“SOLITUDE IS IMPRACTICAL AND YET SOCIETY IS FATAL?” – SOURCES AND EFFECTS OF NETWORK SKEPTICISM IN SMEs

Thomas EhrmannInstitute of Strategic ManagementWestfälische Wilhelms-Universität MünsterLeonardo-Campus 1848149 Münster, GermanyPhone: +49-251-8331959Fax: +49-251-8338333

Brinja Meiseberg(Corresponding Author)Institute of Strategic ManagementWestfälische Wilhelms-Universität MünsterLeonardo-Campus 1848149 Münster, GermanyPhone: +49-251-8331959Fax: +49-251-8338333Email: meiseberg@ism.uni-muenster.de

Paper presented at the EMNet 2011 December 1 – 3, 2011, Limassol, Cyprus(http://emnet.univie.ac.at/)

Abstract In the ongoing evolution of the dominant organizational paradigm and mode of competition along the continuum of single, autonomous firms to dyadic alliances to virtual companies, the current period is marked by a rapidly growing prevalence of the network form of organization. Yet, irrespective of the widespread belief that networks provide the most decisive benefits, there is a striking imbalance of studies researching the beneficial effects of networking compared with those few focusing on potential downsides of interfirm collaboration. Particularly, SMEs face critical challenges in implementing col-laborative strategies, triggered by their owners’ preferences for maximum autonomy, difficulties in identifying adequate partners, or a lack of trust towards larger partner firms. In consequence, SMEs often remain skeptical of cooperations. In this paper, we build on the RBV and organizational econom-ics. Based on case studies and survey data from a sample of 348 German SMEs, we explore the nature and prevalence of network skepticism, and its effects on cooperation decisions. Several contingency factors – coordination, communication and bonding capabilities – that may affect the linkages between concerns and decisions are investigated as well. We provide managerial implications for the design of network cooperations involving SMEs and for how (blind) network skepticism can be overcome.

“This attention to the functionality of network forms of organization explains why economic actors rely on network forms of organization, but it does not explain why they do not.” Podolny & Page (1998: 66)

Keywords: SMEs, alliances, network skepticism, capabilities, resource-based view, organizational economics JEL codes: D85, L14, D83, D74, L26

“SOLITUDE IS IMPRACTICAL AND YET SOCIETY IS FATAL?”1 –SOURCES AND EFFECTS OF NETWORK SKEPTICISM IN SMEs

1. Introduction

Of all the phenomena that have gripped the business world in recent years, few match the im-

pact of networks. In the ongoing evolution of the dominant organizational paradigm and mode

of competition along the continuum of single, autonomous firms to dyadic alliances to virtual

companies, the current period is marked by a rapidly growing prevalence of the network form

of organization (Parkhe et al. 2006). Several environmental shifts have opened up rewarding

opportunities for such interfirm cooperations – including the proceeding globalisation of mar-

kets, the rise of more technologically advanced economies, the convergence of and rapid shifts

in technologies, as well as regulatory changes in and across nations (Gulati 1995). Networks

are reshaping the global business architecture. The ubiquity of networks, and networking, at

the industry, firm, group, and individual levels has attracted significant research attention

(Hendrikse & Windsperger 2004; Parkhe et al. 2006).

In the realm of strategic management and business administration literature, the term “net-

work” often refers to long-term cooperations between firms, like joint ventures, franchising,

R&D agreements, or licensing (Gulati 1995; McGee et al. 1995; Witt 1999). Research empha-

sizes the functionality of networks for managing resource dependencies and fostering learning

and knowledge exchange (Cliquet 2000; Windsperger 2004). With respect to these activities,

networks can provide efficiency advantages that markets or hierarchies do not possess; also,

networks can allow firms to secure resources that would not be available on markets at all, like

reputation or customer contacts (Uzzi 1996). Thus, by creating economic opportunities that are

difficult to replicate in any other organizational form, network relationships can serve as a

prime coping response to individual resource scarcity in the quest for competitive advantage

and economic rents. Studies have documented the dramatic growth of cooperative arrange-

ments across industries in recent years, the variety of contractual agreements that formalize

relations, and the multitude of reasons why firms enter into partnerships (Parkhe et al. 2006).

Yet, irrespective of the widespread belief that networks provide the most decisive benefits,

some practitioners criticize the notion of cooperations as a “quasi-panacea” to organizational

challenges. Anecdotal evidence suggests that often, “network skepticists” can be found in

small and medium-sized enterprises (SMEs) (Hausschild & Wallacher 2003). SME decision-

1 Ralph Waldo Emerson (1803-1882; American poet)2

makers do not necessarily deny that networks can hold out advantages for small firms as well,

including the ability to tap into new markets, access scale economies, obtain complementary

resources in underdeveloped value chain activities, or receive endorsements from reputable

incumbents (Reuer & Ariño 2007). However, unlike large companies, SMEs face specific

challenges in implementing collaborative strategies that can present major obstacles to cooper-

ation (Alvarez & Barney 2001; Baum et al. 2000; Khanna et al. 1998).

Yet, a very limited number of studies investigate the phenomenon of what can be termed “net-

work skepticism”, particularly in the context of SMEs. In this paper, we explore this phenome-

non. “Network skepticism” refers to SME decision-makers’ attitudes of doubt, or their disposi-

tions to incredulity, towards the advantageousness of network participation in general, but

specifically for their own firm. We build on two widely cited theoretical approaches to organi-

zations: First, the resource-based view suggests that firms seek to capitalize on and increase

their capabilities and endowments; second, organizational economics assert that firms focus

on minimizing the costs of organizing (Combs & Ketchen 1999). Although these perspectives

agree on managers’ likely actions in many areas, their predictions diverge when interfirm co-

operation is considered (Combs & Ketchen 1999). Based on these two theoretical strings, and

building on qualitative case studies and quantitative data from a sample of 348 German SMEs,

we examine the nature and prevalence of network skepticism and its effects on cooperation

decisions. Several contingency factors that affect the linkages between concern and decisions

are investigated as well – in particular, SME capabilities as regards coordination, communica-

tion, and bonding in alliances. We offer managerial implications for how (blind) network

skepticism can be overcome, and for network design involving SMEs.

The next section provides an overview of the literature. Then, hypotheses are developed. Sub-

sequently, we describe the three-stage methodological approach used in this study, followed

by the results. The last section concludes, offering managerial and research implications.

2. Theoretical Background and Hypotheses

Research in strategic management has a long history of using the resource-based view of the

firm (RBV) to explain differential firm performance (Barney 2001; Peteraf 1993). Tying re-

sources to competitive advantage, the RBV suggests that the availability of resources enables

the generation of Ricardian rents and quasi-rents (Conner 1991; Peteraf 1993). The RBV has

been broadened to account for external resources that are available to a firm through interfirm

networks (Gnyawali & Madhavan 2001; Gulati 1999; Lavie 2006; McEvily & Marcus 2005).

3

Previous research has emphasized the functionality of networks for managing resource depen-

dencies (Cliquet & Nguyen 2004).2 By focusing on the effects of resource endowments on

managerial action and performance, the RBV holds that firms can combine internal and exter-

nal resources for competitive advantage; thus, when facing resource limitations, managers are

attracted to cooperative arrangements to overcome such constraints (Combs & Ketchen 1999).

In contrast, based on transaction costs and agency theory, the organizational economics (OE)

perspective assumes that managers’ central concern is organizing activities efficiently (Combs

& Ketchen 1999). Accordingly, OE understands the various interfirm arrangements as alterna-

tive ways of organizing the exchange of goods and services in the context of imperfect infor-

mation, self-interested behavior, and diverging goals (Hesterly et al. 1990). Here, interfirm

arrangements offer a variety of incentives and governance mechanisms that are not available

in market transactions (Uzzi 1996; Williamson 1975). For example, when network partners

invest in specific assets, reciprocal dependencies reduce incentives for opportunism, and thus

the costs of mutual control (Dyer 1996; Klein & Murphy 1988; Teece 1987). Accordingly, if

interfirm cooperation minimizes organizing costs, networks will provide efficiency advantages

(Combs & Ketchen 1999). Despite their different emphases, both the resource-based view and

organizational economics have gained considerable currency in recent years in explaining

interfirm cooperation and performance effects of network activities (Combs & Ketchen 1999;

Conner & Prahalad 1996; Markides & Williamson 1996; Roth & O’Donnell 1996).

However, there is a striking imbalance of studies researching the beneficial effects of network-

ing compared with those few that focus on potential downsides of interfirm collaboration (Al-

varez & Barney 2001; Baum et al. 2000; Labianca & Brass 2006; Parkhe et al. 2006). Podolny

and Page (1998: 66) observe that the “attention to the functionality of network forms of orga-

nization explains why economic actors rely on network forms of organization, but it does not

explain why they do not.” Even fewer studies investigate downsides of networking in the con-

text of SMEs (Alvarez & Barney 2001; Baum et al. 2000), although SMEs face specific chal-

lenges when engaging in interfirm collaboration. Accordingly, the phenomenon of what we

term “network skepticism” in SMEs remains largely unexplored. The scarce range of results in

the literature indicates that small firms’ reservations against cooperations are triggered by dif-

ficulties in finding adequate partners, the management’s vision of maximum autonomy, a

strong focus on conservative firm traditions, or a lack of trust towards larger partner firms (Al-

varez & Barney 2001; Baum et al. 2000; Hausschild & Wallacher 2003; Figure 1).

2 For this study, a network is defined as a durable form of interfirm cooperation that is created and maintained by joint history and ongoing collective action, that is underpinned by a strategic orientation, a sense of common interest, and the expectation of gains (similar, Olsen 1965). The terms “network” and “cooperation” are used interchangeably.

4

Figure 1: Reasons for Skepticism towards Cooperation.

However, these concerns are by no means exhaustive, and their prevalence and decision rele-

vance will be contingent on contextual factors inside and outside the firm. An adequate under-

standing of concerns in SMEs is required both for explaining network formation, functioning,

and evolution in theory, as well as for successfully organizing, managing, and governing coop-

erations in practice, among and including SMEs. Yet still, in the current body of organiza-

tional literature, insights on the phenomenon of SME network skepticism are notably sparse.

In an effort to shed some light on the nature and prevalence of such skepticism, we posit that

H1: A firm’s strategic tendency to network is contingent on firm-specificbenefits, and particularly, costs associated with interfirm relationships.

In addition, alliance research indicates that some firms have constantly greater success with

using cooperative arrangements than other firms (Schreiner et al. 2009). Scholars have sug-

gested that successful cooperation depends on firms’ superior abilities to manage interfirm

relationships, that is, on superior “alliance capabilities” (Anand & Khanna 2000; Ariño & De

la Torre 1998; Doz 1996; Dyer & Singh 1998; Ring & Van de Ven 1994). Often, the most

critical challenges in these relationships, “problems of cooperation” and “coordination prob-

lems” (Gulati et al. 2005; Mellewigt et al. 2007), result from uncertainties towards the “true”

5

motivations of partners (Axelrod 1984; Das & Teng 1998; Khanna et al. 1998; Parkhe 1993;

Williamson 1985) and from task interdependence (Borys & Jemison 1989; Gulati & Singh

1998; Litwak & Hylton 1962). Some studies argue that these challenges can be addressed at

the network formation stage – by choosing the “right” partners (Hitt et al. 2000), appropriate

contracts, and adequate governance structures (Argyres & Mayer 2007; Hennart & Zeng

2005; Mayer & Argyres 2004; Reuer & Ariño 2007; Schreiner et al. 2009). Yet, as the net-

work lifecycle unfolds, alliance management capabilities become all the more important; ulti-

mately, those cooperations turn out successful that are able to dynamically adapt and fine-tune

network processes over time. In consequence, research has stressed the significance of three

distinct firm capabilities – coordination, communication, and bonding – in managing any al-

liance successfully (Hansen et al. 2008; Schreiner et al. 2009).

First, alliance management capability entails a firm having the ability to coordinate and man-

age interdependence between partners (Schreiner et al. 2009). It involves the ability to iden-

tify and build consensus about task requirements, to specify the roles and responsibilities of

each participant in task execution, and to adapt internal and interfirm procedures when cir-

cumstances change (Lawrence & Lorsch 1967; Gulati et al. 2005; Schreiner et al. 2009;

Thompson 1967). Second, communication as “the formal as well as informal sharing of mean-

ingful and timely information between firms” (Anderson & Narus 1990: 44) represents the

“glue” that holds an alliance together, and entails a firm having the know-how and skills to

convey relevant knowledge and information about itself to the partners in a timely, accurate,

and complete manner (Schreiner et al. 2009). Third, the bonding dimension includes provid-

ing reliable responses to a partner’s work-related needs, being proactively responsive to their

concerns, attending seriously to their views, ideas, and circumstances to signal respect and

appreciation for the other, and evoking norms of reciprocity (Granovetter 1973; Harrison et al.

1998; Schreiner et al. 2009). In sum, firm capabilities can help SMEs manage relationships

successfully, and capabilities may also ease managers’ concerns towards cooperations and the

restraining effects of these concerns’ on their cooperation decisions. Hence, we posit that

H2: A firm’s strategic tendency to network is contingent on its capabilities to man-age coordination, communication, and bonding needs in interfirm relationships.

3. Methods

We apply a three-stage procedure to investigate sources and consequences of network skepti-

cism in SMEs. First, to examine the nature of network skepticism in SMEs in more detail, we

use a case study approach (Study I). Past research highlights that an area where case studies 6

are particularly relevant is when analyzing the development of particular organizational forms

(Eisenhardt 1989; Rubin & Dnes 2010). For this study, two researchers conducted two-hour

interviews with CEOs from ten SMEs. We used semi-structured questionnaires that asked for

general information on the firm; for current cooperations and network activities; for (dis)ad-

vantages of cooperations in general; for benefits the firm had sought and could (not) realize in

cooperations, and for any concerns and disadvantages the firm associated with their network

activities; and for partner selection, control and governance mechanisms. Respondents were

also offered the opportunity to advance on specific issues they considered important (Jick

1979; Yin 2003). To approach the topic from various perspectives, we select firms from three

different backgrounds and present their summarized interview information below. Yet, there

are important drawbacks to case research, including the limited generalizability of findings,

and potential ambiguity of cause-effect relationships. Large-sample survey techniques can

overcome such shortcomings; however, they do not permit to gather information on theoretical

constructs which are not well understood, as is the case with network skepticism. Hence, we

combine both approaches, integrating findings from case research and survey data.

Thus second, we use a survey approach (Study II and III), to examine the prevalence and ef-

fects of network skepticism in depth. We hand-collected a data set of German SMEs listed in

the Hoppenstedt online firm directory. Firms were classified as “SMEs” according to the Eu-

ropean Union Commission’s definition – based on the number of employees (500 max.), an-

nual revenues (€50m max.) and the balance sheet total. We randomly selected 2000 firms

from the list, including diverse industries like production, construction, retail, and information

services. In August 2011, self-administered questionnaires with a personalized cover letter

that offered a university contact and a complimentary report of results were distributed among

these firms. The questionnaires targeted one highly ranking strategy executive. Following the

procedures to ensure data validity described by Campbell (1955), Kumar et al. (1993), and

Schreiner et al. (2009), we identified these individuals using two criteria – the possession of

sufficient knowledge about their firm’s network activities, and an adequate level of involve-

ment in the issues under investigation. Based on Kumar et al. (1993) and Schreiner et al.

(2009), we use these validation items: (1) How long the informant had been working for the

firm, (2) How knowledgeable she deemed herself about her own company and its product/ser-

vice program, and (3) How knowledgeable she deemed herself regarding the collaboration

management practices and the collaboration partner (item 1 measured in years; items 2 and 3

on a four-point Likert scale anchored by 1 – “Very low knowledge”; 4 – “Very high knowl-

edge”). The mean response for the first item was 10.8 years (standard deviation (SD) 6.7

7

years); for the second and third items 3.23 (SD 0.41) and 3.56 (SD 0.33). All the respondents

indicated to command knowledge about their firm’s network activities and its partner firms

equal or greater than two on the four-point scale. 57% of respondents were either CEOs or

board members; 43% were executives in strategy-related positions such as marketing, sales or

alliance managers. Based on previous research (Combs & Ketchen 1999; Schreiner et al.

2009), the questionnaire asked respondents for company-specific data (firm age, size, scope,

industry, management team composition, finances, investments, firm reputation, alliance ca-

pabilities developed over time (Appendix), partner firms, current network involvement); for

cooperation benefits the firm had sought and (not) realized; for concerns and disadvantages

the firm associated with their network activities, and for these concerns’ relative importance;

and for partner selection, control and governance mechanisms. The exact formulation of the

questionnaire was tested in a qualitative-explorative pre-study involving case study intervie-

wees and five SME researchers. In three rounds of follow-up calls, non-respondents were con-

tacted for telephone interviews. Responses were collected until October 2011. 348 responses

could be used for the analysis (response rate 17.4%). To test for nonresponse bias, we com-

pared early and late respondents in terms of demographic characteristics and other key vari-

ables in the study (Kumar et al. 1993). In addition, we compared respondents with a random

sample of 75 nonrespondents on firm age, industry, and number of employees. Both compar-

isons did not reveal significant differences, indicating that nonresponse was not an issue. We

further controlled for common method bias in the self-reported variables using Harman’s sin-

gle factor test. The test yielded more than one factor, no factor accounted for most of the vari -

ance (the variance explained by the largest eigenvalue was 26%); thus, according to Podsakoff

et al. (2003), common method bias was not an issue either.

Based on the sample SMEs’ responses, first, we provide descriptive statistics on network in-

volvement and on the prevalence of various concerns associated with interfirm relationships

(Study II). Then, we estimate a Polytomous Logit Universal Model (PLUM; an extension of

the general linear model to ordinal categorical data) that reveals firm-specific and coopera-

tion-specific attributes that drive a firm’s decision to engage in versus remain skeptical of

networking (Study III). Here, the dependent variable is the intensity of network involvement

displayed by each firm. From a modeling perspective, this variable is an inherently ordered

multinomial-choice variable. Accordingly, the model is estimated by maximum likelihood and

takes the following form:

Y i=β ' x i+ui with (i = 1, 2, … , n)

8

where Y represents the underlying response variable, x is set of exogenous variables, ui is the

residual. An observation belongs to the jth category if

α j−1<Y≤α j with (j = 1, 2, …, m)

Then, the probability of belonging to a certain category j is given by

Prob (Y= j|x i)=Φ( α j−β ' xi)−Φ(α j−1−β ' x i)

where Φ

stands for the cumulative standard normal distribution. Using a dichotomous vari-

able Zij, which takes a value of 1 if Yi falls in the jth category and a value of 0 otherwise, the

likelihood function can be defined as:

L=∏i=1

n

∏j=1

m

[Φ (α j−β ' x i )−Φ (α j−1−β ' x i )]Z ij

Maximizing the latter equation yields the model’s parameters that help to determine the prob-

ability (Maddala 1983) that a firm displays a certain network involvement.

Thereby, Study I and II provide insights on the nature and prevalence of network skepticism

(in line with H1), Study III investigates determinants of the extent of SME network involve-

ment including SME alliance capabilities (as summarized by H2).

4. Study Results

4.1. Study I: Case Studies

First, to understand the nature of network skepticism in SMEs in more detail, we conducted in-

depth interviews with SME CEOs as described above. Below, we present information gathered

from three firms from different backgrounds to approach the topic from multiple perspectives.

Firm A is a German public company specialized in debt collection, particularly debt arising

from internet services. The company has 50 employees and a total of €5m revenues per year.

The firm is actively involved in a (pre-existing) network of debt collecting firms. The primary

purpose of the network is to provide some additional services to clients that the firms could

not provide solitarily. Firm A is particularly interested in partners that are active in cross-bor-

der operations. Firm A often hands international debt collection mandates over to these firms’

foreign subsidiaries, in return for a (nominal) percentage of profits from the mandate or some

other service performed by Firm A. The greatest risk involved in this form of cooperation, that

had become a substantial problem in the past, was that Firm A lost the “lead” on clients whose 9

debt collection had been handed over. Some clients took their future outstanding bills directly

to the subsidiary firms, so that Firm A lost considerable business. This loss of control had

made Firm A reluctant towards further cooperation. Also, Firm A thought that over time, time

and capital investments needed for coordination activities had grown considerably. Repeat-

edly, Firm A terminated cooperations as company cultures and codes of conduct in doing busi-

ness would cause conflicts, or as a partner would not be honest in keeping agreements. Still,

over the last years, Firm A had tried to select and develop relationships with a few trusted

partners. From Firm A’s perspective, the central factor for network functioning was that the

goals pursued through joint action were clearly spelled out. Although losing influence in the

network, or domineering partner firms, were concerns for Firm A, these were acceptable as

long as existing agreements were kept. Firm A was not concerned about know-how drain, as

from Firm A’s point of view, any “clever” company could gather the desired knowledge in the

market anyway. Yet, Firm A believed that this attitude would rather not be representative of

their industry. In sum, Firm A had joined a pre-existing network and actively developed a se-

lect few relationships over time; the main aim was gaining access to others’ international ex-

perience; and the risk of losing clients, uncertain gains, and coordination costs were Firm A’s

major concerns – particularly, as Firm A is still young and resources are sparse.

Firm B is a family firm with 200 employees and a long tradition in sheet-metal forming and

producing components for automotive suppliers. The family holds both management and own-

ership of the firm. At the beginning of the interview, Firm B’s CEO emphasized that Firm B

would, on principle, not engage in any cooperation. The main reason was that the firm gener-

ates its revenues from superior technical know-how, which needed all the protection it could

get. In addition, in the past, the firm had been “forced” into cooperating by a major customer

once, leading to a substantial know-how drain after external employees had been allowed in-

side the firm and quality control was organized jointly. Some cooperation partners later used

the know-how gained from Firm B for their own operations. Firm B was aware of the exis-

tence of numerous cooperations in their industry. They believed that the major benefit of these

cooperations was improving firms’ abilities to expand. As Firm B had no expansion plans,

they found they could “afford” not to cooperate. Also, the German certification system that

applies to many components used in automobile manufacturing “protected” the industry from

new competitors, and Firm B had never failed to meet certification requirements, so that cus-

tomers often placed long-term orders with Firm B. Therefore, Firm B believed their market

position to be secure. Apart from the fear of know-how drain, Firm B was also concerned that

internal data on cost calculations could leak out to partners or customers. In particular, if oth-

10

ers found out that Firm B used proprietorial financing only, they would demand lower prices

from Firm B, as Firm B obviously did not pay interest for external financing. In sum, unlike

others in the industry, Firm B would not enter cooperations, as gains were considered rela-

tively unimportant and concerns of know-how drain and sensitive data leaking out were se-

vere.

Firm C is a distributor of electrical equipment with over 400 employees in various locations

across Germany. For some time, Firm C had actively worked on forming a network that pur-

sued bulk purchase savings for its members. The network was still growing, and new firms

were welcome to join in, but only if they held a comparably strong market position as the

companies already cooperating. Firm C thought the risks involved in this cooperation to be

uncritical, yet the loss of autonomy caused by joint ordering was seen as a “nuisance”, in addi-

tion to the fact that some network members would grow faster than others and encroach on

others’ customers. From Firm C’s perspective, the latter problem was a natural one as the

stated purpose of the cooperation was to help members grow and become more competitive.

Besides, Firm C indicated concerns of legal problems related to cartelization. What made their

cooperation work, in Firm C’s opinion, was frequent and open communication. In particular,

any secret side-agreements among suppliers and some firm would undermine trust, and even-

tually lead to an expulsion of that firm from the cooperation. Fairness was supported by “con-

tracts” expressing each firm’s goodwill in joint dealings. In sum, Firm C was active in forming

a network that pursued cost reductions for its members, and for Firm C, all concerns towards

cooperations were of minor relevance in face of the realized efficiency gains.

The case study data already indicate that in practice, SME involvement in cooperative rela-

tionships varies substantially. Firms seek diverse benefits by engaging in cooperations, be

those in line with the RBV or OE predictions, and anticipate different relationship downsides

or “costs”, which affects their tendencies to network. Thereby, the case study data lend some

support to H1. To investigate the nature and prevalence of network skepticism in more detail,

Study II explores SME concerns and expectations towards network membership in depth,

based on a sample of 348 German SMEs.

4.2. Study II: Descriptive Empirical Analysis

Previous literature has described the network lifecycle in stages, ranging from firms’ initial

interest to cooperate, a search for adequate partners, network formation, participation, renego-

tiation and network evolution, to network dissolution (Becker 1999; Möller 2006; Parkhe et al.

2006; Schäper 1997). Based on the literature, we distinguish five stages through which firms’ 11

network involvement can develop over time (Figure 2): (1) the firm has a general interest to

cooperate; (2) the firm undertakes efforts to form or join a network; (3) a network was actually

created or the firm joined a network; (4) the firm actively participates in a network, (5) the

firm’s network is constantly adapted and has evolved over time. Following this classification,

we first examine the sample firms’ involvement in networking activity (as of summer 2011).

Figure 2. Involvement in Cooperations in the Sample.

First, as indicated by the case study data, the sample survey results establish that SMEs, in

practice, show very different tendencies to collaborate (Figure 2). Although 89% of the sample

firms claim an interest in cooperating, only 58% are actually engaged in interfirm relation-

ships, and only 31% of the sample firms participate in a network that is functioning well

enough so that it can evolve and adapt over time.

Next, for each stage in the network lifecycle, the concerns that keep firms from engaging in

more intense relationships and their relative importance (seven-point scale, 1 – “Not strong”, 7

– “Very strong”) are displayed below (Figure 3). In the following, we pool those firms that

claim an interest in networking, or an uptake of efforts that however, have not led to any net-

work membership (stages 1 and 2). These firms, unlike others, have not committed to more

intense activities. We term these firms “network skepticists”. We exclude all those firms that

deny any interest in interfirm relationships (like Firm B above) from future analysis, as these

firms cannot be considered as “skepticists”, which leaves a total of 309 SMEs.

Among these 309 firms, the network skepticists fear risk-and management-related problems

most – particularly, they are concerned about know-how drain in cooperations, about losing

sensitive data, and about being exploited by opportunistic partners. Also, due to a lack of expe-

rience, they question their abilities in managing cooperation and competition at the same time.

Firms in the third stage, that belong to a network as “nominal” members rather as they do not

participate in activities intensely, forward profit-and partner-related reasons for their inactivity.

According to the survey results, identifying adequate partners is a major problem for these

firms, as is uncertainty about expected gains from cooperation. Network participants in the

fourth stage forward partner-and risk-related reasons for investing little into developing and

adapting their relationships over time. On the one hand, firms in the fourth stage share the em-12

phasis on risk-related concerns – risks associated with specific investments and hold-up – with

network skepticists (stages 1 and 2); on the other hand, partner-related concerns of costly con-

flicts and overly complex decision-making processes are highly relevant to both the firms that

belong to stage 4 and 5. Besides, firms in stage 5 (network evolution) may believe their current

relationships suffice, so there is no need for additional cooperation.

Figure 3. Concerns towards Network Activities in the Sample.

13

Next, we concentrate on two groups – those firms that engage in network activities (stages 3-5)

and the network skepticists (stages 1 and 2). Interestingly, the advantages of networking are

perceived relatively similar among both groups, even if network skepticists show a strong fo-

cus on resource-related considerations, while network participants consider efficiency-related

benefits as well (Figure 4). Yet, the most relevant concerns associated with interfirm relation-

ships, which restrain the skepticists’ from more intense cooperation, are largely different.

Figure 4. Perceptions of Advantages and Disadvantages of Cooperation.

14

Last, by summing up the major barriers to networking in each of the respective stages as per-

ceived by the sample SMEs, Figure 5 provides an overview of Study II results. It also offers

some implications for the underlying reasons of why these concerns occur, which in turn helps

with their management. Whereas Study I has focused on the nature of cooperation benefits and

costs on the individual firm level, Study II shows commonalities as regards networking bene-

fits and concerns among network skepticists, and among firms in other stages of the network

lifecycle. By demonstrating that firms associate diverse benefits and particularly, costs with

interfirm relationships, and accordingly, they display different tendencies to cooperate, both

Study I and II provide support for H1.

Figure 5. Summary of Study II Results.

15

4.3. Study III: PLUM Regression

H2 argues that firms’ tendencies to cooperate are contingent on their alliance capabilities.

Highly capable firms can “benefit more” from networking than others less well prepared. As

there are no perfect proxies or secondary data on a firm’s alliance management capability (Gu-

lati 1998), in line with previous research, we relied on key informants’ assessments to collect

relevant data (Schreiner et al. 2009), as outlined above. The variables are described below.

Dependent Variable: Interfirm Cooperation

Again, we use the five lifecycle stages that describe the current network involvement of firms

(Figure 2) – (1) the firm has a general willingness to cooperate, (2) the firm undertakes efforts

to form or join a network, (3) a network was actually created or the firm joined a network, (4)

a firm actively participates in network, and (5) the network in which the firm participates

adapts and evolves over time. “Network skepticists” select stage 1 or 2. Focusing on that par-

ticular cooperation which respondents evaluate to be most central to their business, “network

participants” indicate the latest stage of network involvement their firm has currently reached.

Independent Variables: Capabilities (see Appendix).

Coordination dimension. Following Schreiner et al. (2009), we use four items from previous

literature on organization theory (Thompson 1967) and alliances (Gulati & Singh 1998). These

items reflect whether a firm has previously developed processes designed to coordinate activi-

ties, including the adaptation of work processes and incentive structures. For all the variables

measured by multiple items, we build scales by summing and averaging item scores.

Communication dimension. Five items from research on communication in alliances (Das &

Teng 1998; Mohr & Spekman 1994; Schreiner et al. 2009) reflect whether a firm has devel-

oped skills to explain its market position, competency, and value propositions to partners.

Bonding dimension. Six items from organizational literature (Kahn 1993; Kim & Mauborgne

1998; Schreiner et al. 2009) reflect whether a firm has developed attentive, supportive behav-

ior towards partners, like willingness to support in difficult times in their relationships.

Control Variables related to the RBV.

Brand name reputation. SMEs without brand reputation may either engage in cooperation in-

tensely to gain credibility; or, they may cooperate less, e.g. due to difficulties in attracting part-

ners. Following Combs and Ketchen (1999), we measure reputation by four items on seven-

point Likert scales: Comparing this company to competitors, (1) How well respected is this 16

company? (1 – “Not respected”, 7 – “Very respected”); (2) How good of a value is this com-

pany perceived to provide for the price? (Not good/Very good); (3) How strong is this com-

pany’s reputation for consistent quality and service? (Not strong/Very strong); and (4) How

strong is this company’s brand name recognition in its area of activity? (Not strong/Very

strong).

Management team experience. An experienced management team (MT) can be a strategic re-

source (Justis & Judd 1989; Shook & Shook1993). Depending on the amount of managerial

talent already present in the firm, cooperation may be more or less attractive (Bradach 1997;

Shane 1996). Following Combs and Ketchen (1999), MT experience is measured by the num-

ber of years of executive-level industry experience of each SME’s management team.

Slack capital. Scarcity of slack capital has been shown to increase using networks, e.g. joint

ventures and franchising (Martin & Justis 1993). Following Hambrick and D’Aveni (1988) and

Combs and Ketchen (1999), we measure each SME’s equity-to-debt ratio, as of 2009.

Control variables related to OE.

Asset specificity. If assets exist that are required for working together (e.g. technical adjust-

ments in production) and that cannot be easily transferred to alternative uses, partners are

likely to continue to cooperate to recover their investments, which can increase the efficiency

of joint action (Combs & Ketchen 1999; Dyer & Singh 1998). The extent of specific assets is

measured by three items on seven-point Likert scales (Combs & Ketchen 1999): Comparing

this company to competitors, (1) Is equipment for working together customized? (1 – “None

at all”, 7 – “Very much”); (2) Would it be difficult to adjust production processes when coop-

erating with a new partner? (Not difficult/Very difficult); and (3) Would it be difficult to use

this firm’s equipment for another business? (1 – “Not difficult”, 7 – “Very difficult”).

Specific knowledge. Specific knowledge is often tacit or complex (Polanyi 1962; Shane 1998).

Its transfer entails costs that discourage cooperation (Jensen & Meckling 1995; Kogut & Zan-

der 1992). The variable is measured by four items on seven-point Likert scales (Combs &

Ketchen 1999): Comparing this company to competitors, (1) How long would it take to train

competent managers? (1 – “Not long”, 7 – “Very long”); (2) How long would it take to train

competent employees? (Not long/Very long); (3) How difficult would it be to communicate

job requirements to mid-level managers? (Not difficult/Very difficult); and (4) How difficult

would it be to include all of the mid-level manager’s job tasks in a manual? (Not difficult/

Very difficult).

17

Geographic dispersion. As dispersion increases the costs of monitoring fully-owned opera-

tions, it renders cooperation more attractive (Windsperger & Dant 2006). Dispersion is mea-

sured as the number of countries where an SME was doing business in 2009 (Combs &

Ketchen 1999; Lafontaine 1992).

Additional Controls.

A long-term relationship may have already passed through a critical shakeout period, charac-

terized by conflict and renegotiations, after which parties may develop a higher level of joint

action (Heide & Miner 1992; Parkhe 1993). We measure relationship duration as the years of

a firm’s involvement in the cooperation under investigation (Combs & Ketchen 1999). Al-

though by definition, SME size does not vary dramatically, it may still affect the relative SME

attractiveness for potential partners (Heide & John 1990). Size is measured as the number of

employees in 2009. Industry may have an effect on cooperation intensity, as needs and risks

vary across industries (products – 0, services – 1). Table 1 displays descriptive statistics, Ta-

ble 2 shows regression results.

18

Table 1. Descriptive Statistics.

Variable Mean Std. Dev.

Dep. Variable: Networking Stage 3.33 1.51

Capabilities: Coordination 4.30 2.25 0.37***

Communication 4.90 2.05 0.27*** 0.19***

Bonding 4.28 2.25 -0.13* -0.08 -0.01

RBV Controls: Brand Reputation 4.05 2.24 -0.26*** -0.17** -0.09† 0.05

Management Experience 19.45 11.39 -0.22*** -0.12* -0.07 0.04 0.22***

Slack Capital 3.88 2.17 -0.24*** -0.14* -0.10† 0.16** 0.16* 0.21***

OE Controls: Asset Specifity 4.29 2.14 0.17** 0.06 0.05 -0.12* -0.02 -0.05 0.14*

Specific Knowledge 4.14 2.27 -0.26*** -0.06 -0.10† -0.11† 0.04 0.15** 0.19** -0.14*

Dispersion 4.47 2.09 0.05 0.05 0.10† -0.03 -0.08 -0.19** -0.04 0.05 -0.06

Other Controls: Relationship Duration 5.47 2.95 0.23*** 0.13* 0.07 -0.16** -0.07 -0.04 -0.16** 0.12* -0.16*** 0.03

Firm Size 262.78 143.81 0.07 0.01 0.10*** 0.03 -0.08 --0.14* -0.10† 0.00 -0.07 0.05 0.08

Industry 0.17** 0.15** 0.14* -0.16** -0.13* -0.13* -0.23*** 0.11† -0.11* 0.16** 0.07 0.05

Significance levels (two-tailed): *** p < 0.001; ** p < 0.01; * p < 0.05; † p < 0.1.

19

Table 2. PLUM Results.

Model a Model b

Coefficient(Std. Error)

Coefficient(Std. Error)

Capabilities: Coordination 0. (0.

274***051)

Communication 0. (0.

207***054)

Bonding -0. (0.

047050)

RBV Controls: Brand Reputation -0. (0.

178***050)

-0. (0.

151**051)

Management Experience -0. (0.

013**005)

-0. (0.

013*005)

Slack Capital -0. (0.

122*053)

-0. (0.

109*054)

OE Controls: Asset Specifity 0. (0.

134**051)

0. (0.

124*053)

Specific Knowledge -0. (0.

163**050)

-0. (0.

173**051)

Geographic Dispersion -0. (0.

018050)

-0. (0.

039053)

Other Controls: Relationship Duration 0. (0.

055**019)

0. (0.

030*019)

Firm Size 0. (0.

000000)

0. (0.

000000)

Industry 0. (0.

305†221)

0. (0.

142†210)

F 81.007*** 125.133***

Nagelkerke Pseudo-R2 0.243 0.411

N 301 301

Significance levels (two-tailed): *** p < 0.001; ** p < 0.01; * p < 0.05; † p < 0.1. Hit rate: 81.4% of cases classified correctly.Firms that had not entered in any business relationships in the last three years excluded from this analysis.

20

The PLUM results document that those firms that have high coordination and communication capabilities, as predicted by H2, engage in more in-

tense cooperation. Yet, bonding capabilities appear to decrease network involvement rather (but the coefficient is insignificant); eventually, given

that firms’ capability perceptions are accurate, those firms scoring high on bonding capabilities are more easily exploited by opportunistic partners.

Hence, for these firms, risks associated with cooperations may become all the more pronounced.

As regards the RBV controls, a strong brand name is related to low networking activity, which may result from efforts to protect the firm’s brand

image, or as holding a strong market position decreases the need for acquiring resources (e.g., concerning legitimation needs or access to market

channels) through cooperation. A negative relationship also holds for management experience and slack capital – the more experienced the manage-

ment, and the higher slack capital, the lower the tendency to cooperate. Again, resource needs may be tolerable, and as many potential partner firms

will score lower on experience and capital resources, their value proposition may appear unattractive for high-scoring firms. As regards the OE con-

trols, the higher asset specifity, the higher cooperation activity. As specific investment increases the credibility of the firm’s willingness to cooperate,

it decreases the need for costly control, enabling more efficient exchange among partner firms. Specific knowledge, in turn, decreases the firm’s ten-

dency to network. As transferring specific knowledge is time-consuming and costly, cooperation may prove less efficient and thus less attractive

compared with hierarchical, internal operations. Thereby, both theories’ predictions play a central role in SME cooperation decisions. Besides, the

longer a relationship has been in place, the more intense are networking activities; time investment, intuitively, concurs with network evolution.

5. Discussion

Irrespective of the widespread belief that networks provide the most decisive benefits, there is a striking imbalance of studies researching the benefi-

cial effects of networking compared with those few that focus on potential downsides of interfirm collaboration. Yet in practice, particularly SMEs

often remain skeptical of interfirm cooperation. Based on qualitative case study information and quantitative data from a sample of 348 German

SMEs, we investigate the phenomenon of “network skepticism” in SMEs, focusing on its nature, prevalence, and effects.

21

We find that SME managers’ tendencies to network depend partly on the specific benefits, but particularly, on the specific costs associated with en-

gaging in interfirm relationships. Although the anticipated benefits and costs are firm-specific, there are some commonalities among those firms that

can be classified as currently belonging to the same stage of the network lifecycle. For those SMEs that do not actively engage in network relation-

ships, the “network skepticists”, barriers to network entry appear to be mostly management-related – many of these firms question their competen -

cies in handling cooperation and competition at the same time. Network skepticists’ concerns are also risk-related – they often refer to the risk of

know-how drain inherent in collaborations, and to their fear of exploitation by opportunistic partner firms. Whereas for both the two groups of net -

work participants and network skepticists, the advantages associated with networking are similar, the perception of disadvantages largely diverges –

which is particularly interesting in light of the fact that the costs of networking have rarely been explored in the literature (Lavie 2006; Parkhe et al.

2006; Podolny & Page 1998). Our findings highlight the significance of cost considerations for decisions to engage in versus to avoid cooperative

arrangements. We can also establish that both resource-related considerations, as argued by the RBV, and cost or efficiency-related considerations as

argued by OE, play a strong role in SME cooperation decisions.

Effects of cooperation concerns on managers’ decisions to engage in or to refrain from networking may further depend on each firm’s alliance man-

agement capabilities. We observe that firms that have developed strong coordination capabilities over time show higher network involvement than

firms that are less well prepared. Along the same lines, research on alliance performance has argued that due to the divided authority structure and

the physical, cognitive, and cultural distance between partners, alliance functioning and performance suffers from inappropriate interfaces and

boundary-spanning mechanisms, unclear procedures, responsibilities, and loci of control (Doz 1988; Larson 1992; Mohr & Spekman 1994;

Schreiner et al. 2009). In consequence, coordination failures impede concerted actions needed to capitalize on the specialized, but interdependent,

activities of network partners (Thompson 1967). As the cost of failed coordination may even exceed the benefits of cooperation, firms need adapt -

able mechanisms, including procedures, rules and policies, to create an appropriate framework for future interaction (Schreiner et al. 2009). We also

find that firms that have developed communication capabilities engage more actively in networks than others that lack such competency. Similarly,

previous literature has argued that adversarial effects of information asymmetry are intensified by a lack of adequate communication between net -

22

work partners, which prevents them from building a shared understanding of their obligations, from developing shared mental models of how to

work together, as well as from mitigating adversarial group dynamics and managing conflict (Borys & Jemison 1989; Larson 1992; Mohr &

Spekman 1994; Schreiner et al. 2009). Inadequate communication makes it also difficult for firms to assess the value creation opportunities within a

particular relationship (Ring & Van de Ven 1994). Particularly, skills in lateral communication are required to sustain and adapt partnerships through

ongoing renegotiations of initial agreements (Schreiner et al. 2009). Our results support this claim.

Yet, contrary to expectation in the literature, unlike high coordination and communication capabilities, bonding capabilities do not promote intense

networking. Previous research suggests that close personal relationships serve as a conduit for creating expectations of mutual cooperation, for de-

veloping trust and reciprocity, and for facilitating knowledge-sharing (Granovetter 1973; Gulati 1995; Kale et al. 2000; Larson 1992; Ring & Van de

Ven 1994; Yli-Renko et al. 2001). On the upside, interpersonal bonds can also facilitate conflict resolution, secure the adaptation and execution of

long-term exchange, and foster continuity (Schreiner et al. 2009). On the downside however, high bonding abilities may also increase the risk of

exploitation and hold-up by opportunistic partner firms, so this capability may not come as constantly useful.

In sum, our findings document the importance of developing coordination and communication capabilities in the early stages of cooperations, to

form realistic expectations of relevant benefits and risks in joint activity and implement adequate collaborative strategies. In the initial phase of net-

working, establishing a culture of cooperation with clear goals, roles and responsibilities, can promote successful start-up of collaborative arrange-

ments. The more intense networking involvement gets, the higher the perceived risk of costly conflicts becomes. In consequence, governance and

integration mechanisms in the network become increasingly important to capitalize on the specialized, interdependent activities of firms. Among the

sample firms, 45% stated that in their experience, integration and coordination of activities was achieved best by joint meetings of all the firms in -

volved. Another 10% declared that one or more firms took the lead in organizing activities. 17% explained that their network had an organizing

committee of employees from the participating companies that would orchestrate activities. Interestingly, 8% believed that for fairness reasons, the

best coordination device ever used in their network was an external committee, paid jointly by all network members, that would allocate, regulate

and help fine-tune activities among the firms. Here, some potential for more professionalized cooperation management may still remain untapped.

23

To conclude, this study takes a step towards developing a more comprehensive picture of network involvement of small and medium-sized firms by

opening up the black box of sources and effects of network skepticism in SMEs. However, there are numerous limitations to this research. Fore -

most, the analysis partly relies on self-reported data. To guard against the issues related to such data, we use a three-stage methodological approach,

apply previously validated scales and numerous control variables, and check for common method bias. Additionally, to reduce the risk of reversed

causality (Study III), capabilities are related to managers’ previous experience with their respective firm, and the tendencies to network are mea-

sured by the current efforts to cooperate. We suggest that reversed causality is uncritical as the current networking efforts do not allow changing

firm capabilities in an instant, but capabilities develop over time and the current tendencies to network are an outcome of this developmental process

(and of resource and efficiency-related considerations), rather than that the developed capabilities could all be an outcome of current cooperation

efforts. Yet still, networking and developing capabilities will, of course, to some extent co-evolve. Here, using longitudinal and dyadic data could

provide further insights on capabilities-building and on forming and (re)negotiating relationships in SMEs. Besides, while economic rationales are

appropriate to explain governance choices in light of exchange hazards (Cochet & Ehrmann 2007), incorporating concepts from cross-disciplinary

studies on organizational and individual embeddedness, ethics, fairness, or social distance, can be equally useful to understand the evolution and

termination of relationships structures among and including SMEs.

24

References

Alvarez, S.A. and J.B. Barney (2001). How entrepreneurial firms can benefit from alliances with large partners, Academy of Management Execu-tive 15, 139-148.

Anand, B.N. and T. Khanna (2000). Do firms learn to create value? The case of alliances, Strategic Management Journal 21, 295-315.

Anderson, J.C. and J.A. Narus (1990). A model of distributor firm and manufacturing firm working partnerships, Journal of Marketing 54, 42-58.

Argyres, N.S. and K.J. Mayer (2007). Contract design as a firm capability: An integration of learning and transaction cost perspectives, Academy of Management Review 32, 1060-1077.

Ariño, A. and J. De la Torre (1998). Learning from failure: Towards an evolutionary model of collaborative ventures, Organization Science 9, 306-325.

Axelrod, R. (1984). The evolution of cooperation, Basic Books: New York.

Barney, J.B. (2001). Resource-based theories of competitive advantage: A ten-year retrospective on the resource-based view, Journal of Manage-ment 27, 643-650.

Baum, J.A.C., T. Calabrese and B.S. Silverman (2000). Don’t go it alone – Alliance network composition and startups’ performance in Canadian biotechnology, Strategic Management Journal 21, 267-294.

Becker, N. (1999). Regelungsfelder für Unternehmensnetzwerke, Nomos: Wiesbaden.

Borys, B. and D.B. Jemison (1989). Hybrid arrangements as strategic alliances: Theoretical issues in organizational combination, Academy of Man-agement Review 14, 234-249.

Bradach, J.L. (1997). Using the plural form in the management of restaurant chains, Administrative Science Quarterly 42, 276-303.

Campbell, D.T. (1955). The informant in qualitative research, American Journal of Sociology 60, 339-342.

Cliquet, G. (2000). Plural forms in store networks: A model for store network evolution, International Review of Retail, Distribution and Consumer Research 10, 369-387.

Cliquet, G. and M.-N. Nguyen (2004). Innovation management with the plural form network, in: Windsperger, J., Cliquet, G., Hendrikse, G.W.J., Tuunanen, M. (Eds.), Economics and management of franchising networks, Physica: Heidelberg-New York, 109-125.

25

Cochet, O. and T. Ehrmann (2007). Preliminary evidence on the appointment of institutional solutions to franchisor moral hazard – The case of franchisee councils, Managerial and Decision Economics 28, 41-55.

Combs, J.G. and D.J. Ketchen (1999). Explaining interfirm cooperation and performance: Toward a reconciliation of predictions from the resource-based view and organizational economics, Strategic Management Journal 20, 867-888.

Conner, K.R. (1991). A historical comparison of resource-based theory and five schools of thought within industrial organization economics: Do we have a new theory of the firm? Journal of Management 17, 121-154.

Conner, K.R. and C.K. Prahalad (1996). A resource-based theory of the firm: Knowledge versus opportunism, Organization Science 7, 477-501.

Das, T.K. and B-S. Teng (1998). Between trust and control: Developing confidence in partner cooperation in Alliances, Academy of Management Review 23, 491-512.

Das, T.K. and B-S. Teng (2001). Trust, control, and risk in strategic alliances: An integrated framework, Organization Studies 22, 251-283.

Doz, Y.L. (1996). The evolution of cooperation in strategic alliances: Initial conditions or learning processes, Strategic Management Journal 17, 55-83.

Dyer, J.H. (1996). Specialized supplier networks as a source of competitive advantage: Evidence from the auto industry, Strategic Management Journal 17, 271-292.

Dyer, J.H. and H. Singh (1998). The relational view: Cooperative strategy and sources of interorganizational competitive advantage, Academy of Management Review 23, 660-679.

Eisenhardt, K. (1989). Building theory from case study research, Academy of Management Review 14, 532-550.

Gnyawali, D. and R. Madhavan (2001). Cooperative networks and competitive dynamics: A structural embeddedness perspective, Academy of Management Review 26, 431-445.

Granovetter, M.S. (1973). The strength of weak ties, American Journal of Sociology 78, 1360-1380.

Gulati, R. (1995). Does familiarity breed trust? The implications of repeated ties for contractual choice in alliances, Academy of Management Jour-nal 38, 85-112.

Gulati, R. (1998). Alliances and networks, Strategic Management Journal 19, 293-317.

Gulati, R. (1999). Network location and learning: The influence of network resources and firm capabilities on alliance formation, Strategic Manage-ment Journal 20, 397-420.

26

Gulati, R., P.R. Lawrence and P. Puranam (2005). Adaptation in vertical relationships: Beyond incentive conflict, Strategic Management Journal 26, 415-440.

Gulati, R. and H. Singh (1998). The architecture of cooperation: Managing coordination costs and appropriation concerns in strategic alliances, Ad -ministrative Science Quarterly 43, 781-814.

Hambrick, D.C. and R.A. D’Aveni (1988). Large corporate failures as downward spirals, Administrative Science Quarterly 33, 1-23.

Hansen, M.H., R.E. Hoskisson and J.B. Barney (2008). Competitive advantage in alliance governance: Resolving the opportunism minimization-gain maximization paradox, Managerial and Decision Economics 29,191-208.

Harrison, D.A., K.H. Price and M.P. Bell (1998). Beyond relational demography: Time and the effects of surface and deep-level diversity on work group cohesion, Academy of Management Journal 41, 96-107.

Hausschild, W. and L. Wallacher (2003). Ad-Hoc-Befragung über Unternehmenskooperationen – Ergebnisse für das Jahr 2003, Statistisches Bunde-samt: Wiesbaden.

Heide, J.B. and G. John (1990). Alliances in industrial purchasing: The determinants of joint action in buyer-supplier relationships, Journal of Mar-keting Research 27, 24-36.

Heide, J.B. and A.S. Miner (1992). The shadow of the future: Effects of anticipated interaction and frequency of contact on buyer-seller coopera-tion, Academy of Management Journal 35, 265-291.

Hendrikse, G.W.J. and J. Windsperger (2004). Introducing ‘economics and management of franchising networks‘, in: Windsperger, J., Cliquet, G., Hendrikse, G.W.J., Tuunanen, M. (Eds.), Economics and management of franchising networks, Physica: Heidelberg-New York, 1-13.

Hennart, J.F and M. Zeng (2005). Structural determinants of joint venture performance, European Management Review 2, 105-115.

Hesterly, W.S., J. Liebeskind and T.R. Zenger (1990). Organizational economics: An impending revolution in organization theory? Academy of Management Review 15, 402-420.

Hitt, M.A., T.M. Dacin, E. Levitas, J-L. Arregle and A. Borza (2000). Partner selection in emerging and developed market contexts: Resource-based and organizational learning perspectives, Academy of Management Journal 43, 449-460.

Jensen, M.C. and W. Meckling (1995). Specific and general knowledge, and organizational structure, Journal of Applied Corporate Finance 8, 4-18.

Jick, T. (1979). Mixing qualitative and quantitative methods: Triangulation in action, Administrative Science Quarterly 24, 602-627.

Justis, R.T. and R. Judd (1989). Franchising, Southwestern: Cincinnati.

Kahn, W.A. (1993). Caring for caregivers: Patterns of organizational caregiving, Administrative Science Quarterly 38, 539-563.

27

Kale, P., H. Singh and H. Perlmutter (2000). Learning and protection of proprietary assets in strategic alliances: Building relational capital, Strategic Management Journal 21, 217-237.

Khanna, T., R. Gulati and N. Nohria (1998). The dynamics of learning alliances: Competition, cooperation, and relative scope, Strategic Manage-ment Journal 19, 193-210.

Kim, W.C. and R. Mauborgne (1998). Procedural justice, strategic decision making, and the knowledge economy, Strategic Management Journal 19, 323-338.

Klein, B. and K.M. Murphy (1988). Vertical restraints as contract enforcement mechanisms, Journal of Law and Economics 31, 265-297.

Kogut, B. and U. Zander ( 1992). Knowledge of the firm, combinative capabilities, and the replication of technology, Organization Science 3, 383-397.

Kumar, N., L.W. Stern and J.C. Anderson (1993). Conducting interorganizational research using key informants, Academy of Management Journal 36, 1633-1651.

Labianca, G. and D.J. Brass (2006). Exploring the social ledger: Negative relationships and negative asymmetry in social networks and organiza-tions, Academy of Management Review 31, 596-614.

Lafontaine, F. (1992). Agency theory and franchising: Some empirical results, RAND Journal of Economics 23, 263-283.

Larson, A. (1992). Network dyads in entrepreneurial settings: A study of the governance of exchange relationships, Administrative Science Quar-terly 37, 76-104.

Lavie, D. (2006). The competitive advantage of interconnected firms: An extension of the resource-based view, Academy of Management Review 31, 638-658.

Lawrence, P.R. and J.W. Lorsch (1967). Differentiation and integration in complex organizations, Administrative Science Quarterly 12, 1-47.

Litwak, E. and L.F. Hylton (1962). Inter-organizational analysis: A hypothesis on coordinating agencies, Administrative Science Quarterly 6, 395-420.

Maddala, G.S. (1983). Limited-dependent and qualitative variables in econometrics, Cambridge: Cambridge University Press.

Markides, C.C. and P.J. Williamson. (1996). Corporate diversification and organization structure: A resource-based view, Academy of Management Journal 39, 340-367.

Martin, R.E. and R.T. Justis (1993). Franchising, liquidity constraints and entry, Applied Economics 25, 1269-1277.

Mayer, K.J. and N.S. Argyres (2004). Learning to contract: Evidence from the personal computer industry, Organization Science 15, 394-410.

28

McEvily, B. and A. Marcus (2005). Embedded ties and the acquisition of competitive capabilities, Strategic Management Journal 26, 1033-1055.

McGee, J.E., M.J. Dowling and W.L. Megginson (1995). Cooperative strategy and new venture performance: The role of business strategy and management experience, Strategic Management Journal 16, 565-580.

Mellewigt, T., A. Madhok and A. Weibel (2007.) Trust and formal contracts in interorganizational relationships – Substitutes and complements, Managerial and Decision Economics 28, 833-847.

Mohr, J. and R. Spekman (1994). Characteristics of partnership success: Partnership attributes, communication behavior, and conflict resolution techniques, Strategic Management Journal 15, 135-152.

Möller, K. (2006). Unternehmensnetzwerke und Erfolg – Eine empirische Analyse von Einfluss- und Gestaltungsfaktoren, Zeitschrift für betrieb-swirtschaftliche Forschung 58, 1051-1076.

Olsen, M. (1965). The logic of collective action: Public goods and the theory of groups, Cambridge: Harvard University Press.

Parkhe, A. (1993). Strategic alliance structuring: A game theoretic and transaction cost examination of interfirm cooperation, Academy of Manage-ment Journal 36, 794-829.

Parkhe, A., S. Wasserman and D. Ralston (2006). New frontiers in network theory development, Academy of Management Review 31, 560-568.

Peteraf, M.A. (1993). The cornerstones of competitive advantage: A resource-based view, Strategic Management Journal 14, 179-191.

Podolny, J.M. and K.L. Page (1998). Network forms of organization, Annual Review of Sociology 24, 57-76.

Podsakoff, P.M., S.B. MacKenzie and J.Y. Lee (2003). Common method biases in behavioral research: A critical review of the literature and recom-mended remedies, Journal of Applied Psychology 88, 879-903.

Reuer, J.J. and A. Ariño (2007). Strategic alliance contracts: Dimensions and determinants of contractual complexity, Strategic Management Journal 28, 313-330.

Ring, P.S. and A.H. Van de Ven (1994). Developmental processes of cooperative interorganizational relationships, Academy of Management Re-view 19, 90-118.

Roth, K. and S. O’Donnell (1996). Foreign subsidiary compensation strategy: An agency theory perspective, Academy of Management Journal 39, 678-703.

Rubin, P.H. and A.W. Dnes (2010). Managerial economics: A forward looking assessment, Managerial and Decision Economics 31, 497-501.

Schäper, C. (1997). Entstehung und Erfolg zwischenbetrieblicher Kooperation – Möglichkeiten offentlicher Förderung, Schriftenreihe des betrieb-swirtschaftlichen Forschungszentrums/Mittelstand Bayreuth.

29

Schreiner, M., P. Kale and D. Corsten (2009). What really is alliance management capability and how does it impact alliance outcomes and success? Strategic Management Journal 30, 1395-1419.

Shane, S.A. (1996). Hybrid organizational arrangements and their implications for firm growth and survival: A study of new franchisors, Academy of Management Journal 39, 216-234.

Shane, S.A. (1998). Making new franchise systems work, Strategic Management Journal 19, 697-707.

Shook, C. and R.L. Shook (1993). Franchising: The business strategy that changed the world, Prentice-Hall: Englewood Cliffs.

Teece, D.J. (1987). Profiting from technological innovation: Implications for integration, collaboration, licensing, and public policy, in Teece, D.J. (Ed), The competitive challenge, Ballinger: New York, 185-219.

Thompson, J.D. (1967). Organizations in action: Social science bases of administrative theory, McGraw-Hill: New York.

Uzzi, B. (1996). The sources and consequences of embeddedness for the economic performance of organizations: The network effect, American Sociological Review 61, 674-698.

Williamson, O.E. (1975). Markets and hierarchies: Analysis and antitrust implications, Free Press: New York.

Williamson, O.E. (1985). The economic institutions of capitalism: Firms, markets, relational contracting, Free Press: New York.

Windsperger, J. (2004). The dual network structure of franchising firms: Property rights, resource scarcity and transaction cost explanations, in Windsperger, J., Cliquet, G., Hendrikse, G.W.J., Tuunanen, M. (Eds.), Economics and management of franchising networks, Physica: Heidel-berg-New York, 69-88.

Windsperger, J. and R.P. Dant (2006). Contractibility and the ownership redirection in franchising: A property rights view, Journal of Retailing 82, 259-272.

Witt, P. (1999). Information networks of small and medium-sized enterprises, Journal of Enterprising Culture 7, 213-231.

Yin, R. (2003). Case study research: Design and methods, Sage Publications: Thousand Oaks.

Yli-Renko, H., E. Autio and H. Sapienza (2001). Social capital, knowledge acquisition and knowledge exploitation in young technology-based firms, Strategic Management Journal 22, 587-613.

30

APPENDIX.

Measurement Scale and Items – Capabilities

Note: Seven-point Likert scales are used to provide responses for each item, 1 – “Strongly disagree”, 7 – “Strongly agree”. Respondents were re-quested to evaluate the items with reference to a particular firm with whom their firm had an ongoing or past collaborative relationship that was considered as most central to their business, within the last three years. Constructs and items taken from Schreiner et al. (2009).

a) Coordination dimension (CR 0.81, AVE 0.57)

1. For coordinating partner-related activities, we have established internal processes (e.g., for marketing, project coordination) within our com-pany.

2. For the cooperation with partners, we have established cross-company processes, meaning processes reaching across company boundaries.

3. Within our company, we meet regularly to adapt our working procedures to partners.

4. Within our company, we have adjusted our incentive systems (bonus, goal agreement) to serve the goals of a partnership.

b) Communication dimension (CR 0.89, AVE 0.61)

1. On any given occasion, we can explain the win-win situation of a cooperation to partners.

2. We try to achieve an instant link of certain customer needs to our name in partners.

3. We make an effort to let partners know exactly our market positioning.

4. We make an effort to make partners understand our service and product offering.

5. When organizational changes occur, we inform partners about the new contact persons in our company.

c) Bonding dimension (CR 0.89, AVE 0.59)

1. Even in difficult situations, we signal readiness for discussion towards partners.

2. We stand by a partner’s side even in difficult situations.

31

3. We listen attentively when partners explain problems to us.

4. We care about the concerns of partners even if we do not expect any advantages to arise for us in the short term.

5. During conversations we feel intuitively what partners actually want.

6. When discussing points of disagreement, we always try to see a partner’s point of view.

32