Social Capital as the lubricant in Knowledge Transfer; Managing Innovation in the Food Industry

Master thesis E.A. Boot February 18th, 2010

Social Capital as the lubricant in Knowledge

Transfer; Managing Innovation in the Food

Industry

ABSTRACT

Social Capital as the lubricant in Knowledge

Transfer; Managing Innovation in the Food

Industry

Author: Eline Boot

e.a.boot@student.rug.nl s1383930

Supervisors: drs. R.W. de Vries Prof. dr. S. Beugelsdijk

Paper: Master thesis

Program: Msc International Business & Management Faculty of Economics and Business

University of Groningen

TABLE OF CONTENTS

IMPLICATIONS & LIMITATIONS ... 38

REFERENCES ... 40

PREFACE

Finally, my master thesis is finished. As the crown on my study it took me a long way to graduate. After a year with a lot of other interesting other activities, I enjoyed the freedom of writing a thesis. Yet I managed to finish it on time and am finally able to move on to the next phase; a Corporate Management Traineeship at the Rabobank.

I would like to thank all the respondents of the firms, who were so kind to collaborate with my research and reserved some time for my interviews. Furthermore, I would like to thank my supervisor from the ABN AMRO, Niels Dijkman, as well as my supervisors from the university, Rudi de Vries and Sjoerd Beugelsdijk, for their guidance and useful feedback on my thesis. And of course I would like to thank my parents who were very patient with me on finishing my thesis.

Enjoy reading!

INTRODUCTION

For the Dutch food industry to remain competitive in the long run, a switch to a more sustainable food industry is required. In order to achieve this, the Dutch food sector has to increase its innovative performance by creating new products and services.

One widely recognized way to innovate is through collaborating. Surprisingly, however, alliance partners in the food industry are not considered an important source for innovation (Batterink et al, 2006). A recent insight of value chain ambidexterity (Verwaal et al, 2009) is about to change that consideration. Value chain ambidexterity is based on collaboration between firms in a value chain, who specialise or in explorative innovation (innovation; developing new products/processes) or in exploitative innovation (efficiency; enhancing existing competitive advantages). Combining both types of innovation through collaboration leads to the utilisation of the full innovation potential within the value chain. In order to enhance the innovation in the food industry and turn the tide, there is a need for an ambidextrous value chain in the food industry and a need to manage this properly.

Managing ambidexterity in the value chain is complex, understanding the way to manage this ambidexterity asks for a consideration about the way knowledge flows across companies to create innovation, since knowledge transfer is the most important aspect of creating innovation together. Considering the fact that collaboration between firms with different backgrounds and specialties create high barriers for transferring knowledge, the social context comes into play. Due to these barriers between firms, social capital (e.g. trust) becomes more important to facilitate the knowledge transfer and the collaboration between firms. In this context social capital has not been investigated before. Therefore there is a need to understand and optimize the social capital in order to facilitate knowledge transfer in the context of innovation performance in an ambidextrous value chain.

“How should social capital be managed in an ambidextrous value chain, in order to optimize knowledge transfer and enhance innovation performance between firms?”

This research paper delineates the role of social capital in facilitating knowledge flow between firms and further contributes to emerging literature by demonstrating the process of social capital development in collaborations between different type of firms and its impact on innovation performance.

LITERATURE REVIEW

In the upcoming subsections I will introduce the line of reasoning that fits with my research as a funnel method by going deeper into the relationship between alliances and innovation performance; from the need for innovation performance in the food industry, to the need for ambidexterity in the value chain, to the need of management understanding. The way to manage ambidexterity in the value chain, thus the way to overcome barriers for knowledge transfer, is identified by social capital. This leads to a proposed classification per type of alliance linked with social capital structure which leads to optimal knowledge transfer and innovation performance.

The Dutch food industry

Traditionally, the Netherlands is known for a strong competitive food and beverages industry (hereafter called food industry). In order to achieve competitive advantages, the focus of the food industry has been on increasing the production capacity and on continuous cost reduction in the 20th century. However, “after many decades of success, this has led to commoditization, an increased environmental burden and encroachment on public spaces” (Vanhaverbeke, 2007: 3). At the same time, the Dutch food industry is faced with significant challenges that undermine its competitive position. The fast development of technologies in food processing, the rapidly changing markets, the high power of the retail industry, combined with increased global competition due to relieve of EU‟s protection measures and changing customer demands, imply that a firm‟s focus on production capacity and cost reduction can only generate a temporary competitive advantage (Vanhaverbeke, 2007). To remain competitive in the long run, a switch to a more sustainable food industry is required. In order to achieve this, the Dutch food sector has to increase its innovative performance by creating new products and services

(Vanhaverbeke, 2007).

Innovation through alliances; need for ambidexterity in the value chain

emerge (Nooteboom, 2004). Therefore, a combination of diverse parts of knowledge creates new technology (Nelson and Winter, 1982). In this interest, alliances between firms have become increasingly important (Contractor & Lorange, 2002). Alliances with other firms are often recommended as the means to acquire new knowledge, skills, and expertise to enhance the competency of an organization (Hamel, 1991). Sharing knowledge is crucial for the development of new knowledge and joining forces with a complementary partner firms may offer substantial future benefits. Despite their advantages, alliances may also introduce the risk of a firm losing its critical capabilities or skills to a partner without receiving any benefits in return. The knowledge shared is often highly confidential and is key for competitive advantage. Often alliances fail due to mismanagement of these risks of spill over (Nooteboom, 2007). Especially alliances between Multi-National Corporation‟s (MNCs) and Small and Medium Enterprise‟s (SMEs), are a challenge to manage. As O‟Dwyer (2005) states, alliances between different sized firms tend to have an asymmetrical relationship, which determines the nature of the knowledge exchange, as well as the power balance. However, the success of the alliance is not solely dependent on the MNC alone, since the relationship between a MNC and a SME is based on a complex interdependency benefiting both parties (O‟Dwyer, 2005). Consequently, innovation merely requires a combination of knowledge of products, markets and technologies that most companies do not have themselves. Therefore they need to cooperate with complementary partner firms and overcome the risks of spill over. Hence, the management of any alliance is a challenge that needs to balance between realizing benefits together and safeguarding risks (Nooteboom, 2007) as well as accessing novelty and efficient incorporation of the knowledge into an innovation (Vanhaverbeke, 2007).

Deepening out the concept of innovation, the task to manage R&D alliances to access new knowledge and efficient incorporation of knowledge is relevant for both explorative innovation and exploitative innovation, as stated by March (1991). Innovation can be classified by the typology of March (1991), who identified exploitation and exploration. Exploitative innovation relates to enhancing existing products and processes, i.e. refinement, implementation, efficiency, production and selection. Explorative innovation refers to the development of new products and processes, i.e. search, discovery, experimentation and risk taking (Cheng and Van

de Ven 1996, March 1991).

and Szulanski, 2001), organization theory (e.g., Burns and Stalker, 1961, Holmqvist 2004, Van

den Bosch et al. 1999), and managerial economics (e.g., Ghemawat and Ricart i Costa, 1993).

These studies revealed that exploration and exploitation require considerable differences in structures, processes, strategies, capabilities, and cultures. The differences also show that exploration firms have larger performance variation by experiencing substantial success as well as failure, while exploitative firms are likely to generate more stable performance (March,

1991). Concluding, the distinction between “exploration of new possibilities” and “exploitation

of old certainties”, as March (1991) calls it, relate to fundamental differences for a firm.

In order to maximize the innovation potential of a firm, both types of innovation should be combined. The need for an appropriate balance between exploration and exploitation has been crystallized by Tushman and O‟Reilly‟s (1996) conceptualization of the ambidextrous organization and relates to internal innovation. To find the balance, it requires a different type of management approach, which according to March (1991) creates tension within a company and is complex to manage. This internal tension is often at the expense of the explorative activities, which makes a company unable to develop new products and processes to the fullest.

If reaching for internal innovation within a firm is not possible, firms should focus on external innovation and collaborate with complementary partners in the value chain. Benefits from both types of innovation could be maximized by balancing their innovative capabilities. Thus, other than the ambidextrous organization, established explorative organizations who want to benefit from both types of innovation, can find partnerships with exploitative organizations complementing their explorative core competencies (Castiaux, 2007), and share knowledge about exploitative and explorative innovation. Broadening this theoretical perspective of ambidexterity, Verwaal (2009) came up with the concept of ambidexterity in the value chain of the food industry. To maximize innovation potential in the food industry, Verwaal (2009)

states that a single firm should specialize on exploitative or explorative activities and

collaborate with other firms in order to combine both types of innovation. The discrepancy

exploitative, efficiency focused activities. Thus these alliances do not yet utilize the full innovation potential of collaboration within the value chain. Value chain ambidexterity advocates a completely different mindset to be able to see customers and competitors as partners in alliances, since sharing knowledge must be done across the border of the firm and towards a different type of firm. This increased complexity for managing an alliance requires more specific management attention, to be able to utilize the full innovation potential. Therefore there is a need for an ambidextrous value chain in the food industry and a need to manage this properly.

Understanding the complexity of the management of the ambidextrous value chain

So what makes alliances between exploiters and explorers more interesting than normal alliance formations? In general, the greater the degree of diversity between firms, the more difficult it becomes to understand each other and the more difficult it becomes to exchange knowledge and combine it (Miller et al., 2007; Sampson, 2007). Considering the fact that exchange of knowledge is an important determinant for innovation performance, this diversity is on the one hand necessary, yet highly complicated since exploiters and explorers are opposites in approximately all characteristics of a firm.

Looking at the differences in characteristics, exploration is associated with organic structures, loosely coupled systems, path breaking, improvisation, autonomy and chaos, and emerging markets and technologies. Exploitation is associated with mechanistic structures, tightly coupled systems, path dependence, routinization, control and bureaucracy and stable markets and technologies (Ancone et al. 2001, Brown and Eisenhardt 1998, Lewin et al. 1999). The tension March (1991) described seems therefore logical, since the key characteristics are almost opposites.

Explorer versus Exploiter

Organic structure Mechanistic structure

Loosely coupled systems Tightly coupled systems

Path breaking Path dependence

Improvisation Routinization

Autonomy Bureaucracy

Chaos Control

Emerging Stable

Figure 1 Differences in characteristics between explorer and exploiter (Ancone et al. 2001, Brown and Eisenhardt 1998, Lewin et al. 1999)

Solving the tension between alliance partners asks for effective management. Especially the differences in management style, culture and expertise seem to be most distant and need management attention. While differences in expertise reinforce the innovative performance due to complementary knowledge, the differences in management style and culture lead to extra complexity which makes collaboration more difficult (March, 1991). This could even block the complementary benefits the alliance offers. One should not try to solve the differences, but bear in mind and accept the differences in characteristics. The focus should be on efficient management of knowledge as a mutual goal for creating core competencies in the firm (

Bou-Llusare, 2006). “Success does not necessarily count for firms that know the most, but to the

firms that can make the best use of what they know” (Bierly et al., 2000, p596).

Consequently, understanding the way to manage this ambidexterity asks for a consideration about the way knowledge flows across firms to share knowledge in order to create innovation together, by overcoming differences to focus on their common purpose. Knowledge transfer is crucial in creating innovation through collaboration and should therefore be the most important focus of ambidexterity management.

Investigating knowledge transfer and its relation with social capital

Teng, 2003; Mowery et al, 1996; Pérez-Nordtvedt et al, 2008; Sammarra and Bigiero, 2008;

Becerra et al, 2008; Easterby-Smith et al, 2008; Bhagat et al, 2002). Garud and Nayyar (1994)

propose three dimensions of knowledge; simple versus complex, which emphasizes the ease of knowledge transfer, explicit versus tacit knowledge concerns how well articulated the knowledge is, and the third dimension of knowledge deals with the independent versus systemic character of knowledge, regarding the extent to which the knowledge is embedded in the organizational context. In this research the focus is on the explicit versus tacit dimension of knowledge, since tacit knowledge plays a paramount role in the innovation process, and tacit knowledge is often the source of innovation and competitive advantage (e.g. Cohen, 1989).

Next to defining types of knowledge to be examined, there are other antecedents that influence knowledge transfer. Kogut and Zander (1992: 387) see codifiability as crucial in transferring knowledge, which “refers to the ability of the firm to structure knowledge into a set of identifiable rules and relationships that can be easily communicated”. Communication therefore plays a vital role in the transfer, Mu (2008) argues that tacit and explicit knowledge is enforced by face-to-face knowledge and explicit knowledge can also be transferred by indirect contact. Therefore the next antecedent to be defined in knowledge transfer is type and frequency of communication.

Furthermore, there are differences in symmetry of sharing knowledge between firms in an ambidextrous value chain environment as well as information completeness, as argued by the sender-receiver model of knowledge (Lin, 2005), to have impact on knowledge transfer between explorers and exploiters. For example explorative innovation firms could share more new, competitive and vulnerable knowledge. While in contrast, exploitative innovation firms could have much less new vulnerable information on innovation, which makes it less sensitive to share. Furthermore, as stated before, alliances between a MNC and a SME are mostly characterized by asymmetrical relationships, which also affect the symmetry of knowledge exchange, given that the MNC then appears to be the dominant knowledge supplier (O‟Dwyer,

2005). The size of collaborating firms also has in impact on knowledge flow. For this reason it

Summarizing, knowledge transfer is mainly affected by the type of knowledge shared, the kind of communication tools and communication frequency between partners, the codifiability of shared knowledge, the information completeness and symmetry.

Managing these antecedents to maximize knowledge transfer can be done by managing the relationship and the way partners interact; thus managing social capital. Social capital

facilitates relationships in order to share knowledge and refers to a variety of features in the

social structure (e.g. Jacobs, 1961; Coleman, 1990; Burt, 1992; Baker, 1990). Nahapiet and

Ghoshal (1997) identified three dimensions of social capital: relational, structural and cognitive

social capital. In their study, they justified how attributes of each of these dimensions facilitate the combination and exchange of resources within firms. The relational dimension refers to trust, trustworthiness and commitment. These factors are important for all networking partners, since they share (sometimes undisclosed) information across firms. When actors do not trust each other, knowledge will not be transferred as efficiently as wished. The structural dimension of social capital refers to the type of alliance, the diversity and number of alliances in a firm‟s network, but also the social interaction, e.g. the organization of activities. Last but not least, the last dimension of social capital is the cognitive dimension, which is about the mindset the firms have, e.g. the vision of the alliance, and a firms own background of expertise.

Therefore there is a need to understand and optimize the social capital in order to facilitate knowledge transfer in the context of innovation. Hence, when knowledge is transferred optimally in an inter-firm environment, the combined innovation efforts lead to better innovation for the whole value chain. As a result it will lead to an ambidextrous value chain.

Thus, summarizing the line of reasoning; collaborating in the value chain leads to optimal explorative and exploitative innovation, only if the social capital is structured in a way that knowledge is transferred most optimally. Social capital seems to have a central role in this process. Indeed, this seems to put forth a view of social capital being the lubricant in the engine of value chain ambidexterity. Building the engine from a clever blueprint (the alliance contract) is not enough; it must be operated with the right amount of lubricant/ maintenance (managing social capital and knowledge transfer), to make the engine run satisfactory (explorative and exploitative innovation in the value chain).

Coming to the focus of my research, in this paper I aim to contribute to existing literature by investigating the role of social capital in the management of the ambidextrous value chain. In doing so, the research confines itself to (international) R&D alliances in the food industry between MNCs and SMEs. Therefore I propose a research into the question:

“How should social capital be managed in an ambidextrous value chain, in order to optimize knowledge transfer and enhance innovation performance between firms?”

This research paper delineates the role of social capital in facilitating knowledge flow between firms and further contributes to emerging literature by demonstrating the process of social capital development in collaborations between different type of firms and its impact on innovation performance.

Therefore I propose that, next to the differences between explorers and exploiters, the size of the collaborating firms could also lead to differences in the way social capital should be managed. Thus, I question how social capital is structured for each combination specifically.

My line of reasoning and the moderation of the type of firm are shown in figure 2, in my conceptual model.

Figure 2 Conceptual model

METHODOLOGY

Type of research

The conceptual model discussed above is the basic line of reasoning in this study, which is reflected by my type of research; a multiple case study. Building theory from case studies is a research strategy that involves using one or more cases to create and test theoretical constructs from case-based, empirical evidence (Eisenhardt, 1989). In this research, the main concepts dealt with are difficult ones to measure in quantitative way. Social capital, knowledge transfer and its relation to innovation are examples of soft variables and key relationships that need deeper understanding through qualitative research. As Yin (1994) argues, qualitative studies facilitate a deeper understanding of these variables and are particularly useful for discovering and mapping non-formal business practises. When researching in a qualitative way, there is room for interpretation and meaning that would have been suppressed in quantitative research, but is key to the understanding of knowledge transfer and the management of social capital.

The main argument is to use cases as the basis from which to develop theory inductively. “The theory is emergent in the sense that it is situated in and developed by recognizing patterns of relationships among constructs within and across cases and their underlying logical arguments”

(Eisenhardt, 2007, p 25). Inductive case studies are especially suitable for studying complex

social phenomena (Yin, 1994), like social capital and the process of knowledge transfer. Furthermore, inductive studies are known as one of the best bridges from new rich qualitative evidence to mainstream deductive research possibilities (Yin, 1994), in order to ground the (inductively founded) theory more thoroughly in the mainstream literature. However, this is the next step, this research is confined as an inductive case study.

Method of data collection

definitions and measurements, and relationships among constructs to emerge from the process rather than being specified at the outset” (Eisenhardt, 1989 in Mu, 2008: 89).

However, in-depth interviews can become subject of interviewer bias, which relates to the possibility of subjective interpretation of answers as well as the possibility of posing leading questions in order to lead answers into the favoured direction. Even though Straus and Corbin

(1998, 97) emphasize “that it is not possible to be completely free of bias”, my efforts will try

to limit this possible bias. My key approach entails raising multiple questions about one (sub) concept, to rule out the possibility of subjective interpretation of answers. Furthermore, by using numerous and well-informed interviewees with diverse perspectives, the bias of leading questions is minimized.

These interviewees were selected by narrowing down from industry, firm and function criteria levels. Firms were selected based on four criteria. As stated in the literature review, first, I am particularly interested in the food and beverages industry. Second, the firm must be actively involved in alliances with Research & Development (R&D) as the main alliance goal, including one alliance with an international partner, i.e. a firm that derives revenue from operations outside of its home country. Third, the firms must have been founded more than one year prior to the start of the study in February 2009. Firms that are less than one year old are excluded because these firms have not existed long enough to accumulate significant social capital; moreover, learning and innovation, key sources of social capital, generally occur over long periods of time (Mu, 2008). Last of all, I select interviewees from Multi-National Companies (MNC) with a turnover of €50-500 million and Small and Medium Enterprises (SME) with a turnover less than €50 million, according to classification levels of the ABN AMRO at the time I did my internship in 2009.

be made and are shown in figure 3. These classifications were checked with the respondents in each interview.

Cases Exploiter Explorer

1 MNC(A) MNC(B)

2 MNC(C) SME (D)

3 SME(E) SME(F)

4 SME(G) MNC(H)

Figure 3: R&D alliance cases

Finding the key informants within the firms is key in the approach for accurate assessment

(John and Weitz, 1988), therefore managers were selected who were directly responsible for

managing the relationship with their R&D partners. Interviewed managers mainly held the positions of General Manager, Chief R&D Manager, Business Unit Director or Technology Development Manager, which made them well-positioned to provide relevant information. Although this approach could lead to possible errors due to position bias, the research outcomes of Huber and Power (1985) lend support to the method of using single key informants. With the help of managers in the Dutch food industry as well as some scientific experts in the field, I was able to conduct interviews with 8 managers from 8 selected companies.

Each interview lasted about 60 to 90 minutes. In the interviews, subjects were asked a series of closed questions to double check premises, and then followed by open-ended questions in which the respondents were asked to refer to the experiences with R&D alliances. This procedure allowed the respondents to deliberate upon the issues and ask for clarifications from the interviewer to ensure a better understanding of the study. Furthermore, consistency in the answers is monitored by summarizing questions repeatedly and also by minimizing interview bias as discussed before.

Measurement of concepts

(„face validity‟). The main constructs innovation performance, knowledge transfer and social capital shall be further determined into specific items as identified in the literature review.

By distinguishing the firms into explorer versus exploiter characteristics, I follow Cheng and

Van de Ven (1996) and March (1991) in their definition of the concepts, as stated in the

literature review. An explorer can be identified as a company that emphasizes on explorative innovation and an exploiter focuses on exploitative innovation. By analyzing company websites and annual reports1, the firms are labeled into the categories, which were checked with the interviewees. They were asked to scale their company in the explorer exploiter category, in the dimensions of culture (creative, informal versus process, formal) and management style dimension (cooperative and loosely coupled systems, versus hierarchical and controlling).

I focus on innovation performance in terms of relational satisfaction of the R&D alliance. Measuring performance in terms of objective, financial indicators is difficult because the period of payoffs and the underlying goals may vary (Olk, 2002), and outcomes tend to be hidden in the future and are difficult to determine. Following De Jong (2008), I therefore focus not so much on ultimate outcomes of R&D alliances, but on the perceived satisfaction of the relationship that is indicative of positive future outcomes.

Following the definition of knowledge transfer in the literature review, knowledge transfer is measured by four items; type of knowledge (tacit or explicit), kind of communication activities and frequency of communication, codifiability, information completeness and information symmetry.

As argued in the literature review, social capital refers to a relational, structural and cognitive dimension, following Nahapiet and Ghoshal (1997). The relational dimension consists of three items, namely trust, trustworthiness and commitment. The structural dimension is measured in four items, i.e. type of alliance, diversity and number of partners and social interaction, while the cognitive dimension is measured in two items; vision of the alliance and expertise background.

1

A summary of the antecedent per construct can be found in figure 4.

Constructs Antecedents

Innovation performance Satisfaction of the alliance Priority of the alliance

Importance of the alliance for competitive advantage

Knowledge transfer Type of knowledge (explicit or tacit)

Communication (kind of activity & frequency) Codifiability

Information completeness Information symmetry

Social capital Trust

Trustworthiness Commitment Type of alliance

Diversity and number of partners in network Social interaction (activities)

Vision of the alliance Expertise background Figure 4 Concepts and antecedents

A list of explicit questions determining the concepts can be found in the appendix, part I.

Data analysis

Data analysis followed procedures recommended by Strauss and Corbin (1998). Elaborating the four cases will result in making theoretical comparisons between them. Striking differences, similarities or interrelatedness between the cases will emerge from specific to more general, in order to develop theory. Theory development follows suggestions by Eisenhardt (1989) and

Yin (1994), who emphasize the importance of having qualitative study research process

RESULTS

In this section the four cases will be analyzed. The first case encounters an alliance between two MNCs, an exploiter MNC (A) in consumer goods and an explorer MNC (B) in chemicals and nutrition. Case 2 involves an exploiter MNC (C) in consumer goods collaborating with a SME explorer (D), a laboratory firm. Case 3 involves cooperation between two SMEs, an exploiter vegetable firm (E) and an explorer agrifood research firm (F). Furthermore, case 4 entails an exploiter SME (G) in meat processing, in an alliance with an explorer MNC (H), in chemicals and nutrition research.

Case 1 – Two MNCs excelling together on innovation

The firms in this case are both MNCs and are no direct competitors of each other; they complement each other in an ongoing alliance focused on R&D. Firm A is active in the consumer goods industry and firm B is specialized in nutrition and chemicals. Combined they focus on innovative food ingredients.

For a start, both companies agree with the categorization of exploiter (A) respectively explorer (B), and found significant differences in management style. While the explorer firm B rates its management style as cooperative and loosely coupled systems, the exploitative firm A rates its management style far more hierarchical and controlling. Differences in culture were moderate, since both companies described their cultures as informal yet sometimes formal, as well as creative but sometimes strictly following processes.

Innovation

missed”. On the other hand, the explorer is dependent on the exploiter firm, because “the only way to get our products to the consumer market is through our partner firm”. Both firms rate a high satisfaction of the alliance of 8.5 points out of 10, since “the innovation outcomes of our alliance mostly have been very fruitful” according to firm B.

Knowledge transfer

Going deeper into this alliance, the managers in this case communicate on a daily basis over the phone and organize weekly meetings. “Meeting face-to-face is the most efficient way of knowledge transfer and enhances the relationship, that‟s why we do it on a weekly basis” as stated by firm A. In the communication mostly explicit knowledge is shared, for example market research reports and technical feasibility studies. However, due to regular brainstorming in the weekly meetings, relationships develop and some tacit knowledge is shared too. As firm B states: “We organize workshops for the alliance team, in this manner we get to know each other better. (…) This revolves in a smoother collaboration and at times we only need to say a few words to understand”. No codification is necessary in this manner. Furthermore, this clear understanding of the relationship is also reflected by the way the firms perceive information completeness and symmetry in knowledge flow. “Firm A discusses the need for a new application or alternation in an ingredient, and we look how it is technically possible, this is a clear understanding and to my concern our knowledge shared is evenly distributed”, as said by the manager of firm B.

Social capital

As the relationships between the companies develop, knowledge transfer seems to be easier. Starting with the relational dimension, both firms trust each other. “Trusting the individual manager of the partner is the beginning of a fruitful alliance. You have to speak the same language and have a jointly awareness”, said the manager from firm B, “...making things bookable leads to a better understanding and this will be generated into mutual trust.” Abusing knowledge is defined in contracts, but on the other hand firm B states: “the joint relationship that has been built leaves no room for abuse”. So, even if contracts do not apply, they both believe that their partner is trustworthy since they are expected to have the best interest in the alliance. The commitment of the explorer and exploiter to the alliance is highly intertwined. Together they had their “small successes in the beginning, which resulted in more commitment

“Meeting face-to-face is the most efficient way of

knowledge transfer and enhances the relationship, that’s

Looking at the structural dimension of social capital, the diversity between the partners is apparent. Both partners have international partners. The explorer MNC B works with approximately 10 firms on R&D, of which most of them are international oriented and 50% of the partners operate within their sector, e.g. chemicals and nutrition. The exploiter MNC A works with over 100 firms on innovation, ranging from small to large firms, with an even distribution in international and national firms. Most of their innovation alliances focus on complementary capabilities, and mostly take place outside their sector. Another part of the structural dimension is the way the relationship is structured by social interaction; they set up project teams, steering committees and held quarterly evaluations. Furthermore they organize workshops every quarter year for all

employees involved in the collaboration.

Going further on social capital‟s

cognitive dimension, both respondents agreed on the vision of the alliance, and stated that having a shared vision is the most important thing in having an alliance. In this case, the vision was to create effective innovations and doing it efficiently together. Both partners emphasized on keeping in one line, though a lot of communication and organizing joint activities as described in the structural section, only to keep the vision clear and share it throughout the people working in the alliance. The main point of interest is the fact that they share the same vision, despite their differences in expertise. “Our differences in expertise reinforce our alliance, we complement our knowledge base” argues the manager of firm B.

Conclusion

The baseline of managing the alliance in this case, was focused on overcoming the cultural, managerial and expertise differences. By actively working on the relationship, firm A and B overcome these differences and collaborate at the same level of understanding. They made it possible to build a strong relationship by meeting face-to-face, organizing several teambuilding activities and work together on an equal powerbase. This case seems to follow the book and represent the „ideal‟ innovation alliance in an ambidextrous food industry. The summary of antecedents of case 1 can be found in Figure 5 below.

“Small successes in the beginning result in more commitment and being more open to each other”

Figure 5 Summary case 12

Case 2 – Overcoming differences when power balance is shifted

This collaboration involves an exploiter MNC, firm C, in consumer goods collaborating with a much smaller SME explorer (firm D), a laboratory firm. The SME explorer D is challenged to come up with an improvement for a product of the MNC C.

Also in this case, both firms agree with the categorization of explorer respectively exploiter. The exploiter MNC firm C characterized the management style and culture as more creative, informal and cooperative in comparison with the corporate culture. It must be noted that the manager based the classification on the R&D department of firm C and not the corporate culture. Firm D rates itself in the categories of explorer firms, thus both presumed categorizations were correct.

Innovation

Both companies emphasized the importance of trust, openness, a matching culture, with a shared vision with clear complementary value adding perspectives within an alliance, which should be documented in clear agreements and contracts. “At first, contracts should be waterproof and clear agreements must be made as a prerequisite, after that, openness is key to a good relationship”, as stated by firm C. As firm D complements: “Cultures should be matching in order to develop a good relationship, but the most important thing is having a shared vision

2

and focus on the main goal of the collaboration”. A discrepancy arises in the way both companies talk about the importance of the alliance for its competitive advantage as well as the priority given to the alliance. Firm C finds the alliance far less important compared to firm D, and does not share the high priority that firm D gives the alliance. This is probably due to the difference in size and the number of other R&D partners and projects they are involved in. As firm C states: “we have over 80 R&D collaborations and each alliance is important, but relatively this alliance is a little contributor to the total competitive advantage of our multinational firm.” On the other hand, firm D states to have “a strong emphasis on this project, since R&D is the core of our business and working on a project with a firm C is of great value to us.” Even though their priorities are different, both companies are evenly satisfied with the innovative performance of the alliance, by rating it 7 points out of 10.

Knowledge transfer

In creating their innovative performance together, both managers communicate in several ways. For

daily affairs they find mail and phone contact on a daily and weekly basis sufficient. However, as manager from firm D states: “to create a shared vision and to discuss progress, monthly face-to-face meetings with the responsible managers works best and also creates more team spirit.” The information the companies share is mostly explicit knowledge in terms of feasibility studies on innovative applications. As argued by firm C, “the knowledge is not always comprehensive at first, since most of the studies are very theoretical, but my device is; keep on asking questions! Most of the time this leads to a clear understanding of the knowledge and I am able to relate theory to practise.” Both partners are convinced that both partners share all the knowledge they should share: “the basics to share knowledge are being open to each other and share the relevant information”, stated firm C. In this case, the explorer firm D is not that sure about symmetry in knowledge flow; “in practise, sharing knowledge is equal in the early phase of the collaboration when we discuss the need of our partner and the expectations of our collaboration. However, when following the plan, most of the time we share our findings and results and the partner criticizes the findings, without adding new knowledge to the project.” This asymmetry in knowledge is a logical implication when you look at the nature of this collaboration. But as the manager from firm C discusses: “the symmetry of sharing knowledge is also affected by the age of the alliance”, and refers to the experience a firm has in sharing knowledge with other firms, but also the maturity and prior ties of the alliance between partners. In this case, the collaboration was a first time experience with each other, and had no

“The basics to share knowledge are being open to each other and share the relevant

prior ties together and “finds itself in the early phase of an ideal innovative alliance”, as firm C describes.

Social capital

While both partners collaborate for the first time, they are satisfied with the process of sharing knowledge, probably due to the organization of social capital. When looking at the relational dimension into trust and trustworthiness; both firms were convinced their partner would not take advantage of the partner. As the manager of firm D states: “we always start with a Confidential Agreement in the early stage of the process. If we suspected the other partner to abuse the shared knowledge, we would not get started in the first place”, even when no explicit agreements have been made. Both firms did not have a common success yet, however, “we are in the middle of the process in creating an innovative outcome” as said by firm D. They do define common success and are committed to the alliance, however the nature of the alliance results in an unequal the power balance and unequal commitment as argued in the knowledge transfer section.

The structural dimension of social capital in this case also represents differences. Firm C has more than 80 alliances on R&D, from which 90% are international partners, which operate inside and outside their sector. Firm D collaborates with 3 national firms and 1 international firm outside their sector. When looking at the social interaction of this case, both firms organise monthly face-to-face meetings in order to build the relationship, discuss work in progress and managing

a shared vision.

This shared vision of

this case is based on the long term. Both partners emphasize on sharing risks, gaining complementary knowledge and access to external knowledge. As the manager of firm C explains, “We do not innovate within a time limit and we do not ask for an explicit product as a result of an innovation process, we try to innovate without boundaries and try to look into long term future consumer needs instead of products.” Firm D: “we achieve this by making clear agreements and being open about the working processes. Since we just got started, we have to systematically talk things through in order to explore each other‟s needs and expectations.” Both partners are confident that differences in expertise stimulate the collaboration. Firm C:

“The innovative performance is dependent on the characters of responsible managers, in the early stages they should get along on a

complementary knowledge”, but adds to it that “the innovative performance is dependent on the characters of responsible managers, in the early stages they should get along on a business

and personal level”.

Conclusion

Although this is an alliance with an explorer and an exploiter, in this case firms had a different kind of relationship compared to case 1. When looking at the differences in knowledge transfer and the social capital, it is clear that the alliance is more important to explorer firm D compared to exploiter firm C. The nature of the collaboration implies an unequal power balance between the partners. This is affected by the knowledge shared, since firm D shares their findings with firm C, but does not receive more new knowledge in reverse from firm C. The summary of antecedents of case 1 can be found in Figure 6 below.

This case seems therefore different compared to the first case. Perhaps the main point of interest is the difference in maturity of the alliance. Case 1 represented a mature alliance in which partners overcome the differences and know each other very well, while case 2 displayed a young alliance with an unequal power balance. Is it true that firms with less experience in sharing knowledge will be less comfortable in equally sharing knowledge, especially when two partners work together for the first time? Is the maturity of the alliance the antecedent for an ideal organization of social capital in order to facilitate knowledge transfer?

Figure 6 Summary case 23

3

Case 3 – Entrepreneurs as fast learners

This case represents a collaboration between two SME‟s, an exploiter firm E in vegetables and an explorer firm F in agrifood research. The responsible managers for the alliance are at the same time the directors of the company.

Both firms could relate themselves as being an explorer and an exploiter. Firm E was therefore more focused on efficiency and improving existing products and processes. This focus was combined with a cooperative yet hierarchical management style. Firm E stated their culture as being informal and creative. Firm F focuses more on new products and can be identified as an explorer by the book, with an informal and creative corporate culture and a cooperative and self-steering

management style.

Innovation

The entrepreneurs think communication, a clear vision and guarding the progress and results are the most important aspects for collaboration between firms. As the manager from firm E states: “we prefer the other firm to have complementary capabilities and a refreshing vision that can align with, or extend our vision. Both firms prioritize the collaboration as „medium‟, and expect the other partner to have the same priority. Nonetheless, both firms find the knowledge shared particularly important for their innovative performance, firm F: “as being a relatively small company, we are forced to combine our strengths in order to compete with companies with enormous R&D budgets of competitors.” Furthermore, firm E states: “in this way we help each other out, and benefit from our complementary capabilities. We share risks and are now able to access new markets faster, which we could not do on our own.” Both firms are particularly satisfied about the collaboration and the innovative performance and rate the performance an 8 out of 10.

Knowledge transfer

In order to manage the innovative performance, the managers have face-to-face meetings on a monthly basis, weekly telephone contact and communicate through e-mail on a daily basis. “A combination of these communication types and frequencies works best”, as argued by firm E. The managers do not face difficulty in understanding the knowledge shared, “with product and

“As being a relatively small company, we are forced to combine our strengths in order to compete with companies with enormous R&D

explicit knowledge. As yet, the managers only share the knowledge as stated in the contract, but as the manager from firm F states: “our contract was not that tight with regard to knowledge transfer, we formulated a general goal of our collaboration; to make our product ready for the future environment. So in practice, we brainstorm about the whole subject and therefore share everything we think about that subject.” As firm E recalls: “clear added value and complementary knowledge are preconditions for working together. When a partner matches with that precondition we are bound for a good collaboration, in which both partners emphasize on equally

sharing knowledge.”

Social capital

To be able to equally share knowledge, both managers said to have far reaching trust in each other. Within the relational dimension of social capital, they are convinced the other partner would not abuse their partner‟s knowledge, but are not convinced in situations in which no explicit agreements have been made. This concern can be due to the inexperience of the companies in R&D alliances and in knowledge sharing. “When we started the alliance, sharing knowledge was a whole new experience for the both of us, since our small sized companies did not have to share so much information with another company before. We had to get used to the fact that the partner was no competitor and we would work together,” as said by firm E.” However, as firm F adds: “trust was quickly established, since we (both managers/directors) personally were already familiar with each other from regional networking events and our organizations appeared flexible and fast learners. Now we are both highly committed to our collaboration.”

As said, both firms did not have much experience in sharing knowledge in alliances with regard to the structural dimension of social capital. Firm E only experienced an alliance with purchasing benefits as main goal, but none with a mutual R&D goal. Firm F experience in alliances is minor; in the past they “mostly accomplished assignments for companies and did not work this closely with another company before.” In order to structure the social interaction, both managers organize personal brainstorming sessions and have no clear boundaries for where, how and when they will meet.

The alliance´s vision, conform the cognitive dimension of social capital, emphasizes on faster access to new markets and technologies, faster product launch and gaining each other‟s

Our organization learned quickly to share knowledge, (…) due to the fact that the vision of the alliance is championed throughout the

complementary knowledge. Both managers maintain the vision by regularly checking progress on goals and keep in touch on a regular basis. “As said, our organization learned to share knowledge quickly. I think that is also due to the fact that the alliance is supported by the top of the firm (i.e. both managers are also directors), therefore the vision of the alliance is championed throughout the whole company”, argued the manager of firm E. Differences between partners in expertise are present and “makes working together more difficult, but on the other hand, it leads to a good mix of expertise and eventually a more diverse collaboration”, as said by firm F.

Conclusion

This case seems to represent a different type of collaboration, in which maturity of the alliance does not seem to be the crucial factor of the ideal situation for sharing knowledge. Even though both firms did not have much experience in R&D alliances, they did manage to learn the process of sharing knowledge quickly. This can be due to the size of companies, which makes companies flexible for change, but it can also be due to the championship of the directors on the alliances vision throughout the company. These passionate directors show in this case that personal trust breeds organizational trust which enables the partner firms to rise above differences, and create an environment for sharing knowledge. The summary of antecedents of case 1 can be found in Figure 7 below.

Figure 7 Summary case 34

4

Case 4 – An alliance by the contract

The last case involves an exploiter SME, firm G, who is active in the meat production industry and an explorer MNC, firm H, who operates in chemicals and nutrition research. Together they are working on sustainable preservation solutions for meat, to enlarge consumable terms yet keeping the meat as natural as possible.

Also in this case, the firms agreed on the classification of explorer and exploiter. SME firm G rates its culture and management style in accordance with the definition of exploiter, i.e. focussed more on improving existing products, and defines its culture as formal and management style as hierarchical and controlling. MNC firm H focuses more on new products and processes, has an informal and creative corporate culture and characterizes its management style as cooperative and self-steering.

Innovation

Both respondents think the most important factors for collaboration is trust. In addition, “a partner firm should bring new insights and show flexibility to respond on requests quickly”, as stated by firm G. The alliance has medium priority for the MNC firm H, but a medium-high priority for firm G, but they think the partners have the same priority. The information shared within the alliance is particularly important for the innovation performance of both firms. As firm H states: “with our focus on research, we have to work together with firms that can implement our ideas into products, otherwise we cannot bring our knowledge to the market at all.” Nonetheless, both firms are not fully satisfied in the outcomes of the alliance, and rate the alliance both a 6 out of 10. “Unfortunately, our alliance outcomes are not that satisfactory at the moment, probably due to other important projects we both run next to this alliance, our

priorities have

shifted, which is a

loss of used

resources.”

Knowledge transfer

These shifting priorities probably affect the knowledge transfer between the partners. In this case the partners communicate by e-mail and telephone on a daily and weekly basis, which works out fine for both partners. Face-to-face meetings are rare, and were only scheduled in the early stage of the alliance, “we know what our main goal is, and we can work together from a

“Sometimes the information is not that useful for our products, and do not match the requirements we ask for. It can be difficult to facilitate a perfect fit with the research information and the specific

distance just fine” as stated by firm H. The shared knowledge mostly consists of documents sent by post or e-mail that are not hard to interpret. However, as the manager from firm G states: “sometimes the information is not that useful for our products, and do not match the requirements we ask for.” Firm G comments that “it can be difficult to facilitate a perfect fit with the research information and the specific product”. A precondition for adequate knowledge sharing for firm G is “a good collaboration with regular communication.” Nonetheless, both partners were convinced that their partner shared all the relevant information.

Social capital

The misfit in

knowledge sharing could have its basis in the social capital. Starting with the relational dimension, both firms were convinced their partner did not abuse the knowledge shared in the collaboration. “I am 100% sure that our partner strives for the best result of our alliance, since the partner is highly dependent on our knowledge” as said by the manager of firm H. The commitment was not as high as in the beginning of the collaboration, firm H: “we are committed to the alliance and we relate to our achievements as common success, but we just did not have such a success lately.”

Looking at the structural dimension, firm G works together with 5 national and 3 international companies on R&D, but some alliances involves outsourcing collaborations for joint purchasing activities. Firm H works with over 20 companies on R&D from which 80% is international. They structure their social interaction only through communicating on mail and telephone. “In the past we went together to conferences on our main topic of interest, but recently we do not meet face-to-face.”

An important factor is the shared vision, an antecedent of the cognitive dimension of social capital. The vision of the alliance is sharing risks, gaining more complementary capabilities and access to external knowledge. Both partners do not actively take care of the vision to keep the vision in line, “we stay in touch as much as possible” as argued by firm H. The differences in expertise do make working together difficult, but that is just a matter of adjusting working habits and trust in another‟s knowledge” comments firm G.

“We are committed to the alliance and we relate to our achievements as common success, but we just did not have such a

Conclusion

This case represents two firms who work together for a while, but are not satisfied with the collaboration. It seems that there is a shifted power balance and they do not understand each other‟s needs. This could be due to a lack of face-to-face meetings or due to shifting priorities combined with dependence from firm G to firm H. Maturity of the alliance is perhaps turned into an old alliance, but it could also be due to the lack of successes in their collaboration. The summary of antecedents of case 1 can be found in Figure 8 below.

Figure 8 Summary case 45

Case 1 (MNC-MNC) Case 2 (MNC-SME) Case 3 (SME-SME) Case 4 (SME-MNC

DISCUSSION

Comparing the results from the four cases, the cases can be graphically summarized in figure 9 below and these shall be shortly discussed and compared in this section.

Figure 9 Summary of results6

Case 1 seemed to represent the „ideal‟ innovation alliance in an ambidextrous food industry, by showing all high scores on the antecedents. The focus of both MNCs was on overcoming differences and actively building on a relationship. They did this with the focus on involvement of all employees, high frequency of communication and next to the long term alliance vision; they also aimed for small successes in the beginning of the alliance. This led to high social capital scores and high knowledge transfer scores. Concluding, both respondents rated the satisfaction of the alliance as 8.5 out of 10, which is the highest score of this research.

Case 2 was characterized by an unequal power balance between the MNC and SME, which can be related to the low scores on the same priority of the alliance and the symmetry in shared knowledge. Other social capital scores and knowledge transfer scores were medium-high. Both

partners aim for long term performance, but are not that satisfied with the alliance yet and rate their alliance 7 out of 10, which is much lower compared to case 1. They are not always comfortable to share knowledge due to a lack of experience in working together, thus do not trust each other unconditionally yet.

Case 3 involved two SMEs who worked together the first time, but in contrast to case 2 this did not appeared to be a barrier for generating innovative performance together. The organizations appeared flexible and quick learners and shared vision is championed by the directors. These characteristics lead to high scores on social capital and knowledge transfer, except for the diversity and number of alliances. This does not seem to be the most important thing in innovation performance, since the satisfaction is rated 8 out of 10, which is slightly less compared to case 1, which is due to the lack of success yet.

The alliance in case 4 is perceived as low-medium satisfactory, with a rating of 6 out of 10, the lowest of all. The SME and MNC have difficulty in understanding each other‟s needs and do not communicate frequently. Different priorities and lack of shared vision leads to low-medium scores on social capital and knowledge transfer. This alliance is ongoing for some years without much clear successes.

Coming back to the purpose of the research, I recall the research question:

“How should social capital be managed in an ambidextrous value chain, in order to optimize

knowledge transfer and enhance innovation performance between firms?”

Discussing the results and relating these with the research objective, I first check on the assumed relationships between innovation performance, social capital and knowledge transfer. It is obvious to see that the cases 1 and 3 are the most satisfied with the alliance. When you look at the scores on knowledge transfer and social capital of these cases, the rating of the scores on knowledge transfer and social capital should be high too, to create a satisfactory alliance. Therefore it can be concluded that the antecedents of social capital and knowledge transfer are very important for a satisfied innovation performance.

institutionalized into organizational trust. So when the responsible manager gets replaced, the other partner will still have faith in the alliance, since the organizational trust takes over. In starting alliances, a change of position could block the collaboration, since they have to start generating trust all over again.

When further examining figure 9 with the summarized results, you can see that the cases are distributed on vision of the alliances like performance satisfaction, e.g. cases with high performance scores also have high scores on vision. Furthermore, throughout the research, the respondents of all cases presumed that shared vision is the most important factor in a successful collaboration (cognitive dimension).

So how do they manage this shared vision and enable trust to grow? When looking at the alliances with the best innovative performance, they organized their social interaction in a certain way (structural dimension). It was shown in the successful cases, that face-to-face contact is key to keep partners aligned, at least on a monthly basis. Furthermore, the evolvement of all people working for the alliance appeared very important. In case 1 the managers organized workshops for everyone involved and the organized weekly brainstorming sessions. In case 3 the shared vision was actively championed throughout the partner firms by the directors of both companies. Another way of feeding the satisfaction of the alliance is generate quick small successes; this improves the relationship and builds trust.

When you look at the nature of firms of the cases 1 and 3, it is evident that the cases are collaborations between similar sizes of firms. In case 1 two MNCs work together and in case 3 two SME‟s work together. Therefore I can conclude that equal partners seem to be able to work together in the best way. Thus, the social capital and knowledge transfer are more successful organized compared to alliances that work with one MNC and one SME. This is probably due to the power balance inequalities that arise when a SME and MNC work together, as the respondents notified. Recalling the proposed moderation by type of firm in alliances (MNC and SME combinations), I can conclude that innovation performance does differ per alliance combination and social capital and knowledge transfer should be managed different.

CONCLUSION

As a result of the multiple case studies it can be concluded that innovation performance is affected by knowledge transfer and facilitated by social capital and especially trust and having a shared vision.

In addition, the maturity of the alliance plays a central role in managing social capital for optimal knowledge transfer. New alliances need time to let the alliance flourish and as the alliance matures, trust gets institutionalized and knowledge transfer is done more easily. Nonetheless, alliances between SMEs need a much shorter time span compared to other sized alliances to overcome start-up barriers, due to flexible organization and quick learning capabilities.

Furthermore, the shared knowledge is moderated by the size of the collaborating firms. It can be concluded that alliances of firms with the same size (MNC-MNC and SME-SME alliances) are more satisfied with the alliance innovation performance. Alliances of firms with different sizes appeared to suffer from power inequalities, shifting priorities and a too little

communication frequency in order to maintain a shared vision.

IMPLICATIONS & LIMITATIONS

Academic implications

Value chain ambidexterity is a new concept within the food industry, and there is a need for this industry to focus on innovation by working together with complementary partners. By examining the antecedents of innovative performance in an alliance, within value chain ambidexterity, this study contributes to the existing literature by providing a detailed overview of the way to manage an ambidextrous value chain on the level of the manager. Furthermore, this study has academic implications with regard to the maturity stages which are discovered to be present in alliances within the concept of value chain ambidexterity, and especially the finding that small SME firms evolve faster to the next maturity phase due to the fact they are flexible and fast learners. In addition to the maturity stages, it should be noted that firm size differences within alliances influences innovation performance, which makes power equality and priority to the alliance important preconditions for innovative performance, as well as a clear organised communication structure.

Implications for managers

This study provides a guide on the management of value chain ambidexterity and can help managers to manage the relationship in a way to maximize innovation potential of an alliance with a different type of firm. Overcoming differences is possible by implicating the structure of social capital, which leads to a better knowledge transfer and thus innovative performance. When managers in the food industry make the alliances work, it therefore helps the food industry to work towards an ambidextrous value chain. In the appendix part II the managerial implications are clearly presented.

Limitations

Another limitation of the research is the anonymity of the respondents, which made it more difficult to present results. The restriction of this research to take an alliance as focal construct made it difficult to even find respondents who were both willing to cooperate. This had its limitations in restricting firms and their core activities as cases, which led to choosing available cases with different innovation backgrounds. Another limitation that is related to the choice of two cooperating respondents, is the fact that respondents are likely to present an ideal situation and are not likely to talk about problems, and think about the firms image. Nonetheless, I was able to work with the limitations and able to conduct proper research.

Future research