Cooperation, Trust and Performance – Empirical Results from Three Countries


  • The authors would like to thank the two anonymous reviewers for their constructive and helpful comments.


Reverting to the resource-based view of strategic management and cooperation theory, we provide argumentation for the value of two critical resources to cooperating firms: cooperation experience and maxim-based trust. The results of a large-scale survey in three European countries (Austria, Slovenia and the Czech Republic) reveal an important fact: although cooperation experience contributes to business performance, the contribution of maxim-based trust to success is significantly higher. As a result, corporate success depends not only on the quantity of cooperation experience, but also – and to an even greater extent – on the quality of cooperation with regard to the form of coordinative power established within the cooperation arrangement. Given that maxim-based trust has been identified as a feasible coordination mechanism in cooperation relationships, it might therefore be freed from its frequent characterization as utopian and out of touch with reality.


The dynamization of markets in the context of globalization has intensified the need for businesses to develop the ability to create unique sets of resources in order to ensure sustainable corporate success. For this purpose, one promising means of ensuring access to these critical resources – especially for small and medium-sized enterprises (SMEs), which normally do not have extensive and manifold resource configurations at their disposal – is entering into cooperation relationships. By establishing a cooperation relationship, the partners can bundle (parts of) their resources and may thereby create a new and unique set of resources which can hardly be imitated. This is especially the case when the partners succeed in identifying and capitalizing on the synergetic potential of the cooperation arrangement. Under these circumstances, such an arrangement has the power to enhance the performance of both partners. The contribution of cooperation relationships to business performance can be short term or long term in nature (e.g. Macneil, 1980; Williamson, 1991). However, entering into cooperative relationships becomes a risky venture if the exchange relationship involves forgoing one's own short-term profits in order to realize long-term gains together with a cooperation partner (Roessl, 1996). In such transaction relationships – which are the focus of our research – cooperating companies make their own business performance dependent on their cooperation partner's future behaviour. The ability to establish and maintain successful cooperation relationships is a critical resource in its own right, and it is built up in particular through practical experience in inter-firm cooperation relationships (e.g. Brulhart, 2007).

However, it is not only the practical cooperation experience of the partners which makes (the partners in) a cooperation relationship successful, but also – and to an even greater extent – the coordination mechanism within these relationships. We focus on long-term dyadic cooperation relationships between SMEs. These relationships represent contexts that are highly demanding with regard to behavioural coordination and are often characterized by simultaneous market and organizational failure. In such contexts, e.g. joint R&D or cooperative internationalization, interorganizational relationships can only be explained through trust-based behavioural coordination. These situations call for mutual trust as a coordination mechanism between the cooperation partners, as such trust plays a significant role in ensuring the success of the cooperation and – as a consequence – the individual performance of each cooperation partner. In order to fully understand the coordinative power of trust, we have to differentiate between instrumental (extrinsically motivated) trust and maxim-based (intrinsically motivated) trust (Osterloh and Weibel, 2000). We argue that maxim-based trust represents a valuable and particularly inimitable resource for the success of the cooperation and the performance of the cooperation partners.

This paper contributes to the field of cooperation research on several levels. We not only provide theoretical justification for the special value of (1) cooperation experience and (2) maxim-based trust as critical resources for business performance and develop a measurement model for cooperation experience, maxim-based trust and performance (which contributes to sharpening the measurement of trust, as called for by Moellering, Bachmann and Lee (2004), to name one example), but we also demonstrate the value of these two critical resources empirically. To this end, we use data from a large-scale questionnaire survey (n=303) in three European countries (Austria, Slovenia and Czech Republic) and employ hierarchical linear regression analysis to test three hypotheses.

The results show that although cooperation experience contributes positively to business performance, maxim-based trust makes a significantly larger contribution to performance in cooperation arrangements. Therefore, corporate success depends not only on the cooperation experience (quantitative aspect), but also – and to an even greater extent – on the form of coordinative power within the cooperation arrangement (qualitative aspect).

The paper is organized as follows. In the next section we develop three hypotheses against the backdrop of a focused literature review. We then discuss the sampling and operationalization of the variables. Next, we present the empirical results, which are discussed and converted into implications linked to previous results in the two ensuing sections. We conclude by stating the limitations of this study and pointing out several directions for future research.

Theoretical background and development of hypotheses

Cooperation, opportunistic behaviour and success

In order to generate profits, each company needs to have a certain set of resources at its disposal. For sustainable corporate success, it is crucial to secure access to such resources. Companies can employ three different modi operandi in order to ensure this access (Pfeffer and Salancik, 2003): (1) They can either internalize the source or (2) build up the competence and structures necessary to generate the resource themselves. (3) Alternatively, companies may enter into a cooperative arrangement with a company that has access to the resource in question. As regards the third alternative, companies need to reach several decisions: they need to decide which resources are critical for achieving their value proposition and which of them they lack; which companies have those capabilities; and, based on cost, quality and speed considerations, whether the firm should partner with or acquire those companies (Kim and Mauborgne, 2000).

It is easy to see that there is less risk of losing access in the case of internalization or in-house production. Thus, in this context inter-firm cooperation might appear to be a less attractive alternative. However, the resources' future value might not be predictable due to dynamic contextual conditions such as rapid technological change, modification of legal regulations or shifts in demand. In such cases, the risk of sunk costs impedes the development of capacities for in-house production. This issue is also relevant in cooperation relationships, as changing partners gives rise to switching costs (Lipman and Wang, 2000). If the internalization of resources is also complicated, e.g. due to time or legal constraints or relatively high investment requirements, cooperative inter-firm arrangements become the most favourable means of gaining access to resources which are critical to the focal firm's business performance.

In particular, SMEs often face situations in which both in-house production and internalization are unattainable. Manoeuvring within a limited number of rather specific and narrow business areas with a comparatively small ‘war chest’, SMEs typically perceive unacceptably high risks when they consider obtaining control over critical resources single-handedly. Consequently, cooperative arrangements represent an attractive option in the strategic portfolio of these firms. At the same time, inter-firm cooperation provides a vehicle for transactions which would otherwise overburden the focal SME (e.g. joint R&D or internationalization projects). By widening the behavioural portfolio, cooperative arrangements allow SMEs to exploit opportunities which they would have to forgo as isolated firms, and these arrangements hold the potential to create a synergetic, critical and hardly imitable combination of the cooperation partners' individual resources. In this way, inter-firm cooperation may make a positive contribution to the business performance of both cooperation partners.

However, SMEs in cooperation arrangements often find themselves in a rather paradoxical situation. By entering into a cooperative arrangement with another company, they agree to coordinate their behaviour with the cooperation partner, thus restricting their own autonomy. As the elements of performance and reward are temporally separated in a cooperative exchange relationship and a partner can always deviate from the agreement (Macneil (1980), from a contracting perspective; Emerson (1962), from a power-dependence perspective), cooperating companies make their own business performance dependent on their partner's future behaviour. Therefore, cooperative strategies bring about a high level of risk: by frustrating the partner's expectations, a cooperator may skim all of the short-term profits alone at the expense of joint long-term profits, thus defecting from the cooperation relationship. The possibility of such opportunistic behaviour makes cooperative arrangements a risky venture (e.g. Elango and Fried, 1997; Wathne and Heide, 2000). The ability of a firm to build up a sophisticated and effective instrument to handle this room for opportunistic behaviour determines the benefit it can generate from cooperative arrangements.

In order to build up such an ability to coordinate cooperation relationships, the firm may resort to two critical resources: the firm can (1) tap its cooperation experience and (2) establish maxim-based trust. In the following, the different bases, functional mechanisms and their (relative) impact on business performance will be discussed and condensed into three hypotheses.

Cooperation experience as a critical resource for business performance

Organizational learning theory argues that companies may develop the capacity to handle complex transaction relationships by gaining experience in similar settings. In an iterative process, the firm extracts inferences from experience gained in past cooperation relationships and extrapolates them to future situations in order to improve its behaviour (Argyris und Schoen, 1978; Fiol and Lyles, 1985; Levitt and March, 1988). This argument is also supported by evolutionary theory (Kale, Dyer and Singh, 2002), which claims that a firm's competences evolve through incremental adaptation and progressive learning.

In the context of cooperation relationships, these competences grow along with experience on two levels: first on the level of the experience gained in a cooperation relationship with a specific partner, and second on the level of general experience in cooperation management (Brulhart, 2007), which can be gained in the context of either domestic or international cooperation relationships (Nadolska and Barkema, 2007). Based on the argumentation above, we propose the following hypothesis:

H1: A cooperating company's cooperation experience (measured in terms of the number, duration and internationality of cooperation relationships a company has participated in) has a positive effect on the focal firm's business performance.

Maxim-based trust within the cooperation relationship as a critical resource for business performance

It is not only cooperation experience (quantitative aspect), but also – as we argue even to a greater extent – the coordination mechanism within the cooperation relationship (qualitative aspect) that makes a cooperation relationship and its partners successful. When talking about the coordination mechanism, a major issue is the kind of power applied in order to coordinate the participants' behaviour within the field of cooperation.

Consequently, the following question arises: how can cooperators ensure that their partners behave according to the rules stipulated ex ante? There are three ideal-type coordination powers for the purpose of reducing the latitude for opportunistic behaviour. They apply to each real inter-firm transaction relationship in a certain combination (Adler, 2001; Bradach and Eccles, 1989). (1) The market mechanism (which is based on isolated actors who pursue short-term advantages) cannot be the dominant coordination mechanism in a transaction relationship which strives for joint long-term profit (e.g. Ouchi, 1979). Following the logic of the ideal-type market, economic actors would opt for short-term profits, making long-term arrangements impossible in the first place. (2) Behavioural determination by hierarchical governance (e.g. Wathne and Heide, 2000) is equally limited: credible sanction threats (Buckley and Casson, 1988) on an actor's part require sufficient sanctioning power (Backhaus, 1992; Kaas, 1992a, 1992b), ex ante knowledge (Eberl, 2004; Shane 1994) and ex post perceptibility (Dwyer, Schurr and Oh, 1987) of the behaviour a cooperation partner is expected to show. The coordinative power of hierarchical governance is limited especially in those areas of inter-firm cooperation where objectives cannot be programmed at all, or only at prohibitively high transaction costs (Ring and Van de Ven, 1992).

Thus, in transaction relationships which are complex and pursue long-term goals, neither market and hierarchy nor hybrids of these two coordination powers (Borys and Jemison, 1989) can govern the actors' behaviour. Transaction cost economics ignore the fact that, beyond a certain level of complexity, market and organization failure impede exchange relations (Furubotn, 2001; Roessl, 1996). In direct contrast to Baucus, Baucus and Human (1996), we argue that this deficit cannot be remedied by mixing elements of those two ideal-type coordination mechanisms or by delimiting contractual and relational obligations as proposed by Williamson (1991). From a transaction cost perspective, trust cannot be accepted as an alternative because of its neo-institutional roots, which preclude non-rational behaviour and with it the acceptance of uncertainty and trust. However, highly complex transaction relationships obviously arise in real business life (Roessl, 1996) and form the focus of our investigation. This insight opens up the view to a third coordination mechanism which has slowly but steadily made its way into economic thinking. This third ideal-type coordination mechanism is particularly well suited in situations of both market and organizational failure. It is referred to as ‘relational contracting’ (Carson, Madhok and Wu, 2006), ‘trust’ (Eberl, 2004), ‘self-commitment’ (Frey and Osterloh, 2002) or ‘Selbstverpflichtung’ (Fink, 2005; Sydow and Windeler, 2000).

In society, trust was identified as a strong coordinative power long ago. In the early twentieth century, the Austrian writer Egon Friedell postulated: ‘The most reliable way to make people decent is to take them for decent’ (Friedell, 1983). However, research on the coordinative role of trust within economic transactions did not become a serious issue for economists until the 1960s, when researchers such as Bator (1958), Ouchi (1979), Dwyer, Schurr and Oh (1987), Rotter (1971) and Wurche (1994) highlighted the shortcomings of the two classic coordinative powers of market and hierarchy, and pointed to the catalytic effect of trust. After that first in-depth introduction to the phenomenon of ‘trust’ in economic theory, transaction cost economics gained the upper hand, especially in the Anglo-Saxon world, widely ignoring the crucial role of trust in economic transactions. The subsequent debate focused on hybrids between market and hierarchy. Whereas authors such as Zenger and Hesterly (1997) as well as Holland and Lockett (1997) detected the rising importance of these hybrid coordination mechanisms, Williamson (1991) asserted their infeasibility and ineffectiveness. Again, these obviously inconsistent standpoints opened up the field for trust to be viewed as a key to the controversy. Meanwhile, European economists in particular pressed ahead, theorizing on the role of trust in the economic context (e.g. Osterloh and Weibel, 2000; Roessl, 1994, 1996) and providing a profound basis for a new global research effort on the unresolved issue of coordination. In his integrative work, Adler (2001) reintroduces trust as ‘a third increasingly significant coordination mechanism’.

How can trust effectively coordinate the cooperation partners' behaviour? Following Ring and Van de Ven (1992), Osterloh and Weibel (2000) or Adler (2001), we define trust as the response of an actor (an individual, not an organization) to subjective uncertainty regarding the interaction partner's behaviour. In order to understand the coordinative power of trust, it is necessary to differentiate between instrumental trust and maxim-based trust. Instrumental trust refers to the exogenous conformity of the cooperation partner's behaviour with the explicit and implicit rules of cooperation. This kind of trust draws its coordinative power from sanction and control. The awareness that the cooperation partner may face disadvantages in the case of defective behaviour motivates the actor to place instrumental trust in him.

By contrast, maxim-based trust is intrinsically motivated, drawing its coordinative power from the actor's self-commitment to a maxim (Kant, 1998).

How does a maxim-based trust relationship evolve? The evolution of maxim-based trust can be described as a reciprocal, self-reinforcing process. It starts with the actors mutually conceding self-commitment to their cooperation partners, which is based on socialized information on the cooperation partner (e.g. reputation and perceived behavioural history). In this situation, the actors feel compelled to provide risky advance performance (irreversible commitments such as specific investments). In this way, they communicate their own self-commitment in a credible manner. Based on congruent expectations, both sides perform acts of maxim-based trust, which in turn reinforce the initial expectations and justify additional acts of maxim-based trust (Fink, 2005). They forgo individual short-term profits in favour of common long-term profits. As a result, a maxim-based trust relationship evolves. Although latitude for opportunistic behaviour still exists in such transaction relationships, restricting the participants' inclination toward opportunistic behaviour reduces behavioural uncertainty. Therefore, the complexity of the transaction relationship and the risk of betrayal can be partly absorbed. Thus, maxim-based trust provides a key to double contingency and prevents the development of social dilemmas such as the prisoner's dilemma from the very outset. In this way, maxim-based trust enables transaction relationships which would otherwise not take place due to high behavioural uncertainty.

The prototypical transaction relationship, which can only be realized by interaction partners who place maxim-based trust in one other, is heterarchic cooperation. Heterarchic cooperation relationships can be defined as voluntary and organized relationships between autonomous and equal partners who mutually adapt their behaviour to each other, thus bringing about the possibility of one-sided defection. Thus, if two actors who are ready to commit to each other enter into a heterarchic cooperation relationship, we can assume that a maxim-based trust relationship has been established between them (Fink, 2005).

The competence necessary to build up and maintain such complex cooperation relationships enables the cooperators to handle behavioural uncertainty. Consequently, they are able to capitalize on additional opportunities which their competitors have to go without. Profits will rise in cases where only few firms are capable of carrying out a transaction due to their control over rare, inimitable resources (e.g. Barney, 1986, 1991). In fact, firms will then be able to apply this highly sophisticated and efficient coordination power to realize profitable transaction relationships in risky contexts. The competitive advantage of being able to develop and manage cooperation relationships coordinated by maxim-based trust has a positive effect on the focal firm's business performance. Therefore, the following hypothesis can be postulated:

H2: The more behavioural coordination relies on maxim-based trust in a cooperation relationship, the better the performance of the focal participating company will be.

The superiority of maxim-based trust as a contributor to business performance

Both cooperation experience and the ability to establish and maintain a cooperation relationship coordinated by maxim-based trust can be seen as a firm's resources. From this perspective, cooperation experience can be expected to have a weaker effect on the firm's business performance, as it is easier to acquire and less bound to the socio-psychosocial profile of the actors in charge of cooperation management. As a result, the competitive advantage of cooperation experience is easier to imitate and therefore of less value to the company. Accordingly, we propose the following hypothesis:

H3: Maxim-based trust within a cooperation relationship has a stronger effect on the business performance of the focal firm than cooperation experience.


Sampling frame and response rates

The quantitative part of this paper is based on a survey carried out in Austria, the Czech Republic and Slovenia between March and July 2006. A total of 10,000 (Austria, 2000; Czech Republic and Slovenia, 4000 each) SMEs (i.e. up to 249 employees) was selected from national databases (Austria, AURELIA; Czech Republic, ALBERTINA; Slovenia, IPIS) as a stratified random sample. The region (province) and size of each business (number of employees) were employed as criteria for stratification. Stratification by region (total number of SMEs of a region × 2000 or 4000 divided by the total number of SMEs in the country) was employed in order to avoid over- or under-representing certain regions in the sample. Stratification by the ‘size of business’ ratio – 1:3:1 for micro businesses (up to nine employees), small businesses (10–49 employees) and medium-sized businesses (50–249 employees), respectively – was employed in order to avoid over-representing micro businesses, which show a low propensity to cooperate.

The questionnaire was addressed to the owner/manager of each SME, as – in view of the topic of the survey – knowledgeable informants were not available below that hierarchical level.

The survey yielded a total of 458 (4.6%) returned questionnaires: 119 from Austria (response rate 6.0%), 199 from Slovenia (response rate 5.0%) and 140 from the Czech Republic (response rate 3.5%). A check based on telephone interviews with a random sample of 45 non-respondents from each country as well as a test comparing early, middle and late responders showed no systematic bias. Of these 458 SMEs, 303 (91 Austrian, 150 Slovenian and 62 Czech) indicated that they participate in cooperation activities. Therefore, these 303 businesses serve as the basis for our analyses in this paper. The breakdown of the sample into cooperating and non-cooperating businesses showed that the propensity to cooperate was significantly lower in the Czech sample (44.3%) than in the Slovenian (75.4%) and Austrian (76.5%) samples (χ2=43.12; p=0.000).

The sample for analysis consists of 49 (16.2%) micro, 153 (50.5%) small and 101 (33.0%) medium-sized enterprises across a broad range of industries. Approximately 43% of the businesses in the sample belong to the service sector, some 37% belong to the production sector, and the remaining 20% can be attributed to the trade sector.

Variables and measures

We used four-point scales (‘completely agree’, ‘inclined to agree’, ‘inclined to disagree’ and ‘completely disagree’) to measure all items.

Cooperation experience. Cooperation experience was measured using the number of cooperation relationships the business had had at the time of the survey (1, one; 2, two; 3, more than two), the duration of the cooperation arrangement with the firm's main partner (1, up to one year; 2, one to three years; 3, three to five years; 4, five to ten years; 5, ten to 20 years; 6, more than 20 years), and participation in an international cooperation arrangement (0, no international cooperation; 1, international cooperation).

Maxim-based trust. As outlined above, mutual trust can only evolve if both interaction partners are willing to make a commitment to each other. Therefore it is necessary to measure the level of maxim-based trust on both actors' sides. As the questionnaire survey was kept anonymous in order to increase the return rate, we could not match up the partners in cooperation systems. As a result, we had to apply a combination of direct and indirect measurements.

On the side of the cooperation partner surveyed, we measured the level of self-commitment to the cooperation relationship as a manifest expression of the maxim-based trust placed in his/her cooperation partner (direct measurement). On the side of the cooperation partner not surveyed, maxim-based trust could be observed by identifying whether a heterarchic cooperation relationship had been established. Based on the argumentation outlined above, the existence of a heterarchic cooperation relationship allows for interference in the second cooperation partner's level of maxim-based trust (indirect measure).

As the individual items in maxim-based trust were considered independent from one another, we calculated a formative index.

Self-commitment. Our conceptualization of the self-commitment phenomenon is based on the work of Roessl (1994, 1996) and comprises several dimensions. The present cooperation partner's reputation provides information on the extent to which he/she has met the expectations of his/her interaction partners in the past (Roessl, 2001), thus affecting an actor's decision to commit to the relationship. Familiarity is based on personal impressions and provides information about the specific cooperation partner in the ongoing relationship (Roessl, 1994). Another indicator is the cooperation partner's perceived behavioural history. In particular, the stability of the maxims underlying perceived behaviour is crucial here. Self-commitment requires observable behavioural norms which remain stable over time and therefore allow a prognosis of the cooperation partner's future behaviour (Luhmann, 1989; Roessl, 1994). As perceived behavioural history is not based on personal impressions, it has to be obtained actively. The source of this information is socialized impressions of others. If the cooperation partners build up a personal relationship, the relationship will be enriched by personal connotations, taking the relationship to a higher level. Such personal relationships between self-committed cooperators have no short-term perspective (Becaerra and Gupta, 2003; Kanter, 1995; Roessl, 1994).

A further dimension of self-commitment is the actor's self-restriction; the actor confines himself/herself to cooperative behaviour. He/she takes the risk that his/her expectations concerning the cooperation partner's behaviour might be frustrated. Therefore, the willingness to take a risk is another dimension of self-commitment. Self-commitment also requires frustration tolerance, i.e. the actor's belief in his/her ability to cope with situations resulting from a frustration of expectations (Roessl, 1994). An actor's self-commitment represents self-exposure. Furthermore, self-commitment calls for a leap of faith (e.g. advance performance) which the interaction partner might capitalize on by defecting from the relationship unexpectedly.

Heterarchic cooperation relationship. We measure heterarchic cooperation based on (1) structural characteristics and (2) interpersonal characteristics, which are a suitable means of delimiting this specific form of cooperation relationship from other forms of inter-firm cooperation relationships.

Structural characteristics delimit from ‘informal relationship’: whereas informal relationships are characterized by a minimum share of elements typical of organizations, heterarchic cooperation relationships are organized relationships and can therefore be characterized as systems (Plassmann, 1974).

Structural characteristics also delimit from ‘hierarchical cooperation’ and ‘concentration’: the essential difference here lies in the form of coordination in the transaction relationship. Coordination based on mutually adjusted behaviour on the part of autonomous and equal elements in a heterarchic cooperation relationship (Strohmayer, 1996) is delineated from coordination based on power, control and sanction in a hierarchy system (Pleitner and Roessl, 1995). Consequently, each cooperator has the possibility of one-sided defection in the heterarchic cooperation relationship at any time (Plassmann, 1974). Hierarchical systems have a rigid structure of competences with a portfolio of sanctions attached, whereas heterarchic relationships are characterized by voluntary participation and inputs (Strohmayer, 1996).

The interpersonal characteristics typical of heterarchic cooperation arrangements are captured using four indicators. The measure communication quality describes how the cooperators communicate with each other. Communication quality is crucial for exchanging opinions and thoughts between the subsystems of the cooperation relationship. Only high-quality communication ensures that all participants have the opportunity to contribute their ideas and safeguard their interests. In this way, high communication quality contributes to high relationship quality (e.g. Becaerra and Gupta, 2003; Kanter, 1995).

The measure resilience captures those aspects of the cooperation relationship which only move to the centre of attention in times of crisis. How robust the cooperation relationship is in times of crisis and how elaborated problem-solving competences are determine the relationship quality to a great extent (De Búrca, Fynes and Roche, 2004).

The measure transparency captures the cooperation partners' openness concerning the internal processes of their firms. To what extent do the cooperation partners provide such insight, and how well and accurately informed do they feel? Trust can only evolve if the cooperation partners deal with each other openly and honestly. The more the actor knows about his/her interaction partner, the less risk he/she will perceive in the trust relationship, and the more likely a heterarchic cooperation relationship will evolve (De Búrca, Fynes and Roche, 2004).

Once a heterarchic cooperation relationship has been established and the self-reinforcing process has started, relationship intensity rises automatically.

For the purpose of measuring the components of maxim-based trust, we used four-point scales (‘completely agree’, ‘inclined to agree’, ‘inclined to disagree’ and ‘completely disagree’). Table 1 shows the measurement of maxim-based trust and its components.

Table 1. Measurement of maxim-based trust
  • a

    Reverse item.

Self-commitmentReputationRoessl, 2001Before establishing the cooperation relationship, I had heard good things about my cooperation partner
FamiliarityRoessl, 2001I have cooperated with my present cooperation partner in the past
Perceived behavioural historyRoessl, 2001Before establishing the cooperation relationship, I gathered information about my cooperation partner
Personal relationshipBecaerra and Gupta, 2003; Kanter, 1995I also meet my cooperation partner in my private life
No short-term perspectiveDe Búrca, Fynes and Roche, 2004; Rusbult, Martz and Agnew, 1998With the cooperation relationship, I aim to realize noticeable success as fast as possiblea
Self-restrictionOsterloh and Weibel, 2000; Roessl, 1994I attune my behaviour to the aims of the cooperation relationship
Willingness to take a riskMcLain and Hackman, 1999I am willing to take a risk
Frustration toleranceLuhmann, 1989; Roessl, 1994I am convinced that I am able to cope with setbacks
Self-exposureRoessl, 1994The cooperation has a strong influence on the success of my company
Leap of faithLuhmann, 1989In order to make cooperation work, one has to take a leap of faith with one's cooperation partner, even though this involves risk
Heterarchic cooperation relationship
Structural characteristicsOrganized relationshipPlassmann, 1974; Roessl, 1994My cooperation partners and I talk about the cooperation
Mutually adjusted behaviourRoessl, 1994My cooperation partner and I take joint action in the area of cooperation
AutonomyTroendle, 1987I have remained legally independent within the cooperation arrangement
EqualityRuehl, 1980In decisions regarding the cooperation relationship, the opinion of each cooperation partner is equally important
Possibility of one-sided defectionPlassmann, 1974By behaving opportunistically, I could damage the cooperation relationship
VoluntarinessStrohmayer, 1996I can terminate the cooperation relationship unilaterally at any time
Interpersonal characteristicsCommunication qualityBecaerra and Gupta, 2003; De Búrca, Fynes and Roche, 2004; Kanter, 1995I can get right to the point when speaking with my cooperation partner
ResilienceDe Búrca, Fynes and Roche, 2004Discussions with my cooperation partner always result in a solution
TransparencyDe Búrca, Fynes and Roche, 2004I know the internal processes in my cooperation partner's company
Relationship intensityLorenz, 1999Since its establishment, the cooperation relationship has gained intensity

Performance. Our measurement of entrepreneurial performance is based on an adapted formal structure of the balanced scorecard (Kaplan and Norton, 1996). In this way, we can ensure integrated coverage of the latent variable ‘performance’ within the framework of our empirical investigation.

As the individual performance items were considered to be independent from one another, we calculated a formative index. Table 2 shows the variables employed along with their sources and the items used. As in the case of maxim-based trust, we used four-point scales (‘completely agree’, ‘inclined to agree’, ‘inclined to disagree’ and ‘completely disagree’) to measure all items.

Table 2. Measurement of performance
Endogenous perspectiveEmployee qualificationsKaplan and Norton, 1996Since the establishment of the cooperation relationship, the qualifications of my employees have improved
Employee turnoverGomes, Yasin and Lisboa, 2006; Hatch and Dyer, 2004Since the establishment of the cooperation relationship, fewer employees have left my company
Exogenous perspectiveCustomer satisfactionShare of regularcustomersAnderson and Sullivan, 1993; Anderson, Fornell and Lehmann, 1994Bruhn, 1996; Horovitz and Panak, 1993; Quartapelle and Larsen, 1996My customers are always satisfied with my products and servicesMost of my customers are regular customers
Market developmentKaplan and Norton, 1996Since the establishment of the cooperation relationship, I have enlarged my market share
Share of regular suppliersRiffner and Weidelich, 2001Most of my suppliers are regular suppliers
Financial perspectiveCash flow developmentKaplan and Norton, 1996Since the establishment of the cooperation relationship, I have boosted my cash flow
Sales development Since the establishment of the cooperation relationship, I have boosted my sales
Development of investment activity Since the establishment of the cooperation relationship, I have boosted my investments

Control variables. We used firm size (number of employees), firm age (years of existence) and country of origin (0, Austria as a traditional market economy; 1, Czech Republic and Slovenia as emerging market economies) as control variables, as these characteristics can also have an impact on performance.


We employed hierarchical linear regression analysis to test our hypotheses. In the first step of the analysis, the control variables were inserted into the model, using business performance as the dependent variable. In the next two steps, the variables cooperation experience and maxim-based trust were added to the model, and incremental R2 and F tests of statistical significance were evaluated.


The means, standard deviations and correlations of the variables are displayed in Table 3. First, it is striking that (with the possible exception of the duration of cooperation and maxim-based trust) the correlations between the independent variables are relatively low, ranging from –0.185 to 0.177. However, the positive correlation between the duration of cooperation and maxim-based trust meets our expectations, as it supports the argument that trust can normally only evolve and increase with time (e.g. Jones and George, 1998; Lafontaine and Kaufmann, 1994). With regard to the correlations between the independent variables and the dependent variable, maxim-based trust shows by far the highest positive correlation with performance, followed by the duration of the cooperation. The negative correlation between firm age and performance is also noticeable. This negative correlation may result from the fact that our performance measure, which is based on dynamic indicators, tends to favour younger, more flexible businesses in dynamic markets in comparison to more established, experienced businesses in stable environments.

Table 3. Means, standard deviations and correlations
 MeanStandard deviation(1)(2)(3)(4)(5)(6)(7)(8)
  1. * p>0.1 ; ** p<0.05 ; *** p<0.01.

(1) Performance34.114.901       
(2) Firm size2.310.920.0791      
(3) Firm age2.520.81−0.147**0.150***1     
(4) Country (Austria versus CZ/SI)0.700.460.0900.004−0.185***1    
(5) Number of cooperation relationships1.900.900.1000.112*−0.018−0.158***1   
(6) Duration of cooperation3.201.350.204***−0.0170.114*0.0080.177***1  
(7) International cooperation (yes/no)0.480.500.161***0.039−0.106*0.127**0.0800.0281 
(8) Maxim-based trust61.926.160.421***0.0620.019−0.0500.107*0.128*0.0081

In order to check for multicollinearity in the regression analysis, the variance inflation factor was calculated for the individual predictors. All of the values are just over 1 and thus far below critical levels. In order to test the hypotheses, we first added the control variables (see Table 4, column 2, for results), then the cooperation experience variables (column 3) and finally the maxim-based trust variable (column 4).

Table 4. Performance: control variables, cooperation experience and maxim-based trust (n=303)
Cooperation experience,
control variables
Maxim-based trust, cooperation
experience, control variables
  1. Standardized regression coefficients are displayed in the table.
    * p>0.1 ; ** p<0.05 ; *** p<0.

Firm size0.1010.3700.0970.3630.0740.332
Firm age−0.151**0.429−0.162**0.423−0.159**0.386
Country (Austria versus CZ/SI)0.0620.7440.0500.7400.0660.675
Number of cooperation relationships  0.0460.3790.0170.346
Duration of cooperation  0.212***0.2480.165***0.228
International cooperation (yes/no)  0.124*0.6620.124**0.604
Maxim-based trust    0.398***0.049
R20.036* 0.104*** 0.258*** 
Adjusted R20.022* 0.077*** 0.232*** 
ΔR20.036* 0.068*** 0.154*** 

The control variables (firm size, firm age and country) explain 3.6% of the variation in performance, and the model only attains statistical significance at the 90% level in this step (p=0.057). Nevertheless, while firm size and country do not show a significant impact on performance, firm age turns out to be a significant predictor (p=0.034) for firm performance. As pointed out above in the discussion of correlations, the relationship between firm age and performance is negative. Once again, we repeat our assumption that this outcome is partly caused by the fact that we measured performance using dynamic performance indicators.

In the next step of the regression analysis, the cooperation experience variables (number of cooperation relationships, duration of cooperation, and existence of international cooperation) are reviewed beyond the base model. These three variables account for an additional 6.8% of the variation in performance (p=0.002) and increase the statistical significance of the model (p=0.001). Explained variance thus attains a value of 10.4%. Aside from the negative relationship between firm age and performance already discovered in the control variables block, the existence of international cooperation (p=0.068) and particularly the duration of cooperation (p=0.002) show significant positive relationships with business performance.

This means that Hypothesis 1 can partially be supported. Cooperation experience in the form of the duration of cooperation and – with some limitations due to lower significance – also the existence of international cooperation make a positive contribution to business performance.

In the final step of our analysis, we added maxim-based trust to the regression model. The integration of this variable increases the explained variance considerably by 15.4% (p=0.000) to 25.8% (p=0.000). Maxim-based trust shows a highly significant positive relationship with business performance (p=0.000). In combination, these outcomes support Hypotheses 2 and 3: maxim-based trust has a positive influence on business performance (Hypothesis 2) and has a stronger effect on business performance than cooperation experience (Hypothesis 3). In fact, maxim-based trust explains a higher percentage of the variance in performance (15.4%) than all the other variables in the final model combined.


Empirical analysis shows that cooperating firms with more cooperation experience are more successful. The longer these firms manage to maintain their cooperative relationships, the better the firms perform. Moreover, the internationality of cooperation relationships contributes to firm performance. Interestingly enough, the data do not indicate that the firms' number of cooperation relationships has a significant impact on performance. This can be interpreted as a first indication of the greater success contribution of continuous, systematic and focused investment in the development of an ongoing cooperation relationship which lies within the core of one's business and widens the firm's strategic portfolio. In contrast, the development of cooperation relationships with ever-changing partners does not contribute to firm performance. From this perspective, the firm's number of cooperation relationships alone is not a decisive factor. Moreover, the number of cooperation relationships maintained seems to be influenced by firm size, as increasing company size automatically leads to an increasing number of external contacts. At the same time, a larger number of external contacts increases the probability that cooperatively coordinated transaction relationships will evolve.

Although the results show that cooperation experience makes a positive contribution to the performance of cooperating firms, we were also able to identify a far stronger success factor for cooperators: maxim-based trust. Inter-firm cooperation relationships are characterized by double contingency and are therefore a suitable context for empirical research into the effect of maxim-based trust on cooperators' performance. In this context, we showed that maxim-based trust is a resource that substantially contributes to the cooperating firms' performance. We interpret this trust based on maxims as a critical resource which is especially difficult to imitate and may thus serve as a possible key to developing competitive advantages. Firms that manage to evolve maxim-based trust possess a capability which enables them to manage cooperation relationships which could not be coordinated otherwise. They can seize and capitalize on opportunities which their competitors have to forgo due to the high complexity and uncertainty involved.

We can sum up our findings as follows. It is not so much the quantity of cooperation experience, but the quality of the cooperation relationship that accounts for its value to the company. These findings concur with those of Lavie (2006), who highlights the special value of the nature of inter-firm relationships.


As cooperation experience has proved to be a success factor for cooperating firms, it seems beneficial to build up the appropriate management capacities in due time. From our results, we have learned that it is not the number of cooperation relationships a firm has experienced but the intensity of these relationships that contributes to future success. The management capacities relevant to coordinating cooperative relationships and the resulting firm performance obviously grow along with the challenge. This idea leads to the assumption that, in order to boost business performance, entrepreneurs have to venture into increasingly demanding transaction relationships. We argue that with rising cooperation experience firms build up a sophisticated and effective instrument for handling behavioural uncertainty within cooperation relationships. The challenge of coordinating cooperation relationships grows with longer time horizons and higher internationality, as these factors increase complexity and uncertainty. More demanding settings force cooperating firms to improve their coordination instruments, thus creating a more valuable resource. Those who invest in the development of their cooperation relationship and push the limits within this relationship will outperform those who only dare to act within the secure, familiar territory of the past.

Our results show that the more a cooperation arrangement relies on maxim-based trust, the more successful it is. However, a firm cannot establish a maxim-based trust cooperation relationship overnight in order to boost its performance. First, the firm needs to find a like-minded partner who is willing to commit to the relationship to the same extent as itself. This is not an easy task, as self-commitment can only be communicated by leaps of faith and mutual-based trust can only evolve if the interaction partner does not capitalize on this self-exposure. The tricky thing is the fact that self-exposure is only legitimated by its result. Thus, one can never be sure to succeed with this kind of advance. On the one hand, this dilemma is unpleasant for the actor who is willing to develop a maxim-based trust relationship with a cooperation partner, as it forces the actor to take a risk that cannot be legitimated beforehand. On the other hand, it also serves as a safety mechanism as it avoids instrumentalizing maxim-based trust: once you fake it, you break it.

Second, such relationships typically grow over time. The evolution process of maxim-based trust cannot be accelerated by force. It rests on a long-term strategy aimed at building up a good reputation and ensuring a positive perceived history. Additionally, it requires a long-lasting personal relationship with the cooperation partner in the course of which one has credibly communicated a willingness to take risks, a sufficient level of frustration tolerance and readiness for self-restriction and self-exposure.

It is easy to see that, although maxim-based trust is a possible key to boosting firm performance, it is not a management tool suitable for short-term intervention. As the word maxim implies, it is more a constant socio-psychological predisposition underlying the entrepreneurs' decisions and actions.

However, as our results identify maxim-based trust as a possible key to competitive advantage and enhanced business performance in the long run, researchers as well as practitioners may regard it as an important phenomenon in the cooperation context. Our findings may contribute to freeing this social phenomenon from its frequent characterization as utopian and out of touch with reality. In this respect, our results challenge theoretical concepts that adhere to the concept of homo oeconomicus. This may provide support for those who have appropriate resources at their disposal and are willing to develop a maxim-based trust relationship. The more maxim-based trust cooperation relationships are realized in highly uncertain and complex contexts, the less society suffers from the consequences of market and organization failure.

In the field of SME cooperation, our results challenge arguments based on transaction cost economics alone, such as those put forth by Williamson (1991), as well as explanations of exchange transactions based on rational choice theory (as argued by Axelrod (1984), for example). The results also provide empirical support for more holistic concepts of inter-firm transactions as proposed by Roessl (1994), Osterloh and Weibel (2000), Adler (2001) and Carson, Madhok and Wu (2006), to name just a few examples.

In light of our empirical results, further research in this field is certainly worthwhile, both from a scientific as well as a practical point of view.

Limitations and directions for future research

First, the moderate response rate has to be qualified in light of the fact that surveys on SMEs (especially in transition economies) typically show low response rates. This difficulty is exacerbated when surveys address sensitive issues such as trust in cooperation partners. However, our check for non-response bias as well as a test comparing early, middle and late responders showed no systematic bias, thus indicating robustness of the results presented.

Second, although the survey instrument was tested in a 2004 survey of over 600 Austrian SMEs and the consistency of the results with those of the study at hand indicates reliability, further use in other contexts would be required in order to legitimate the claim of reliability. This could likewise demonstrate whether our findings are valid in other geographical and cultural contexts as well as in a sample of large companies.

Third, our one-sided measurement of maxim-based trust is justified by theoretical arguments and therefore does not compromise the empirical results. However, the measure should be subjected to further validation in qualitative as well as quantitative studies using pairs of cooperators. Pairing would further increase the reliability of the data, but at the same time represents a major challenge with regard to the anonymity of the respondents and, consequently, the resulting response rate.

Fourth, as we employed a cross-sectional design, we cannot rule out reverse causality. In order to enhance clarity in this regard, a longitudinal study would have to be conducted. Such a design would also yield even higher explained variance in performance.

However, we are convinced that by presenting innovative lines of argumentation and current empirical results, we have been able to enhance our understanding of how SME cooperation arrangements generally contribute to business performance, and to add another piece to the puzzle regarding the special value of maxim-based trust relationships.

Matthias Fink is an assistant professor at the Institute for Small Business Management and Entrepreneurship at the WU Vienna University of Economics and Business where he also earned his PhD in Small Business Management. Furthermore, he is a senior researcher at the Research Institute for Co-operation and Co-operatives and Visiting Professor at Vaasa University (Finland) and Universidad Autónoma de Barcelona (Spain). Mr. Fink is lecturer at several European universities. He holds a three-year fellowship (APART – Austrian Program for Advanced Research and Technology) granted by the Austrian Academy of Sciences. His main research interests are interorganizational cooperation, trust in the economic context, internationalization of SMEs, community-based entrepreneurship and entrepreneurial marketing.

Alexander Kessler is an associate professor and head of the Competence Center Entrepreneurship at the Institute for Management and Entrepreneurship at FHWien University of Applied Sciences of WKW, Vienna. Furthermore he is a lecturer and researcher at the Institute for Small Business Management and Entrepreneurship at the WU Vienna University of Economics and Business and a visiting professor at the Masaryk University in Brno, Czech Republic. He earned his master's degree, his PhD and his Habilitation in business administration at WU Vienna University of Economics and Business. His main research interests are business start-up and development, corporate entrepreneurship, entrepreneurship in countries of transition, international comparisons in entrepreneurship research, family business research, and trust in SME cooperation relationships.