The influence of dynamic capabilities on the relation
between uncertainty and learning performances in a
buyer-supplier relationship
Uncertainty reduction with the use of dynamic capabilities
The influence of dynamic capabilities on the relation
between uncertainty and learning performances in a
buyer-supplier relationship
Uncertainty reduction with the use of dynamic capabilities
Nawed Popalziy
University of Groningen
Faculty of Economics and Business
Master Thesis
August 2016
Leliestraat 63 8012 BL, Zwolle 0614514331 n.popalziy@student.rug.nl s2397722The influence of dynamic capabilities on the relation between uncertainty and learning
performances in a buyer-supplier relationship
The purpose of this paper is to examine the influence of uncertainty on the perceived performance in a buyer-supplier relationship and whether the dimensions of Absorptive Capacity (ACAP) influence this relation. ACAP can be conceptualized as a set of organizational routines and processes that consist of acquisition, assimilation, transformation and exploitation of knowledge. These processes can also be divided in potential ACAP (PACAP) and realized ACAP (RACAP). PACAP refers to the processes acquisition and assimilation and makes it possible to acquire and evaluate external knowledge. RACAP refers to the processes transformation and exploitation and makes it possible to leverage the knowledge that has been absorbed. This study also posits two constructs of uncertainty and two constructs of performance. The constructs of uncertainty are Market dynamics and Customer heterogeneity and the constructs of performance are Exploitative and Explorative performance. Whereas Exploitative performance refers to efficiency, production, refinement and variance decreasing activities, explorative performance refers to play, flexibility, innovation and variance increasing activities. The current study used dyadic data to examine the perceived performance and to check whether buyers and suppliers perceive a relationship differently. After an introduction and discussion of the current literature in the field of uncertainty reduction and performance, it is argued that both constructs of uncertainty have a negative effect on both constructs of performance and that this effect would mitigate with the use of the moderating effects of PACAP and RACAP. The results indicate that buyers perceive a relationship differently than suppliers in a buyer-supplier relationship. Moreover, only in case of the buyers Customer heterogeneity has a negative effect on Exploitative and Explorative performance. However, Market dynamics has a positive effect on Exploitative and Explorative performance for the buyers and suppliers. Furthermore, In case of the suppliers RACAP makes the positive relation between Market Dynamics and both constructs of performance negative and PACAP enhances the positive effect of Market dynamics and both constructs of performance. In case of the buyers only RACAP has a positive influence on the relation between Market dynamics and Explorative performance and PACAP has a negative influence on the relation between Market dynamics and both constructs of performance. In addition, the main effect of PACAP on both constructs of performance is not found in any case and the main effect of RACAP on both constructs of performance is positive in all cases.
These results are important for managers. First of all, managers must understand that buyers and suppliers perceive a relationship differently. This consideration would lead to a better understanding of a partner in a relationship. Furthermore, Market dynamics has a positive effect on learning performance. This means that managers should constantly monitor whether their market is turbulent enough and in case of buyers RACAP enhances the effect of a turbulent market on Explorative performance. In addition, managers can use RACAP to directly enhance their Exploitative and Explorative performance. This holds for buyers and suppliers. The negative effect of Customer heterogeneity on Exploitative and Explorative performance in case of buyers is also important for managers. This means that managers in a buying role should consider that a high heterogeneous customer base would have a negative impact on their Exploitative and Explorative performance. Therefore, it is for the managers important to segment their customers or market in an appropriate manner.
1.
Introduction
Facing any kind of high uncertainty in a relationship can be a very dangerous position to be in. From the transaction cost theory, Williamson (1985) states that uncertainty gives room for opportunism. Following Fleischhacker and Pak-Wing Fok (2015) from the demand uncertainty theory, the valuation of demand uncertainty is very important. Therefore, they have some models and techniques to reduce demand uncertainty. Moreover, predict the demand.
In the transaction cost theory uncertainty reduction is discussed in literature, but the techniques for reducing uncertainty are mainly formal. A good example of a formal technique or tactic, to reduce uncertainty, is the use of contractual guarantees or relation specific investments, which shows the commitment of a partner in a given relationship (Anderson & Weitz, 1992). Moreover, Williamson (1985) states that these safeguards will increase the transaction costs. Therefore, this study looks for opportunities to bypass such costs. Possible solutions for these increasing costs are unique firm resources. For example, human capital can be seen as a unique resource, which has a positive effect on the performance of a firm. Human capital refers to the education, experience and skills of employees (Hitt et al., 2001). Firms can use these capabilities to comprehend with transaction costs. In contrast to safeguards (Williamson, 1985), human capital is about using tacit knowledge that can become a unique resource, as defined by Barney (1991) (Hitt et al., 2001). Although firm resources are well elaborated in past studies (Barney, 1991; Dyer and Sing, 1998; Hitt et al., 2001), the literature in relationship marketing lacks information about uncertainty reduction by firm resources that are valuable, rare, not substitutable or imitable (Barney, 1991).
the Explorative and Exploitative learning performance in a buyer-supplier relationship is influenced by uncertainty and whether it has a negative influence. Explorative learning is about adding new knowledge, resources or competences and being innovative and Exploitative learning is about refining existing resources or competences. But how can a firm reduce the uncertainty to improve its Exploitative and explorative performances?
From the resource based view perspective (Dyer & Singh, 1998) absorptive capacity (ACAP) can be seen as a firm resource that can be valuable, non substitutable, not imitable and rare (Zahra & George, 2002). Besides this, Zahra and George (2002) state that ACAP is a dynamic capability that can be conceptualized as a set of organizational routines and processes that consist of acquisition, assimilation, transformation and exploitation of knowledge. These dimensions of ACAP can also be divided in potential ACAP (PACAP) and realized ACAP (RACAP). PACAP consists of acquisition and assimilation and RACAP consist of transformation and exploitation. PACAP is about acquiring and evaluating new external knowledge and RACAP is about leveraging knowledge that has been absorbed (Zahra & George, 2002).
In the past, several researchers have studied the effects of the environment turbulence on the relation of ACAP and performance (Jansen et al., 2006; Lichtenhaler 2009). However, in prior research the environment was mainly an endogenous variable with a moderating effect. Whereas, Eisenhardt and Martin (2000) state that it is possible to influence the environment by using dynamic capabilities of the firm. Therefore, although it is very difficult for firms to influence their environment (Lichtenhaler, 2009) and reduce uncertainty, it is valuable to research whether ACAP can help to reduce the uncertainty that partners in a relationship are experiencing. This brings us to the first contribution to the current study. This study looks whether a capability of a firm can influence the perceived uncertainty in the environment of a firm.
The third and last contribution of the current study is the use of dyadic data. Latent studies have mainly focused on the effects of relationship success by only studying the buyer or supplier. The main reasons where cost or time constraints (Ambrose et al., 2010). The current study uses dyadic response to research the perceived performance from the perspective of the buyer and a supplier.
In summary, this study has three contributions. First, the main contribution of the study, environmental uncertainty is researched as a factor that can be significantly influenced by a dynamic capability of a given firm in a buyer-supplier relationship. This can help managers to reduce uncertainty and enhance the relationship with a buyer or supplier. Second, ACAP and its dimensions are researched as a moderating variable that can help to reduce the effects of uncertainty. Lastly, the current study uses a dyadic response data to create demonstrable value for all the participant. Past literature mainly used data from the perspective of a buyer or supplier due to cost or time constraints. Similar to the current study Ambrose et. al (2010) also used dyadic data. However, the difference between this study and the study of Ambrose et al. (2010) is the use of capabilities to influence the environmental uncertainty.
2. Literature review, hypotheses and conceptual model
This chapter contains a review of literature, presentation of the hypotheses and the conceptual model about relationship performance, uncertainty and absorptive capacity. The first part is a review about the variables of the conceptual model. The chapter follows with the effects of the variables, the formulation of the hypotheses and ends with the presentation of the conceptual model
2.1 Literature review
The first part is a review about relationship performance. The second part is a review about uncertainty and its dimensions. The last section pertains a review of absorptive capacity and the dynamic capabilities Potential Absorptive Capacity (PACAP) and Realized Absorptive Capacity (RACAP).
2.1.1 Relationship performance
Following Berger (2015), the current study also uses Exploitative and Explorative learning performances to measure the relationship performance between a buyer and supplier. Explorative learning is related to flexibility, play, innovation and variance-increasing activities and Exploitative learning is related to refinement, production, efficiency, control and variance decreasing activities (Berger, 2015). Furthermore, past research (Berger, 2005; Ambrose, 2010) have also found that a buyer and a supplier can perceive the performance of a relationship differently than the other partner. This topic will be further elaborated in paragraph 2.2.1
2.1.2 Uncertainty
Uncertainty comes in different shapes and sizes. From the transaction cost theory it can be stated that uncertainty can have environmental and behavioural characteristics (Williamson, 1985). Williamson (1985) states that high rates of uncertainty give probability for opportunism. Hence uncertainty has a negative effect on the relation between two partners. Duncan (1972) describes environmental uncertainty with three components. The first component entails, not having enough information about certain environmental factors in a given decision making situation. The second component includes, not knowing the results of a decision in ways of how much an organization would suffer if the decision were not correct. The last component, regards not being able to appoint chances with concern to how environmental factors are going to effect the achievements or errors of the decision unit in performing its function. Moreover, Morris and Carter (2005) also support this definition of environmental uncertainty. According to Arndt (1983) environmental uncertainty is a function of four dimensions. The four dimensions are environmental capacity, environmental differentiation, environmental concentration and environmental turbulence.
including organizations, individuals, and any social forces affecting resources” (Achrol & Stern, 1988: 37). Hence, this definition can be stated as customer heterogeneity. Environmental capacity is defined as “the perceived favorableness-unfavorableness of economic and demand conditions characterizing the output market’s capacity to absorb resources of the focal dyad” (Achrol & Stern, 1988: 37). Hence, this definition can be stated as market dynamics.
The concentration on these two dimensions is mainly due to the restrictions on the data used in this study.
2.1.3 Absorptive capacity and its dimensions
In an uncertain environment it is necessary to be flexible and have the capabilities to respond to unforeseen environmental changes. Capabilities such as absorptive capacity (ACAP) can help organizations to comprehend with uncertainties. Zarha and George (2002) conceptualized absorptive capacity as a set of organizational routines and processes. These processes consist of acquisition, assimilation, transformation and exploitation of knowledge.
Acquisition
Following Zahra and George (2002) acquisition is defined as a capability to identify and acquire knowledge that is generated external to the firm. It is vital that the identified and acquired knowledge is critical for the operations of the firm. Actions to enlighten knowledge acquisition routines contain three attributes, namely intensity, speed and direction.
Assimilation
“Assimilation refers to the firm’s routines and processes that allow it to analyse, process, interpret, and understand the information obtained from external sources” (Zahra & George, 2002; 189).
Exploitation
Exploitation comprehends the routines that gives firms the opportunity to refine, extend and leverage existing competencies or generate new competencies by using acquired and transformed knowledge (Zahra & George, 2002).
These four dimensions make it for a organization possible to manufacture a dynamic organizational capability. From the resource based view perspective (Dyer and Singh, 1998; Barney, 1991), ACAP can be a rare, valuable, non-substitutable and difficult to imitate resource (Zahra and George, 2002). The authors also divide the four dimensions of ACAP into potential and realized capacity. Potential capacity (PACAP) refers to the capabilities acquisition and assimilation and realized capacity (RACAP) refers to the capabilities transformation and exploitation. Both capacities work separately. However, they are also complementary. PACAP makes it possible to evaluate and acquire external knowledge, but this does not necessarily mean that the knowledge is exploited. “RACAP reflects the firm’s capacity to leverage the knowledge that has been absorbed” (Zahra & George, 2002; 190). Following Berger (2015), the current study proposes that both capacities of ACAP coexist and are simultaneously performed. Berger (2015) also states that PACAP corresponds to Exploitative learning and RACAP to Exploratory learning.
2.2 Hypotheses
This part contains the development of the hypotheses. In section 2.1 we have reviewed the literature and defined the variables and in this part we will use the literature to present the hypotheses. The first paragraph of this section is about the different perceptions that buyers and supplier can have about the performance of a relationship. The second part is about the effects of uncertainty on the performance of a buyer-supplier relationship and the last part of this paragraph contains the moderating effects of PACAP and RACAP on the relationship between uncertainty and relationship performance.
2.2.1 Different perception of a relationship by a buyer and a supplier
Ambrose et al. (2010) have found that a buyer and a supplier in the same relationship can perceive the relationship differently and that the antecedents for relationship performance differ. But according to Ambrose et al. (2010) uncertainty is a significant negative predictor for relationship performance in the perception of a buyer and supplier. In their study they investigate how a buyer and a supplier perceive the performance of a relationship. An important contribution of their study is the dyadic approach and both sides of the relationship see uncertainty as a predictor of relationship quality. However, their study does not foresee issues regarding different capabilities of both sides, for instance absorptive capacity and safeguards or any other implications to reduce the uncertainty.
H1a: A buyer perceives the performance of a relationship different than a supplier in a buyer-supplier relationship
H1b: A buyer perceives RACAP different than a supplier in a buyer-supplier relationship.
H1c: A buyer perceives PACAP different than a supplier in a buyer-supplier relationship.
The constructs of Uncertainty are not taken in the analysis to measure whether there is a difference between the perception of a buyer and a supplier in a buyer-supplier relationship. This decision is based on the fact that the buyer and supplier are asked to give the degree of turbulence and diversity in their own market and not only their combined market (Berger, 2015). Therefore, it is not valid to use the constructs of Uncertainty to measure whether buyers and suppliers have different perceptions.
2.2.2 Effect of uncertainty on relationship performance
Several studies have examined how uncertainty affects relationship performance (Achrol & stern, 1998; Williamson, 1985; Morris and Carter, 2005). All these studies found that uncertainty has a negative effect on performance. In addition, Ambrose et al. (2010) also found that uncertainty has a negative effect on perceived relationship performance. As stated in paragraph 2.1.1, we defined two dimensions of relationship performance, namely explorative performance and Exploitative performance and the current study defined two constructs of uncertainty in section 2.1.2, namely Customer heterogeneity and Market dynamics. First, we discuss the effects of Market dynamics on both performance dimensions. Second, the effects of Customer heterogeneity on both performance dimensions will be discussed and lastly, we will compare the effects of Customer heterogeneity and Market dynamics on the effects of Exploitative and explorative performance.
2.2.2.1 The effect of Market dynamics on Exploitative and explorative performance
Jansen et al. (2006) concluded that a high environmental dynamism has a positive effect on Exploratory innovation. Moreover, Jansen et al. (2006) also stated that a stable environment has a negative effect on explorative innovation. However, Ambrose et al. (2010) measured the effect of uncertainty on performance and this effect was negative. In addition, Jansen et al. (2006) conceptualized environmental dynamism as a moderating variable, whereas Ambrose et al. (2010) measured the direct effect of uncertainty on performance. Moreover, Dahlstrom et al. (1996) also stated that marketplace uncertainty has a negative effect on performance. The study of Morris and Carter (2005) underlines these effects. Morris and Carter (2005) have concluded that uncertainty reduction is a must for relationship performance.
We defined Market dynamics as a dimension of uncertainty that can absorb a firm’s resources and characterizes markets favourableness or unfavourableness conditions. Furthermore, in previous sections we have mentioned the negative effects of uncertainty on performance. Moreover, Williamson (1985) states that safeguards increase the costs, absorb resources, and eventually decrease performances. The current study pertains a synergetic view about performance (Larsson and Finkelstein, 1999) and this view requires two or more parties to work together and trust each other. With a high degree of uncertainty the trust between partners will decrease (Williamson, 1985) and partners will not trust each other and eventually the performance will decrease. Therefore, the current study also pertains a negative effect of market dynamics on Exploitative and explorative performance. Hence, the following two hypotheses are presented.
H2a: The more dynamic the market, the lower the perceived Exploitative performance of the relationship
H2b: The more dynamic the market, the lower the perceived Exploratory performance of the relationship
2.2.2.2 The effect of Customer heterogeneity on Exploitative and explorative performance
Dess and Davis (1984) state that firms can be categorized into strategic groups and this would enhance the performance. These are groups with the same generic strategy of Porter (1980). When firms focus on strategic groups they reduce the uncertainty in their market and try to make more homogenous groups to comprehend and understand the strategic groups. This means that more heterogeneity would decrease the performance. Moreover, more diverse groups would mean that the costs would also increase and eventually has a negative effect on performance, because every group has its own way of maintaining and servicing. The same holds for the customer base. According to Gilmour et al. (1994) firms can segment their customers into customer segments. When firms use customer segments, the heterogeneity of their customers are brought back to comprehendible groups and firms can deliver services by customer segment. This means that the uncertainty is reduced. Gilmour et al. (1994) also state that firms can obtain competitive advantages (Barney, 1991) and this would eventually lead to higher performances. Hence, less Customer heterogeneity increases the performance.
As the same for the effects of Market dynamics on performance, we also follow the view of Larsson and Finkelstein (1999) in case of the effects of Customer heterogeneity on performance. As stated before, this view requires two or more parties to work together and trust each other. With a high degree of uncertainty the trust between partners will decrease (Williamson, 1985) and partners will not trust each other and eventually the performance will decrease. Hence, higher customer heterogeneity will have a negative effect on the Explorative and Exploitative performance.
H3a: More heterogeneity of the customer base lowers the perceived Exploitative performance of the relationship
H3b: More heterogeneity of the customer base lowers the perceived Exploratory performance of the relationship
2.2.2.3 Different effects on Exploitative and Explorative performance
The current study looks at Exploitative and explorative performance and as discussed in the pervious sections, both performance dimensions need different competences (Jansen et al., 2006). The researchers also found that Exploratory innovation has a positive effect on performance when environmental dynamism is high and explorative innovation has a negative effect when the environment is stable (Jansen et al., 2006). Therefore we assume that the effects of uncertainty will be different for Exploitative performance and explorative performance. Due to the characteristics of Exploratory being associated with search, flexible and experimentation and Exploitative with refinement, efficiency and certainty (Berger, 2015) we assume that the effect of uncertainty on Exploratory performance will be lower than on Exploitative performance. Due to past literature we assume that the direct relationship is negative. Hence, the following hypothesis is presented
H4: The overall effect of uncertainty is stronger for Exploratory performance than for Exploitative performance
2.2.3 Moderating effect of absorptive capacity
2.2.3.1 Moderating effects of PACAP and RACAP
Ambrose et al. (2010) stated that both the supplier and buyer see uncertainty as a predictor of relationship performance. Therefore, the focus of the current study will also be on the direct effects of both constructs of uncertainty on perceived relationship performance and what effects PACAP and RACAP have on the perceived performance of the buyer-supplier relationship. The effect of both learning capabilities can be seen as a moderating role in this concept. The right kind of resource, in this case ACAP, can enhance or weaken the effect of both constructs of uncertainty on perceived relationship performance. However, because ACAP can be seen as a valuable resource (Dyer & Sing, 1998) and can finally lead to a competitive advantage (Barney, 1991), that ultimately can have relational rents as an outcome, we will assume that ACAP will decrease the effects of both constructs of uncertainty on performance. In the following parts we will review the moderating effects of PACAP and RACAP on the relation of both constructs of uncertainty, Customer heterogeneity and Market dynamics, on explorative and Exploitative performance.
As stated before in section 2.3.2, we made assumptions that Customer heterogeneity has a negative effect on exploitative and explorative performance. Furthermore, following Zahra and George (2002) and Berger (2015) we can see RACAP and PACAP as a capability of a relation. This capability can become a resource, which ultimately can lead to a competitive advantage (Dyer & Singh, 1998; Barney, 1991). Therefore, we assume that PACAP and RACAP can weaken the effects of Customer heterogeneity. Hence, the following hypotheses are presented.
H5a: RACAP can reduce the influence of customer heterogeneity on the perceived Exploitative performance of the relationship
H5b: RACAP can reduce the influence of customer heterogeneity on the perceived Exploratory performance of the relationship
In section 2.1.2 we have reviewed the effects of Market dynamics on Explorative and Exploitative performance. The current study assumes that the effect of Market dynamics has a negative impact on both dimensions of performance. Furthermore, the current study assumes that these effects can be mitigated by firm capabilities. From the resource based view (Dyer & Singh, 1998) and following Berger (2015), stating PACAP and RACAP as a unique resource, we assume that the capabilities RACAP and PACAP can weaken the effects of Market dynamics on Explorative and Exploitative performance. Hence, the following hypotheses are presented.
H6a: RACAP can reduce the influence of market dynamics on the perceived Exploitative performance of the relationship
H6b: RACAP can reduce the influence of market dynamics on the perceived Exploratory performance of the relationship
H6c: PACAP can reduce the influence of market dynamics on the perceived Exploitative performance of the relationship
H6d: PACAP can reduce the influence of market dynamics on the perceived Exploratory performance of the relationship
2.2.3.2 Different strengths of RACAP and PACAP
Lichtenthaler (2009) also identified the effects of environmental turbulence, as a moderating effect, in a relation between ACAP and performance. He found that technological and market turbulence positively moderates the effect between ACAP and performance. Lichtenthaler (2009) and Jansen et al. (2006) have some similar outcomes. In both studies the effect of Exploratory learning is more significant than Exploitative learning. Therefore, the current study also assumes that the effect of Exploratory capabilities (PACAP) is more present than the effect of Exploitative capabilities (RACAP) on the relationship between both constructs of uncertainty and perceived relationship performance. Moreover, the assumption is that RACAP will have a stronger effect than PACAP. Hence, the following hypothesis is presented.
H7: The overall effect of PACAP is stronger than the overall effect of RACAP on the relation between uncertainty and perceived relationship performance.
Furthermore, Jansen et al. (2006) stated that the duration of a relationship could have a significant positive effect of Market dynamics on performance. Therefore, the current study controls for the duration of the relationship in the analysis.
3. Method
3.1 Data collection procedure
The data used in the current study is primary data. However, the current study is part of a broader research of Berger (2015). Therefore, the data used in this study is collected in an earlier stage for the research of Berger (2015), but the current study has other aims.
Following Berger (2015), to assess the interfirm relationship between an independent buyer and supplier, data was collected from the buyer and supplier between June 2011 and April 2013. The data consisted of 166 matched-pair relationships. Selnes and Sallis (2003) state that relationships are not directly observable and therefore there is a large potential for measurement errors. Because of this the data was collected from key informants from the buyer and supplier of the dyad. Purchase and high ranked managers were asked to deliver contact data of four employees within their organizations which were important for the their customer relationships. Service organizations were not taken into account, because according to Arbussa and Coender (2007) manufacturing firms show a higher probability of acquiring new knowledge. Several different industries were investigated, such as automotive, pharmaceuticals, machinery, electronics and semiconductors to support the generalizability of the research.
3.2 Measures
The current study has used the scales that the research of Berger (2015) has used. Berger (2015) has used existing scales and created new scales. New scales were developed for firm learning, intrafirm learning or interfirm learning not related to buyer-supplier relationships. The current study uses first-order and second-order constructs. Moreover, following Berger (2015) the current study also uses formative and reflective scales. The difference between reflective and formative scales is that high correlations are assumed among reflective indicators whereas formative scales are not related, but do measure different aspects of the same construct.
The questionnaire was examined among four suppliers and seven buyers. The questionnaire was made in English and translated in Dutch. This was done to limit the nonresponse. Appendix A contains the measurement scales and its sources. The Likert scales range from 1 “strongly disagree” to 7 “strongly agree”. There is only one exception. Explorative learning performance was stated as “to no extent” and “to a great extent”.
Performance of the relationship is measured by the explorative and Exploitative learning performance of the relationship. Following Berger (2015) and taking Larson and Finkelstein view about performance, the current study also states that performance “is gauged by the degree of synergy realization” (Larsson and Finkelstein, 1999; 1).
Berger (2015) generated scales to measure ACAP and its dimensions, because previous scales were not sufficient to measure it. Berger (2015) states that all dimensions of ACAP are connection to the individual, group and relationship level. This is done to specify the nature of the separate dimensions. The following section pertains the discussions of the measures of each dimension of ACAP separately and lastly the measurements and dimensions of uncertainty.
Following Berger (2015) assimilation consists of firm routines and processes to allow a firm to analyse, process, interpret and understand the information obtained from external sources. Furthermore, the relevant component of firm routines and processes is “understanding”. Berger (2015) based the measures on previous work by Jansen et al. (2015) and Camison and Fores (2010).
The definition of transformation refers to a firm’s capability to develop and refine the routines that supports co-existing of previous knowledge, new knowledge and assimilated knowledge. Furthermore, internalization and conversion are the most important components. However, according to Berger (2015) these components are not well explained and discussed. Berger (2015) states that when you match new and old knowledge you have incremental and radical learning. The four last items are created to measure how the incremental and radical learning knowledge is transferred and shared between all the parts in an organization. The measures are the same as Berger (2015).
According to Berger (2015) the important components for exploitation are use and implementation. The measures are based on the study of Berger (2015).
PACAP and RACAP are second order constructs. PACAP is measured by the dimensions acquisition and assimilation, whereas RACAP is measured by the dimensions transformation and exploitation.
To measure whether there is a difference in the perception of a buyer or a supplier in a buyer-supplier relationship, the current study examined and compared the mean scores of the buyer and the supplier on both constructs of performance and ACAP. The constructs of performance are Exploitative learning and Explorative learning and the constructs of ACAP are PACAP and RACAP.
3.3 Statistical procedure
The conceptual model has several elements that are important. However, the moderating role of RACAP and PACAP are one of the most important. They can enhance or weaken a certain effect between an independent and a dependent variable. A multiple regression analysis is performed to measure the effects of the independent variable, moderating variable and dependent variable. To measure whether a buyer perceives a relationship different than a supplier, the current study compared the means of PACAP, RACAP, Exploitative and Explorative performance. This study used the Independent Samples T-Test to measure whether there is a difference between the means of a buyer and a supplier on PACAP, RACAP, Exploitative and Explorative performance.
4. Analysis and results
To measure the different perspectives of the supplier vs. the buyer, the current study filtered the cases in SPSS and created new datasets. One dataset consists of the suppliers and the other dataset consists of buyers. This chapter contains the analysis and the results from the data of the supplier and buyer. First, we look at the reliability and validity of the latent constructs for both the supplier and buyer. Second, the results and analyses of the Independent Samples T-Test and multiple regressions are presented and discussed. Lastly, the testing of the hypotheses is presented.
4.1 Validity and Reliability
The buyer and supplier database are separately examined on the validity and reliability of the constructs. This is done, because both databases are separately analysed. The combined validity and reliability of the constructs can be found in Appendix B. The combined scores indicate that all constructs are valid and reliable. For the separate analysis we first conducted a Cronbach’s alpha and estimated the VIF scores for both the supplier and buyer. The Cronbach’s alpha is estimated to test the construct of the reflective scales and the VIF scores are estimated to validate the construct of the formative scales. Table 1 shows the scores of all the reflective scales and their estimated Cronbach’s alpha, used in the current study.
Formative scales cannot be measured by the Cronbach’s alpha, because Cronbach’s alpha measures how much certain scales are related to each other and formative scales are not necessarily related to each other. Formative scales measure different parts of the similar construct. Therefore, we should look whether the formative scales do not have the problem of mulitcollinearity. Table 2 presents all the formative scales with their own VIF scores for the buyers and suppliers database.
As stated before, formative scales measure different parts of the same construct. Therefore, their VIF score should be low. A VIF score is satisfactory if it is lower than the value of 3.3 (Petter, Straub and Rai, 2007; Cenfetelli and Basselier, 2009). As can be seen in table 2, all scores of the VIF are for all items, for both the supplier and buyer, lower than 3.3. Therefore, all the constructs are satisfactory.
Furthermore, the second order constructs of PACAP and RACAP should also be investigated for their validity. Moreover, PACAP and RACAP’s scale have both different forms. PACAP refers to Acquisition and Assimilation, which is respectively constructed of formative and reflective scales. RACAP refers to Transformation and Exploitation, which is respectively constructed of formative and reflective scales. Moreover, scientists (Jarvis, 2003; Diamantopoulos and Siguaw, 2006; Coltman et al., 2008) have discussed the difference between the two scales and state that it is important and researcher have to consider the distinction. Therefore, we will follow the study of Berger (2015). Berger (2015) investigated the validation of the constructs and concluded that it was reliable. Although the study of Berger (2015) and the current study use the same constructs and data, we tried to confirm the outcomes of Berger (2015) in the current study.
Supplier indicators VIF scores Buyers indicators VIF scores PACAP PACAP Acquisition 1.554 Acquisition 1.820 Assimilation 1.554 Assimilation 1.820 RACAP RACAP Transformation 1.652 Transformation 1.634 Exploitation 1.652 Exploitation 1.634 Table 3. Validity of PACAP and RACAP 4.2 Results of analysis
This section contains the results of the analysis. First, we will compare the results of the buyers with the results of suppliers. Second, we will look at the effects of the supplier database and lastly the results of the buyer database are discussed. All the results of the multiple regression analyses are presented in table 4.
4.2.1 Results of the comparison between buyer and supplier
To measure whether a buyer perceives a relationship different than a supplier, we performed an Independent Samples T-Test to compare the means of the buyer and supplier for PACAP, RACAP, Exploitative and Explorative performance. The results are presented in Table 5.
Supplier indicators Buyers indicators Mean Standard deviation Mean Standard deviation Explorative 3.64 1.35 3.37 1.22 Exploitative 4.42 0.96 4.30 1.01 PACAP 4.91 0.82 4.65 0.79 RACAP 4.92 0.79 4.65 0.87
t-value p-value Levene statistic p-value Explorative 1.88 0.06* 2.11 0.15 Exploitative 1.09 0.28 0.23 0.63 PACAP 2.76 0.006*** 2.06 0.15 RACAP 3.02 0.003*** 0.26 0.61 Table 5. Results Independent Samples T-Test Note: *** p<0.01; ** p<0.05; *p<0.10
From the results in table 5 we can indicate that there are significant differences between the perception of the buyer and supplier in a buyer-supplier relationship. The results indicate that buyers and suppliers perceive PACAP (p=0.006) and RACAP (p=0.003) significantly different at 0.05-level. In addition, Explorative performance (p=0.06) is also significant at 0.10-level. This means that buyers and suppliers also perceive Explorative performance as different. Furthermore, Exploitative performance (p=0.28) is not significant. This means that buyers and suppliers do not have different perceptions about Exploitative performance on any level.
4.2.2 Results of the supplier database
As stated before, relationship performance consists of two constructs. Therefore, we have estimated two regressions, one for Exploratory performance and one for Exploitative performance to measure the effects of the supplier database. The model for explorative performance is significant (F=6.251; p=0.000) at 0.05-level. The R-square of the model is 0.231. To measure whether there is a problem with multicollinearity, we also performed the VIF score for the model. All VIF scores are below the threshold of 3.3. Therefore, we can conclude that we do not have a problem with multicollinearity.
Furthermore, the moderating effects of PACAP and RACAP are somewhat in line with the main effects of the variables. The results show that PACAP (p=0.000) and RACAP (p=0.004) have a significant effect on the relation between Market dynamics and Explorative performance. However, the contributions of PACAP and RACAP differ. The moderating effect of PACAP has a positive contribution (B=0.354) and the moderating effect of RACAP has a negative contribution (B=-0.254). Likewise, the moderating effect of RACAP on the relation between Customer heterogeneity and Explorative performance is also significant (p=0.033) and shows a negative effect (B=-0.191). In contrast to RACAP, the effect of PACAP on the relation between Customer Heterogeneity and Explorative performance is not significant (p=0.502).
The results for Exploitative performance are in line with the results of Explorative performance. The model for Exploitative performance is significant (F= 6.320; p=0.000). Moreover, Market dynamics is also significant (p=0.042) and has a direct positive effect (B=0.149) on Exploitative performance. Furthermore, the effect of Customer heterogeneity on Exploitative performance is not significant (p=0.713). Similar to Explorative performance, the effect of RACAP on Exploitative performance is significant (p=0.000) and the contribution is positive (B=0.352). In contrast to RACAP, PACAP does not have a significant (p=0.296) effect on Exploitative performance.
The moderating effects of PACAP and RACAP on the relation between Market dynamics and Exploitative performance are similar to Explorative performance. RACAP has a significant negative effect (p=0.018; B=-0.206) on the relation between Market dynamics and Explorative performance and PACAP has a significant positive effect (p=0.008; B=0.231) on the relation between Market dynamics and Exploitative performance. Furthermore, RACAP has also a moderate significant negative effect (p=0.056; B=-0.171) on the relation between Customer heterogeneity and Exploitative performance. However, the main effect of Customer heterogeneity is not significant and therefore we assume that the total effect is entirely explained by RACAP.
4.2.3 Results of the buyer database
The current study also performed two regressions for the results of the buyer database. First, we made a Multiple regression for the Explorative performance and second, we performed a multiple regression for the results of Exploitative performance. To check for multicollinearity, we also analysed the VIF scores. Not one VIF score is above the threshold of 3.3. Therefore, we conclude that we do not have any problems with multicollinearity.
The results show that the model for Explorative performance is significant (F=3.414;
p=0.001). Moreover, the effects of Market dynamic (p=0.037) and Customer heterogeneity
(p=0.039) on Explorative performance are both significant. The contribution of Market dynamics (B=0.166) is positive and the contribution of Customer heterogeneity is negative (B=-0.166). Furthermore, the results also indicate a significant effect (p=0.007) for RACAP and this contribution is positive (B=0.318). However, PACAP does not have a significant effect (p=0.799) on Explorative performance.
The moderating effects of PACAP and RACAP show different effects. Both PACAP (p=0.020) and RACAP (p=0.029) have a significant effect on the relation between Market Dynamics and Explorative performance. The moderating effect of PACAP on Market dynamics and Explorative performance is negative (B=-0.307) and the moderating effect of RACAP on Market dynamics and Explorative performance is positive (B=0.281). Furthermore, the results indicate that PACAP (p=0.345) and RACAP (p=0.325) do not have any significant effect on the relation between Customer heterogeneity and Explorative performance.
Furthermore, only PACAP has a significant (p=0.011) moderating effect on the relation between Market dynamics and Exploitative performance. This effect has a negative contribution (p=0.275). Hence, The effect of PACAP on the relation between Customer heterogeneity and Exploitative performance is not significant (p=0.423). The results also show that RACAP is not significant for the relation between Market dynamics (p=0.147) and Exploitative performance and Customer heterogeneity (p=0.963) and Exploitative performance.
4.3 Hypotheses testing
For the hypotheses testing we refer to table 4 and 5 for an overview of all the outcomes of the regression analysis and Independent Samples T-Test. Table 6 presents an overview of all the supported and rejected hypothesis. We refer to table 5 for the testing of hypotheses 1a, 1b and 1c. Hypotheses 1a is not supported, because the effect of Exploratory performance is moderately significant and the effect of Exploitative performance is not significant. This means that buyers do not perceive the Exploitative and Explorative performance different than suppliers and vice versa. However, the results do indicate that buyers and suppliers perceive PACAP and RACAP different in a buyer-supplier relationship. This means that hypotheses 1b and 1c are both supported.
Hypothesis Suppliers Buyers
H1a: Difference buyer-supplier on performance rejected rejected H1b: Difference buyer-supplier on RACAP supported supported H1c: Difference buyer-supplier on PACAP supported supported
H2a: Direct effect Market dynamics on perceived Exploitative performance rejected rejected H2b: Direct effect Market dynamics on perceived Exploitative performance rejected rejected
H3a: Direct effect Customer heterogeneity on perceived Exploitative performance rejected supported H3b: Direct effect Customer heterogeneity on perceived Explorative performance rejected supported
H4: Overall effect of uncertainty stronger for Exploratory than Exploitative performance supported rejected
H5a: RACAP reduces influence of CH on perceived Exploitative performance rejected rejected H5b: RACAP reduces influence of CH on perceived Exploratory performance rejected rejected H5c: PACAP reduces influence of CH on perceived Exploitative performance rejected rejected H5d: PACAP reduces influence of CH on perceived Exploratory performance rejected rejected
H6a: RACAP reduces influence of MD on perceived Exploitative performance rejected rejected H6b: RACAP reduces influence of MD on perceived Exploratory performance rejected rejected H6c: PACAP reduces influence of MD on perceived Exploitative performance rejected rejected H6d: PACAP reduces influence of MD on perceived Exploratory performance rejected rejected
To test hypotheses 2a and 2b we look at the effects of Market dynamics on the Exploratory and Exploitative performance. For the buyers and suppliers the effects of a dynamic market is significant. However, the Exploratory and Exploitative performances increase when the market is more dynamic. Therefore, we cannot support hypotheses 2a and 2b for the buyers or the suppliers.
Hypotheses 3a and 3b contain the effects of Customer heterogeneity on Exploitative and explorative performance. In the case of the suppliers, Customer heterogeneity does not have a significant effect. However, buyers do notice the effects of Customer heterogeneity on Exploitative and explorative performance. Moreover, both effects are significantly negative. Hence, we only support hypotheses 3a and 3b for the buyers and not the suppliers.
Furthermore, the overall effect of uncertainty is different for the buyer and supplier. To test hypotheses 4, we look at the Beta of the results. For the suppliers we only look at the Market dynamics and for the buyers we look at both constructs of uncertainty. The results show that suppliers perceive Market dynamics stronger on Explorative performance than on Exploitative performance. In the case of the buyers the results are reversed. The effects of Market dynamics and Customer heterogeneity are stronger on Exploitative performance than on Explorative performance. Hence, we only support hypotheses 4 for the supplier and not for the buyers.
To test hypotheses 6a, 6b, 6c and 6d we look at the effects PACAP and RACAP on the relation between Market dynamics and both constructs of performance. The main effects of PACAP are not present in the current study. However, PACAP does have a moderating effect on the relation between Market dynamics and Explorative and Exploitative performance. In addition, both moderating effects are not in the direction as we have assumed. The effect of Market dynamics becomes more negative when PACAP is considered. Therefore, we cannot support hypotheses 6c and 6d.
For hypotheses 6a and 6b we take a closer look at the effects of RACAP for the buyer and supplier. The results show that RACAP has a positive significant influence on the relation between Market dynamics and Explorative performance for the buyers. However, in our hypotheses we assumed a negative effect of Market dynamics and that this effect would mitigate with the use of RACAP. The results indicate that this effect is positive and enhanced. Therefore, we cannot support hypotheses 6b. In the case of the suppliers the effects are also not as we have assumed. As stated before, Market dynamics has a positive influence on Exploitative and Explorative performance and this effect is made negative when RACAP is considered as a moderating variable. Therefore, we also cannot support hypotheses 6b for the suppliers.
Furthermore, some of the results of RACAP are unforeseen in the current study. For example, RACAP has a significant negative effect on the relation between Market dynamics and Exploitative and Explorative performance for the suppliers. Although this effect was assumed, it was not expected that RACAP made the relation between Market dynamics and both constructs of performance more negative. For the buyers, this effect only occurs when RACAP is tested on the relation between Market dynamics and Explorative performance. Therefore, we cannot support hypothesis 6a.
5. Conclusion and Discussion
This chapter contains the conclusion of the analysis and hypothesis. First, the main results are discussed in the light of the hypothesis. Second, the most remarkable results of the analysis are reviewed. In the following sections a short scientific and practical discussion is presented. The chapter ends with some limitations and future direction of the current study.
5.1 Conclusions
To test whether buyers perceive the relationship different than suppliers, we performed an Independent Samples T-Test. The results indicate that buyers perceive PACAP and RACAP different than suppliers. Moreover, suppliers have a significant higher mean score than buyers for all variables. In contrast to PACAP and RACAP, the buyers and suppliers did not perceive the constructs of performance as different at a 0.05 significance level. However, Exploratory performance does become significant at 0.10-level. Therefore, we can conclude that buyers perceive Exploratory performance moderately different than suppliers. Hence, we conclude that buyers perceive a relationship different than suppliers in a buyer-supplier relationship. We conducted four multiple regression analysis to estimate the effects of Market dynamics and Customer heterogeneity on Exploitative and Explorative performance for suppliers and buyers. All analyses showed a significant model and a moderate R-square. The main effects of Market dynamics are significant for all cases. This means that the higher the market dynamic, the higher the Exploitative and explorative performances. Hence, when firms operate in turbulent markets, their learning performance will increase.
The moderating effects of PACAP and RACAP are somewhat unforeseen. The main effect of PACAP is not significant in any case. This means that PACAP does not have any direct effect on both constructs of performance. However, PACAP does have a significant moderating effect on the relation between Market dynamics and Explorative and Exploitative performance. This holds in case of the buyers and suppliers. In case of the suppliers, the results indicate that the interaction effect of PACAP on the relation between Market dynamics and Explorative and Exploitative performance is positive. In case of the buyers, the results indicate that PACAP has a significant negative effect on the relation between Market dynamics and Explorative and Exploitative performance. Moreover, the direct positive effect of Market dynamics on Explorative and Exploitative performance becomes negative when PACAP is considered as a moderating variable. This means that PACAP weakens the positive effect of a turbulent market on the Explorative and Exploitative performance of a buyer. The main and moderating effects of RACAP are significant and have some distinct effects. All the main effects of RACAP are significantly positive. This means that RACAP increases the Exploitative and Explorative performance of the buyers and suppliers. However, suppliers state that RACAP has a negative effect on the relation between Market dynamics and both constructs of performance. This means that a supplier in a turbulence market does not need capabilities to transform or exploit knowledge. Furthermore, in case of the buyers, the positive effect of Market dynamics on Explorative performance becomes more positive when RACAP is considered as a moderating variable. This means that RACAP enhances the effect of a turbulent market on the Explorative performance of a buyer.
5.2 Discussion
In line with our assumptions, we have concluded that buyers perceive the relationship different than suppliers in a buyer-supplier relationship. This result is in line with previous studies of Berger (2015) and Ambrose et al. (2010). Berger (2015) and Ambrose et al (2010) also stated that buyers and suppliers perceive a relationship different. Moreover, the suppliers scored higher than the suppliers on all the variables. This is also in line with the study of Berger (2015) and Barnes et al. (2007). This difference can be an explanation for the different results for the buyer and supplier in the multiple regression analyses of this study.
In contrast to our assumption, which is in line with previous studies (Achrol and Stern, 1998; Williamson, 1985; Morris and Carter, 2005), the current study shows some different results. We have theorized that uncertainty should have a negative effect on performance. However, the current results show that market dynamics has a significant positive effect on both dimensions of performance for the buyers and suppliers. Some of these contradictions can be explained. One of the main contradictions can be explained by the chosen dependent variable. Where previous studies (Jansen et al. 2006; Ambrose et al., 2010) researched hard performance rates, the current study looked at the learning performance. When we consider learning, we have to state that the knowledge can become tacit and ultimately lead to a competitive advantage (Barney, 1991). This can explain the positive sign of Market dynamics on both dimensions of the learning performance. In addition, when firm’s have a competitive advantage in a dynamic market the results should be positive, as is the case in the current study.
It is rather surprising that the effects of PACAP are not significant for explorative learning performance and that the effects of RACAP do not have the proposed directions for suppliers when we consider it as an interaction variable. The easiest explanation for this result is, that RACAP is not fit to comprehend with uncertainty. However, while Eisenhardt and Martin (2000) do state that influencing the environment is possible, other studies (Duncan, 1972; Morris and Carter, 2005; Achrol and Stern, 1988) see uncertainty as an endogenous variable were firm’s have to deal with.
Another point of discussion is the effect of PACAP on the relation between Market dynamics and both constructs of performance for suppliers. The results are somewhat in line with our assumption. However, the current study assumed that the main effect of Market dynamics would be negative, but this was positive and became more positive when PACAP was considered as a moderating variable. Hence, PACAP does not mitigate a negative effect, but enhances a positive effect. This would mean that Uncertainty could be influenced by capabilities. However, the focus should be on other dimensions of Uncertainty (Achrol and Stern, 1988), dimensions that have a negative effect on performance.
5.3 Implications
Another implications can be the negative influence of Customer heterogeneity on explorative and Exploitative performance for buyers. It is for managers important to consider the negative influence of high Customer heterogeneity. Hence, the results show that the more heterogeneous the customer base is, the lower the explorative and Exploitative performance for buyers. Managers who do not segment their market or customers (Dess and Davis, 1984; Gilmour et al., 1994) in an appropriate manner will have a decreasing Exploitative and Explorative performance.
Third, RACAP showed a significant positive direct effect on explorative and Exploitative performance for the buyers and suppliers and this is in line with Berger (2015). Meaning that firm’s focusing on RACAP could enhance their learning performances. When firms are noting that their learning performances are lacking, they could invest in RACAP to enhance their learning performance. Ultimately, this would give them opportunities to strengthen their Exploitative or Exploratory capabilities.
Fourth, buyers perceive a relationship different than suppliers. Therefore, it is for managers important to notice this difference at any decision-making opportunity. When knowing that there is a difference in the perception, managers can act on this knowledge and better understand their partner and its culture in the relationship. Moreover, Ribbink and Grim (2014) state that cultural differences have a significant effect on negotiation outcomes in a buyer-supplier relationship.
5.4 Limitations
The biggest limitation of this study is the data of the research of Berger (2015). The data made us focus on only two dimensions of uncertainty and two “soft” dimensions of performance. Furthermore, it was for the current study difficult to measure the validity of the formative scales. All the measure about the validity of the formative scales is based on the VIF scores with SPSS and the research of Berger (2015).
5.5 Future research
In this research we tried to examine whether absorptive capabilities can weaken the negative effect of uncertainty on learning performances. However, we found different effects for uncertainty. Whereas the effects of Market dynamics are significantly positive, the effects of Customer heterogeneity are negative. Therefore, it is for future researcher maybe interesting to look at other dimensions of uncertainty, such as demand uncertainty (Fleischhacker and Pak-Wing Fok, 2015) or environmental concentration (Arndt, 1983).
Furthermore, the current study only looked at “soft” measures of performance. For future research directions it can be learn full to explore more “hard” measures of performance, such as return on investment, return on assets and how much profit a relationship can make. These measures make it for managers and CEO’s more insightful to see whether the relationship has a direct positive contribution to the firm.
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