36334.51 2 1 3 25723.56(a) 4388.46 22620.45 28826.67 3 2 6 12039.00(b) 2685.08 10194.27 15119.47 4 1 3 10392.83(b,c) 1186.92 9230.45 11602.86 5 1 3 22601.15(a) 1645.33 20810.57 24046.43 6 3 9 20862.99(a) 5842.55 13856.96 27918.71 Total 10 30 21739.96 9238.64 9230.45 36334.51
Note: * p<0.05. a. Significantly larger value. b. Significantly smaller value. c. Value is smaller than the mean value of all hotels in the base sample.
86
Hotel Owner Three
The results of the Kruskal Wallis Tests and the follow-up Tukey’s Multiple
Comparison Tests are presented in Table 18. The RevPAR and NOIPAR performance of
the hotels of Hotel Owner Three does not vary by segment, brand, or MSA. Therefore,
there is no statistical evidence suggesting Hotel Owner Three’s core competencies
regarding its expertise in choosing hotel segments, brands, and MSAs have different
influences on its hotels. On the other hand, the results suggest that this owner’s expertise
in choosing hotel operators do not have equal effects on all of its hotels. The superior
RevPAR and NOIPAR of Hotel Owner Three are both primarily due to the performance
of the hotels managed by Operator 3. Therefore, Hypothesis H4 is partially supported.
87
Table 18. Effects of Core Competencies – Hotel Owner Three
Kruskal Wallis Tests Independent Variable Level DV = RevPAR DV = NOIPAR Segment 2 1.271 ---- Brand 3 3.351 5.604 Operator 3 7.938* 6.738* MSA 3 ---- 6.483 Tukey’s Multiple Comparison Tests DV=RevPAR Hotel Case Mean S.D. Minimum Maximum Operator 1 2 6 72.11(b) 5.90 63.00 78.54 2 5 15 68.21(b) 10.02 49.07 85.53 3 1 3 132.49(a) 18.86 113.95 151.66 Total 8 24 77.22 23.62 49.07 151.66 DV=NOIPAR Hotel Case Mean S.D. Minimum Maximum Operator 1 2 6 12788.44 1365.41 11362.61 15156.97 2 5 15 9920.21(b) 2468.38 5729.45 13274.32 3 1 3 19581.40(a) 11884.86 6378.57 29425.33 Total 8 24 11844.91 5181.87 5729.45 29425.33
Note: * p<0.05; ** p<0.01. a. Significantly larger value. b. Significantly smaller value.
88
Hotel Owner Four
As shown in Table 19, Hotel Owner Four retains only one operator to manage all
of its 11 hotels, and the mean RevPAR of the hotels does not vary by segment. However,
the results suggest that this owner’s expertise in choosing hotel brands and MSAs have
different effects on its hotels. Specifically, the hotels affiliated with Brand 1 are the
primary source of its superior RevPAR and NOIPAR; on the other hand, the hotels
affiliated with Brands 3 and 4 have lower RevPAR and NOIPAR than the other hotels of
the owner. In addition, the hotels in MSAs 4 and 5 made significant contributions to
NOIPAR, while hotels in MSAs 3 and 6 had lower NOIPAR. Hypothesis H4 is partially
supported by Hotel Owner Four.
89
Table 19. Effects of Core Competencies – Hotel Owner Four Kruskal Wallis Tests Independent Variable Level DV = RevPAR DV = NOIPAR Segment 2 2.314 ---- Brand 5 19.210** 12.508* Operator 1 ---- ---- MSA 7 ---- 17.954** Tukey’s Multiple Comparison Tests DV=RevPAR Hotel Case Mean S.D. Minimum Maximum Brand 1 2 6 87.05(a) 6.24 81.43 98.39 2 2 6 75.42 8.21 63.93 81.35 3 1 3 58.61(b) 12.61 44.68 69.26 4 5 15 69.79(b) 5.40 59.49 78.67 5 1 3 81.84(a) 8.32 72.72 89.01 Total 11 33 73.94 10.73 44.68 98.39 DV=NOIPAR Hotel Case Mean S.D. Minimum Maximum Brand 1 2 6 13220.31(a) 2085.28 10485.44 16442.06 2 1 3 10980.15 5279.75 4885.56 14160.39 3 1 3 6297.22(b) 3463.68 2504.46 9292.82 4 5 15 9541.09(b) 1717.88 7204.51 12968.65 5 2 6 11545.97 1650.72 9709.58 12906.47 Total 11 33 10410.49 3006.73 2504.46 16442.06 MSA 1 1 3 11545.97 1650.72 9709.58 12906.47 2 3 9 10342.03 1621.03 8746.31 12823.71 3 1 3 7739.84(b) 2039.85 4885.56 9285.03 4 2 6 13135.02(a) 871.61 12134.45 14160.39 5 2 6 12074.05(a) 3166.67 8646.09 16442.06 6 1 3 6297.22(b) 3463.68 2504.46 9292.82 7 1 3 8082.59 760.45 7204.51 8523.17 Total 11 30 10296.94 3006.73 2504.46 16442.06
Note: * p<0.05; ** p<0.01. a. Significantly larger value. b. Significantly smaller value.
90
Hotel Owner Five
Hypothesis H4 was partially supported by Hotel Owner Five. As presented in
Table 20, all 14 hotels of this owner were managed by one operator. Both the mean
RevPAR and NOIPAR vary by brand, suggesting Hotel Owner Five’s expertise in
choosing hotel brands have different effects on its hotels. Specifically, the superior
RevPAR and NOIPAR are primarily due to Brand 4 hotels, while little is contributed by
the hotels affiliated with Brands 1 and 7. In addition, the results reveal that the mean
NOIPAR of the hotels in MSA 4 is significantly higher than the one of the hotel in MSA
1. While the mean RevPAR values of the midscale with F&B ($58.19) and without F&B
($67.09) hotels are significantly less than the one of the owner’s upscale hotels ($95.99),
both numbers are above the mean value of their respective segments ($48.58 and $49.66,
respectively), suggesting an overall superior performance of Owner Five’s hotels.
91
Table 20. Effects of Core Competencies – Hotel Owner Five
Kruskal Wallis Tests Independent Variable Level DV = RevPAR DV = NOIPAR Segment 5 15.402** ---- Brand 7 16.325** 12.508* Operator 1 ---- ---- MSA 3 ---- 17.954** Tukey’s Multiple Comparison Tests DV=RevPAR Hotel Case Mean S.D. Minimum Maximum Segment Upscale 2 6 95.99(a) 13.49 79.24 117.55
Midscale
w/ F&B 7 21 58.19(b) 15.90 35.08 86.50
Midscale
w/o F&B 5 15 67.09(b) 12.31 48.29 88.91 Total 14 42 66.77 18.97 35.08 117.55 Brand 1 1 3 62.31(b) 0.60 61.80 62.97 2 2 6 64.27(b) 9.41 53.37 79.60 3 1 3 88.79(a) 9.93 79.24 99.06 4 1 3 103.19(a) 14.17 89.21 117.55 5 2 6 69.83 15.20 48.29 88.91 6 1 3 67.22 14.66 52.06 81.33 7 6 18 57.5(b) 17.14 35.08 86.50 Total 14 42 66.77 18.97 35.08 117.55
(continued)
92
Table 20. Effects of Core Competencies – Hotel Owner Five (continued)
Tukey’s Multiple Comparison Tests DV=NOIPAR Hotel Case Mean S.D. Minimum Maximum Brand 1 1 3 8639.18(b) 1067.29 7535.33 9665.71 2 2 6 12019.15 2265.22 9235.67 16080.65 3 1 3 14941.84 1262.83 13617.74 16132.87 4 1 3 21961.50(a) 2583.79 19424.33 24589.52 5 2 6 10476.61(b) 3279.79 5963.42 14107.22 6 1 3 9033.41(b) 2449.80 6385.34 11219.02 7 6 18 8173.47(b) 3688.45 2794.50 16143.76 Total 14 42 10614.88 4743.15 2794.50 24589.52 MSA 1 1 3 3454.42(b) 662.13 2794.50 4118.73 2 1 3 8639.18 1067.29 7535.33 9665.71 3 1 3 5450.90 568.92 4969.25 6078.61 4 11 33 11914.89(a) 4392.10 5963.42 24589.52 Total 14 42 10614.88 4743.15 2794.50 24589.52
Note: * p<0.05; ** p<0.01. a. Significantly larger value. b. Significantly smaller value.
Hotel Owner Six
Hypothesis H4 was also partially supported by Hotel Owner Six. While all 30
hotels of Hotel Owner Six are managed by one operator and consequently no “operator”
differences can be detected, the mean RevPAR varies by brand and segment, and the
mean NOIPAR varies by brand and MSA. Therefore, Hotel Owner Six’s core
competencies of choosing hotel segments, brands, and MSAs have different effects on its
hotels.
93
First, as shown in Table 21, hotels affiliated with different brands made different
contributions to RevPAR and NOIPAR. The overall superior RevPAR and NOIPAR
performance of Hotel Owner Six are primarily due to the hotels of Brands 1, 4, and 6,
while the hotels affiliated with Brands 3, 5, and 7 have significantly lower RevPARs. In
addition, the hotels in MSAs 7 and 9 have significantly larger NOIPAR than the hotels in
MSAs 2, 3, 10, 11, 13, and 14. Finally, the mean RevPAR values vary significantly
across the hotel segments. Particularly, the mean RevPAR of the owner’s three luxury
hotels are significantly greater than the ones of the hotels in all other segments. It is also
worthy to point out that, among Hotel Owner Six’s hotels in five segments, the mean
RevPAR of luxury ($215.90), upper upscale ($108.06), and economy hotels ($42.62) are
higher than the segment means of the base sample ($147.35, $82.35, and $30.07,
respectively). However, the mean RevPARs of Hotel Owner Six’s three upscale ($61.88)
hotels and one midscale with F&B hotel ($38.07) are lower than their respective segment
means ($67.82 and $48.58, respectively). This finding indicates that the upscale and
midscale with F&B hotels had negative influences on the overall RevPAR performance
of Hotel Owner Six.
94
Table 21. Effects of Core Competencies – Hotel Owner Six
Kruskal Wallis Tests Independent Variable Level DV = RevPAR DV = NOIPAR Segment 5 56.688*** ---- Brand 8 59.642*** 57.638*** Operator 1 ---- ---- MSA 14 ---- 44.682*** Tukey’s Multiple Comparison Tests DV=RevPAR Hotel Case Mean S.D. Minimum Maximum Segment Luxury 9 27 215.90(a) 95.73 104.75 540.22
Upper Upscale 15 45 108.06(b) 45.07 49.91 235.80
Upscale 3 9 61.88(b,c) 6.88 54.58 73.47
Midscale
w/ F&B 1 3 38.07(b,c) 12.59 23.58 46.37 Economy 2 6 42.62(b) 3.57 39.07 48.73 Total 30 90 129.10 86.26 23.58 540.22 Brand 1 1 3 423.83(a) 103.68 341.37 540.22 2 4 12 119.96 58.62 62.79 235.80 3 3 9 61.88(b) 6.88 54.58 73.47 4 2 6 224.55(a) 46.52 187.09 308.12 5 1 3 38.07(b) 12.59 23.58 46.37 6 6 18 178.37(a) 54.49 104.75 284.92 7 2 6 42.62(b) 3.57 39.07 48.73 8 11 33 103.73 39.24 49.91 162.38 Total 30 90 129.10 86.26 23.58 540.22
(continued)
95
Table 21. Effects of Core Competencies – Hotel Owner Six (continued) Tukey’s Multiple Comparison Tests DV=NOIPAR Hotel Case Mean S.D. Minimum Maximum Brand 1 1 3 108420.15(a) 18056.59 90152.54 126258.04 2 4 12 25022.56 14999.68 9500.56 52744.61 3 3 9 7414.46(b) 2714.52 3297.83 11791.23 4 2 6 50557.43(a) 13926.48 27620.22 62091.37 5 1 3 -335.02(b) 797.25 -1210.68 348.82 6 6 18 33182.79(a) 13485.44 20118.93 66368.01 7 2 6 4763.21(b) 1602.49 2855.29 6649.16 8 11 33 14353.71 10557.01 -12679.17 35951.29 Total 30 90 23268.25 23093.68 -12679.17 126258.04 MSA 1 7 21 24281.03 16257.00 -12679.17 56486.15 2 1 3 5803.95(b) 1128.51 5143.92 7107.00 3 1 3 8727.25(b) 1777.27 6793.08 10288.41 4 2 6 21897.30 2020.34 20118.93 25644.83 5 1 3 33752.67 7911.06 28081.60 42790.14 6 2 6 22655.01 11353.51 9500.56 35951.29 7 4 12 51504.41(a) 40477.32 5231.50 126258.04 8 3 9 9356.12 5182.95 3297.83 16943.34 9 1 3 60027.79(a) 2166.29 57771.65 62091.37 10 1 3 5600.75(b) 1276.92 4155.61 6576.72 11 2 6 8239.35(b) 2534.88 5536.80 11791.23 12 1 3 29952.98 3460.81 26635.88 33541.51 13 3 9 13690.51(b) 13077.49 -1210.68 30690.03 14 1 3 3474.02(b) 1058.17 2855.29 4695.86 Total 30 90 23268.25 23093.68 -12679.17 126258.04
Note: * p<0.05; ** p<0.01. a. Significantly larger value. b. Significantly smaller value. c. Value is smaller than the mean value of all hotels in the same segment in the
base sample.
96
Chapter V
DISCUSSIONS AND CONCLUSION
In this chapter, findings of the study are summarized, followed by the discussions
of the results. Conclusions of the study are then provided, and theoretical and empirical
implications are presented. Finally, the limitations of the study and recommendations for
future researchers are tendered.
Summary of Major Findings
The purpose of the study is to complement existing research in corporate effects
and hospitality strategic management by exploring the corporate effects in the lodging
industry from a hotel owner’s perspective. The specific objectives of this study are:
(1) To examine the existence of corporate effects in the lodging industry,
(2) To investigate the effects of corporate strategies in determining hotel property
financial performance, and
(3) To explore the core competencies of hotel owners in terms of influencing
hotel property financial performance.
These objectives are accomplished by investigating the following four research
questions:
97
(1) Do corporate effects exist in the lodging industry?
(2) Can a hotel owner’s corporate effects on property financial performance be
attributed to the owner’s strategic decisions regarding hotel location, segment,
brand, and operator, as well as corporate specialization strategies regarding
hotel location, segment, brand, and operator?
(3) What are the core competencies of the best-performing hotel owners?
(4) For a particular hotel owner, do its core competencies influence all the hotels
of this owner equally? Or, do the effects of the owner’s core competencies
influence some hotels more or less than other hotels? If the answer to the
second question is yes, then, how do the effects of the core competencies vary
among this particular owner’s hotels?
The results of this study provide answers for these research questions. First,
corporate effects do exist in the lodging industry. The owner of a hotel is not simply a
statistically significant factor for the hotel’s financial performance (i.e., RevPAR and
NOIPAR), but rather the most important factor attributing to the hotel’s financial
performance because the owner explains the largest portion of the variance in hotel
RevPAR and NOIPAR. Specifically, based on Sample 1-A, the variance in hotel
RevPAR may be partitioned approximately by the following effects: owner (71.54
percent), hotel size (7.14 percent), room price level (5.62 percent), hotel age (4.83
percent), year (1.1 percent), and residual errors (the remaining 9.77 percent). And
similarly, Sample 1-B, the largest sample with available hotel NOI information, shows
that hotel NOIPAR may be partitioned approximately by the following effects: owner
98
(40.74 percent), hotel size (23.77 percent), hotel age (20.11 percent), room price level
(2.58 percent), year (0.93 percent), and residual error (the remaining 11.86 percent).
Second, the results show that effects of hotel owner can be effectively
represented by the corporate strategies implemented by the owner. All eight proposed
corporate strategies (i.e. location, segment, brand, operator, location specialization,
segment specialization, brand specialization, and operator specialization) have significant
effects on hotel financial performance. Based on the results of Samples 1-A and 1-B,
among the eight strategies, segment strategy explains the largest portion of variance in
hotel RevPAR (37.63 percent), followed by brand specialization and brand strategies
(17.32 percent and 12.59 percent, respectively). The most important strategy related to
hotel NOIPAR is brand specialization (27.27 percent), followed by brand and segment
strategies (20.47 percent and 16.98 percent, respectively). On the other hand, although
statistically significant, a hotel owner’s strategies regarding operator, location, as well as
the specialization strategies regarding segment, location, and operator only explain little
variance in hotel financial performance. While little variance in hotel RevPAR and
NOIPAR is attributable to most measures of location and location specialization
strategies (i.e., by region, state, MSA, and market type), one exception is the market type
specialization strategy, which accounts for seven and ten percent of RevPAR and
NOIPAR, respectively.
Third, when the best-performing hotel owners are identified and compared to the
“worst” performing hotel owners, segment, brand, and brand specialization strategies are
99
still the most important among all eight corporate strategies. In addition, operator, a
relatively less significant strategy in Samples 1-A and 1-B, becomes a much more
important factor in explain the variance of hotel RevPAR and NOIPAR in Sample 2
(approximately eleven percent for both financial performance measures). Moreover, the
significance of a hotel owner’s location and location strategies, when measured as MSA
and MSA specialization, also increase to account for approximately ten percent variance
of hotel RevPAR and NOIPAR. Therefore, corporate strategies regarding segment, brand,
operation, location-MSA, brand specialization and location-MSA specialization are
identified as the core competencies of the sixteen best-performing owners in Sample 2,
because they account for over eighty percent of the variance in hotel financial
performance, measured as RevPAR and NOIPAR. Specifically, the results suggest that
hotel RevPAR and NOIPAR are negatively related to the degree of a hotel owner’s brand
specialization, but positively related to its degree of MSA specialization.
Finally, case studies on the top six best-performing hotel owners indicate that a
hotel owner’s core competencies (i.e., the expertise in adopting favorable segment, brand,
operator and location-MSA strategies) may have different effects on its hotels. Although
the hotels of an owner could have collectively achieved overall superior performance,
individual hotel’s performance may vary by segment, brand, operator, and/or location-
MSA. Therefore, while a hotel owner’s capabilities in choosing superior segment(s),
brand(s), operator(s), and/or location(s) can be regarded as the owner’s core
competencies, it does not guarantee that all the segments, brands, operators, and/or
locations chosen by this owner contribute to the superior overall RevPAR and NOIPAR
100
of its hotels. The results reveal that, in some cases, a hotel owner’s hotels in certain
segments, MSAs, and/or affiliated with certain brands and operators have actually lower-
than-average RevPAR and NOIPAR levels.
Discussions
Existence of Corporate Effects in the Lodging Industry
The findings confirm the existence of corporate effects in the lodging industry.
Compared to other factors that are well recognized in the literature as related to a hotel’s
financial performance such as hotel size, hotel age, price level, and time (i.e., year), the
owner is indeed the most significant factor in that it accounts for the largest variance of a
hotel’s financial performance. This study supports the previous research suggesting that
the effects of corporate parent may be substantially larger in some industries, such as the
non-manufacturing industries, than in others (McGahan & Porter, 1997). Unlike most
other studies on corporate effects that incorporated samples from various industries and
consequently report significantly larger industry effects than corporate effects, this study
focuses on the lodging industry only. The results reveal that corporate parent, or owner,
of a hotel is the dominating factor in determining the hotel’s RevPAR and NOIPAR. This
finding reveals that, in addition to franchisors and management companies that are
commonly considered as influences on a hotel’s performance, hotel owners also play a
critical role, in that they not only buy and sell hotels but also have significant influences
on their individual hotels’ financial performance.
101
Role of Corporate Strategy
This study indicates that the owner’s corporate strategies are significantly related
to a hotel’s financial performance. This finding supports the previous research suggesting
that corporate strategies are part of total corporate effects (Bowman & Helfat, 2001).
Specifically, in the lodging industry, a non-operating hotel owner can choose strategies
regarding: (1) at which location(s) to possess a property/properties, (2) which type(s) of
hotels to possess, (3) what brand(s) to affiliate with, and (4) which operator(s) will
manage its property/properties. Moreover, literature in the strategic management
indicates that well developed and implemented strategies can be important sources of a
firm’s core competencies (Aharoni, 1993; Peteraf, 1993). Consequently, this research
identified eight statistically significant corporate strategies for hotel owners, namely
location strategy (i.e., by region, state, MSA and market type), segment strategy, brand
affiliation strategy, operator strategy, location specialization strategy, segment
specialization strategy, brand specialization strategy, and operator specialization strategy.
Building on the empirical results of the analysis on the best-performing hotel owners, this
study links the concepts of corporate strategy and core competence and suggests that a
hotel owner’s expertise in implementing superior strategies regarding segment, brand,
operator, location-MSA, brand specialization, and MSA specialization can be deemed as
the core competencies of the owner.
102
Selection of Segment, Location, Brand, and Operator
The findings of this study support the popular notion found among industry
practitioners: a hotel’s segment, location, brand affiliation and operator do matter. More
importantly, the relative importance of these factors on hotel performance is assessed in
this research. Because hotel segment is defined by a hotel brand’s system-wide ADR and
consequently is directly linked to RevPAR, its significant prediction power on RevPAR
is not surprising. As shown in the descriptive statistics of the base sample, the mean
values of RevPAR and NOIPAR are ranked by segment from luxury to economy. In
addition, the importance of location has been long recognized for a long time in the
lodging industry. Particularly, from a hotel owner’s viewpoint, it is suggested that a hotel
investment is only as good as its local market, because the revenues of a hotel are highly
correlated to the economy of the local market (Corgel, 2002).
Compared to segment, location, and operator, brand affiliation is the most
important factor and explains the largest portion of variance in both RevPAR and
NOIPAR. Literature on branding and brand equity has suggested that a good brand is
valuable not only to the brand owner (e.g., franchisors) but also to the brand user (e.g.,
franchisees) and the ultimate customers of the product (e.g., Baldauf, Cravens, & Binder,
2003; Kim et al., 2002; Prasad & Dev, 2000). Taking a hotel owner’s perspective, brand
names are suggested to be relevant to hotels’ revenues, profits, and return on investment
(e.g., Prasad & Dev, 2000; Wolff, 2005). A study of Kim et al. (2002) on 12 upscale hotel
brands reveals that a strong brand can contribute to hotel RevPAR through increased
103
brand image, brand awareness, perceived quality, and brand loyalty. Moreover, a recent
study has shown that brand affiliation contributes significantly to a hotel’s market value,
and certain brands have greater influences on hotel valuations than other brands do
(O’Neill & Xiao, 2006). While the actual brand names were not made available for this
research, results of this study support such a view of “brand power” by revealing that
some brands have achieved higher RevPAR and NOIPAR levels than the others across
the owners.
Literature in strategic alliance provides particular theoretical explanations with
regard to the critical aspect of choosing certain brands and operators over the others.
Franchises and management contracts are important types of non-equity strategic alliance
in the lodging industry. Based on RBV, previous research suggests that the key reason for
organizations to form alliances is to access the resources of the partners (Das & Teng,
1998). In the context of lodging franchises and management contracts, the critical
resources contributed from partners include financial and physical resources from the
owner/franchisee, and technological and managerial resources from the franchisor and
operator (Chathoth & Olsen, 2003). While the goal of a franchise or management
contract as a strategic partnership is to achieve competitive advantage for both partners,
based on the agency theory, it is widely recognized that the partners (i.e., franchisor and
franchisee, or operator and owner) do not always share the same views regarding goals,
values and competitive methods (e.g., Baucus, Baucus, & Human, 1996; Contractor &
Kundu, 1998; Chathoth & Olsen, 2003; Eyster, 1997; Galen & Touby, 1993). Therefore,
to achieve long term success of a franchise or management contract, the owner’s ability
104
to choose franchisor(s) and operator(s) with strategic fit involving complementary
resources, trust, and appropriate governance mechanism is critical to the long term
success of a franchise or management contract (e.g., Chathoth & Olsen, 2003).
While the significant effects of segment, location, brand, and operator on hotel
performance is widely acknowledged, from hotel owners’ perspectives, how they choose
the superior segment, location, brand, and operator strategies is worth further scrutinizing.
Results of this study suggest that the best-performing hotel owners are selective in
implementing their segment, location, brand, and operator strategies. As shown in Table
19, the segments, locations, brands, and operators between the hotels of the best-
performing and the ones of the under-performing owners are compared. First, the top
sixteen best-performing hotel owners focus more on owning luxury, upper upscale, and
upscale hotels than the under-performing hotel owners, who do not own any luxury
hotels but concentrate more on midscale and economy properties. Second, the majority of
the hotels of the best-performing hotel owners are located in a small number of better
locations (i.e., regions, states, MSAs, and markets). The best-performing owners have a
large number of hotels in the Middle Atlantic and Pacific regions, in which the under-
performing owners almost do not exist. Best-performing owners also focus on the top 25
markets (62 percent), while the under-performing owners have more hotels in the third-
tier markets (53 percent). In addition, while the 156 hotels of the sixteen best-performing
hotel owners are in 27 states, nearly 59 percent of them are located in the top five states:
California, Florida, New York, Virginia, and Illinois. Comparably, the under-performing
owners have concentrated their hotels in five different states: Ohio, North Carolina,
105
Arizona, Indiana, and Georgia. Moreover, 64 hotels (41 percent) of the best-performing
owners are located in only five MSAs, while 39 percent of the under-performing owners’
hotels are located in five MSAs that are completely different from the top five MSAs of
the hotels of the best-performing owners..
Furthermore, 83 hotels (53 percent) of the best-performing owners are affiliated
with only five brands regardless of a total of 30 brands in this sub-sample. Noticeably,
only one of these five brands (Brand 2) is adopted by the under-performing owners.
Finally, while 31 operators are retained by the sixteen best-performing owners, 86 hotels
(55 percent) are managed by only five operators, and none of these five operators are
retained by the under-performing owners. Although the exact MSAs and actual names of
hotel brands and operators are not available, one potential interpretation of these results is
that the best-performing owners have realized the power of certain segments, locations,
brands, and operators, and consequently they have adopted their strategies accordingly,
seeking to make their hotels associate with certain “better” segment(s), location(s),
brand(s), and operator(s).
106
Table 22. Comparison of Best-Performing and Under-Performing Owners
Top 16 Owners Bottom 16 Owners Hotel Percentage Hotel Percentage Segment Luxury 5 3.21% 0 0.00% Upper Upscale 31 19.87% 12 8.76% Upscale 38 24.36% 18 13.14% Midscale w/ F&B 26 16.67% 37 27.01% Midscale w/o F&B 37 23.72% 46 33.58% Economy 19 12.18% 24 17.52% Total 156 100.00% 137 100.00% Region New England 3 1.92% 1 0.73% Middle Atlantic 34 21.79% 0 0.00% South Atlantic 40 25.64% 32 23.36% East North Central 16 10.26% 41 29.93% East South Central 0 0.00% 11 8.03% West North Central 7 4.49% 22 16.06% West South Central 12 7.69% 10 7.30% Mountain 6 3.85% 19 13.87% Pacific 38 24.36% 1 0.73% Total 156 100.00% 137 100.00% Market Type Top 25 Markets 97 62.18% 34 24.82% Second 25 Markets 20 12.82% 30 21.90% Other Markets 39 25.00% 73 53.28% Total 156 100.00% 137 100.00%
(continued)
107
Table 22. Comparison of Best-Performing and Under-Performing Owners (countiued)
Top 16 Owners Bottom 16 Owners Hotel Percentage Hotel Percentage Top Five States California 32 20.51% Ohio 17 12.41%Florida 16 10.26% North Carolina 14 10.22%New York 21 13.46% Arizona 14 10.22%Virginia 12 7.69% Indiana 13 9.49%Illinois 11 7.05% Georgia 13 9.49%Total 92 58.97% Total 71 51.82% Top Five MSAs MSA 1 19 12.18% MSA 6 24 17.52%MSA 2 17 10.90% MSA 7 10 7.30%MSA 3 11 7.05% MSA 8 8 5.84%MSA 4 9 5.77% MSA 9 6 4.38%MSA 5 8 5.13% MSA 10 5 3.65%Total 64 41.03% Total 53 38.69% Top Five Brands Brand 1 26 16.67% Brand 6 16 11.68%Brand 2 19 12.18% Brand 7 11 8.03%Brand 3 19 12.18% Brand 2 10 7.30%Brand 4 11 7.05% Brand 8 10 7.30%Brand 5 8 5.13% Brand 9 7 5.11%Total 83 53.21% Total 54 39.42% Top Five Operators Operator 1 30 19.23% Operator 6 24 17.52%Operator 2 14 8.97% Operator 7 19 13.87%Operator 3 11 7.05% Operator 8 13 9.49%Operator 4 14 8.97% Operator 9 9 6.57%Operator 5 17 10.90% Operator 10 9 6.57%Total 86 55.13% Total 74 54.01%
108
Specialization/Diversification Strategies
One of the important findings of this study is the effects of hotel owner’s
specialization (or diversification) strategies with regarding to segment, location, brand
and operator. Particularly, this study suggests strong influences of brand specialization
and location (MSA) specialization on the financial performance of the best-performing
hotel owners’ properties. However, the influences of these two strategies are in the
opposite direction: while MSA specialization is positively related to hotel financial
performance, it is brand diversification (but not brand specialization) that benefits hotel
financial performance.
First, the findings suggest that brand specialization has negative effects on hotel
financial performance. Indeed, the more brands the owner has, the higher mean RevPAR
and NOIPAR of its hotels. This is consistent with a popular view held particularly by the
relatively larger hotel owners that brand diversification benefits all hotels in the portfolio
(Kidd, 2006). Support of this notion can be found from the theories of strategic alliance
and organizational learning. Literature suggests that the formation of an alliance is the
acknowledgment that both partners have useful resources, which can be financial,
physical, technological, and managerial (Das & Deng, 1998; Inkpen, 1998).While some
resources are tangible, others are knowledge-based and can not be obtained overnight.
Therefore, previous research indicates that strategic alliance is indeed a learning process,
in which a firm can obtain certain expertise from its alliance partner and such knowledge
would be inaccessible in the absence of the alliance (e.g., Inkpen, 1998; Iyer, 2002;
109
Manrakhan, 2006). Specifically, Inkpen (1998) argues that the knowledge learned from
the partner has value to the firm outside the specific terms of the alliance agreement,
because it may enable the firm to enhance its own strategy and operations. This could be
the case of brand diversification among hotel owners: Through learning and comparing
various marketing and operational skills from different franchisors, the corporate owner
can improve its overall managerial capabilities and can implement the best practices
learned from various brands to all of its hotels.
A real example is provided by a senior executive of a relatively large hotel owner.
This hotel owner has its designated revenue management personnel in its asset
management department, while, in the meantime, they closely work with several different
revenue management teams of various brands with which its hotels are affiliated. The
reason is that the owner’s revenue management personnel have different goals than those
of the branded revenue management teams. While each brand makes efforts to improve
the performance of the owner’s hotels affiliated with this particular brand, such effects do
not take into consideration the other hotels of the owner. By establishing its own revenue
management personnel, the owner can combine the valuable information provided by
different brands, and implement best practices and most appropriate tactics learned from
different brands in all of its hotels; consequently all hotels benefit from such knowledge
transfer (Kidd, 2006).
However, on the other hand, the positive relationship between owner’s brand
diversification and property financial performance should be interpreted with caution,
110
because, although one can argue that the brand diversification causes the superior
performance, an alternative explanation could be that hotel owners do not diversify
across brands until they have already achieved superior performance. It is possible that
only the best-performing hotel owners have the expertise in dealing with the complexities
of working with multiple brands; therefore, an “average” hotel owner may not like to
affiliate with too many brands. While little empirical and theoretical support is found to
support this view, only a longitudinal study that considers the change of the degree of
brand diversification over a relatively long period of time can reveal the causal
relationship between owner’s brand diversification and property financial performance.
While the above discussion regarding brand diversification/specialization may be
technically applicable to justify the effects of operator diversification/specialization, such
effects remain unclear based on the findings of this study. Operator specialization has the
relatively smallest effects (although statistically significant) on the hotel financial
performance in Samples 1-A and 1-B, but such effects become not even statistically
significant in Sample 2. One possible explanation might be the lack of variance due to the
unbalanced data: A total of 58 percent hotel owners in Sample 1-A and 53 percent hotel
owners in Sample 2 did not diversify by operator. Such dominance of single-operator
strategy may have contributed to the trivial effects of operator specialization. To better
assess the relationship between owner’s operator specialization and property financial
performance, future research may take a longitudinal approach by studying the changes
of the degree of operator specialization of hotel owners over a relatively long period of
time.
111
Unlike the effects of brand specialization, the owner’s degree of location
specialization, particularly MSA, is shown to have an important positive influence on
hotel RevPAR and NOIPAR. That is, it is the strategy of location specialization rather
than location diversification that benefits the financial performance of the owner’s hotels.
When an owner implement a location (i.e., MSA) specialization strategy and have hotels
located in a smaller number of MSAs, these hotels tend to have better financial
performance. Although this finding does not support the common practice of geographic
diversification found in the real estate investment community, the power of local markets
has been revealed in the literature. In economics, market power refers to the ability of a
firm to set the market price of a product or service, and such power may be positively
influenced by market share, efficiency and specialization (e.g., Guevara & Maudos,
2007). In the lodging industry, a hotel’s performance is highly correlated to its local
market (Corgel, 2002). Consequently, compared to the owners who diversify properties
into a large number of markets (i.e., MSAs), a hotel owner specializing in certain markets
can achieve relatively larger market share in each of the respective markets of its hotels,
and can better use local market information to improve local operational efficiency.
Different Effects of Core Competence
By definition, core competence has always been linked to superior performance in
the literature of strategic management (e.g., Coyne et al., 1997). However, this study
reveals that core competence can not be taken for granted as equally influencing all
business units of a firm. While the expertise in choosing better segment(s), brand(s),
112
operation(s) and MSA(s) have been identified as the core competencies of the top sixteen
hotel owners in the study, the effects of these core competencies vary for each owner.
The findings suggest that, for example, while an owner’s core competence may be its
expertise in choosing the best brands with which to affiliate, it is not necessary that all the
brands chosen by the owner have made equal contribution to the overall superior
performance of its hotels. Instead, perhaps, while all hotels of the owner outperformed
the hotels of other owners, this owner’s hotels affiliated with some brands contributed
more to the overall performance than its hotels with other brands. Therefore, the other
brands become the weak ones in the portfolio of the particular owner. Moreover, it is also
possible that, while the overall performance of the owner is superior, a small number of
the owner’s hotels affiliated with certain brands may actually have not even achieved the
average performance level of its competitors. Therefore, instead of making a positive
contribution to the hotel owner, the latter brands, indeed, negatively influenced the
overall performance of the hotel owner. Consequently, while a hotel owner can declare
branding strategy as its core competence, the owner may not be able to claim that all the
brands it chose are better ones.
Similarly, an owner specializing in working with good operators may have hotels
managed by relatively weak or even “bad” operators, and an owner whose expertise is
identifying good MSAs may have hotels in relatively weak or even “bad” MSAs. This
finding is particularly important not only to hotel owners but also to firms in general,
because it cautions that a firm should not be over-confident about their core competencies.
Particularly, when a corporate strategy is identified as a core competence, simple
113
repetition of such strategy would not always guarantee superior results. The fitness
between the strategy and the current environment, as well as appropriate execution of the
strategy should be carefully assessed every time before implementing such strategy. In
addition, the results of the strategy should be evaluated properly. It is suggested that a
firm should seek to continuously develop and improve its core competencies to stay
competitive (Olsen et al., 1998). Most strategic resources, including corporate strategies
as core competences, can be improved by identifying and then eliminating the weak
components over time.
Combination of Corporate Strategies/Core Competencies
While this research primarily focuses on partitioning the relative importance of
the hotel owner’s corporate strategies and on identifying the core competencies
accordingly, when taking into consideration the identified core competencies altogether,
this study also suggests the collective influence of a number of corporate strategies that
have the strongest impact on hotel financial performance. Empirically, two or more
strategies are commonly implemented or altered by hotel owners simultaneously. For
instance, acquiring an existing hotel or building a new hotel both involve considerations
of all segment, location, brand, and operator strategies. Because a significant number of
hotel franchisors also operate hotels for the owners (i.e., branded managers, such as
Marriott, Hilton, Starwood, etc.), hotel owner’s brand and operator strategies may
influence each other, because change in one strategy may lead to change in the other.
While interaction effects of the identified core competences are not examined in this
114
study, it is likely that the most sophisticated hotel owners are the ones that can make
multiple best strategic choices for their hotels: Their hotels with highest RevPAR and
NOIPAR are more likely in upscale or higher segments, located in good markets,
affiliated with strong brands, and managed by operators with superior operational
expertise.
Conclusion
The purpose of the study is to explore corporate effects in the lodging industry
from a hotel owner’s perspective. Three specific research objectives are accomplished.
The first objective is to examine the existence of corporate effects in the lodging
industry. The study concludes that corporate effects do exist in the lodging industry.
Compared to other factors such as hotel size, hotel age, price level, and time (i.e., year),
the owner is indeed the most significant factor in determining a hotel’s financial
performance. Hotel owners play a crucial role in influencing the performance of their
hotels.
The second objective of this study is to investigate the effects of corporate
strategies on hotel financial performance. Findings reveal that a hotel owner can
influence its hotels through corporate strategies. Eight corporate strategies of the hotel
owner, namely, location strategy (i.e., region, state, MSA and market type), segment
strategy, brand affiliation strategy, operator strategy, location specialization strategy,
115
segment specialization strategy, brand specialization strategy, and operator specialization
strategy are significant factors in determining hotel financial performance. Specifically,
an owner’s strategic decisions regarding segment, brand, and brand specialization are the
most important factors that influence both revenue and profit of its hotels.
The third objective is to explore the core competencies of hotel owners. Linking
the concepts of corporate strategy and core competence, the findings suggest that a hotel
owner’s expertise in implementing superior strategies regarding segment, brand, operator,
location (MSA), brand diversification, and location (MSA) specialization are the core
competencies of the owners whose hotels have collectively achieved the highest financial
performance. Moreover, this research reveals that, for a particular hotel owner, its core
competence may have different effects on the financial performance of its hotels because
some hotels may benefit more from the core competence than the others. Finally, this
research suggests that the most powerful strategy may be the combined effects of several
core competencies/strategies. Most likely is that the most sophisticated hotel owners are
the ones that can make multiple best strategic choices for their hotels.
Theoretical Implications
This study provides empirical evidence of the existence of corporate effects.
Previous studies, incorporating data from multiple industries, have revealed a wide
variety regarding the magnitude of corporate effects, and have suggested that such
corporate effects may be influenced by industry characteristics (e.g., Bowman & Helfat,
116
2001). By focusing on one single industry, this research indicates that corporate effects
not only exist, but also may be more important than other factors in a particular industry,
such as the lodging industry. Such a large influence of corporate effects also empirically
supports previous studies suggesting greater corporate effects in services industries than
in manufacturing industries (McGahan & Porter, 1997).
This research expands the literature on corporate effects by examining the
underlying sources of corporate effects. Study findings indicate that corporate strategies
can be effective sources of corporate effects because a firm can influence the
performance of its business units by implementing certain strategies, while the degree of
importance may vary by strategy.
In addition, building on the resource-based view of the firm, this study further
contributes to the concepts of corporate effects and core competence. Corporate core
competencies are identified as the most important corporate strategies of the best-
performing hotel owners in this research. The results suggest that the effects of a core
competence may vary: For a particular firm, a core competence may have more
influences on some of its business units than on the others.
This study is the first of its kind to examine the corporate effects in the context of
the hospitality industry, and consequently adds significant value to hospitality
management research. This study expands the strategy research in the hospitality field by
linking several key strategy constructs – corporate effects, corporate strategy, and core
117
competence together and by revealing their influences on hotel performance. Moreover,
to the best of my knowledge, this study is the first to examine the relationship between
hotel financial performance at the property-level and hotel owner’s
specialization/diversification strategies at the corporate level, and it provides empirical
evidence on the various impacts of corporate specialization/diversification strategies.
Managerial Implications
Study findings provide several important implications for practitioners in the
lodging industry. First, this research clearly shows the importance of the owner’s
relationship to the performance of its hotel properties. As an industry that is heavily
franchised and requires specific managerial expertise, hotel franchisors and management
companies have received the primary attention pertaining to hotel property’s performance,
while hotel investors and owners are more likely to be mentioned in topics regarding
hotel development and acquisition. However, a non-operating hotel owner can, indeed,
have significant impact on the performance of its hotels through implementing a number
of corporate strategies. Specifically, all strategic decisions regarding a hotel’s location,
segment, brand affiliation, and operator are made by the owner, and consequently the
owner has the largest influence on hotel property performance.
Second, the findings support the notion that location, segment, brand affiliation
and operator do matter. Hotels in certain locations and segments, affiliated with certain
brands, and managed by certain operators can achieve superior revenue and profit.
118
Therefore, for hotel owners, choosing the most appropriate locations, segments, brands,
and operators are critical to the performance of their hotels. For hotel franchisors and
management companies, proving their capabilities in bringing superior performance to
the hotels will create competitive advantage.
Third, this study reveals that, although all significant, the magnitude of the above
mentioned factors are different. While little surprise exists in seeing a hotel’s revenue
affected largely by segment, brand affiliation has shown a consistently larger impact on
both revenue and profit than location and operator. Therefore, hotel owners should pay
particular attention to the brand and carefully assess the brand’s potential contribution to
the hotel before engaging in a franchise agreement.
Fourth, the findings of this study support the notion regarding the benefits of
brand diversification. Since working with one brand may enable a hotel owner to gain
specific knowledge of that particular brand and then use such knowledge in its hotels
affiliated with other brands, hotel owners may consider adopting a multi-brand strategy to
improve their hotels’ performance through sharing brand-specific knowledge. On the
other hand, this study does not support the common practice of geographic diversification.
Instead, this research reveals that the degree of market specialization is positively related
to hotel performance. Because hotels compete in their respective local markets, hotel
owners should be aware of that having multiple hotels in one market can achieve better
information efficiency and relatively larger market share than having hotels in different
markets.
119
Fifth, the findings provide a number of corporate strategies as sources for hotel
owners’ core competencies. This research specifically reveals that segment, brand,
operator, location, brand diversification, and location (MSA) specialization are the core
competencies of the best-performing hotel owners in the sample. Hotel owners can self-
evaluate the implementations and results of these strategies, and identify their own core
competencies. Moreover, core competencies are found to influence some hotels more or
less than others. Therefore, even after the core competencies are identified, a hotel owner
should not be “blinded” by its core competencies. For example, a hotel owner
specializing in choosing good brands may choose average or “bad” brand(s) at some time,
and similarly, an owner with expertise in working with good management companies
may also have hotels that are managed by average or “bad” operator(s). This finding is
valuable not only to hotel owners but also to other types of players in the lodging industry,
because it reminds industry practitioners that core competence also needs continuous
improvement and development, and it can only improve through actively assessing its
results, and identifying and eliminating the weak components of it.
Sixth, industry practitioners should realize that segment, location, brand, and
operator strategies often work together rather than separately, particularly in projects of
new hotel development and hotel acquisition. For an existing hotel, change in one factor
may cause change in another factor, such as that shown in the relationship between brand
and operator. In addition, a hotel’s decision on quality and facility upgrade or downgrade
may also involve changes in brand and/or segment. Therefore, multiple strategies are
often adopted simultaneously and a hotel’s performance depends on their collective
120
effects. Therefore, hotel owners should not overly rely on one particular strategy but
ignore the potential effects of the others.
Limitations and Recommendation for Future Research
Several limitations are associated with this study. First, corporate strategy is a
focal factor examined in this research. However, corporate strategy only represents one
source of corporate effects, while literature has suggested a number of other potential
sources of corporate effects, such as organizational structure, organizational climate,
planning and control systems, etc. (Bowman & Helfat, 2001). Similarly, the resource-
based view of the firm proposes different types of core competencies including financial,
human, physical and knowledge resources (Harrison & Enz, 2005). In this study,
corporate strategy is suggested as the only type of core competence. In addition, this
research adopts a relatively subjective, and consequently arguable, approach in
determining the core competencies of the best-performing hotel owners. Future research
incorporating other sources of corporate effects and core competencies, and adopting
different measures of core competencies is needed to further our understanding on these
topics.
This research adopts the data provided by STR. Although the STR database is the
largest available in the lodging industry, a significant limitation is that it does not disclose
the actual names of the owners, brands, and operators, which in turn limits the
interpretation of the results. A particularly interesting question for future research is:
121
Which owners, brands, and operators are better or worse than the others? Future studies
linking specific brand, operator and owner names will be able to further examine firm-
specific characteristics and their effects on hotel performance. In addition, because brand
names were coded by STR in the sample, this study measures brand and brand
specialization strategies with an assumption that all brands are equally different. However,
the distances between brands may be different. In the lodging industry, the practice of
brand extension has caused most franchisors to have multiple brands. Therefore, for
example, a hotel owner choosing to diversify its brands from Hilton to Doubletree may
have a different impact on its hotels than diversifying from Hilton to Marriott. Future
researchers could measure the effects of brand and brand specialization more precisely by
taking into consideration the degree of difference between brands.
Moreover, this research builds on a convenience sample only with information
from 2003 to 2005, which limits the generalizability of the results. While having more
than one year’s data can help to partially assess the “year” effects, it should be noted that
such effects are not totally controlled in this research. For example, because the revenue
and profit performance of the whole lodging industry has greatly improved from 2003 to
2005, these three years represent a recovery period with a favorable market environment.
However, the financial performance of hotels in different segments and locations may
vary in different market environments. For example, as discussed in Chapter II, compared
to the midscale and economy hotels, luxury and upscale properties may be more
profitable in a favorable economic environment, and can be affected more severely
during an economic downturn (e.g., Brady & Conlin, 2004; Imperiale, 2002; O’Neill &
122
Lloyd-Jones, 2002; Poutasse, 1997). Therefore, the “best-performing” hotel owners in
this study may simply have more hotels in certain segments and locations that
outperformed the hotels in other segments and locations between 2003 and 2005; and the
performance of these hotels may be affected significantly during a less favorable
economic environment, which in turn may cause the owners of these hotels become less
competitive than the others. In addition, hotel owners may adopt different strategies in
different market environments. One possibility is that, when the economic environment
becomes unfavorable, sophisticated hotel owners may become more likely to diversify
into different markets in order to reduce the risk of having most hotels in one of the worst
markets. While the current available data prevented this study from examining any
changes in strategies over time, future research studying a full life-cycle of the lodging
industry, when such data become available, would reveal a more complete picture on the
effects of the corporate strategies.
Furthermore, as the first comprehensive research focusing exclusively on the
effects of multiple corporate strategies on hotel performance, this study examined eight
strategies that are most commonly discussed and implemented by hotel owners. Although
efforts have been made to control for the well-recognized correlations among the eight
strategies (i.e., nesting the brands in hotel segments to minimize the brand-segment
connection), this study only investigates the main effects of the eight strategies.
Interaction effects among the eight strategies were not included in the model due to
complexity. While examining all interaction effects of these strategies within one single
study is difficult, future research on the interaction effects among hotel owner’s corporate
123
strategies can be broken into a series of smaller studies in order to provide additional
insights on this topic. This is a planned pursuit for the near future.
It is also worth noting that this research focuses on the operating performance of
hotels, measured as RevPAR and NOIPAR, but does not take into consideration the value
or investment of the hotels. A hotel’s operating performance (i.e., RevPAR and NOIPAR)
is related to the owner’s investment in the particular hotel. While hotels that are in certain
locations and segments, and are associated with certain brands and operators, have been
revealed to achieve higher RevPAR and NOIPAR in this research, it is not surprising that
the market values of these hotels may be higher as well, and consequently their owners
may have invested more in these hotels to obtain the superior locations, segments, brands
and/or operators. While a hotel’s operating performance is essential to its value, one of
the ultimate goals of hotel owners is to achieve superior, or at least acceptable, return on
investment. Hypothetically, a hotel may have the highest possible RevPAR and NOIPAR,
but may be still unprofitable to its owner because of its excessive investment cost. Future
research linking hotel owners’ strategies to their desired and/or realized return on
investment will be particularly valuable to the hotel investment community.
Finally, this study focuses only on the realized strategies of hotel owners.
Literature has suggested a number of internal and external factors that may affect the
realization of corporate strategies, such as organizational structure, organizational culture,
managerial capabilities, financial capabilities, market dynamics, and industry
macroculture, etc. (e.g., Barr, Stimpert, & Huff, 1992; Chandler, 1962; D’Aveni, 1990;
124
Hambrick & Mason, 1984; Harrison & Enz, 2005; O’Neill, 2004). Strategic decision
making of organizations is one of the key concepts in strategic management and has been
intensively studied from different paradigms, including rationality and bounded
rationality, politics and power, and garbage can. For instance, Eisenhardt and Zbaracki
(1992, p.17) suggest that an organization’s strategic decision may be the outcome of a
complex process involving many factors, in that “decision makers are boundedly rational,
power wins battles of choice, and chance matters.” Specifically, in the lodging industry,
previous research indicates that, before the establishment of a long term
franchise/management contract agreement, hotel owners and franchisors/operators
evaluate each other with a number of criteria to assess the potential of reaching a
successful long term partnership (e.g., Altinay, 2006; Clarkin & Swavely, 2006;
Jambulingham & Nevin, 1999; Scatchard, 1998). Therefore, it is possible that a hotel
owner, even with the knowledge of superior location(s), segment(s), brand(s), and
operator(s), may lack necessary capabilities and/or resources to pursue the desired
strategies. Future studies regarding the factors influencing the development and
implementation of hotel owners’ corporate strategies will shed further light on the topics
of corporate effects and core competencies of lodging organizations.
125
REFERENCES Adner, R., & Helfat, C. E. (2003). Corporate effects and dynamic managerial capabilities.
Strategic Management Journal, 24, 1011-1025. Aharoni, Y. (1993). In search for the unique: Can firm-specific advantages be evaluated?
Journal of Management Studies, 30 (1), 31-50. Altinay, L. (2006). Selecting partners in an international franchise organisation.
International Journal of Hospitality Management, 25 (1), 108-128. Ambrose, B. W., Ehrlich, S, R., Hughes, W. T., & Wachter, S. M. (2000). REIT
economies of scale: Fact or fiction? Journal of Real Estate Finance and Economics, 20 (2), 211-220.
Amit, R., & Schoemaker, P. (1993). Strategic assets and organizational rent. Strategic
Management Journal, 14, 33-46. Anderws, K.R. (1971). The Concept of Corporate Strategy. Homewood, IL: Irwin. Ansoff, I. (1965). Corporate Strategy. New York, NY: McGraw Hill. Artusio, D. (March 13, 2006). President and CEO, Dellisart Lodging. Personal
communication. Baldauf, A., Cravens, K.S., & Binder, G. (2003). Performance consequences of brand
equity management: Evidence from organizations in the value chain. The Journal of Product and Brand Management, 12, 220-234.
Baldo, A. (October 11, 1994). Heartbreak hotels? Financial World, 163 (21), pp.74-75. Barney, J. (1986). Types of competition and the theory of strategy: Towards an
integrative framework. Academy of Management Review, 11 (3), 656-665. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of
Management, 99-120.
126
Barr, P.S., Stimpert, J.L., & Huff, A.S. (1992). Cognitive change, strategic action, and
organizational renewal. Strategic Management Journal, 13, 15-36. Baucus, D.A., Baucus, M.S., & Human, S.E. (1996). Consensus in franchise
organizations: A cooperative arrangement among entrepreneurs. Journal of Business Venturing, 11, 359-378.
Beals, P., & Arabia, J.V. (1998). Lodging REITs. Cornell Hotel and Restaurant
Administration Quarterly, 39 (6), 52-59. Beals, P., & Denton, G. (2004). The current balance of power in North American hotel
management contracts. Journal of Retail & Leisure Property, 4 (2), 129-145. Berger, P. and Ofek, E. (1995). Diversification’s effect on firm value. Journal of
Financial Economics, 37, 39-65. Berke, J. (May 9, 2003). CNL scoops up RFS hotels for $685 million. The Daily Deal. Bers, M., & Springer, T. M. (1997). Economies-of-scale for real estate investment trusts.
The Journal of Real Estate Research, 14 (3), 275-290. Bettis, R. A. (1981). Performance differences in related and unrelated diversified firms.
Strategic Management Journal, 2 (4), 379-392. Bowman, E. H., and Helfat, C. E. (2001). Does corporate strategy matter? Strategic
Management Journal, 22 (1), 1-23. Brady, P.J., & Conlin, M.E. (2004). The performance of REIT-owned properties and the
impact of REIT market power. Journal of Real Estate Finance and Economics, 28 (1), 81-95.
Brueggeman, W. B., & Fisher, J. D. (2005). Real estate finance and investment (12th ed.).
Boston: McGraw Hill.
127
Carl, R.P. (November 16, 2006). Senior Vice President, Felcor Lodging Trust. Personal
communication. Capozza, D.R., & Seguin, P.J. (1998). Managerial style and firm value. Real Estate
Economics, 26 (1), 131-150. Capozza, D. R., & Seguin, P. J. (1999). Focus, transparency and value: The REIT
evidence. Real Estate Economics, 27 (4), 587-619. Chandler, A.D. (1962). Strategy and Structure: Concepts in the History of American
Industrial Enterprise. MIT. Chang, S.J., & Hong, J. (2002). How much does the business group matter in Korea?
Strategic Management Journal, 23 (3), 265-274. Chang, S., & Singh, H. (2000). Corporate and industry effects on business unit
competitive position. Strategic Management Journal, 21 (7), 739-752. Chathoth, P.K., & Olsen, M.D. (2003). Strategic alliances: A hospitality industry
perspective. International Journal of Hospitality Management, 22, 419-434.
Chung, W., & Kalnins, A. (2001). Agglomeration effects and performance: a test of the Texas lodging industry. Strategic Management Journal, 22 (10), 969-988.
Clarkin, J.E., & Swavely, S.M. (2006). The importance of personal characteristics in franchisee selection. Journal of Retailing and Consumer Services, 13, 133-142.
Collis, D.J., & Montgomery, C.A. (1995). Competing on resources: Strategy for the 1990s. Harvard Business Review, 73 (4), 118-128.
Contractor, F.J., & Kundu, S.K. (1998). Modal choice in a world of alliances: Analyzing
organizational forms in the international hotel sector. Journal of International Business Studies, 29 (2), 325-358.
Corgel, J.B. (2005). Hotel real estate markets. Journal of Portfolio Management,
September, 91-99.
128
Corgel, J.B. (2002). A hotel investment is only as good as its local market! Real Estate
Issues, 27 (2), 64-66. Corgel, J.B., & deRoos, J.A. (1997). Hotel investments in the portfolio: Are they part of
the core? Real Estate Finance, 14 (2), 29-37. Coyne, K.P., Hall, S.J.D, & Clifford, P.G. (1997). Is your core competence a mirage? The
McKinsey Quarterly, 1, 40-54. Crossland, C., & Hambrick, D.C. (2007). How national systems differ in their constraints
on corporate executives: A study of CEO effects in three countries. Strategic Management Journal, in press.
David, F.R. (2001). Strategic Management Concepts. Upper Saddle River, NJ: Prentice
Hall. D’Aveni, R. (1990). Introduction: Hypercometition. Free Press. Dev, C.S., Erramilli, M.K., & Agarwal, S. (2002). Brands across borders: Determining
factors in choosing franchising or management contracts for entering international markets. Cornell Hotel and Restaurant Administration Quarterly, 43 (6), 91-104.
Eisenhardt, K.M., & Zbaracki, M.J. (1992). Strategic decision making. Strategic
Management Journal, 13, 17-37. Eyster, J.J. (1996). The revolution in domestic hotel management contracts. In Lefever,
M.M. (ed.), Hospitality in Review, pp.223-235. Dubuque, IA: Kendall/Hunt Publishing.
Eyster, J.J. (1997). Hotel management contracts in the U.S.: The revolution continues.
Cornell Hotel and Restaurant Administration Quarterly, 38 (3), 14-20. Galen, M., & Touby, L. (March 22, 1993). Franchise fracas. Business Week, 68-72.
129
Gordon, S., & McCarthy, W. (1998). Hotel REITs: The great disconnect. Real Estate
Finance Journal, 14 (3), 59-64. Green, J.V. (March 12, 2006). President and Chief Financial Officer, Winston Hotels.
Personal communication. Guevara, J.F., & Maudos, J. (2007). Explanatory factors of market power in the banking
system. The Manchester School, 75 (3), 275-296. Hambrick, D.C., & Mason, P.A. (1984). Upper echelons: The organization as a reflection
of its top managers. Academy of Management Review, 9 (2), 193-206. Hambrick, D.C., & Fredrickson, J.W. (2005). Are you sure you have a strategy? The
Academy of Management Executive, 19 (4), 51-60. Hanson, B. (1991). An exploratory study of operating income relative to replacement cost
for alternative combinations of affiliation and management for mid-size full-service hotels. Unpublished dissertation.
Harrison, J.S. (2003). Strategic analysis for the hospitality industry. Cornell Hotel and
Restaurant Administration Quarterly 44 (2), 139-152. Harrison, J.S., & Enz, C.A. (2005). Hospitality strategic management: Concepts and
cases. Hoboken, NJ: John Wiley & Sons, Inc., pp. 67-100. Hayes, D.K., & Ninemeier, J.D. (2007). Hotel Operations Management. (2nd Ed.). Upper
Saddle River, NJ: Pearson Prentice Hall. Henderson, R., & Cockburn, I. (1994). Measuring competence? Exploring firm effects in
pharmaceutical research. Strategic Management Journal, 15, 63-84. Higley, J. (September 18, 2006). Climate dictates solid history, cash reserves. Hotel &
Motel Management, 221, 16, pp. 1, 85.
130
Hofer, C., & Schendel, S. (1978). Strategy Formulation: Analytical Concepts. St. Paul,
MN: West. Iyer, K.N. (2002). Learning in strategic alliances: An evolutionary perspective. Academy
of Marketing Science Review. 10, 1-14. Imperiale, R. (2002). Real Estate Investment Trusts: New Strategies for Portfolio
Management. New York, NY: John Wiley & Sons, Inc. Inkpen, A.C. (1998). Learning and knowledge acquisition through international strategic
alliances. The Academy of Management Executive, 12 (4), 69-80. Ismail, J.A., Dalbor, M.C., & Mills, J.E. (2002). Using RevPAR to analyze lodging-
segment variability. Cornell Hotel and Restaurant Administration Quarterly, 43 (6), 73-80.
Jambulingham, T., & Nevin, J.R. (1999). Influence on franchisee selection criteria on
outcomes desired by the franchisor. Journal of Business Venturing 14, 363-395. Kalnins, A. (2005). Quantifying impact: The efeect of new hotels and brand conversions
on revenues of existing hotels. The Center for Hospitality Research Reports, 5 (8), 1-19.
Kay, J. (1993). The structure of strategy. Business Strategy Review, 2, 17-37. Kidd, W. (February 1, 2006; November 11, 2006). Vice President, Host Hotels and
Resorts. Personal communication. Kim, H., Kim, W.G., & An, J.A. (2003). The effect of consumer-based brand equity on
firms’ financial performance. The Journal of Consumer Marketing, 20, 335-351. King, A.W., Fowler, S.W., & Zeithaml, C.P. (2001). Managing organizational
competencies for competitive advantage: The middle-management edge. The Academy of Management Executive, 15 (2), 95-106.
131
Kish, L.A. (September 21, 2006). Chief Operating Officer, Milestone Hospitality
International. Personal communication. Lang, L., & Stulz, R. (1994). Tobin’s q, corporate diversification and firm performance.
Journal of Political Economy, 102, 1248-1280. Leonard-Barton, D. (1992). Core capabilities and core rigidities: A paradox in managing
new product development. Strategic Management Journal, 13, 111-125. Manrakhan, S.N. (2006). Knowledge acquisition and creation in the portfolio of
international strategic alliances. Unpublished dissertation. McGahan, A. M., & Porter, M. E. (1997). How much does industry matter, really?
Strategic Management Journal, 18, 15-30. McIntosh, W., Liang, Y., & Thompkins, D.L. (1991). An examination of the small-firm
effect within the REIT industry. Journal of Real Estate Research, 6 (1), 9-18. Miles, R.E., & Snow, C.S. (1978). Organizational Strategy, Structure, and Process. New
York, NY: Prentice-Hall. Mintzberg, H. (1978). Patterns in strategy formation. Management Science, 934-948. Mintzberg, H. (1990). Strategy formulation: Schools of thought. In Fredrickson, J.W. (ed.)
Perspectives on Strategic Management. New York: Harper & Row Publishers. Montgomery, C.A. (1985). Product-market diversification and market power. Academy of
Management Journal, 28 (4), 789-798. Montgomery, C.A. (1994). Corporate diversification. Journal of Economic Perspectives,
8 (3), 163-178. Mooradian, R.M., & Yang, S.X. (2001). Dividend policy and firm performance: Hotel
REITs vs. non-REIT hotel companies. Journal of Real Estate Portfolio Management, 7 (1), 79-87.
132
Mueller, G.R., & Ainkeeff, M.A. (2001). Real estate ownership and operating businesses:
Does combining them make sense for REITs? Journal of Real Estate Portfolio Management, 7 (1), 55-65.
Nelson, R. (1994). Why do firms differ and does it matter? Strategic Management
Journal, 12, 61-74. Nelson, T.R., & Nelson, S.L. (2003). Regional models for portfolio diversification.
Journal of Real Estate Portfolio Management, 9 (1), 71-80. Okumus, F. (2002). Can hospitality researchers contribute to the strategic management
literature? International Journal of Hospitality Management, 21 (2), 105-110. Olsen, M.D., Tse, E.C., & West, J.J. (1998). Strategic Management in the Hospitality
Industry (2nd ed.). New York, NY: John Wiley and Sons. Olsen, M.D. (2004). Literature in strategic management in the hospitality industry.
International Journal of Hospitality Management, 23 (4), 411-424. O’Neill, J.W. (2004). An automated valuation model for hotels. Cornell Hotel and
Restaurant Administration Quarterly, 45 (3), 260-268.
O’Neill, J.W., Beauvais, L.L., & Scholl, R.W. (2004). Strategic issues and determinant factors of an interorganizational macroculture in the lodging industry. Journal of Hospitality & Tourism Research,28 (4), 483-506.
O’Neill, J.W., & Lloyd-Jones, A.R. (2002). One year after 9/11: Hotel values and strategic implications. Cornell Hotel and Restaurant Administration Quarterly 43, (5), 53-64.
O’Neill, J.W., & Mattila, A.S. (2004). Hotel branding strategy: Its relationship to guest satisfaction and room revenue. Journal of Hospitality & Tourism Research, 28, 156-165.
133
O’Neill, J.W., & Mattila, A.S. (2006). Strategic hotel development and positioning: The
effect of revenue drivers on profitability. Cornell Hotel and Restaurant Administration Quarterly, 47 (2), 146-155.
O’Neill, J.W., & Xiao, Q. (2006). The role of brand affiliation on hotel market value.
Cornell Hotel and Restaurant Administration Quarterly, 47 (3), 1-14. Pearce, J.A.,II, & Robinson, R.B. (1997). Strategic Management (3rd ed.). Chicago, IL:
Richard D. Irvin. Peteraf, M. (1993). The cornerstones of competitive advantage: A resource-based view.
Strategic Management Journal, 14, 179-191. Porter, M.E. (1980). Competitive Strategy. New York, NY: Free Press. Porter, M.E. (1985). Competitive Advantage: Creating and Sustaining Superior
Performance. New York, NY: Free Press. Porter, M.E. (1996). What is strategy? Harvard Business Review, 74 (6), 61-78. Poutasse, D.M. (1997). Public markets reward top-performing REITs. National Real
Estate Investor, 39 (9), 8-11. Prahlad, C.K., & Hamel, G. (1990). The core competence of the corporation. Harvard
Business Review, 68 (3), 79-91. Ramanujam, V., & Varadarajan, P. (1989). Research on corporate diversification: A
synthesis. Strategic Management Journal, 10, 523-551. Roquebert, J.A., Phillips, R. L., & Westfall, P. A. (1996). Markets vs. management: What
drives profitability? Strategic Management Journal, 17, 653-664. Rumelt, R.P. (1974). Strategy, Structure and Economic Performance. Boston, MA:
Harvard Business School Press.
134
Rumelt, R.P. (1982). Diversification strategy and profitability. Strategic Management
Journal, 3, 359-369. Rumelt, R.P. (1991). How much does industry matter? Strategic Management Journal,
12, 167-185. Sandman, I.W. (2003). Management contract and franchise agreements in the sale of a
hotel. Retrieved on June 24, 2006, from http://www.grahamdunn.com/pdfs/iws_lodging2003_managementcontracts.pdf
Scatchard, B. (September, 1998). Is one franchisor better than the other? AAHOA
Hospitality, 48-51. Schmalensee, R. (1985). Do markets differ much? American Economic Review, 341-351. Simon, E.Y. (October 16, 2006). Record year: Transaction volume reach new heights.
Hotel & Motel Management, 221 (18), pp.4, 58. Smith Travel Research. (2006). Chain scales. Retrieved on November 10, 2006, from
http://www.smithtravelresearch.com/SmithTravelResearch/Documents/Chain_Scales.pdf
Stalk, G., Evans, P., & Shulman, L.E. (1992). Competing on capabilities: The new rules
of corporate strategy. Harvard Business Review, 70 (2), 57-69, Stutts, A.T. (2001). Hotel and Lodging Management: An Introduction. New York, NY:
John Wiley & Sons. Taylor, M.H. (2002). A test of the co-alignment principle in independent hotels: A case
study. Unpublished dissertation. Tse, E.C., & Olsen, M.D. (1999). Strategic management. In Brotherton, B. (ed.), The
Handbook of Contemporary Hospitality Management Research, pp.351-373. New York, NY: John Wiley & Sons.
135
Turkel, S. (2006). In hotel franchising, reality trumps wishful thinking. Retrieved on
February 10, 2007, from http://www.hotel-online.com/News/PR2006_3rd/Aug06_HotelFranchising.html
Wernerfelt, B. (1984). A resource-based view of the firm. Strategic Management Journal,
5, 171-180. Wernerfelt, B., & Montgomery, C.A. (1988). Tobin’s q and the importance of focus in
firm performance. American Economic Review, 78, 246-250. Wolff, C. (March 15, 2005). How to value a brand. Lodging Hospitality, 61 (4), 44-45. Woods, R. (June, 2006). Hotel Portfolio Topics, 1, 5.
136
VITA
Qu Xiao
EDUCATION
Ph.D., Hospitality Strategic Management and Real Estate. 2007. School of Hospitality Management, Penn State University
M.H.M., Hospitality Management. 2002. Conrad N. Hilton College of Hotel and Restaurant Management, University of Houston
B.A., Chinese Language and Literature. 1996. Department of Chinese Language and Literature, Beijing Normal University
WORK EXPERIENCE
Instructor, School of Hospitality Management, Penn State University Assistant General Manager, ExtendedStay America NASA Hotel, Houston, TX Human Resources Specialist, Marriott Medical Center Hotel, Houston, TX Guest Services Representative, Holiday Inn Astrodome Hotel, Houston, TX Front Desk Agent, Hilton University Hotel, Houston, TX Journalist, China Tourism News, China
PUBLICATIONS
Xiao, Q., O’Neill, J.W., & Wang, H. International Hotel Development: A Study of Potential Franchisees in China. International Journal of Hospitality Management. (In press).
Mount, D.J., & Xiao, Q. Economic value of the recovered guests by hotel call centers. Journal of Hospitality Financial Management. (In press).
O’Neill, J.W., Xiao, Q, & Mattila, A.S. (2007). Suburban hotel development: Choosing a franchise brand. Case Research Journal, 26 (2), 43-60.
O’Neill, J.W., & Xiao, Q. (2006). The role of brand affiliation on hotel market value. Cornell Hotel and Restaurant Administration Quarterly, 47 (3), 1-14.
O’Neill, J.W., Mattila, A.S., & Xiao, Q. (2006). Hotel brand performance and guest satisfaction: The effect of franchising strategy. Journal of Quality Assurance in Hospitality & Tourism, 7 (3), 25-39.
O’Neill, J. W., & Xiao, Q. (2005). Towards a strategic approach to smoking bans: The case of the Delaware gaming industry. FIU Hospitality Review, 23 (1), 39-50.
AWARDS Best Article Award, Cornell Hotel and Restaurant Administration Quarterly (2006) Best Paper Award, International Council on Hotel, Restaurant and Institutional
Education (CHRIE) Conference (2006) The Annual Grace M. Henderson Award for Outstanding Graduate Student,
College of Health and Human Development, Penn State University (2006)