Inter-firm absorptive capacity

(1)

Inter-firm absorptive capacity

Relational norms and the length of a buyer-supplier

relationship. Does it affect the innovative

performance of a firm?

MSc. Marketing Management Master Thesis

January 16th, 2017

Ágnes Timea Balogh

Eleanor Rooseveltlaan 60, 1183 CL, Amsterdam, The Netherlands e-mail: agness.balogh@gmail.com, student number: 2908387

First supervisor: Dr. Hans J. Berger, e-mail: j.berger@rug.nl.

(2)

2 | P a g e

Acknowledgements

My master thesis marks the end of a relatively short but very relevant chapter in my life. One year and a half have went by since I moved to a country that rapidly became home. One year and a half in which I constantly challenged myself and never gave up even thought was faced with several personal challenges. During this time I had the chance to pursue my master’s degree studies and also to develop personally and professionally. Time period that wasn’t easy, sometimes stressful, many times very busy…still, I do not regret any moment of it.

A huge acknowledgment goes to the person closest to my heart, my Mother. A women whom since my adolescent years allowed me to live a life that I chose to myself, without ever

stopping or doubting my decisions to move away from home to far away countries, be that for work or studies. Thank you Mom! Thank you for your tireless support and for always

believing in me!

“I am awfully greedy; I want everything from life. I want to be a woman and to be a man, to have many friends and to have loneliness, to work much and write good books, to travel and enjoy myself, to be selfish and to be unselfish… You see, it is difficult to get all which I want. And

(3)

3 | P a g e

ABSTRACT

Innovation has been previously defined as one of the most important issues in business research today, hence it is not surprising that it is a very relevant concept for firms that are striving to be competitive in their respective industries and markets.

Knowledge has been proven to be one of the most important resources to facilitate innovation, therefore, knowledge sharing among firms and the nature of the relationship between these firms’ deserves to receive more attention (Volberda et. al, 2010). A firm’s ability to identify, assimilate, transform and apply valuable external knowledge is defined as absorptive capacity. We can distinguish between two complementary parts of this notion, potential absorptive capacity and realized absorptive capacity. Potential absorptive capacity is defined as the ability of the firm to add new knowledge via acquisition and assimilation and furthermore relates to explorative learning performance. On the other hand, realized absorptive capacity is explained by a firm’s ability to refine knowledge via transformation and exploitation and relates to exploitative learning performance. The two roles of potential and realized absorptive capacity coexist at all times and fulfill a necessary condition to achieve long-term

performance (Zahra and George, 2002).

Literature proves that companies increasingly consider relationships with other companies as a source of competitive advantage and that these relationships constitute a context in which firms may learn, share knowledge and build absorptive capacity (Knoppen, Saenz & Johnston, 2011). It has been shown that relational norms among inter-firm relationships encourage the learning, interaction and knowledge sharing between the partners (Berger, 2015). Also, that a longer, well established relationship can boost the innovative performance of a firm (Penrose, 1959; Kotabe et. al. 2003). Therefore, this study will discuss how relational norms among the buyer and supplier, as well as the length of their relationship can affect a firm’s innovative performance. This study aims to add to current literature in the following way: by linking absorptive capacity with innovative performance and analyzing the moderating effect that relational norms and the length of a buyer-supplier relationship can have between the two. Hence, the goal of this paper is to answer the following research question: To what extent do

relational norms and the length of the buyer-supplier relationship moderate the effect of absorptive capacity on innovative performance?

The empirical research of this study uses a data set of 166 matched-pair buyer-supplier relationships, obtained by key informants from both sides of the dyed by Berger (2015). In order to conduct the statistical analysis, Partial Least Squares (PLS), a Structural Equation Model (SEM) is used.

(4)

6 | P a g e

1. Introduction

Innovation is definitely not a new concept that was defined in the recent century, it is probably as old as the world. If we think about it for a second, this thesis would have been written on a typewriter and not on a small sized personal computer, if firms wouldn’t have had the desire to innovate and bring forward new ideas. Innovation has been highly linked to be dependent on knowledge, which proves to be constitutional for firms when they strive to learn, grow and stay competitive (Grant, 1996). Reasoning supported by Nonaka (1991) whom holds that “in an economy were the only certainty is uncertainty, the one sure source of lasting competitive advantage is knowledge.” Still, the amount of knowledge available today is immeasurable. Hence, it is important for firms to know how to combine these resources, because firms that know how to combine resources in unique ways, will be able to reach competitive advantage over firms that were unwilling or not able to do so (Dyer and Singh, 1998).

Besides being noted as the most important issue in business research today (Hauser et. al. 2006), the obvious reliance of innovation on external knowledge has been proven to be essential by Cohen and Levinthal (1990). Literature has shown that companies increasingly consider relationships with other companies as a source of competitive advantage and that these relationships constitute a context in which firms may learn, share knowledge and build absorptive capacity (Knoppen, Saenz & Johnston, 2011). Alongside Cohen and Levinthal (2010) whom emphasized that outside sources of knowledge are critical to the innovation process, Volberda et. al. (2010) defined that gaining knowledge from external sources and learning from partners are critical parts of the inter-organizational antecedents of absorptive capacity. Large firms, such as Procter and Gamble have changed their innovation strategy and managed to reach superior performance by “outsourcing” and learning from their suppliers. Strategy that lead to new product and process developments (Huston and Sakkub, 2006). Thus, the importance of exploring and exploiting external knowledge, which is further defined as absorptive capacity (Cohen and Levinthal, 1990) is inevitable.

(6)

8 | P a g e

leverage its knowledge through collaboration” (Mohr & Sengupta, 2002). Thus, only through a set of knowledge, firms will be able to improve current processes, products and innovate new ones (Nonaka and Takeuchi, 1995).

Williamson (1985) argued that the study of economic organizations in a regime of rapid innovation poses much more difficult issues than those addressed in his study, since new hybrid forms of organizations appear in a rapidly changing word, hence much more study about organizations and innovation is needed.

Berger (2015) mentioned that “what is known, perceived and communicated depends on the past of the firm – it is embodied in its culture and routines – and its context.” When partners are part of this context, they can be very useful sources of information and knowledge. But, according to Penrose (1959) experience among partners can never be transmitted and longer (on average above 10 years), well-established relationships (Ambrose et. al, 2010) have shown to lead to both competitive advantage (Dyer and Singh, 1998) and higher knowledge diffusion patterns (Cavusgil, Calantone and Zhao, 2003).

On the other hand, relational norms have proven to foster trust and to lead to higher levels of knowledge sharing (Inkpen and Tsang, 2005), whereas an atmosphere that does not foster trust, has shown to lead to confusion, possible opportunistic behavior, lack of creativity and information search (Selnes and Sallis, 2003). Relational norms do not only encourage the interaction between the members of an inter-firm relationship but also reduce knowledge sharing-barriers (Berger, 2015).

Accordingly, the perspective of the knowledge based view is taken in this study with the aim to offer further understanding on how absorptive capacity can impact the innovative

performance of a buyer-supplier relationship. More specifically, this study focuses on the length of a buyer-supplier relationship and on the relationships atmosphere, which is defined by relational norms. Hence, the purpose of this paper is to advance the understanding of absorptive capacity, its underlying dimension and their impact on the innovative performance of the firm. Impact that is proposed via the moderating effect of the duration of a buyer-supplier relationship and their relational norms.

Thus, this paper aims to answer the following research question: To what extent does the

duration of the buyer-supplier relationship and relational norms moderate the effect of absorptive capacity on innovative performance?

(7)

9 | P a g e

2. Theoretical background

Based on current literature, the theoretical background contains the research context of this paper. It explains the line of reasoning and describes the variables that will be used in the further chapters. In the first subchapter the knowledge based view is detailed, which represents the perspective taken by this research. Second, absorptive capacity and its dimensions are clarified which relate to exploring and exploiting external knowledge and result in an increased knowledge base. An increase in knowledge base leads to innovative performance which is described in the last subchapter along with organizational learning.

2.1. Knowledge based view

Given the context of this study, which will be detailed in the further chapters, it is relevant to mention that it is built upon the knowledge based view. This, because of its focus on the importance of knowledge as a resource and its proven superior effects on competitive advantage (Teece et. al, 1997).

Grant (1996), the eminent proponent of the knowledge based view, conceptualized the firm as an institution for integrating knowledge, and it emphasizes that knowledge resides within individuals and the primary role of the organization is applying knowledge rather than creating it. Highlighting that individuals do need organizations in order to apply and exploit knowledge. Grant (1996) argued that knowledge is the most valuable resource of an

organization and an essential factor of sustained competitive advantage.

Given their affinity, it can be disputed that the resource based view could also offer a strong frame in order to conduct this research. Nevertheless, Eisenhard & Santos (2001) posited that the knowledge based view can be considered as an extension of the resource based view since its focus on a detailed examination of knowledge as a resource and its further effects on the firms capabilities. This reasoning was maintained by Nelson & Winter (1982) whom

mentioned that knowledge is more important than the tangible assets and resources of a firm. Therefore, sustaining that knowledge it the most relevant asset available for a firm that has the possibility to boost performance.

The importance of knowledge transfer in order to achieve and maintain innovative performance has also been emphasized by Szulanszki (1996), whom mentioned that “the ability to transfer best practices internally is critical to a firm's ability to build competitive advantage through the appropriation of rents from scarce internal knowledge.” Given this, Szulanszki (1996) mentions that “the major barriers to internal knowledge transfer to be knowledge-related factors such as the recipient's lack of absorptive capacity, causal

ambiguity, and a difficult relationship between the source and the recipient”, accentuating the importance of absorptive capacity.

(8)

10 | P a g e

inter-organization is obvious, especially if the aim is to reach profit returns while aiming for innovative performance.

2.2. Absorptive capacity and its dimensions

Significant consideration has been given to the concept of absorptive capacity in the last decade, starting with the two seminal studies of Cohen and Levinthal (1989, 1990) and followed by many more scholars (e.g. Zahra and George, 2002; Szulanski, 1996; Berger, 2015).

In their second work, Cohen and Levinthal (1990) extend their view on absorptive capacity to include characteristics of learning, besides a purely economic perspective (Cohen and

Levinthal, 1989), and argue that it is critical for a firm’s innovative capability to recognize the value of new, external information, assimilate it and apply it to commercial ends. This is what they characterize as the firms absorptive capacity.

Zahra and George (2002) define absorptive capacity (APAC) as “a set of organizational routines and processes by which firms acquire, assimilate, transform, and exploit knowledge to produce a dynamic organizational capability.” They believe that the previously mentioned capabilities represent four dimensions of APAC which are combined by their nature and built upon each other in order to produce dynamic organizational capabilities. The four dimensions of acquisition, assimilation, transformation and exploitation separate APAC in two building blocks: potential absorptive capacity (P9) and realized absorptive capacity (RACAP). Potential absorptive capacity (PACAP) is defined as adding knowledge via acquisition and assimilation. “Acquisition refers to a firm's capability to identify and acquire externally generated knowledge that is critical to its operations” (Zahra and George; 2002) e.g. knowledge generated by suppliers, whereas “assimilation refers to the firm’s routines and process that allow it to analyze, process, interpret, and understand the information obtained from external sources” (Zahra and George; 2002).

Realized absorptive capacity (RACAP) refines knowledge via transformation and

exploitation. Transformation refers to a firm’s capability to develop and refine routines and processes that help combining already existing knowledge with the newly acquired and assimilated knowledge. This is reached by adding, deleting or simply interpreting the same knowledge in a different manner (Zahra and George, 2002). Whereas, exploitation reflects a firm's ability to harvest and incorporate knowledge into its operations (Crossan and Inkpen, 1997) based on certain routines that allow firms to refine, extend and leverage existing competencies or also to create new competencies by involving the acquired and transformed knowledge into its operations (Zahra and George, 2002).

The above described four dimensions of absorptive capacity (APAC) are further discussed by many academics whom hold that absorptive capacity (APAC) does not only facilitate

competitive advantage (Teece et. al., 1997; Kogut and Zander, 1992) but it also enables firms to exploit new knowledge (Cohen and Levinthal, 1990) in order to ensure superior

(9)

11 | P a g e

According to Tsai (2012) “high absorptive capacity is associated with a better chance to successfully apply new knowledge toward commercial ends, producing more innovations and better business performance.” Therefore, he supports the previously presented arguments which emphasize that absorptive capacity does have a significant influence on a business units’ innovation and performance.

2.3. Organizational learning and innovative performance

The work of Penrose (1959) in which she defines “The theory of the growth of a Firm” can be considered as a stepping stone in organizational learning. She defines that as management structures try to make the best out of the available resources a dynamic interacting process happens which facilitates continuous growth, while arguing that “there is a close relation between the various kinds of resources with which a firm works and the development of ideas, experiences, and knowledge of its managers and entrepreneurs.” In the latter statement emphasizing the importance of knowledge, in order to generate new ideas that lead to

innovative performance. Researchers defined organizational learning in different ways, but there is a consensus that its core is represented by a change in the organization that occurs as the organization gains more experience over-time (Argote and Miron-Spektor, 2011). In the context of inter-organizational learning and absorptive capacity, Lane and Lubatkin (1998) re-conceptualized Cohen and Levinthal’s (1990) firm level construct of absorptive capacity and studied the effect of partner characteristics on the success of inter-organizational learning. They argue that one firm’s ability to learn from the other one depends on, among other factors, the similarity of their knowledge bases and prove that firms are heavily relying on knowledge acquired from each other in order to facilitate the development of their own capabilities. This knowledge sharing requires as much attention as managing their own physical assets since as competition becomes more knowledge-based, a firm must develop a thorough understanding of its own knowledge. Without this level of self-awareness, a firm will be slow to react to the market forces that inevitably erode the combined strategic value of its set of capabilities (Cohen and Levinthal, 1990). Argumentation that is aligned with

Penrose’s proposition and it is extended with depicting that in inter-organizational learning, such as a buyer-supplier relationship, the similarity of the partners’ basic knowledge base is positively related to inter-organizational learning. Also, studies conducted by Powell (1999) and Von Hippel (1988) suggest that partners are in many cases the most important sources of new ideas and information that can lead to superior performance and innovations. Hence, knowledge transfer among inter-organizational relationships has proven to be very important due to reasons such as work arrangements, globalization etc.

(10)

12 | P a g e

absorptive capacity, causal ambiguity and the quality of relationship between the source and the recipient. A weak relationship between the source and the recipient can lead to best practices that are not being transferred. When best practices do not transfer it is less because the organization cannot learn, rather because they do not know how to. Hence, Szulanszki (1996) concluded that in order to foster close relationships between organizational units, and to systematically understand and communicate practices, inter-organizational learning is definitely a promising alternative worthy of future research.

According to Larsson et. al. (1998) inter-organizational learning is playing an increasingly important role in achieving innovative performance in a relational context – where the outcome of the learning heavily depends upon the interaction with partners. When partners exchange, or invest in idiosyncratic assets, knowledge, resources and capabilities, relational rents also become possible. Relational rents can be achieved by effective governance, by lowering transaction costs or also by offering incentives for value-creation initiatives. Incentives that will encourage partners to be transparent towards each other, to transfer knowledge and not to free ride on the knowledge acquired from the partners involved. Not only formal financial incentives, such as for e.g. equity arrangements can lead to relational rents but also informal norms of reciprocity (Dyer and Singh, 1998). Hence, in order to reach economically efficient relationships among independent firms, norms have shown to play a very important role (Heide and John, 1992). This because organizations do not only store knowledge in their procedures, rules and forms but also in the definition of their norms (March, 1991).

Norms are defined as expectations about behavior that are at least partially shared by a group of decision makers (Gibbs, 1981). Norms have been found to differ regarding the extent to which they define behaviors towards individual or collective goals. Hence, two different norms can be determined based on their content and general orientation (Heide and John, 1992). The difference among the two is clarified by Macneil (1980) who describes “discrete” versus “relational norms”. Discrete norms contain expectations about an individualistic or competitive interaction between the partners. The individual parties in the exchange are expected to remain autonomous and pursue strategies aimed toward the attainment of their individual goals. In contrasts, relational norms, are based on the expectation of mutuality of interest, essentially prescribing “caring” behavior, and are designed to enhance the wellbeing of the relationship as a whole (Heide and John, 1992). Both are viewed as norms, even though they represent fundamentally different behavioral expectations (Heide and John, 1992). Thus, norms are expected to affect the need for effective governance and to positively moderate the relationship between absorptive capacity and innovative performance. Therefore, the

governance structure that this study takes into consideration are relational norms. Relational norms will be detailed in the conceptual part of this study.

(11)

13 | P a g e

innovative performance, investing in the duration of the relationship is beneficial. Thus, it is expected that the duration of the buyer-supplier relationship will positively moderate the effect of absorptive capacity on innovative performance.

Based on the above arguments, this study hopes to offer deeper understanding on the importance of relational norms and relationship duration in the context of buyer-supplier relationships. Furthermore, it aims to define the importance of the above mentioned two factors on the innovative performance of a firm. Innovative performance which is defined by potential absorptive capacity and realized absorptive capacity.

3. Conceptual model and hypotheses

In the following chapter the conceptual framework of this study and its proposed hypotheses will be discussed. Demonstrating how the length of the buyer-supplier relationship and their relational norms may moderate the relationship between absorptive capacity and the

innovative performance of a firm. At the end of the chapter the conceptual model is presented, which aims to serve as a visual guide.

3.1. Absorptive capacity and learning performances

The two dimensions of acquisition and assimilation, as previously mentioned, constitute potential absorptive capacity (PACAP) and correspond to explorative learning (Berger, 2015). According to March (1991) the core of exploration is defined by experimentation with new alternatives” and it “includes things captured by terms such as search, variation, risk taking, experimentation, play, flexibility, discovery, innovation”, therefore making it clear that it requires out of the box thinking on some sort of a level. Cohen and Levinthal (1990) defined that firms whom constantly look out for growth opportunities even in a turbulent environment will reach competitive advantage. This way proving that, explorative learning itself can be an important source of competitive advantage. Hence, this study will assume that potential absorptive capacity (PACAP) is positively related to explorative learning.

The other two dimensions of absorptive capacity, transformation and exploitation, constitute realized absorptive capacity (RACAP) and relate to exploitative learning (Berger, 2015). The essence of exploitation is the refinement and extension of existing competences, technologies, and paradigms and includes “refinement, choice, production, efficiency, selection,

implementation, execution” (March, 1991). Hence, are constituted about following processes and standards rather than out of the box thinking. This study will assume that realized

absorptive capacity (RACAP) is positively related to exploitative learning.

(12)

14 | P a g e

suboptimal stable equilibria.” Hence, proving that a balance among the two is an essential factor in the performance and prosperity of the firm. Zahra and George (2002) supported this and established a strong link between the components of APAC and the process of applying acquired knowledge, noting that “realized capacity allows creation of a competitive

advantage; potential capacity provides strategic flexibility to change and reconfigure firm operations, providing means to sustain such performance differences.”

Accordingly, two hypotheses have been formulated, which constitute the base of the conceptual framework of this study:

H1a: Potential absorptive capacity (PACAP) is positively related to explorative learning. H1b: Realized absorptive capacity (RACAP) is positively related to exploitative learning.

3.2. Relationship duration

According to Berger (2015) a long-term buyer-supplier relationship as itself can be an

important source of knowledge creation. By sharing information and know-how a platform is created for both parties to learn about new technologies, new markets and operations.

Therefore, these long-term buyer-supplier relationships can be described as an answer to the uncertainty that firms have to deal with (Powell, 1990; Ahuja and Lampert, 2001).

Ambrose et. al., (2010) proves that there are significantly different drivers of relationship success in buyer-supplier relationships but when it comes to the length of the relationship it is clearly found that the business relationship among his selected sample is on average above 10 years and concludes that the context of buyer-supplier relationships is clearly one of long-term, well-established and high-valued relationships. Showing that the length of the

relationship is valued by both parties and they both pay attention and careful management to it. According to a prominent personality in the definition of organizational learning, Penrose (1959), these long term relationships can lead to experiences that further produce increased knowledge about things and also contribute to objective knowledge in such a way that it can be transmitted to others. However, Penrose (1959) does highlight that experience in itself can never be transmitted. Later on, Cavusgil, Calantone and Zhao (2003) agree with Penrose’s (1959) reasoning that experience cannot be transferred and have shown that only partners with embedded relationships that have developed over time will learn to facilitate the mechanisms of knowledge diffusion. Also, they will learn and acquire routines that will become stable expectations over time (Squire et. al., 2009).

Overall, these knowledge-sharing partners in long term relationships produce relation-specific assets (Dyer and Singh, 1998). The importance of which as a source of competitive advantage is confirmed by Kotabe et. al. (2003). His study has shown that buyer-supplier relations with a longer duration, build and exploit relationship-specific assets that make the transfer of

knowledge more efficient.

(13)

15 | P a g e

refinement of this knowledge via realized absorptive capacity (RACAP). Hence, a longer relationship among buyers and suppliers represents experience which can furthermore produce increased knowledge and innovative performance. Therefore, this study hypotheses that the duration of the relationship between a buyer and a supplier will positively moderate the relation between PACAP and innovative performance, respectively RACAP and

innovative performance. Innovative performance which in present study is defined by the two learning performances: explorative learning and exploitative learning.

H2a: The duration of the relationship between the buyer and supplier will positively moderate the relation between PACAP and explorative learning.

H2a: The duration of the relationship between the buyer and supplier will positively moderate the relation between RACAP and exploitative learning.

3.3. Relational norms

Relational norms can be defined as behavioral expectations that are partially shared by a group of decision makers. It is based on the expectation from both parties in the partnership that the general goal is the wellbeing of the relationship. These norms can protect the relationship by acting as safeguards against exploitative use of decision rights. It has been proven that overtime, relational norms can provide knowledge sharing stability (Heide and John, 1992).

Mcneil (1980) defined that interfirm norms are multidimensional, in a way that they can relate to different types of behaviors. These domains are different, though related and are described by the following norm types: flexibility, solidarity and information exchange.

The norm type flexibility reflects the willingness of partners to make adaptations as

circumstances change (Heide and John, 1992) while taking into account the partners interest (Berger, 2015). According to Heide and John (1992), from a supplier’s perspective, flexibility “represents insurance that the relationship will be subject to good-faith modification if a particular practice proves detrimental in the light of changed circumstances”.

The norm type information exchange reflects the expectation that the alliance partners will proactively provide information that is useful to the other partner (Heide and John, 1992; Berger, 2015). Information exchange represents a safeguard to the supplier in the sense that the buyer can be expected to provide unforeseen information that may affect supplier operations. An expectation of receiving all known information on an ongoing basis, by regularly exchanging information, enables the supplier to cope efficiently with the vulnerability associated with transferring decision control to the buyer (Heide and John, 1992).

(14)

16 | P a g e

The above three overlapping norm types have proven to separately have relevance (Macneil, 1980) and even though they are different, these elements originate from a single, higher order, relational norm (Noordewier, John and Nevin, 1990).

Relational norms foster trust, and once partners perceive that their counterparts are

trustworthy, they will be more inclined to share information (Inkpen and Tsang, 2005; Lee and Cavusgil, 2006). Whereas a lack of trust may lead to confusion about whether a firm is really an ally or not (Powell, Koput and Smith-Doerr, 1996). An atmosphere that suggests trust will contribute to the free exchange of information among partners, because they will not feel like they need to protect themselves from opportunistic behavior (Lee and Cavusgil, 2006). According to Inkpen and Tsang (2005) as trust develops overtime, opportunities for knowledge transfer between network members should also increase. With the development of a pattern of interactions, organizations will decrease their efforts to protect their knowledge and skills. Hence, partners will feel comfortable to share information, to work on joint efforts in order to reach continuous performance improvement and collaborative innovation.

According to Berger (2015) relational norms encourage the interaction between the members of an inter-firm relationship and reduces knowledge sharing barriers as well. Also, it is assumed that relational norms are based on search, discovery, play, experimentation (Berger, 2015). Hence, it is proposed relational norms it will positively moderate the relationship between PACAP and explorative learning performance.

Since knowledge exploitation requires the sharing of relevant knowledge in order to facilitate mutual understanding and comprehension (Zahra and George, 2002). It is expected that when these knowledge sharing barriers are minimized relational norms will also stimulate

exploitation. Accordingly, it is expected that relational norms will be positively moderate the relation between RACAP and exploitative learning performance.

Even though relational trust does facilitate information sharing and development of shared relationship memories, higher levels of relational trust can also lead to problems that might reduce the effect of relationship learning on performance. These hidden costs are the

following: (1) Systematic avoidance of negative information. Since emotions are involved as the parties start to like each other, they believe that the pleasant atmosphere needs to be maintained; (2) heightened risk of opportunistic behavior due to more relaxed control

mechanisms and less opportunities for learning. When trust is low or moderate, each party is likely to perceive some level of risk in which it believes the other party might exploit it, and for that reason both parties seek critical information to monitor each other's behavior. In addition, reduced monitoring means reduced questioning of the status quo and less opportunity for learning; (3) loss of creativity due to too much congruence among the thinking of the participants (Selnes and Sallis, 2003). Accordingly, the positive moderating effect of relational norms, between the APAC dimensions and the learning performances is assumed to level off at higher levels of relational trust.

(15)

17 | P a g e

H3a: Relational norms among the buyers and suppliers will positively moderate the relation between PACAP and explorative learning.

H3a: Relational norms among the buyers and suppliers will positively moderate the relation between RACAP and exploitative learning.

4. Methodology

The following chapter will discuss the data collection, measurement scales and the statistical procedure of this study.

4.1. Sample and data collection

The focus of the analysis is on the vertical relationships among independent firms operating at successive stages in the production chain (Berger, 2015). As these relationships are not

(16)

18 | P a g e

independent firms involved but from both. This will allow for understanding differences in perceptions of the relationship between the buyer and supplier (Ambrose et. al., 2010) Data was collected by Berger (2015) from heads of purchasing or high-ranking technology managers whom were asked to provide contact data of four people within their companies, who were relevant to their customer relationships. As manufacturing firms show a higher probability in acquiring knowledge in order to further develop and improve new products are processes (Arbussa and Coenders, 2007) the service sector was excluded from the study. Hence, for variance purposes, data was collected from the automotive, machinery, chemical, pharmaceutical, electronics and semiconductor industry.

As for the distribution of the questionnaire, firstly, buyer companies were asked to provide information of their contacts in the supplier organization. Buyer informants, all located in the Netherlands, were interviewed using a standardized questionnaire after which informants from the supplier organizations, located all around the world, were contacted via e-mail and asked to fill in the questionnaire available both in English and Dutch, this way hoping to prevent non-response. The questions relevant for this study can be found in Appendix 1. The data collection resulted in data from 166 matched-pair relationships, collected in the period between June 2011 and April 2013.

4.2. Measures

The measures of this study are based on previous research and were collected by Berger (20150). The existing scales on previous buyer-supplier relationship, learning and interfirm learning (not necessary related to buyer-supplier relationships but e.g. IJV, mergers and acquisitions) were adopted and extended in order to measure vertical interfirm relationships (Berger, 2015).

The questionnaire filled in by the respondents contained both first order and second order constructs. Which are defined as following: “First-order construct is a latent construct that has observed variables as indicators, whereas second-order construct have other latent (first-order) constructs as their indicators (Berger, 2015)”. Depending on the link between the indicators and the latent indicators a differentiation was made between reflective and formative scales. The reflective indicators reflect the latent construct, and it changes in value if the indicators change in value (Berger, 2015). The reflective indicators are represented by single-headed arrows that are pointing from the latent construct outward towards the indicator variables. The associated coefficients for these relationships are called outer loading in PLS-SEM. The formative scales are represented by single headed arrows that are pointing from the indicators towards the latent variables and the associated coefficients to these relationships are called outer weights. In formative scales the indicators are expected not to be related, since they measure separate aspects of the same construct (Hair et. al. 2011).

(17)

19 | P a g e

The measures for the dimensions of absorptive capacity (ACAP) were not previously

available, hence they were generated for the study of Berger (2015). PACAP a second-order construct, was measured by combining the dimensions of acquisition and assimilation (first-order constructs). RACAP a second-(first-order construct was measured by combining the

dimensions of transformation and exploitation (first order-constructs). The first dimensions in measuring PACAP, acquisition refers to the relationships ability to recognize and acquire new external knowledge, whereas the second dimension, assimilation refers to the relationships ability to make sense out of new external knowledge. Regarding RACAP, the first dimension, transformation, indicates the relationships ability to relate newly acquired knowledge to what is already known, whereas the second dimension, exploitation refers to indicating how external knowledge is shared and transferred in the relationship. Both dimensions, PACAP and RACAP, resulting in second-order formative constructs.

Relational norms are measured by a second order construct that represents three norm types: flexibility, information exchange and solidarity. All three norm types are first order, latent constructs. Relational norms were assessed based on the measures developed by Heide and John (1992) who defined them as the following: (1) Flexibility: Flexibility as a response for changes is a characteristic of the relationship. The parties expect to make adjustments in the ongoing relationship and to cope with the changing circumstances. When unexpected events arise, the parties are flexible in working out new deals, rather than holding each other to the old ones. (2) Information exchange: It is expected in the relationship that any information that might be useful to the other party, it will be provided to them. Information exchange happens freely and not just according to a pre-specified agreement. It is expected that the parties will provide proprietary information if it can help the other party. It is expected that they keep each other informed about events or changes that may affect the other party. (3) Solidarity: Problems that arise in the course of their relationship are treated by the parties as joint rather than individual responsibilities. The parties are committed to improvements that may benefit the relationship as a whole and not just the individual. The parties in the relationship do not mind owning each other favors.

(18)

20 | P a g e

4.3. Statistical procedure

For the statistical analysis Partial Least Squares (PLS), a variance based Structural Equation Model (SEM) is used, which combines factor analysis and multiple regression analysis (Hair et. al. 2011). Variance-based SEM was introduced in the 70’s by Herman Wold (Wold, 1973) but software packages, such as SmartPLS used in this study, were developed much later (Ringle et. al. 2005). PLS-SEM is a causal modeling approach which aims to maximize the explained variance of the dependent latent construct (Hair et. al. 2011).

It is the preferred approach for the analysis since it allows for complex models, non-normal data and formative measures (Hair et. al 2011). Since this research includes, moderating relationships, higher order constructs and both formative and reflective constructs the choice for PLS is justified. In order to conduct the partial least squares equation modelling (PLS-SEM) one of the leading software tools was used, SmartPLS.

In order to conduct the analysis, as mentioned, the PLS path modeling method was chosen which was developed by Wold (1982). In essence, the PLS algorithm is a sequence of

regressions in terms of weight vectors and the weight vectors obtained at convergence satisfy fixed point equations (Dijkstra, 2010). While calculating weights, the algorithm considers the factor score as an exact linear combination of its indicators (Hair et. al. 2011).

Additionally, since PLS-SEM does not presume that the data are normally distributed (Hair et. al. 2011), in order to support the significance of the found effects, the resampling method to estimate the p-values was bootstrapping. Bootstrapping is a nonparametric procedure that allows testing the statistical significance of various PLS-SEM results such as path

coefficients. Given the sample size of n=166 the choice for bootstrapping seems to be

obvious. Bootstrapping, which involves the repeated random sampling with replacement from the original sample to create a bootstrap sample, results in obtaining standard errors for hypothesis testing (Hair et. al., 2011).

According to Chin (1998) a PLS study should have a minimum sample size that fulfills one of the following two conditions: ten times the amount of indicators of the scale with the largest number of formative indicators or ten times the largest number of structural paths directed to a dependent variable. In the model of this study there are: six indicators and two structural paths. As the sample used for this research consists of n=166 for the buyer database and n=166 for the supplier database, it can be concluded that it is sufficiently large.

5. Analysis and results

(19)

21 | P a g e

relationships between the latent constructs. But before assessing the structural model, the reliability and validity of the latent constructs is examined, once this proves to be strong enough, the structural model can be assessed (Berger, 2015; Hair et. al. 2011). Since it is important to specify the measurement model before analyzing the structural model and conducting the study, the first subchapter will address the measurement model.

5.1. Measurement model

Whether the measurement model is adequate in order to further conduct the study it needs to be assessed for its convergent and discriminant validity (Berger, 2015). “Convergent validity refers to the extent to which indicators of the same latent construct share a high proportion of variance in common, while discriminant validity refers to the degree to which a latent

construct is truly different from other latent constructs (Berger, 2015; Hair et. al 2010)”. Hence, in order to ensure that the measurement model is adequate the convergent and discriminant validity will be assessed.

The measurement model is assessed for the combined buyer and supplier (n=332) database and it is tested for consistency by developing measurement models for the buyer (n=166) and the supplier (n=166) database separately. When evaluating the measurement model, according to Henseler et. al. 2009, one must also distinguish between the reflective and formative scales in order to evaluate them. This, because a different approach is needed in order to evaluate the convergent and discriminant validity (Hair et. al, 2010).

5.1.1. Reflective scales

In Table 5.1. the assessment of convergent validity can be seen, as previously discussed for reflective scales only. First, the indicator reliability is measured. All indicator loadings should have p-values under 0.05 and indicator loadings equal or higher then 0.05 (Hair et. al, 2010). For all constructs seen below in Table 5.1. the p-values were lower than 0.05 (not shown) and all standard loadings of the indicators exceeded 0.5.

Cronbach alpha measures provide an estimate for construct reliability (Berger, 2015) and assume that all indicators contribute equally to overall reliability while using equal weights (Henseler et. al. 2009). On the other hand, composite reliability includes the actual factor loadings of individual factors and is recommended in case of path models (Berger, 2015). As suggested by Nunnally and Bernstein (1994) a value equal or greater than 0.70 is considered satisfactory for both Cronbach alpha and the composite reliability. By looking at the

(20)

22 | P a g e

Table 5.1: Construct reliability and convergent validity of reflective scales

Constructs

Buyer and Supplier Buyer Supplier

Standard loadings: Cronbach’s alpha: Composite reliability: Standard loadings: Cronbach’s alpha: Composite reliability: Standard loadings: Cronbach’s alpha: Composite reliability: Assimilation .79 .86 .80 .86 .76 .84 Assim1 .64 .65 .63 Assim2 .78 .77 .80 Assim3 .81 .80 .83 Assim4 .76 .79 .72 Assim5 .67 .72 .63 Exploitation .77 .84 .77 .84 .76 .84 Exploit1 .70 .67 .72 Exploit2 .67 .61 .71 Exploit3 .80 .84 .73 Exploit4 .86 .85 .86 Exploit5 .57 .60 .54 Flexibility .74 .85 .67 .82 .78 .82 Flex1 .81 .80 .83 Flex2 .84 .80 .86 Flex3 .77 .72 .80 InfoExchange .78 .85 .74 .83 .80 .83 InfoEx1 .74 .64 .79 InfoEx2 .78 .72 .79 InfoEx3 .77 .78 .75 InfoEx4 .80 .78 .82 Solidarity .83 .89 .80 .88 .85 .88 Solid1 .82 .79 .84 Solid2 .87 .89 .85 Solid3 .89 .85 .93 RelationalNorms (2nd_{order const.)} .87 .90 .82 .86 .90 .86 Flexibility .76 .62 .85 InfoExchange .87 .85 .90 Solidarity .88 .88 .89 5.1.2. Formative scales

Since the indicators of formative scales are not necessarily related to each other, and are assumed to be error free (Hair et. al, 2011) a different approach is needed for the formative scales. Their convergent validity is measured by assessing the p-values and the VIF (variance inflation factor) scores of the indicator weights. Indicators with p-values under 0.05 are seen to be valid (Berger, 2015). Whereas VIF scores should be under the value of 3.30 (Petter et. al. 2007). In order to assess the p-values and significance, bootstrapping was used.

After running the analysis, Acquis2, Transform2 and Transform3 showed inadequate p-values for all three databases. Hence, in order to prevent measurement inconsistencies these items were removed from all three database configurations. Additionally Transform5 showed a very low indicator weight of 0.09, however it showed to be consistent and the VIF score is

(21)

23 | P a g e

The results of the convergent validity of the formative scales, including the remaining indicators, can be seen in Table 5.2. Bootstrapping was used to test their significance, which showed p values under 0.005 for all indicators, as well as VIF scores below 3.

Table 5.2: Convergent validity of formative scales

Constructs

Buyer and supplier Buyer Supplier

(22)

24 | P a g e 5.1.3. Discriminant validity

As a next step discriminant validity is assessed for both formative and reflective scales. Discriminant validity became a generally accepted way to analyze relationships between latent variables and it is conducted in order to ensure that a construct has the strongest relationship with its own indicators, in comparison with any other indicators (Hair et. al, 2014). This is assessed by “comparing the squared roots of the average variances extracted (AVE) of a specific latent construct with the correlation coefficients of that specific construct and the other latent construct” (Berger, 2015).

The results of the assessment can be seen in below two tables, for both first order constructs (Table 5.3a) and second order constructs (Table 5.3b). The average variance extracted (AVE) of each latent construct shows to be greater than the latent construct’s highest squared

correlation with any other latent construct (Hair et. al, 2011), hence, it does reflect discriminant validity.

Table 5.3a: Squared roots of the average variance extracted (AVE) and correlation matrix (first order constructs)

1 2 3 4 5 6 7 8 9 1. Acquisition .726 2. Assimilation .645 .739 3. Transformation .545 .646 .751 4. Exploitation .541 .650 .676 .724 5. Flexibility .181 .346 .324 .351 .811 6. Information Exchange .300 .410 .490 .336 .501 .777 7. Solidarity .245 .380 .408 .363 .533 .668 .865 8. Explorative LearnPerf .277 .319 .287 .319 .338 .336 .205 .784 9. Exploitative LearnPerf .425 .529 .532 .529 .351 .372 .334 .551 .637

Table 5.3b: Squared roots of the average variance extracted (AVE) and correlation matrix (second order constructs)

1 2 3

1. Relational norms (Flexibility + Info Exchange + Solidarity) .690

2. PACAP (Acquisition + Assimilation) .424 .663

3. RACAP (Transformation + Exploitation) .540 .617 .658

The analysis of the measurement model shows that it is strong enough for further

(23)

25 | P a g e

5.2. Structural model

As previously discussed the structural model is assessed for both the supplier and buyer databases separately. The primary criteria in order to evaluate the structural model are the R Square measures and the significance of the path coefficients. Another assessment involves the model’s capability to predict. This predictive relevance is measured by Stone-Geiser’s Q Square, which entails that the model should be able to adequately predict each endogenous latent construct’s indicators (Hair et. al, 2011).

Table 5.4: Full collinearity VIF's, explained variance, and predictive validity measures (PLS-SEM)

Full collinearity VIFs Explained variance (R

Square)

Predictive validity

(Stone-Geiser Q Square)

Buyer Supplier Buyer Supplier Buyer Supplier

Relationship duration 1.258 1.390 - - - - Relational norms 1.792 1.292 - - - - RACAP 1.023 2.025 - - - - PACAP 1.041 1.563 - - - - Explorative LearnPerf 1.042 1.011 .163 .138 .077 .065 Exploitative LearnPerf 1.036 1.020 .407 .303 .136 .143

In order to estimate the path coefficients, bootstrapping was used. Bootstrapping is a

nonparametric procedure that allows testing the statistical significance of several PLS-SEM results such as, R Square etc. “In bootstrapping, subsamples are created with observations randomly drawn (with replacement) from the original set of data. To ensure stability of results, the number of subsamples should be large” (Ringle et. al., 2015) hence the number of subsamples used is this analysis was 5000, this exceeds the minimum of 200 suggested by Chin (1998).

Above Table 5.4 shows the full collinearity measures for all latent variables (VIF scores), the explained variance (R Square) and the predictive validity (Stone-Geiser Q Square) of the endogenous latent variables.

Furthermore, all VIF values are under the threshold of 3.3 which indicates no

multicollinearity issues among the measurements (Kock and Lynn, 2012), whereas the explained variance (R Square) and the predictive validity (Stone - Geiser Q Square) of the dependent variables ranges from 0.07 to 0.40.

(24)

26 | P a g e

A two-stage partial least squares approach was required to conduct the moderation effect, this because PACAP and RACAP are based on formative indicators and they need to be

multiplied with the two moderators, relationship duration and relational norms. Since the constructs of absorptive capacity are independent of each other and measure different constructs the two stage approach is justified (Vinzi et. al. 2010). First the latent variable scores are calculated followed by the interaction term (X*Moderator). The interaction of X*Moderator is further used, along with the scores of X and Moderator, as independent variables on the latent scored of Y (Vinzi et. al., 2010).

“The multi-group analysis allows to test if pre-defined data groups have significant

differences in their group-specific parameter estimates e.g., outer weights, outer loadings and path coefficients” (Ringle et. al., 2015). In this case a multi-group analysis was run in order to find out if there is a significant difference in the path coefficients of the buyer and supplier databases. These can be seen in the last two columns of table 5.5. The relationship duration to PACAP moderation effect (p-value=0.017) and the relationship duration to RACAP

moderation effect (p-value=0.024) shows significantly different values for both databases at the level of p ≤ 0,05. For the moderation effect of relational norms on PACAP and RACAP no significant difference can be seen among the two different databases. Same can be said for the direct effects of PACAP on explorative learning performance and RACAP on exploitative learning performance, there is no significant difference among the two, buyer only and

supplier only databases.

Table 5.5: Estimated direct and moderation effects

Independent Dependent Buyer Supplier Multi-group

analysis

Beta: P-value: Beta: P-value: Beta:

(25)

27 | P a g e

6. Hypotheses Testing

In order to test the hypotheses, first the estimated direct effects are taken into consideration followed by the moderation effects. In the following chapter these are discussed for both sides of the dyad. Separately for the buyer only and the supplier only databases because the results may differ.

6.1. Buyer only database

An overview of the supported and rejected hypotheses for the buyer only database is summarized in Table. 5.6. As hypothesized there is a significant direct effect of PACAP on explorative learning performance (beta=0.450, p-value=0.000) as well as of RACAP on exploitative learning performance (beta=0.559, p-value=0.000). Therefore, PACAP

respectively RACAP is positively related to explorative learning performance, respectively exploitative learning performance. Hence, H1a and H1b are supported.

Table 5.6: Overview of (supported and rejected) hypotheses for the “buyer only” database

Dependent Independent Hypothesis

Explorative LearnPerf

PACAP H1a Supported

PACAP*RelationshipDur H2a Supported

PACAP*RelationalNorms H3a Rejected

Exploitive LearnPerf

RACAP H1b Supported

RACAP*RelationshipDur H2b Supported

RACAP*RelationalNorms H3b Rejected

As expected, duration of the buyer-supplier relationship positively moderates the relationship between PACAP and explorative learning performance (beta=0.217, p-value=0.016),

respectively between RACAP and exploitative learning performance (beta=0.208, p- value=0.023). Therefore, H2a and H2b are also supported.

(26)

28 | P a g e

6.2. Supplier only database

An overview of the supported and rejected hypotheses for the supplier only database is summarized in Table. 5.7. As hypothesized there is a significant direct effect of PACAP on explorative learning performance (beta=0.387, p-value=0.000) as well as of RACAP on exploitative learning performance (beta=0.482, p-value=0.000). Therefore, PACAP

respectively RACAP is positively related to explorative learning performance, respectively exploitative learning performance. Hence, H1a and H1b are both supported.

Table 5.7: Overview of (supported and rejected) hypotheses for the “supplier only” database

Dependent Independent Hypothesis

Explorative LearnPerf

PACAP H1a Supported

PACAP*RelationshipDur H2a Rejected

PACAP*RelationalNorms H3a Rejected

Exploitative LearnPerf

RACAP H1b Supported

RACAP*RelationshipDur H2b Rejected

RACAP*RelationalNorms H3b Rejected

Contrary to what is expected, the duration of the buyer-supplier relationship does not moderate the effect of PACAP on explorative learning performance (beta=-0.037. p-value=0.535) and neither does it influence the effect of RACAP on exploitative learning performance (beta=0.059, p-value=0.486). Contradicting the buyer’s point of view, from the supplier’s angle the duration of the buyer-supplier relationship does not moderate between absorptive capacity and learning performances. Therefore, H2a and H2b are rejected. The same can be concluded for the moderating effect of relational norms between PACAP and explorative learning performance (beta=-0.046, p-value=0.463), respectively RACAP and exploitative learning performance (beta=--0.025, p-value=0.723). H3a and H3b are rejected.

7. Conclusion and discussion

This paper focuses on finding insights on social aspects that can impact the innovative

(27)

29 | P a g e

7.1. Direct effects

The hypothesized direct effects of the study refer to the previously discussed absorptive capacity among buyer-supplier relationships and learning performances. It represents the base of the conceptual framework of this study.

The results from both the buyer and supplier perspectives have shown that PACAP is positively related to explorative learning (p-value=0.000), as well as that RAPAC to

exploitative learning (p-value=0.000). Hence out of the box thinking (PACAP) does facilitate explorative learning performance, from both perspectives (buyer/supplier) along with

RACAP, which requires the vigilant following of processes and facilitates exploitative learning, again, from both perspectives (buyer/supplier). As also seen in the multi-group analysis (Table 5.5.) the effect of PACAP on explorative learning performance and RACAP on exploitative learning performance does not seem to show relevant differences among the two databases.

Therefore, two conclusions can be drawn that prove the defined assumptions and do not provide novelty: (1) knowledge acquisition and assimilation positively affects explorative learning performance, (2) knowledge transformation and exploitation positively affects exploitative learning performance. Hence, the assumed positive relation of absorptive capacity on the learning performances and furthermore on the innovative performance of the firm is supported by the results of the analysis, both from the buyer and suppliers perspective.

7.2. Moderating effects

The moderators included in this study are represented by the relationship duration between a buyer and supplier and by relational norms that define the relationships atmosphere.

The first moderating effect that was assumed for this study is the effect that relationship duration (between the buyer and supplier) can have on the relation between PACAP (knowledge acquisition and assimilation) and explorative learning, respectively RACAP (knowledge transformation and exploitation) and exploitative learning. The findings did show contradicting perceptions from the buyer and suppliers view regarding the value of their relationships duration. Relationship duration as being very self-explanatory, refers to the number of years that the buyers and suppliers have spent working together.

From the buyers perspective the duration of the relationship with their supplier does have a significant moderating effect between both PACAP, explorative learning performance and RACAP, exploitative learning performance. Hence from the buyer’s view, the longer the buyer-supplier relationship, the more chances there are that the collaboration will lead to enhanced innovative performance.

From the suppliers perspective the amount of years spent working together with their partners does not seem to be significantly moderating the relationship between PACAP and

(28)

30 | P a g e

performance. Therefore, contradicting the buyers view, from the supplier’s outlook the duration of the relationship among the two is less relevant.

It needs to be noted that buyers in this study were all located in the Netherlands, whereas interviewed suppliers were from different cultures situated all over the world. Culturally similar partnerships have been proven to show higher patterns of knowledge transfer and the ability to have better and longer lasting interactions, which has a positive effect on their efforts to integrate and transform tacit knowledge into creation of new ideas (Parkhe, 1993). Hence, it can be concluded that the difference in culture could be one reason that explains the difference in the perception that buyers and suppliers have regarding the length of their relationship. Differences in perception among them are supported by Ambrose et. al. (2010) who has shown that buyers and suppliers have significantly different perceptions about both the strength and the dynamics of buyer-supplier relationships. These perceptions vary across different attributes and domains regarding relationship performance. Thus, the discrepancy among the two databases seems to be justified. The contrast between the two perspectives is supported by the multi-group analysis as well, which does show differences in the two analyzed databases (p=0,017; p=0,024).

In this study relational norms captured the relationships atmosphere and its proposed effect on innovative performance (explained by explorative and exploitative learning performances) via three norm types: flexibility, information exchange and solidarity. Flexibility is explained by a bilateral expectation of willingness to adapt to changing circumstances. Information

exchange defines the expectation that partners will proactively provide useful information to each other. Solidarity is defined by the expectation that high value is placed on the

relationship (Heide and John, 1992).

The assumed moderating impact of relational norms on the relationship between PACAP (knowledge acquisition and assimilation) and explorative learning performance, as well as RACAP (knowledge transformation and acquisition) and exploitative learning performance does not seem to be supported for the buyer and supplier database either.

Findings of Berger (2015) reveal that relational norms show positive direct effect on both ACAP dimensions, from the perspective of both partners. Therefore, even though relational norms do serve as attributes that aid knowledge acquisition, assimilation, transformation and exploitation, this study has shown that relational norms do not seem to facilitate between absorptive capacity and learning performances. Hence, these norms that are based on the expectation from both sides that the general goal is the wellbeing of the relationship can directly affect organizational routines and process that produce dynamic organizational capabilities. But, do not seem to moderate between these capabilities and the learning performances of the firm.

(29)

31 | P a g e

8. Managerial implications

This study aimed to further advance the understanding of aspects that drive the innovative performance of a firm. Relevant issue in inter-firm relations because as defined by Dyer and Singh (1998), a pair or network of firms have the ability to develop relationships that will lead to superior competitive advantage and innovative performance.

Innovative performance, as previously discussed, in this study is defined by the two learning performances. Regarding which, the simultaneous fostering of both, showed to be crucial in order to enhance long term competitiveness (Berger, 2015). The focus was on investigating two aspects: whether the years that buyers and suppliers spend collaborating together affects the innovative performance of a firm (1), whether relational norms (defined by flexibility, information exchange and solidarity) affect the innovative performance of a firm. Hence, this study found it important to offer further insights on these underlying dimensions.

The results are threefold and can support managers to reach higher performance via their inter-firm relations. The three implications are further defined below.

First of all, the results have clearly indicated that PACAP and RACAP do have a significant and direct positive effect on the learning performances, from both the buyers and suppliers point of view. Hence, in line with previous literature, it does validate the notion that it is relevant for managers to invest in dimensions that define absorptive capacity in order to develop superior learning capabilities that will also facilitate innovation.

Furthermore, the second implication of this study demonstrates that the effect that the length of the relationship has on the learning performances is only relevant from the buyer’s

perspective. This is not supported from the supplier’s point of view. Proving managers that from the buyer’s perspective it is worthy investing in a lengthier relationship with the suppliers in order to reach innovative performance. Whereas, from the suppliers perspective the time they have spent working together with the buyer does not seem to have a positive effect on their innovativeness. This insight can be valuable for managers of buyer firms, whom should realize that even thought for them the time they have spent working together with their supplier is relevant and might involve more confidence in sharing certain

information, the situation might not be the same from the perspective of their partners.

As for the third implication, regarding relational norms, the results have shown that it does not seems to be a relevant aspect in moderating the effect that absorptive capacity has on the learning performances from neither the buyer and suppliers perspective. Hence, relational norms, defined by flexibility, information exchange and solidarity, do not have a moderating effect between the buyer or supplier’s absorptive capacity and innovative performance. It is an important insight for manager from both sides of the dyad, since it shows that even though relational norms positively impacts their absorptive capacity (Berger, 2015). It does not act as a moderator between absorptive capacity and learning performance, hence has no further effect on their firms innovative performance. Demonstrating that buyers, nor suppliers

(30)

32 | P a g e

Lastly, even though previous research has shown that the perception of buyers and suppliers tends to differ, many scholars only focused on one point of view and not both (Amber et al., 2010; Oosterhuis et al.,2013). Therefore, this study, since it is based on data collected by Berger (2015) from both sides of the dyad, allows to add to current literature by highlighting the effect that the previously discussed moderators have on the learning performances, from both the supplier and buyers view. This allowed to research discrepancies. Particularly when discussing the effect of the buyer-supplier relationship duration, which only showed

significant effect on a firms innovative performance from the buyers standing point.

9. Limitations and future research

As closure for present study there are a few limitations that need to be mentioned which hope to offer ideas well worth of future research.

First, the research was done based on respondents from specific industries. Automotive, machinery, chemical, pharmaceutical, semiconductor and electronics. Hence the results are limited to the technological, more process oriented branch that allows little space for out of the box thinking, especially with service industries excluded, it can be said that the results are quite difficult to be generalized for other firms from different industries, especially for more “customer experience” oriented ones. Therefore, it would an interesting area of research to expand to more industries and to investigate if similar patterns can be found regarding dimensions that can affect buyer-supplier relationship performance.

Second, the buyer respondents were all located in the Netherlands, whereas the supplier respondents all over the world. This restricts the results and conclusions in such a way that there is always a Dutch buyer firm involved. Hence the results might be biased because it does not fully account for cultural differences that could have a significant impact. Which might be the reason why relational norms, from the buyer’s perspective does not seem to have a moderating effect between the relationships of ACAP and the learning performances.

Concluding that this result is very specific to buyers located in the Netherlands. Furthermore, it is recommended to expand the area of study to multiple countries, hence offering the ability to count for different cultural backgrounds and not just from the Dutch buyer’s perspective. As known, learning performances do play an important role in this study, since innovative performance is defined by it. Still, learning intent, which refers to the partner’s ability to view collaboration as an opportunity to learn from the other’s knowledge and skills (Hamel, 1991) is not accounted for. This could be an interesting factor to account for, especially in industries where more technological skills are required and where firms could provide and access complementary skills (Hamel, 1991). Hence, even though learning intent is not included in the scope of this study, it could be an interesting area that might have influence on the learning performance, of both suppliers and buyers.

Inter-firm absorptive capacity