Controlling interorganizational relationships:
the influence of formal and informal control on
partner performance
Master Thesis
MSc Organizational & Management Control
Faculty of Economics and Business
University of Groningen
02-09-2018
Word count: 11022
Anoek Abbingh
S2370123
a.abbingh@student.rug.nl
Supervisor: A. Rehman Abbasi
2
Abstract
4
Introduction
Ever since the 80s, western countries have seen an increase in interorganizational relationships (Agranoff and McGuire, 1998; Bryson, Crosby and Stone, 2006). These interorganizational relationships are described as the fairly enduring transactions, flows, and linkages that occur among or between an organization and one more organization in its environment in order to reach mutual objectives (Oliver, 1990). Although interorganizational cooperation seems to be a trend, scientific research shows that this cooperation is a difficult process (Einbinder, Robertson, Garcia, Vuckovic and Patti, 2000). It is not guaranteed that the objectives may be achieved in the way it was planned and most of the time the mutual objectives are not achieved at all (Einbinder et al., 2000). Besides that, interorganizational relationships can lead to tensions between the organizations, frustration at both parties and disappointing results (Huxham and Vangen, 2005). Most of the failed interorganizational relationships or objectives are due to the lack or insufficiency of organizational control (Einbinder et al., 2000).
In this study, I focus on the roles of formal and informal control in an interorganizational relationship, particularly on how control affects the partner performance. The moderating effects of market volatility and behavioral uncertainty on the relationship between control and partner performance were also studied. An organization can control the interorganizational relationship by using formal control and informal control. Formal control refers to ‘officially sanctioned institutional mechanisms, such as visible, objective forms of control’. Whereas informal control refers to ‘unwritten, unofficial, less objective, uncodified forms of control’ (Cardinal et al., 2004). Visibility and explicitness are the key differentiators between formal and informal control (Kreutzer, Cardinal, Walter and Lechner, 2016). Both types of control have an influence on partner performance. Partner performance can be described as a measure of satisfaction one party has about the performance of its partner in an interorganizational relationship (Poppo and Zenger, 1998). All the variables will be further explained in the theoretical framework section.
5 important, since it is the basis of maintaining and ultimately achieving objectives. Managing interorganizational relationships seems to be difficult, making successful interorganizational relationships a rarity (Ireland, Hitt, and Vaidyanath, 2002). Based on the information stated above, the conclusion is that control is of great importance for the success of interorganizational relationships and the partner performance. For this reason, the outcomes of this study are relevant.
At a conceptual level, the three types of control as described above can be extracted to formal- and informal control. In this study, I focus on the roles of both the formal- and informal aspect of controls in an interorganizational relationship, particularly on how these controls affect partner performance. Partner performance can be described as a measure of satisfaction one party has about the performance of its partner in an interorganizational relationship (Poppo and Zenger, 1998). Research in the relationship between control and partner performance in interorganizational relationships is important for several reasons. In 2000, Einbinder et al. stated that the effect of control on partner performance in interorganizational relationships has not been made clear, and still this is a relevant point of attention in studies in interorganizational relationships. For the interorganizational relationship to be successful, a good partner performance is necessary. Therefore, the effect that both formal and informal control has on partner performance should be made clear. In order for control to have a positive influence on partner performance it is necessary to understand how control should be structured. Control has been both positively and negatively linked to partner performance (Aulakh, Kotabe and Sahay, 1996; Bello and Gilliland, 1997). These conflicting statements root from the distinction between formal control and informal control.
6 This study is extending the existing literature by exploring the formal and informal control mechanisms of interorganizational relationships located in the Netherlands, as Hopwood argues that ‘planning, budgeting and control processes flow from one organization into others, creating, as they do, a more explicit awareness of the interdependency of actions and the role which joint action can play in organizational success’ (1996). Effective management control provides accurate information, which is essential for effective decision making as well as maintaining the effective functioning of the organization (Jap and Ganesan, 2000). Since control mechanisms are a huge influence in the success of interorganizational relationship, it is an important topic to study.
This study also contributes to the existing literature by assessing the moderating effects of market volatility and behavioral uncertainty. At this moment, market volatility is increasing. R. Detrick (Chief Market Strategist) argues that this year markets have not seen moves this wild since the financial crisis (Lahiff, 2018). Since the market volatility is increasing, it gets more interesting to have a look at. Having a higher uncertainty might result in different outcomes than previous studies. Behavioral uncertainty refers to the possibility of opportunistic behavior (Cechin, Bijman, Pascucci, Zulbersztajn and Omta, 2013). In an alliance, behavioral uncertainty always plays a part, which makes it an important moderator to study. Practically, the results of this research on the effects of control on partner performance will be interesting for managers within an interorganizational relationship. Jap and Ganesan (2000) argue that developing and implementing effective control mechanisms is a must when managing interorganizational relationships.
8
Theoretical framework
In this chapter, I will discuss the theoretical framework. First, I will explain the main variables of this study. Then the theory will lead to the hypotheses. At last I will show the conceptual model.
Organizations belong to the most significant structures through which society functions (National Research Council, 1997). Organizations are seeking ways to defend against competitive attacks, enter into new markets, and gain access to developing technologies. Organizations are commonly using interorganizational relationships as a strategy (National Research Council, 1997). An interorganizational relationship is defined as the formal linkages (e.g., contractual, equity) between two or more organizations to produce or coordinate some good or service (Hearld and Carroll, 2016). Organizations start an interorganizational relationship, because it is believed that both parties can benefit more from working with one another in some relationship than working independently. Interorganizational relationships may provide many benefits, but they are also quite unstable (Das and Teng, 2000). There is a probability that the interorganizational objectives will not be achieved because of the lack of collaboration (Das and Teng, 1996). Control in an interorganizational relationship reduces this probability.
9 control are rules. This type of control can be seen as formal control. Clan control not only requires a norm of reciprocity and the idea of legitimate authority, but also social agreement on a broad range of values and beliefs. Clan control lacks the explicit price mechanism of the market and the explicit rules of the bureaucracy. However, clan control relies upon a deep level of common agreement between members on what constitutes proper behavior, and it requires a high level of commitment on the part of each individual to those socially prescribed behaviors. This control can be seen as informal control. Clan control is more demanding than either a market or a bureaucracy in terms of the social agreements which are prerequisite to its successful operation. For this study, I will be using the terms formal control and informal control. Ouchi (1979) stated that there exist two underlying issues which are of central importance in determining which form of control will be more efficient. First is the issue of the clarity with which performance can be assessed. Second is the degree of goal incongruence.
Control mechanisms are used to coordinate the input of resources and the activities, improving the partner performance in an interorganizational relationship (Dekker, 2004). Partner performance assesses a party’s satisfaction with the performance of its partner (Poppo and Zenger, 1998). Ariño (2003) argues that partner performance consists of both ‘the degree of accomplishments of the partners’ goal and the extent to which their pattern of interactions is acceptable to the partners. De Rond (2003) found evidence that in an alliance organizations not only assess the performance of their relationship on economic or strategic outcomes, but most of all on factors such as the ease of cooperation, the presence of conflicts, and the partners’ satisfaction with coordination and communication processes.
Gulati (1998) portrays the problem of understanding the factors influencing partner performance as ‘one of the most interesting and also one of the most frustrating questions’ on the research agenda. The complexity has been widely recognized in research over the last decade (Zollo, Reuer and Singh, 2002). The difficulty in studying partner performance has been attributed to the lack of objective performance data and the diversity in firms’ strategic intents in pursuing alliances (Anderson, 1990).
Formal control
10 are planning, procedures, rules and regulations (Gulati and Singh, 1998). Ouchi (1979) argues that behavior control works best in a situation where there is a low ability to measure outputs and a perfect knowledge of the transformation process. Output control, according to Ouchi (1979), works best in a situation where there is a high ability to measure outputs and an imperfect knowledge of the transformation process.
Transaction cost economics states that in principle transactions can take place within three governance structures: market, hierarchy or hybrid (Williamson, 1991). The governance mechanisms related to these governance structures are: price mechanism (market), authority, rules, and regulations (hierarchy), and contractual arrangements (hybrid). Transaction costs depend on a combination of three characteristics of the transactions taking place, i.e. asset specificity, uncertainty (environmental and behavioral uncertainty) and frequency of the transactions, and two characteristics of human nature, i.e. bounded rationality and opportunistic behavior. In interorganizational relationships, organizations make investments specifically for the IOR. These investments could have little value outside the IOR. Organizations therefore need to safeguard their investments from being appropriated by opportunistic behavior of their partner (Dekker, 2004). Transaction cost economics argues that in case of a high degree of asset specificity the hierarchy is the most appropriate governance structure. In case of a medium degree of asset specificity the hybrid governance structure is the most appropriate structure. If the parties choose to establish an IOR, contractual arrangements need to be established in order to adequately control the IOR (Poppo and Zenger, 1998). As contractual arrangements can be classified as formal control mechanisms, it can be argued that formal control has a positive influence on partner performance.
In a study of Van de Ven and Walker (1984) it is found that excessive formalization and monitoring of the terms of interorganizational relationships leads to conflict and distrust among parties. Companies keep their own unique identities and autonomy when they are growing into interdependency (Gouldner, 1959). This shows that a high level of formal control negatively influences the partner performance of an interorganizational relationship.
11 Vlaar, Van den Bosch and Volberda (2007) proposed that very low and very high levels of formal control have a negative effect on partner performance. There is a low level of control when e.g. the contract does not precisely define the responsibilities of the partner. There is a high level of formal control when e.g. the contract does precisely define the responsibilities of the partner. Formal control might also have an impeding effect on creativity and innovation (Nooteboom, 1999).
As shown above, there are many different opinions on the influence of formal control on partner performance. Therefore, it is important to test this relationship in a specific geographical area: companies in the Netherlands. Combining the different opinions, a curvilinear relationship between formal control and firm performance is expected.
H1A: The relationship between formal control and partner performance is curvilinear (inverted
U-shaped).
Informal control
Informal control relates to the informal cultures and systems influencing parties of an interorganizational relationship (Dekker, 2004). Informal control can be seen as a control based on mechanisms inducing self-regulation.
Ouchi (1979) stated that clan control relies upon a deep level of common agreement between members on what constitutes proper behavior, and it requires a high level of commitment on the part of each organization within an interorganizational relationship, because the clan lacks the explicit price mechanism of the market and the explicit rules of the bureaucracy. Clan control is an informal control mechanism. According to Ouchi (1979), clan control is used when market control and bureaucracy control are not possible. Clan control, and therefore informal control, is used to improve the performance of the interorganizational relationship and the partner performance.
12 Relational exchange theory (RET) explains interpersonal relations in terms of the exchange of perceived gains and losses (Morgan and Hunt, 1994). Relational exchange theory argues that relational norms serve to prescribe and prohibit certain behavior in exchange relationships (Morgan and Hunt, 1994). Joshi and Stump (1998) argue that relationships are effectively governed if they are characterized by high levels of commitment and low levels of opportunism, which is realized by relational norms. Relational norms are a form of control. It is argued that the behavior in the relationship is not controlled through incentives, but through internalization (Kelman, 1958) and moral control (Larson, 1992). Relational norms improve the relationship efficiency (Barney and Hansen, 1994). When the relationship efficiency improves, the partner performance improves. Therefore, it is expected that informal control positively influences partner performance in an interorganizational relationship.
In the inter-firm relationship literature most researchers agree that partners benefit by getting along with one another and equitable sharing of benefits (Dyer & Singh, 1998; Muthusamy & White, 2006). The chance for partners to get along better increases when both organizations have the same morals. Relational norms are part of informal control, which suggests that informal control will positively influence the partner performance.
The combination of these different views from existing literature on informal control, has led to the following hypothesis:
H1B: Informal control has a positive influence on partner performance.
Market volatility
Market volatility refers to unpredictable changes in the external environment (Poppo et al., 2016). Poppo et al. (2016) argue that the uncertainties someone has about the surrounding environment and the uncertainties about the consequences of his behavior are some of the most important factors to influence an individual’s job satisfaction and job performance. Environmental uncertainties are described as unpleasant and harmful to effective decision-making and performance (Weed and Mitchell, 1980). They create instability, which is difficult to understand and respond to, and it requires adaption (Poppo et al., 2016).
13 therefore becomes less valuable. This is because important factors such as pricing, product specifications, and technologies are constantly changing (Krishnan, Martin and Noorderhaven, 2006). Formal control can be used to ensure that important information is often shared, however it is difficult to include all possible situations in formal control mechanisms when the market is constantly changing.
Burns and Stalker (1961) claim that organizations will find it difficult to establish formal rules and procedures when the environment is constantly changing. Poppo et al. (2016) stated that uncertainty requires adaption. Formal control is usually written down in contracts, which makes it difficult to quickly adapt to changes. It takes time to write a contract, and to constantly change parts of the contract when the market changes are expensive. Organizations might reject changing the contracts, or do change the contracts at high costs. This results in a lower partner performance. Krishnan et al. (2006) argue that uncertainty increases the information processing demands required to navigate the future. For organizations to receive the requested information, formal control must increase. This will also lead to higher costs, which will result in a lower partner performance.
Krishnan (2016) argued that adopting formal control under high market volatility may hinder rather than help partner performance. Fast and well-informed responses become difficult. In a highly changing environment decisions should be made on lower levels in an organization. This ensures that decisions are made more quickly. Flexibility will be lost with formal control. This could result in an inappropriate response to the market and damage to the partner performance (Krishnan, 2016).
Combining the different views on market volatility, the following hypothesis has been made:
H2A: Market volatility will negatively moderate the relationship between formal control and
partner performance.
14 Furthermore, research suggests that relying on informal control can cause organizations to become insensitive to environmental changes (Krishnan, 2016). Trust is seen as the principal mode of informal control. Building trust is a time consuming project, which cause organizations to be anxious about responses to market volatility that require major changes. The fear of harming the relationship may encourage them to prefer ‘inaction over action’ (Kahneman and Lovallo, 1993). As a consequence, an organization might not react to changes in the market, which could result in not meeting the relationship objectives. This may harm the partner performance. If market volatility is not been dealt with the correct way, it can harm the relationship between informal control and partner performance.
Therefore, it is expected that market volatility negatively influences the relationship between informal control and firm performance.
H2B: Market volatility will negatively moderate the relationship between informal control and
partner performance.
Behavioral uncertainty
Behavioral uncertainty refers to the extent to which one party cannot effectively observe or evaluate the activities of the other party. When behavioral uncertainty arises, the other party is more likely to misbehave or not disclose information in order to maximize self-gain (Schepker, Oh, Martynov and Poppo, 2014). When behavioral uncertainty is high, it is hard to observe the inputs or the activities of the other party (Poppo et al., 2016). In this situation bounded rationality weakens and opportunistic behavior will arise. It is harder for formal control mechanisms to influence the partner performance.
As stated before, formal control consists of output control and behavior control (Ouchi, 1979). If the output can be measured, output control is still possible in a situation where there is high behavioral uncertainty. Rewards and sanctions can still effectively be applied. For example, if the company detects poor qualitative output from their partner, the company can still fall back on written contracts. Behavioral control, however, is in a situation of high behavioral uncertainty not quite possible to carry out.
15 (Mayer and Nickerson, 2005). Also, an organization might value the benefits more than the costs of ending a relationship.
Behavioral uncertainty will make it harder for formal control to be effective (Poppo et al., 2016), and will have less impact on partner performance. Therefore, it is expected that behavioral uncertainty will weaken the relationship between formal control and partner performance.
H3A: Behavioral uncertainty will negatively moderate the relationship between formal control
and partner performance.
Informal control relies on each partners’ confidence that the other will not abuse its vulnerability, even if the benefits outweigh the potential losses (Barney and Hansen, 1994). Behavioral uncertainty arises when organizations cannot clearly observe the behavior of their partner. Since informal control relies on confidence instead of contracts, behavioral uncertainty does not necessarily have a great impact. Informal control makes partners likely to respect the others’ boundaries and to not cross them (Krishnan et al., 2006). Hence, certainty on the partners’ behavior is not needed.
The relational exchange theory states that the relational norms within an interorganizational relationship are implemented to reduce opportunistic behavior. If there is a situation where there is much behavioral uncertainty, the organizations will establish more relational norms in order to reduce the chance of opportunistic behavior by the other party. The relational norms are extended to assure a positive partner performance. This implies that the relationship will positively be moderated by a high behavioral uncertainty.
Ouchi (1980) argues that clan control is most suitable for tasks characterised by behavioral uncertainty, because clan control will reduce behavioral uncertainty. In a clan culture there is harmony of shared interests and goals aligns joint action, and results in effective task performance. Effective task performance will eventually lead to improvement of partner performance. This culture is seen in organizations acting as family and has social features as trust, solidarity and unity (Acar and Acar, 2014). Clan control is seen as informal control, and therefore seems to be beneficial in situations with high behavioral uncertainty.
16
H3B: Behavioral uncertainty will positively moderate the relationship between informal control
and partner performance.
These six hypotheses are combined into the conceptual model, which is shown in figure 1.
17
Methodology
In this section I will first explain how the sample is chosen and how the data is collected. Then, I will explain how the dependent and the independent variables are measured. Next, I will discuss the control variables used in this research. At the end of this section I will discuss the construct validity and reliability and the common method assessment.
3.1 Sampling and data collection
The aim of this research is to explore in which amount formal control and informal control influence partner performance in an interorganizational relationship. This research will be conducted using a quantitative research method. A quantitative approach is used when there is a need for confirmation or disconfirmation of hypotheses and there is a need for information about the effect of variable X on variable Y, a quantitative research method is used (Blumberg, Cooper and Schindler, 2014). This corresponds to the aim of this research, which is why the quantitative research method is used.
Data was collected using a survey. This survey is developed by my thesis supervisor, and had a series of pretests and quality checks. The data are collected by seven students from the University of Groningen. Every student has contacted multiple organizations with the following characteristics; the organizations have a signed contract with their partner(s); the organizations are for-profit companies; the organizations have a minimum revenue of one million euros per annum; and the organizations have at least ten employees. These organizations are either private or public limited and are all established in the Netherlands. I have contacted owners, directors and managers from different organizations, because the possibility was high that these people have good knowledge about their interorganizational relationships. I have contacted them by telephone and my email to request their collaboration. I have contacted 67 persons and found 10 willing to cooperate, which brings my personal response rate to 14,9%. I have combined my data with the data collected by my fellow students, which forms a sample size of 112. The respondents were visited in their offices, where they got presented the survey. The respondents could ask for clarification to the interviewees if questions were unclear. The information given to them was kept at a minimum; this way the answers could not be manipulated. After eliminating one survey with missing data, a sample of 111 complete responses was used to test the hypotheses.
3.2 Dependent and independent variables
18 consist of three items. Two items assess the preciseness of the contract on the role/responsibilities of both parties and on the performance expectations. The other item assesses in which level the contract is a primary mechanism to regulate the behavior of the partner. The measures of informal control consist of four items. The measures indicate whether control was exercised through the reliance on promises, participatory decision-making, joint problem solving and fine-grained information exchange. The measures of partner performance were adopted, based on the paper by Poppo and Zenger (1998). The measures of partner performance consist of four items. These items assess the satisfaction with the partners’ firm performances. The measures of market volatility were adopted from the paper by Carson, Madhok and Wu (2010). The measures consist of four items. Two items assess the preferences and demands of the customers. One item assesses how rapidly the competitors change their product technologies. The last item assesses the changes in the industry. The measures of behavioral uncertainty were adopted from the paper by Poppo, Zhou and Li (2016). The measures consist of two items. The items assess the difficulty in evaluating if the supplier follows the recommended operating procedures, and the presence of accurate reports about the supplier’s difficulties.
3.3 Controls
In order to diminish the effects of other variables influencing the relationships investigated in this study, I have controlled for the relationship history and the type of alliances. Heimeriks and Duysters (2007) studied the effect of experience on alliance performance. Their results show a positive significant relation, which implies that experience is indeed an important cause of alliance performance. Furthermore, an organization might have a tendency to create new alliances with organizations they already had alliances with (Gulati, 1995). Organizations gain knowledge about preventing conflicts in these alliances. This suggests that partner performance will be better in relationships between parties that already had previous relationships, rather than new relationships. The interorganizational relationship history is measured by the question ‘how many times have the two firms worked together?´. Experience is necessary for firms to learn (Levitt and March, 1988).
19 suggests that having a successful interorganizational relationship, and also a good partner performance, depends on the type of the interorganizational relationship and on the partner characteristics.
3.4 Construct validity and reliability
To understand the underlying structure of the items and to validate the measures, I will conduct an exploratory factor analysis. The results are shown in table A1 and shows which questions are coherent with each other and the factor loading of each question. In table A1, the results are shown of the rotated component matrix. The rotation method used is varimax with Kaiser normalization, since varimax is considered to be the best rotation method (Fabrigar, Wegener, MacCullum and Strahan, 1999). This is why the varimax with Kaiser normalization was chosen. To test the size of the sample, there has been conducted the Kaiser-Mayer-Otkin (KMO) test and the Bartlett’s Test of Sphericity. KMO test shows a value of 0.667, and the Bartlett’s Test of Sphericity shows a significant result. This indicates that the collected data is suited for factor analysis. Table A1 reports the factor loading of each item. All factor loadings were higher than 0.7, which meets the requirements. The factor analysis revealed five factors with eigenvalues greater than one.
The Cronbach’s alpha of all variables have been tested and the results are shown in table A1. Cronbach’s alpha is commonly used to examine the internal reliability of summated rating scales (Cronbach, 1951). It measures the extent to which responses given to the survey questions correlate with each other (Vaske. Beaman and Sponarski, 2017). The value of the alpha depends on the number of items in the scale (Streiner, 2003). The average reliability increases when the number of items increases. The Crohnbach’s Alpha is acceptable if the value is higher than 0.7. The Cronbach’s alpha of behavioral uncertainty is 0.45. The construct behavioral uncertainty is measured by only two items. This predicts a lower Cronbach’s alpha. Bernardi (1994) argued that a low Cronbach’s alpha does not immediately put the results of the analysis into question. In addition, the measurements of behavioral uncertainty were adopted from the paper of Poppo et al. (2016). These factors combined, is why I accept the low Cronbach’s alpha.
3.5 Common method assessment
21
Results
In this section I will discuss the correlation of all variables, explain if multicollinearity is likely to be a problem and at last the results of the multiple regression analyses.
Table 1. Correlation matrix
Mean S.D. 1 2 3 4 5 6 1. Formal control 4.36 1.42 1 2. Informal control 5.30 1.10 0.232** 1 3. Partner performance 5.30 0.98 0.091 0.244** 1 4. Market volatility 4.19 1.39 0.157 0.255** 0.024 1 5. Behavioral uncertainty 3.24 1.23 -0.142 -0.034 -0.279** -0.047 1 6. Relationship history 3.79 1.87 -0.089 -0.177* 0.001 -0.027 0.072 1 N=111; **p<0,01; *p<0,05 (1-tailed).
Table 1 shows the means, standard deviations and the Pearson correlation coefficients for all variables. The dummy variables from the control variable ‘relationship type’ have been excluded from this table. Notable is the mean of ‘partner performance’. With a minimum of one and a maximum of seven, it scores a fairly high 5,3. Partner performance is measured by the question how satisfied the respondent is, in comparison to pre-established performance expectation with the partner firm’s performance. The mean score of 5.3 implies that the respondents are quite satisfied with the partner firm’s performance. Table 1 also shows that control is mostly performed through informal control and less through formal control. The conceptual model has been tested by using a multiple regression. The results of the multiple regression analysis, shown in table 2, are divided in five different models. In model 1 I regressed for the control variables. This model has an insignificant F value of 0.231. Therefore, the results of this model cannot be interpreted. In model 2 I added the direct effects of formal control, informal control, market volatility and behavioral uncertainty. This model has a significant F value of 2.543. The adjusted R squared changed with 0.103. To assess the effect of each moderator, I have added interactions stepwise in model 3 and 4. Whereas in model 3 the interaction with market volatility is regressed and in model 4 the interaction with behavioral uncertainty. Model 3 decreased in F value, to a significant value of 1.964. Model 4 has a significant F value of 2.110, with an increase in the adjusted R squared of 0.010. In the last model, model 5, I have regressed the whole model. This model has a decreased significant F value of 1.458.
22 multicollinearity might be present. This could violate the independence. Since I used multiple linear regression to test my hypotheses, a check for multicollinearity is necessary. There are two ways to assess multicollinearity. The first one is by looking at the highest VIF. VIFs above 10 indicate multicollinearity. In this research the highest VIF is 2.279, therefore it does not indicate multicollinearity. The second way to assess multicollinearity is by examining the tolerance. A small tolerance value indicates a risk for multicollinearity. My lowest tolerance is 0.725. It is unlikely for multicollinearity to be present in this study.
Model 2 in Table 2 is used to test de direct effects on partner performance. Because this model has a significant Model F and the highest VIF is within requirements, model 2 is suitable for accepting or rejecting hypotheses. In H1A, it has been hypothesized that formal control will have a curvilinear relationship with partner performance. This is tested by comparing the variable Formal control with the variable Squared Formal control. Both variables do not have a significant regression (b=-0.049, p>0.05; b=-0.073, p>0.05). Thus, H1A is not supported. In H1B, it has been predicted that informal control will positively influence partner performance. The results show that the impact is positive and significant (b=0,257, p<0.05). Therefore, H1B is supported.
Model 3 is used to test the interaction of market volatility on formal- and informal control. In H2A it is expected for market volatility to positively moderate the relationship between formal control and partner performance. The results show an insignificant relationship (b=-0.005, p>0.05). Thus, H2A is not supported. In H2B it is expected for market volatility to positively moderate the relationship between informal control and partner performance. The results show an insignificant relationship (b=0.041, p>0.05). Thus, H2B is not supported.
Model 4 is used to test the interaction of behavioral uncertainty on formal- and informal control. In H3A it has been predicted for behavioral uncertainty to negatively moderate the relationship between formal control and partner performance. The results show an insignificant relationship (b=-0,089. p>0,05). Thus, H3A is not supported. In H3B it is expected for behavioral uncertainty to positively moderate the relationship between informal control and partner performance. The results also show an insignificant relationship (b=-0,031, p>0,05). Therefore, H3B is not supported.
23
Table 2. Standardized estimates of regression analysis
Partner performance Independent variables M1 M2 M3 M4 M5 Control variables IOR history -0.014 0.031 0.031 0.038 0.038 Buyer supplier 5.377 5.290 5.281 5.288 5.251 Joint venture 5.010 4.842 4.837 4.814 4.809 Outsourcing 5.727 5.461 5.442 5.399 5.384 R & D 5.613 5.413 5.396 5.351 5.335 Other 4.993 5.039 5.009 4.992 4.966 Direct effect
Formal control H1A: - -0.049 -0.045 -0.053 -0.049
Squared Formal control H1A: - -0.073 -0.071 -0.076 -0.075
Informal control H1B: - 0.257* 0.269* 0.253* 0.263*
Market volatility - -0.062 -0.056 -0.066 -0.061
Behavioral uncertainty - -0.253** -0.25* -0.256* -0.254*
Interactions
FC x market volatility H2A: - - -0.005 - -0.001
IC x market volatility H2B: - - 0.041 - 0.035
FC x behavioral uncertainty H3A: - - - -0.09 -0.089
24
Conclusion
25
Discussion
In this section I will discuss the results of this research. Then I will mention the limitations of this research and give recommendations for further future research on this topic.
Discussion
This study examined the influence of control on partner performance in interorganizational relationships. Drawing on the literature, in this study, the concept of control consists of formal control and informal control. The moderating effects of market volatility and behavioral uncertainty were studied as well.
The data collected has only found support for one out of six hypothesis in the model. The multiple regression analysis shows that the influence of informal control on partner performance is positive and significant, while the influence of formal control on partner performance is insignificant. Existing literature has conflicting views on how formal and informal control interact. The traditional view argues that either formal control or informal control is the most appropriate (Ouchi, 1979). My study is based on this view. However, a more recent view argues that formal control and informal control are complementary (Cardinal et al., 2004). It states that these forms of control cannot be seen as separate forms of control, but as substitutes. Up until now, there is no clearance which view is the right view. Based on this more recent view, the results presented in this study could be incorrect.
The results do not support H2A and H2B. These hypotheses suggested that market volatility negatively moderates the relationship between formal control and partner performance and between informal control and partner performance. Between these variables no significant interaction has been found. Market volatility refers to the unpredictability of environmental changes over time (Carson, Madhok and Wu, 2010). Carson, Madhok and Wu (2010) argue that with high market volatility formal control is not the optimal control mechanism, since formal control is not flexible enough. However, these results are not linked to partner performance.
26
Limitations
The first limitation of this study is about the respondents. The data used in this study has been collected in the Netherlands. For example, the company culture in the United States of America is different than the company culture in the Netherlands. In the Netherlands companies often have a flatter organizational structure in comparison to companies in the USA (Kamer van Koophandel). In addition, companies in the USA are mostly oriented on the short term, whereas companies in the Netherlands often use a longer time perspective. This could influence the way companies control their interorganizational relationships. Therefore, the results of this study might not be applicable to interorganizational relationships in the USA. This harms the generalizability of this study.
In total, there were five different types of alliances used in this research. From the 112 respondents, 72 claimed to have a buyer-supplier relationship. The other 40 respondents were divided over the four other types of alliances. This means that 64.3% of the collected data is based on the buyer-supplier relationship. In this study, the different types of alliances were not distinguished in the regression analysis. This study focuses on interorganizational relationships in general. However, the results might be more applicable to buyer-supplier relationships and less to the other types of alliances.
The sample size used in this research is rather small. Poppo and Zhou (2016), for example, studied the impact of trust on partner performance. Their sample size consisted of 211 complete responses. There are many different recommendations about the size of the sample, but the common recommendation is that a larger sample size is better, since a larger sample size is more representative of the population and it limits the influence of outliers (Marsh, Balla and McDonald, 1988).
Future research
In connection with the previous section, I have some recommendations for future research. In this study the interorganizational relationship has been studied by using information from one organization. This shows one side of the relationship. For future research it might be interesting to investigate the relationships from both sides. The partner performance may be experienced quite differently by both firms.
27
28
References
Acar, A., & Acar, P. (2014). Organizational culture types and their effects on organizational performance in Turkish hospitals. Emerging Markets Journal, 3(3), 18.
Agranoff, R., & McGuire, M. (1998). Multinetwork management: Collaboration and the hollow state in local economic
policy. Journal of Public Administration Research and Theory, 8(1), 67-91.
Anderson, E. (1990). Two firms, one frontier: On assessing joint venture performance. MIT Sloan Management Review, 31(2), 19.
Ariño, A. (2003). Measures of strategic alliance performance: An analysis of construct validity. Journal of international Business studies, 34(1), 66-79.
Aulakh P. S., Krotabe, M., & Sahay, A. (1996). Trust and performance in cross-border marketing partnerships: A behavioral approach. Journal of international business studies, 27(5), 1005-1032.
Barney, J. B., & Hansen, M. H. (1994). Trustworthiness as a source of competitive advantage. Strategic management journal, 15(S1), 175-190.
Barringer, B. R., & Harrison, J. S. (2000). Walking a tightrope: Creating value through interorganizational relationships. Journal of management, 26(3), 367-403.
Bello, D. C., & Gilliland, D. I. (1997). The effect of output controls, process controls, and flexibility on export channel
performance. the Journal of Marketing, 22-38.
Bernardi, R. A. (1994). Validating research results when Cronbach's alpha is below. 70: A methodological procedure. Educational and Psychological Measurement, 54(3), 766-775.
Blumberg, B. F., Cooper, D. R., & Schindler, P. S. Business research methods. 2014.
Bryson, J. M., Crosby, B. C., & Stone, M. M. (2006). The design and implementation of cross‐sector collaborations: Propositions from the literature. Public Administration Review, 66(s1), 44-55.
Burns, T. E., & Stalker, G. M. (1961). The Management of Innovation (SSRN Scholarly Paper No. ID 1496187). Rochester, NY: Social Science Research Network.
Cardinal, L. B., Sitkin, S. B., & Long, C. P. (2004). Balancing and rebalancing in the creation and evolution of organizational control. Organization Science, 15(4), 411-431.
Carson, S. J., Madhok, A., & Wu, T. (2006). Uncertainty, opportunism, and governance: The effects of volatility and ambiguity on formal and relational contracting. Academy of Management Journal, 49(5), 1058-1077. Cechin, A., Bijman, J., Pascucci, S., & Omta, O. (2013). Decomposing the member relationship in agricultural
cooperatives: Implications for commitment. Agribusiness, 29(1), 39-61.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. psychometrika, 16(3), 297-334.
Das, T. K., & Teng, B. S. (1996). Risk types and inter‐firm alliance structures. Journal of management 7 studies, 33(6), 827-843.
Das, T. K., & Teng, B. S. (2000). A resource-based theory of strategic alliances. Journal of management, 26(1), 31-61.
Das, T. K., & Teng, B. S. (2001). Trust, control, and risk in strategic alliances: An integrated framework. Organization studies, 22(2), 251-283.
Dalton, G. W., & Lawrence, P. R. (1971). Motivation and control in organizations.
De Rond, M. (2003). Strategic alliances as social facts: Business, biotechnology, and intellectual history. Cambridge University Press.
Dekker, H. C. (2004). Control of inter-organizational relationships: evidence on appropriation concerns and coordination requirements. Accounting, Organizations and Society, 29(1), 27-49.
Dyer, J. H., & Chu, W. (2003). The role of trustworthiness in reducing transaction costs and improving performance: Empirical evidence from the United States, Japan, and Korea. Organization science, 14(1), 57-68.
Dyer, J. H., & Singh, H. (1998). The relational view: Cooperative strategy and sources of interorganizational competitive advantage. Academy of management review, 23(4), 660-679.
Einbinder, S. D., Robertson, P. J., Garcia, A., Vuckovic, G., & Patti, R. J. (2000). Interorganizational collaboration in social service organizations: A study of the prerequisites to success. Journal of Children and Poverty, 6(2), 119-140. Emerson, R. M. (1976). Social exchange theory. Annual review of sociology, 2(1), 335-3627 Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor
29 Fryxell, G. E., Dooley, R. S., & Vryza, M. (2002). After the ink dries: The interaction of trust and control in US‐based
international joint ventures. Journal of Management Studies, 39(6), 865-886 Gargiulo, M., & Ertug, G. (2006). The dark side of trust1. Handbook of trust research, 165.
Gouldner, A. (1959). "Reciprocity and autonomy in functional theory." In Llewellyn Gross (ed.), Symposium on Sociological Theory: 241-270. New York: Harper & Row.
Gulati, R. (1995). Social structure and alliance formation patterns: A longitudinal analysis. Administrative science
quarterly, 619-652.
Gulati, R. (1998). Alliances and networks. Strategic management journal, 19(4), 293-317.
Gulati, R., & Singh, H. (1998). The architecture of cooperation: Managing coordination costs and appropriation concerns in strategic alliances. Administrative science quarterly, 781-814. Hearld, L. R., & Carroll, N. W. (2016). Interorganizational relationship trends of critical access
hospitals. The Journal of Rural Health, 32(1), 44-55.
Heimeriks, K. H., & Duysters, G. (2007). Alliance capability as a mediator between experience and alliance performance: An empirical investigation into the alliance capability development process. Journal of
Management Studies, 44(1), 25-49.
Hopwood, A. (1996). Looking across rather than up and down:on the need to explore the lateral processing of information. Accounting, Organizations and Society, 21, 589–590
Huberty, C. J. (2003). Multiple correlation versus multiple regression. Educational and Psychological
Measurement, 63(2), 271-278.
Huxham, C. & Vangen, S. (2005). Managing to collaborate : The theory and practice of Collaborative
Advantage. New York: Taylor & Francis.
Ireland, R. D., Hitt, M. A., & Vaidyanath, D. (2002). Alliance management as a source of competitive advantage. Journal of management, 28(3), 413-446.
Ittner, C. D., Larcker, D. F., Nagar, V., & Rajan, M. V. (1999). Supplier selection, monitoring practices, and firm performance. Journal of Accounting and Public Policy, 18(3), 253-281.
Jap, S. D., & Ganesan, S. (2000). Control mechanisms and the relationship life cycle: Implications for safeguarding specific investments and developing commitment. Journal of marketing research, 37(2), 227-245.
Jaworski, B. J. (1988). Toward a theory of marketing control: environmental context, control types, and consequences. The Journal of Marketing, 23-39.
Joshi, A. W., & Stump, R. L. (1998, January). The evolution of governance in exchange relationships: Adaptations to the transaction cost analysis framework and an empirical test. In American
Marketing Association. Conference Proceedings (Vol. 9, p. 296). American Marketing Association. Kahneman, D., & Lovallo, D. (1993). Timid choices and bold forecasts: A cognitive perspective on risk
taking. Management science, 39(1), 17-31.
Kamer van Koophandel. Cultuurverschillen. Retrieved August 18, 2018 from
https://www.kvk.nl/advies-en-informatie/internationale-handel/zakendoen-met-/zakendoen-met-de
verenigde-staten/cultuurverschillen/
Kelman, H. C. (1958). Compliance, identification, and internalization three processes of attitude change. Journal of conflict resolution, 2(1), 51-60.
Kerr, S., & Slocum, J. W. (1981). Controlling the performances of people in organizations. Handbook of organizational design, 2, 116-134.
Kreutzer, M., Cardinal, L. B., Walter, J., & Lechner, C. (2016). Formal and informal control as complement or substitute? The role of the task environment. Strategy Science, 1(4), 235-255.
Krishnan, R., Geyskens, I., & Steenkamp, J. B. E. (2016). The effectiveness of contractual and trust‐based governance
in strategic alliances under behavioral and environmental uncertainty. Strategic Management Journal, 37(12),
2521-2542.
Krishnan, R., Martin, X., & Noorderhaven, N. G. (2006). When does trust matter to alliance performance?. Academy of Management journal, 49(5), 894-917.
Lahiff, K. (2018, April 11). Stocks haven’t seen this much volatility since the financial crisis. Retrieved June 18, 2018, from
https://www.cnbc.com/2018/04/11/stocks-havent-seen-this-much-volatility-since-the-financial-crisis.html
30 collinearity. Electronic Journal of Applied Statistical Analysis, 11(1), 340-368.
Larson, A. (1992). Network dyads in entrepreneurial settings: A study of the governance of exchange relationships. Administrative science quarterly, 76-104.
Lawler, E. L. (1976). Combinatorial optimization: networks and matroids. Courier Corporation. Levitt, B., & March, J. G. (1988). Organizational learning. Annual review of sociology, 14(1), 319-338.
Li, Y., Xie, E., Teo, H. H., & Peng, M. W. (2010). Formal control and social control in domestic and international buyer–supplier relationships. Journal of Operations Management, 28(4), 333-344.
Lu, J. W., & Beamish, P. W. (2006). Partnering strategies and performance of SMEs' international joint ventures. Journal of Business Venturing, 21(4), 461-486.
Luo, Y. (2003). Industrial dynamics and managerial networking in an emerging market: the case of China. Strategic
Management Journal 24: 1315–1327.
Macneil, I. R. (1980). Economic analysis of contractual relations: its shortfalls and the need for a rich classificatory apparatus. Nw. UL Rev., 75, 1018.
Marsh, H. W., Balla, J. R., & McDonald, R. P. (1988). Goodness-of-fit indexes in confirmatory factor analysis: The effect of sample size. Psychological bulletin, 103(3), 391.
Mayer, K. J., & Nickerson, J. A. (2005). Antecedents and performance implications of contracting for knowledge workers: Evidence from information technology services. Organization Science, 16(3), 225-242.
Meyer, J. W., & Rowan, B. (1977). Institutionalized organizations: Formal structure as myth and ceremony. American journal of sociology, 83(2), 340-363.
Miner, J. B. (1975). "The Uncertain Future of the Lead- ership Concept: An Overview," in Leadership Frontiers, 1 James G. Hunt and Lars L. Larson, eds. Kent, OH: Kent State University Press, 197-2.
Mintzberg, H. (1978). Patterns in strategy formation. Management science, 24(9), 934-948.
Mjoen, H., & Tallman, S. (1997). Control and performance in international joint ventures. Organization science, 8(3),
257-274.
Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. The journal of marketing, 20-38.
Muthusamy, S. K., & White, M. A. (2006). Does power sharing matter? The role of power and influence in alliance performance. Journal of Business Research, 59(7), 811-819.
Nooteboom, B. (1999). Innovation, learning and industrial organization. Cambridge Journal of economics, 23(2), 127-150.
Oliver, C. (1990). Determinants of interorganizational relationships: Integration and future directions. Academy of management review, 15(2), 241-265.
Ouchi, W. G. (1977). The relationship between organizational structure and organizational control. Administrative science quarterly, 95-113.
Ouchi, W. G. (1979). A conceptual framework for the design of organizational control mechanisms. In Readings in Accounting for Management Control (pp. 63-82). Springer US.
Ouchi, W. G. (1980). Markets, bureaucracies, and clans. Administrative science quarterly, 129-141.
Ouchi, W. G., & Maguire, M. A. (1975). Organizational control: Two functions. Administrative science quarterly, 559-569.
Park, C. V., Sheath, J. N. (1975). Impact of prior familiarity and cognitive complexity on information processing rules.
Communicating with Consumers: The Information Processing Approach, Ray ML, Ward S. Sage: Beverly Hills, CA; 71-78
Paswan, A. K., Hirunyawipada, T., & Iyer, P. (2017). Opportunism, governance structure and relational norms: An interactive perspective. Journal of Business Research, 77, 131-139.
Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research: Problems and prospects. Journal
of
management, 12(4), 531-544.
Poppo, L., & Zenger, T. (1998). Testing alternative theories of the firm: transaction cost, knowledge-based, and measurement explanations for make-or-buy decisions in information services. Strategic management
journal,
853-877.
31 complements?. Strategic management journal, 23(8), 707-725.
Poppo, L., Zhou, K. Z., & Li, J. J. (2016). When can you trust “trust”? Calculative trust, relational trust, and supplier performance. Strategic Management Journal, 37(4), 724-741.
Reed, M. I. (2001). Organization, trust and control: a realist analysis. Organization studies, 22(2), 201-228. Ring, P. S., & Van de Ven, A. H. (1994). Developmental processes of cooperative interorganizational
relationships. Academy of management review, 19(1), 90-118.
Saxton, T. (1997). The effects of partner and relationship characteristics on alliance outcomes. Academy of management journal, 40(2), 443-461.
Schepker, D. J., Oh, W. Y., Martynov, A., & Poppo, L. (2014). The many futures of contracts: Moving beyond structure and safeguarding to coordination and adaptation. Journal of Management, 40(1), 193-225.
Siggelkow, N. (2002). Misperceiving interactions among complements and substitutes: Organizational consequences. Management Science, 48(7), 900-916.
Sitkin, S. B., Cardinal, L. B., & Bijlsma-Frankema, K. M. (Eds.). (2010). Organizational control. Cambridge University Press.
Streiner, D. L. (2003). Being inconsistent about consistency: When coefficient alpha does and doesn't matter. Journal
of personality assessment, 80(3), 217-222.
Uzzi, B. (1997). Social structure and competition in interfirm networks: The paradox of embeddedness. Administrative
science quarterly, 35-67.
Van de Ven, A. H. (1976). On the nature, formation, and maintenance of relations among organizations. Academy of management review, 1(4), 24-36.
Van de Ven, A. H., & Ring, P. S. (2006). Relying on trust in cooperative inter-organizational relationships. Handbook of trust research, 144-164.
Van de Ven, A. H., & Walker, G. (1984). The dynamics of interorganizational coordination. Administrative science quarterly, 598-621.
Van Maanen, J., & Barley, S. R. (1984). Occupational communities: Culture and control in organizations. In BM Staw
& LL cummings (Eds), research in organizational behavior. Google Scholar.
Vaske, J. J., Beaman, J., & Sponarski, C. C. (2017). Rethinking internal consistency in Cronbach's Alpha. Leisure Sciences, 39(2), 163-173.
Vlaar, P. W., Van den Bosch, F. A., & Volberda, H. W. (2007). On the evolution of trust, distrust, and formal coordination and control in interorganizational relationships: Toward an integrative framework. Group & Organization Management, 32(4), 407-428.
Waterhouse, J. H., & Tiessen, P. (1978). A contingency framework for management accounting systems research. Accounting, Organizations and Society, 3(1), 65-76.
Weed, S. E., & Mitchell, T. R. (1980). The role of environmental and behavioral uncertainty as a mediator of situation-performance relationships. Academy of Management journal, 23(1), 38-60.
Williamson, O.E. (1985). The Economic Institutions of Capitalism. Free Press, New York.
Williamson, O.E. (2008). Outsourcing: Transaction cost economics and supply chain management. Journal of Supply Chain Management 44 (2), 5–16.
Wuyts, S., & Geyskens, I. (2005). The formation of buyer—supplier relationships: detailed contract drafting and close
partner selection. Journal of Marketing, 69(4), 103-117.
32
Appendix
Table A1. Factor loadings and Cronbach’s alpha
Formal control: =0.739, Li et al. (2010)
Factor loading 1. The contract precisely defines the role/responsibilities of the partner and our firm. 0.801
2. The contract precisely states how each party is to perform. 0.826
3. Generally, the contract is primary mechanism to regulate the behavior of the partner. 0.751
Informal control: =0.809, Li et al. (2010)
1. Control is currently exercised through reliance on the partner to keep promises. 0.782 2. Control is currently exercised through participatory decision making. 0.757
3. Control is currently exercised through joint problem solving. 0.868
4. Control is currently exercised through fine-grained information exchange. 0.689
Partner performance: =0.849, Poppo and Zenger (1998)
In comparison to pre-established performance expectation are you satisfied with:
1. the partner firm's performance on overall cost. 0.757
2. the partner firm's performance on the quality of output or service. 0.809 3. the partner firm's performance on responsiveness to problems and inquiries. 0.810 4. the partner firm's performance on achievement of (alliance) goals. 0.870
Market volatility: =0.830, Carson, Madhok and Wu (2010)
1. Customers’ preferences for my firm’s products change constantly. 0.819
2. The customers of my firm demand the very latest technologies. 0.751
3. The competitors of my firm rapidly advance their product technologies. 0.836
4. Nothing stays the same for long in the industry my firm is in. 0.828
Behavior uncertainty: =0.452, Poppo, Zhou and Li (2016)
1. It is difficult to evaluate if the partner firm follows our recommended operating procedures. 0.813
2. We don’t have accurate reports about partner firm’s activities. 0.742
Notes.
Cronbach’s alpha,
All items, unless indicated otherwise, are measured using a seven-point Likert scale (1 = ‘completely disagree’; 7 = ‘completely agree’).
