KNOWLEDGE EXCHANGE THROUGH
SOCIAL NETWORK INTERACTION:
Effects of Gift Exchange
on Network Centrality
University of Groningen Faculty of Economics & Business Master of Business Administration
Specialization of Small Business & Entrepreneurship First supervisor: Prof. dr. Wilfred Dolfsma
Second supervisor: Dr. Clemens Lutz
“The dangers and the difficulties of the present time are great.
The troubles are not unlike those of adolescence,
rapid growth beyond the ability of organizations to manage,
uncontrollable emotion, and a desperate search for identity.
Out of adolescence, however, comes maturity.
In which physical growth with all its attendant difficulties comes to an end,
but in which growth continues.
In knowledge. In spirit. In community. And in love.
It is to this that we look forward as a human race.
This goal, once seen with our own eyes, will draw our faltering feet toward it”.
ABSTRACT
Firms operating in today’s markets are considered to be highly dependent on their ability to use knowledge and information. Exhange of knowledge between individuals leads to a higher degree of innovation success and can only be achieved through social interaction, taking place within the social network environment. As a so called cluster-organization the Energy Valley Foundation recognizes the difficulties with dealing with these processes for they bring together knowledge institutes, public sector and a wide variety of small and large organization in an attempt to develop the existing- and create new and innovative energy markets in the Northern Netherlands.
Dynamic cooperation between individuals by means of intensive knowledge exchange is said to have positive effects on generating innovation. Considering that environmental,
economical and political challenges will further push technologies and innovations to develop at an even faster rate, traditional cooperative actions between firms will no longer be able to keep up with demand for it is unable to escape the current technological trajectories. At this point, dynamicity’s will become increasingly important as industries continue to develop into more interconnected markets while sharing- and generating more expertise knowledge. In current markets, innovation reflects complex, dynamic and socially interactive processes resulting in extremely diverse innovation goals and innovation paths and traditional large firm R&D activities will eventually be unable to keep up.
The establishment of strong social relationships and social structures can be valuable for entrepreneurs operating within complex markets. The possession and intensity of these social relationships are said to facilitate new business through innovation. Additionally, individuals that engage in these of relationships and that are willing to exchange information and knowledge with others are though to achieve a positional advantage within their respective social network
allowing them to informally control or influence the information available in the market. When knowledge is considered complex, stronger social relationships will allow partners to focus less on profitability but relations are driven by intrinsic equitability which enables transparent exchange of resources underlying the core capabilities of their firms. This allows firms to take full advantage of each others expertise knowledge as trust and reputation develops over time. At this point, cooperation will become more valuable then competition and complementary
PREFACE
This thesis was written for the achievement of a master degree in Business
Administration; specialization Small Business & Entrepreneurship. The main topics of this study entail the concepts of network development and gift exchange, closely tied in with social and social-economic theory. Considering this thesis is written for finalization of a my specialization in Small Business and Entrepreneurship one should note that the heart of this text lies as close to small business oriented economic- and business theories as it does to social theory.
In my personal experience, small business development on a regional level (under pressure from economic and political uncertainty) cause market development to be highly influenced by a more socially interconnected way of working. In addition to popular
communication channels as Facebook or Linked-In, social oriented tools have been developed to capture social processes and working relationships that can be used to actively support
development of stronger working relationships. These methods potentially allow groups of small business owners to take full advantage of the existing uncertainties and eliminate traditional SME barriers caused by e.g. small economies of scale and scope.
The integration of SME oriented business theory with perspectives on network development and knowledge exchange introduces a perspective characterized by an almost innate sense of interconnectedness and social responsibility. In a world where we are becoming increasingly aware of purely consumptive and wastefull action, real growth can perhaps be seen as increased interconnectedness controlled through social relations rather then formal or hierarchical measures. In this situation, social perspectives will prove fundamental to business development and SME’s can utilize their inherent capabilities to define business development more in line with todays shifting paradigm ”…but in which growth continues. In knowledge. In spirit. In community” (Boulding, 1973). On a very modest level, I have enjoyed my efforts in contributing to combining these different perspectives and look forward to recognizing them in practice in my further professional career.
put my methodology into practice and test my insights with experts inside and outside the Energy Valley organization.
Secondly, I would like to thank my first supervisor Prof. dr. Wilfred Dolfsma for his time and effort in helping me develop and finish my work. His research papers and articles prove to be my most valuable resources in coming to grasp with the theory and defining my own research model.
Thirdly, thanks goes out to my second supervisor dr. Clemens Lutz. For introducing me to highly stimulating insights about small business and small business development, and for his flexibility and support in allowing me to finish this thesis.
CONTENT
1. INTRODUCTION ... 10 1.1 Research objectives ... 12 1.2 Research questions ... 14 1.2.1 Problem statement ... 14 1.2.2 Sub-questions ... 141.3 Conditions and limitations ... 15
1.4 Report outline... 16
2. CONTEXT ... 18
2.1 The Energy Valley Platform ... 19
2.2 Knowledge in the energy sector ... 21
2.3 Cooperation in the energy sector ... 22
2.4 Innovation in the energy sector ... 23
2.4.1 Innovation processes and performance ... 27
2.5 Conclusion ... 29 3. THEORETICAL BACKGROUND ... 31 3.1 Social networks ... 33 3.1.1 Characteristics of networks ... 34 3.1.2 Centrality... 35 3.2 Knowledge transfer ... 38 3.3 Gift exchange ... 40
3.3.1 Gifts and gift exchange ... 40
3.3.2 Gift giving incidence... 42
3.3.3 Gift giving occurrence ... 43
3.3.4 Gift giving prerequisites ... 43
3.3.5 Perceived generosity in gift exchange ... 45
3.3.6 Gift exchange through reciprocity ... 46
3.3.7 The effects of gift exchange on network structure... 48
3.4 Knowledge complexity ... 51
3.4.2 Knowledge intensive entrepreneurship ... 52
3.4.3 Knowledge as a competitive advantage ... 54
3.4.4 The effects of knowledge intensity on cooperation ... 55
3.4.5 The effects of knowledge intensity on innovation ... 56
3.4.6 The effects of knowledge complexity on knowledge transfer ... 59
3.5 Social Ties ... 61
3.5.1 Tie strength ... 62
3.5.2 The effects of tie strength on knowledge transfer ... 67
4. METHODOLOGY ... 69
4.1 Social network analysis... 69
4.1.1 Level of analysis ... 70 4.1.2 Centrality... 71 4.1.3 Name generator ... 74 4.2 Measurement ... 77 4.2.1 Independent variable ... 77 4.2.2 Dependent variable ... 78 4.2.3 Moderating variables ... 79
4.2.4 Extraneous / control / attribute variables ... 84
4.3 Instrument ... 88
4.3.1 Codebook of variables ... 88
4.4 Data ... 91
5. ANALYSIS & RESULTS ... 92
5.1 Analyses process ... 92
5.3 Results ... 93
6. CONCLUSIONS... 97
6.1 Interpretation of analysis results ... 97
6.2 Resolving the problem statement and sub-questions ... 97
6.2.1 Gift Exchange and Network Centrality... 97
6.2.2 Moderating effect of Knowledge Complexity ... 98
6.3.1 Monitor and communicate ... 100
6.3.2 Develop power strategies based on social embeddedness ... 101
6.3.3 Start mapping knowledge and add to SNA insights ... 103
6.4 Recommendations for further research ... 106
6.4.1 Collaboration and governance ... 106
6.4.2 Knowledge sharing and sustainability of competitive advatages ... 106
6.4.3 Innovation in social network environments (and SME’s) ... 107
APPENDIX I: Members Energy Valley Platform ... 109
APPENDIX II: Invitation email... 110
APPENDIX III: Centrality Measures ... 112
BIBLIOGRAPHY ... 113
Articles ... 113
Books ... 123
1. INTRODUCTION
Firms operating in today’s markets are considered to be highly dependent on their ability to use knowledge and information. In fact, knowledge development and application plays such an important role that is has become a central issue in developing a competitive advantage and secure long-term survival in an increasingly competitive environment (Kogut & Zanders, 1992; Nahapiet & Goshal, 1998). Firms aim to achieve high innovation success rates, high return on innovation investments and are thereby pushed to understand the process of knowledge creation and application. It is important to recognize that innovation in the business environment may come in many different forms but is mainly driven by individuals inside the organization that carry, develop and diffuse it (Nonaka, 1994).
The main driver behind this report is the assumption that he transfer (exchange) of knowledge leads to a higher degree of innovation success for it allows new combinations of existing knowledge, and enables existing knowledge to develop (Granovetter, 1973; Kogut & Zanders, 1992). In addition, we assume that effective and efficient knowledge exchange can only be achieved through intensive social interaction. “As knowledge may be dispersed across different parties within and outside the organization, knowledge exchange underpins knowledge creation and results in technological progress”. (Van der Eijk, 2009; 16). Van der Eijk describes a process that has been widely recognized to be of increasing strategic importance. The
transference of knowledge into new economic activity is known in policy as the process of “knowledge valorization” and ranks high on all political agenda’s (e.g. VSNU, 2005; European Union, 2012). However, flows and transfer of knowledge in- and outside organizations remain highly unclear in business environments (Kogut & Zanders, 1992; Hansen, 1999; Szulanski, 1996; Cross, Parker & Borgatti, 2001). In addition, actors in business environments may not know about the need that others have for knowledge or actors might be reluctant to participate in knowledge exchange (Van der Eijk, 2009).
knowledge partners. These included; Syntens, NOM, Hanzehogeschool, Chamber of Commerce etc.
These types of initiatives start processes that are not only aimed at the exploitation of opportunity but are based on new or academically derived knowledge and innovation. A concept known in literature as knowledge intensive entrepreneurship or KIE (Groen, 2005). A different example focusing more on knowledge intensive cooperation through social ties is an initiative of the regional Chamber of Commerce. In 2010 the Chamber of Commerce started a project called KIND (translated; kennisintensief netwerk doorgroeiers) helping established entrepreneurs coping with life-cycle developments by using small knowledge intensive networks. Successful life-cycle progression through social innovation is a key issue in this project (KvK Noord-Nederland Activiteitenplan 2010, 2009).
Knowledge intensive firms operate in environments where innovation causes new products and services to be put in the market frequently. The resulting decrease of a products’ lifespan causes their reproduction processes to become obsolete relatively fast. In general, KIE thus faces a highly dynamic and complex environment while information about the dynamics and complexity of knowledge intensive markets is often scattered and difficult to find. Governments try to facilitate this demand by streamlining information and building networks that support entrepreneurs. However, the different initiatives generate an excessive amount of information on markets that deal with rapidly developing technologies, and reproduction processes. According to Blaauw (2005) this makes it difficult for starting entrepreneurs to extract useful information. It therefore becomes clear that there exists a demand for assistance and coaching tailored to the needs of a specific entrepreneurs. More importantly, this dynamicity and complexity of knowledge intensive markets stresses the benefits of cooperation through social networks. However, the manner in which this social interaction takes place, and the effects it has on network structure often remains unspecified in the practical environment.
It is within this context of changing environments and entrepreneurial effort that Energy Valley brings together many different parties and industries in order to facilitate the exchange of high value knowledge and thereby takes steps to secure more durable energy solutions for the future. This report will elaborate on the process of complex knowledge exchange in the Energy Valley network and the social structures underlying it. It will thereby engage in a process termed in popular theory as “social network analysis” to analyze the social and relational externalities at the level of individuals operating in extensive social environments. Eventually, this will show how social interaction resolves the conflict between altruistic vs. self-interested goal obtainment and enables entrepreneurship through knowledge exchange. In addition, it will elaborate on the social structure of the Energy Valley network and how it is influenced by this process.
Before we come to discuss these issues in more detail, the following will first elaborate on more practical limitations and circumstances concerned with writing this report.
1.1 Research objectives
This research report aims to fulfil the demands of the Energy Valley Foundation. The platform forms a social network that brings together knowledge and knowledge carriers in an effort to activate businesses, governments and institutions to develop durable energy solutions for the future. By doing so they wish to use and develop the knowledge based economy in the northern part of the Netherlands. Members of the network often represent important firms and organizations different markets that have the potential to undertake projects that can influence the regional economy to a significant extend. The individuals and their relationships constituting the Energy Valley Platform network are therefore considered to be highly valued resources and are treated with the utmost care and respect.
The network members and their relations (enabling the innovation exchange process) are managed by project managers with high technical expertise knowledge on what goals can be achieved and who should be involved. In taking this perspective, managing knowledge exchange becomes a repetitive process that forms the core function of the Energy Valley network.
Operating at the intersection of knowledge, business and government, Energy Valley operates within particular structural patterns used to enable knowledge exchange and facilitate innovation processes. The nature of these structural patterns and the specific context variables makes
facilitated and optimized and how this will affect the social network structure. In short, this reflects the main focus of this research report.
Within the Energy Valley platform Dr. Koos Lok en Mr. Patrick Cnubben will supply input and feedback to secure that the scope of this research remains aligned with the
1.2 Research questions
In high-technology industries that deal with strong demands for innovation, firm performance and viability is highly dependent on the development and transfer of knowledge. Recognizing that knowledge stems from individuals constituting an organization or business, it becomes obvious that knowledge interaction has both economic and social externalities. The process of interaction is however primarily facilitated by social network interaction. Being a social process, this report will provide special attention to selfless acts of giving that help facilitate the process of knowledge exchange (or knowledge transfer) in environments of strong social connectedness.
1.2.1 Problem statement
Networks like Energy Valley bring together different individuals with the ultimate goal of creating and developing innovations through the transference of complex knowledge.
Networks play a crucial part in facilitating innovation, by functioning as a platform that is able to coordinate knowledge transfer by means of “selfless acts or generosity” known as gifts.
Considering the limited understanding of the motivational reasons behind knowledge transfers, knowledge flows and the effects it has on the structural and social environment, the main research question addressed in this report is the following:
How does gift exchange influence the centrality of actors in social networks?
1.2.2 Sub-questions
The main research questions will be answered in the conclusion to this report. Before this can be done, links and relations between the underlying theoretical concepts need to be explained and tested in the context of the Energy Valley network. In order to come to a consistent set of sub-questions we draw upon the insights stated in the introduction to this report and elaborate on the topic of “knowledge intensity” before we come to test the independent variable; “gift
exchange”. The strong embeddedness of gift exchange in theory on knowledge intensive entrepreneurship requires this report to discuss the theoretical context of this concept, more extensively then would be considered normal. Because some of the issues related to knowledge are important to test in social network environments and in relation to innovation, but are not explicitly discussed in gift exchange theory, the following sub-question is formulated.
1. How does gift exchange influence knowledge transfer?
1.3 Conditions and limitations
This research report is motivated by prior efforts of Energy Valley to make sense of different social roles in their direct environment. Prior research elaborated on the contribution of tie strength between the knowledge broker and seeker to the effectiveness and efficiency of the knowledge brokering process. It explored the role of Energy Valley in its environment and helped to understand its position in the knowledge sharing process.
The relationship between knowledge sharing through social networks and innovation is expected to comprise of a wide variety of theoretical concepts. As one can imagine by reading the introduction to this report, many theoretical concepts overlap even though different sources will prove to disagree on definitions of even the most insignificant of issues. For research purposes, this is obviously not an ideal starting point. Unfortunately, real world issues are not likely to confine themselves to individual concepts either. One can therefore expect that at certain points in the research process small but conflicting issues might be ignored for sake of general clarity. The value of this research report thereby lies in the fact that it takes a second step in analyzing drivers underlying the core function of the Energy Valley Platform; knowledge exchange through social interaction.
The author of this report has taken into account the demands and conditions to which this report is limited, as prescribed by the Rijksuniversiteit Groningen. The following bullets represent these demands and conditions and as such provide a guideline for the appropriate formation of this thesis.
This thesis is part of the master specialization in small business and entrepreneurship of the program of business administration as offered by the Rijksuniversiteit Groningen. As such it must primarily fulfill the demands of the faculty of economics and business administration and additional requirements laid on by university thesis supervisors.
Due to the overlap in theoretical concepts this report will limit itself to discussing topics only as far as these topics are relevant to answering the main research question.
This thesis must meet the demands of the Energy Valley Foundation as translated by dr. Koos Lok and Mr. Patrick Cnubben. Regular discussions on the progress of this report will provide opportunity for Dr. Lok and Mr. Cnubben to shape the content to the needs of the platform. The Energy Valley platform will provide the author with contacts and thereby facilitate the research part of this report.
1.4 Report outline
This report consists of six chapters. While the current chapter (one) forms an introduction to the study, the following chapters will elaborate on the concepts of knowledge transfer (gift exchange) in relation to network structure (centrality).
Chapter two will describe the theoretical context of this report. This chapter will introduce the concepts underlying the operations of Energy Valley as they are relevant to understanding choices made in later stages of the research process. It thus determines the
foundation on which further theoretical analysis will take place. For insiders, this chapter may be skipped for its contribution lies mainly in addressing industry specific characteristics. Besides describing these Energy Valley specific characteristics, it introduces some industry specific issues regarding energy innovation. In doing so it builds primarily on a research report of Kaloudis and Pederson (2008). In addition, please note that this chapter deals with the concepts of interest (addressed in the research questions) from the perspective that is discussed in this chapter. It tries to bridge the gap between the more practical perspective described earlier, addressing knowledge complexity and innovation issues, and the purely theoretical perspectives discussed in chapter three.
Chapter three contains an extensive literature review of the theoretical concepts of knowledge exchange through social network environments. It will introduce the concept of gift exchange and its related concepts. Please note that it take a social perspective in describing knowledge transfer issues and thereby builds on the early works of Mauss (1954) and more currently Van der Eijk (2009). In addition, it will introduce the insights of Granovetter (1974) and elaborate on the different types of tie strength. The combination of these two perspectives will not only lead to the development of an extensive insight in topics constituting and surrounding the main research question, it will allow us to test the different concept (described in this chapter by research questions) while ensuring mutual exclusivity. At this point in the report, a first attempt can be made to translate the theoretical insights to answers the research questions formulated. This conclusion can actually be thought of as propositions that, will function as hypothesis, and are to be further studied in the remainder of the report.
(network structure centrality measures) and allows us to empirically test the relationship between gift giving and network structure using empirical techniques.
Chapter five will present the research outcomes based on the empirical study. Based on these outcomes, answers will be defined regarding the stated research questions based on the data presented in chapter five.
In the final chapter of this study (six) conclusions will be compared to theoretical insights and interesting deviations or addendums will be discussed while obtaining in depth insight in the studied concepts. In addition, recommendations are made on how Energy Valley could benefit from what is presented in this report.
2. CONTEXT
This chapter will introduce the contextual environment in which this research was conducted. It will describe industry specific circumstances as they are appropriate for further understanding the theoretical discussion in chapter three. Please note that the following concepts will be addressed.
Concept Purpose Main Sources
2.1
Energy valley Platform
Characterize Energy Valley and describe its general context. This will allow later elaboration on specific social context in which the organization operates.
Energy Valley Foundation, 2011
2.2
Knowledge in the energy Sector
Introduce energy sector specific issues regarding the role of knowledge. This will bridge the gap between the position of knowledge (as a competitive advantage) and the later described issues of knowledge transfer
(through gift exchange) and knowledge intensive environments.
Kaloudis and Pedersen, 2008
2.3
Cooperation in the energy sector
Introduce energy sector specific issues regarding the propensity of firms to work together. This prepares the introduction of a social theory perspective in describing knowledge exchange in social networks (using Social Network Analysis).
Kaloudis and Pedersen, 2008
2.4
Innovation in the energy sector
Discuss specific issues regarding innovation. Because this report takes the perspective that innovation is knowledge based, an introduction of general energy industry related innovation issues is in order before innovation issues regarding knowledge complexities are addressed (chapter three).
Gallagher, Holden and Sager, 2006;
Kaloudis and Pedersen, 2008
Table 2.1
2.1 The Energy Valley Platform
Energy Valley offers entrepreneurs, institutions and governments a place where they can think, discuss and be informed about durable energy developments in the Energy Valley region (see figure 2.1) The provinces of Drenthe, Friesland, Groningen en Noord-Holland are seen as the focal region to develop clean, reliable and innovative energy solutions. Firms actively cooperate and initiate projects that help to establish themselves as the primary knowledge region for Europe’s energy based economy. In general, Energy Valley actively engages in initiatives related to one or more of the focal areas. Presented in figure 2.1, the black, grey and white dots represent the different activities initiated in the region. For more- and up to date information please see www.energyvalley.nl.
The Northern part of the Netherlands is especially suitable for these purposes because it contains a significant part of the international gas supply. In addition, it is positioned in the centre of Europe’s gas and electricity network; it enjoys the presence of important harbors suited to facilitate offshore wind projects as well as energy and agricultural industries that are strongly embedded in the local economy.
CONVENTIONAL ENERGY
expansion of the gas & power cluster
CONVENTIONAL ENERGY expansion of the gas & power cluster
RESEARCH & EDUCATION
concentration of energy science institutes
RESEARCH & EDUCATION concentration of energy science institutes
ENERGY TRANSITION
incubator for (innovative) sustainable solutions
ENERGY TRANSITION incubator for (innovative) sustainable solutions E N E R G Y V A L L E Y E N E R G Y V A L L E Y CONVENTIONAL ENERGY
expansion of the gas & power cluster
CONVENTIONAL ENERGY expansion of the gas & power cluster
RESEARCH & EDUCATION
concentration of energy science institutes
RESEARCH & EDUCATION concentration of energy science institutes
ENERGY TRANSITION
incubator for (innovative) sustainable solutions
ENERGY TRANSITION incubator for (innovative) sustainable solutions E N E R G Y V A L L E Y E N E R G Y V A L L E Y Figure 2.2
Energy Valley focal areas (Source: Energy Valley Platform, 2011)
All these aspects have lead to the formation of energy related clusters comprising of roughly 400 companies that are involved with energy developments in this region. These clusters are supported by a strong knowledge base and focussed government policy. About a third of these firms are a member of the Energy Valley platform (see appendix I for an overview of all
members). Membership of Energy Valley is available to all energy industry related firms and institutions, ranging from consultants and local governments to large producers of electricity. In recognizing the benefits of increased connectedness in the clusters, about 160 organizations have paid to join the Energy Valley platform.
2.2 Knowledge in the energy sector
Knowledge production and the generation of innovative ideas in the energy sector (often measured in number of patent applications) is said to be a variable dependent on resource
investments in R&D and existing knowledge (knowledge stock). The idea is that innovation builds on existing knowledge and an increase in R&D expenditure will normally result in a steady flow of patents after a research project has finished (Kaloudis and Pedersen, 2008).
An estimate shows that every factor 1 increase in R&D expenditure would result in a short-term 0.2 factor increase in patent applications. Remarkably, every 1 increase of investment in the current knowledge stock would lead to an estimated 0.2 short-term increase in patent applications. For the long-term, the difference in the value of knowledge stock becomes even more significant showing a 0.08 increase for R&D investment and a 0.78 increase in patent applications for every increased unit of knowledge stock investments. In other words, developing knowledge that is already present in the firm is more fertile ground for future innovation then investments in new R&D activities. It is likely that new innovations are therefore determined by what was invented in the past suggesting a tendency towards incremental innovation and strong knowledge cumulativeness in this sector (Kaloudis and Pedersen, 2008).
Besides this, it is important to know that R&D investment in this sector show a positive correlation with government R&D subsidies, deregulation and low levels of market competition. On the other hand, exposure to international trade seems to reduce the willingness to invest in R&D and high levels of competition leads to reduced R&D intensity (Kaloudis and Pedersen, 2008).
Firms should innovate in order to maintain and strengthen the position they hold in their competitive environment (Caldwell, 1987; Danneels, 2002). As explained in the following chapter, Schumpeter suggests that innovations are often new combinations of existing knowledge and incremental learning. In light of this report, we stress the emphasis on the learning
2.3 Cooperation in the energy sector
With regard to the actual achievement of innovation goals in the energy sector,
cooperation seems to be dependent on the character of the innovating firm. In the traditional sub-sectors of energy production and transformation, competitors can hinder innovation by exerting market dominance. However, impulses initiated by competitors can also be imitated or learned from. Especially in the energy sector competitors are valued as important sources of information for further innovation. Accordingly, 20% of the energy sector states to recognize these benefits of competitor innovation where other sectors average at a mere 11% (Kaloudis and Pedersen, 2008). Actual cooperation between competitors in innovation is considered to be quite common also. The study shows that 35% of all innovative energy sector firms participated in such
relationships between the years 1998 and 2000 (Kaloudis and Pedersen, 2008). Especially when cooperation was no direct threat to the market position of the cooperating firms (due to a focus on different regional markets) firms pursued cost reductions through shared innovation (Kaloudis and Pedersen, 2008).
Besides this, more then a quarter of innovative energy sector firms said to value their customers as an important partner in the innovation process. This is especially true for traditional large-scale and complex firms operating in the maturity stage of their life-cycle. In these companies,
innovation is considered incremental in nature and often the result of intense user-supplier-interaction. Due to the complexity and scale of the innovating firms, even incremental innovation needs large scale investment (Kaloudis and Pedersen, 2008).
2.4 Innovation in the energy sector
On its most elementary level, energy technology and its developments are important because energy delivers one of the most basic and necessary of services such as; heat for cooking, boiling water, keeping people warm etc. On many levels developments in energy technology shape and fulfil fundamental human needs. Energy is used for mining, manufacturing, materials processing, construction, transport, communication, computing, comfort, illumination and is thereby essential to economic and societal prosperity. On a more practical note, energy
developments shape the monetary costs of providing energy for these abovementioned purposes which form a significant component of the cost of living and the balance of trade, for energy-importing countries. The eminent role energy takes in these issues causes some reason for concern.
The environmental and political impacts of the way in which energy is supplied are often significant and unwanted. A typical example of such a situation is reflected by our strong
dependency on oil imports (see figure 2.3 and note that the red circle indicates the share of oil imports for the Netherlands) produced in politically unstable countries like Iran, Saudi-Arabia, Nigeria etc. (see figure 2.4).
Figure 2.3
Figure 2.4 Dutch oil suppliers (Source: CBS, 2011)
“Improvements in energy technology are changes that reduce the monetary cost of delivering a given energy service or increase the quality of the energy service delivered for a given cost, or reduce the environmental or political impacts of providing a given energy service at a cost deemed worthwhile in exchange for the benefit of such reduction.” (Gallagher et al., 2006) The processes Gallagher et al describe thus result in improvements in energy technology that may take the form of refinements of existing technologies or can replace them. However, they have to be conceived, studied, built, demonstrated, and refined. In practical circumstances this environment may range from laboratories to the commercial marketplace; where new technologies are propagated into widespread use. Innovation therefore does not consist of
research and development (R&D) alone; it is not complete unless it includes further steps through which new technologies or improvements attain widespread application.
the consumer; who is simultaneously responsible for facilitating widespread use of the innovation, thereby helps to make the developments more cost-efficient, and assign value to a particular development (Brooks, 1995) In this type of situation, where production and consumption are simultaneous and under pressure of uncertainty in value assignment by the consumer, it becomes clear that durable innovation is a complex, incremental, cumulative and interactive process (Fri, 2003).
Figure 2.5
The energy innovation process and its interactions (Source: Gallagher et al., 2006)
Figure 2.5 presents a visual representation of energy related innovations as described by Gallagher et al. in 2006. The innovation process is described here as a process including many chain-linked interactions involving a variety of actors, during different stages of development. Margolis (2002) states that this variety of actors have a strong impact on the extend to which the final innovation becomes and is considered “durable”. Furthermore, stages of research,
introduction for it stresses the value of social interaction in innovation processes. This is based on its ability to circumvent market- and hierarchical coordination that only add more complexity to this innovation process.
In general terms, innovations in the energy sector refer to technological developments in the means of locating, assessing, harvesting, transporting, processing, and transforming primary forms of energy that can be found in nature (e.g.; sunlight, biomass, petroleum, coal, uranium-bearing rocks) to obtain direct energy services (e.g.; heat from fuel-wood or coal) or secondary forms more convenient for human use (e.g., charcoal, gasoline, electricity). In addition, it
includes ways of distributing secondary forms to their end-users and the ways of converting these forms to energy services (e.g.; electricity to light and refrigeration, electricity and gasoline to motive power) (Gallagher et al., 2006).
Knowing this, a distinction can be made between energy-supply technologies that are used to bring energy forms to the location of final use, and energy end-use technologies representing developments applied at the point of final
use to convert an energy to a directly consumable service (e.g.; light, motive power etc.). Supply technologies are said to receive more attention in discussions on energy technology innovation but this does not mean that end-use technologies deserve less attention (Gallagher et al, 2006). In policy trajectories, energy innovations are thought to face three important
objectives (see figure 2.6). Figure 2.6
Innovation focus areas
Focus on these particular energy related issues is the result of changing patterns in energy production and consumption that have diverged strongly since the industrial revolution.
Nowadays both energy quantity and quality are thought to interact in numerous ways. It
represents the increased awareness of the impact of energy consumption on the environment and society as a whole. This shifting perspective is considered to be a global phenomenon and continuous to unfold in industrial and developing countries alike. It indicates a strong trend towards increased energy use and environmental impacts as the direct result of increased
population rates and economic growth. Energy technology innovations therefore strive to improve the quality of energy by moving from traditional energy sources like oil and coal to so called
2.4.1 Innovation processes and performance
Innovation paths in the energy sector are extremely diverse and can focus on a
heterogeneous field of issues. Without prioritizing it is possible to divide the different innovation challenges into technologically generic application issues focussing on greening existing
technologies (expressed in terms of incremental innovation) and disruptive trends of technology (expressed in radical innovations). These last group of issues determine how and how fast renewable technologies are developed and diffused in society. Further activities of the energy sector in general should be described and assessed with care. Considering that energy and electricity (primary outputs of this sector) is produced from carriers like hot water, gas, wind etc. the transformation to output products is considered to be a highly standardised process and a fundamental good in human welfare, typically suited for incremental innovations (Kaloudis and Pedersen, 2008).
The energy sector in the EU is said to be thriving in terms of employment, productivity and value added. Innovation activities are pushed by ambitious environmental goals set by and for the EU, which triggers continuous efforts to improve and innovate. In general these activities are said two have two underlying causes. First, there are expectations of technological
improvement based on environmental concerns. Second, national energy markets become more and more competitive due to ongoing market liberalization efforts.
The following will elaborate on the sectoral innovation performance and challenges facing this cluster. Please note that the described insights are based on a research report of Europe INNOVA (Innovation Watch – SYSTEMATIC project 2006-2008) which is an initiative of the European Union, DG Enterprise and Industry. This report is aimed at the statistical demarcation of input-, output- and knowledge interactions in the energy sector in Europe thereby including the following activities: energy extraction, transformation/conversion/processing, transport, storage, consumption and management. It thereby also becomes clear that it does not fully capture the value of all upstream R&D- and technology transfer activities. It does however provide an insight into the characteristics of the cluster regarding its innovation capacities and innovation system (Kaloudis and Pedersen, 2008).
(non-organized) incremental improvements of products or processes ii. Purchasing and applying technology / equipment or ii. (organized) project-based R&D investments.
In general and without addressing the issue of defining innovation in more practical terms, the study shows that only 36% of energy sector firms are said to be “innovative”. Qualitative data explains this disappointing estimate by stating that the standardised nature of most throughput processes cause ongoing incremental innovation efforts that become part of the character of energy sector firms. In addition, energy production is considered to be a low-tech sector where the R&D share of value added, is well below the manufacturing average. The energy sector therefore seems to rely less on R&D investments to reach the ever more stringent production (emission) goals. Focus shifts to knowledge exploration, knowledge exploitation, competence from highly educated employees and external R&D inputs from upstream suppliers, business services (KIBS) etc.
Firms can pursue innovation goals through a highly diverse set of activities. Based on the use of these methods, different innovation “modes” can be identified:
Source of development
R&D Newness Market Diffusion
Strategic innovators
At least party in-house
Continuous New to market National or
International Many products and processes Intermitten t innovators At least partly in-house
Occasional New to market National or
International Unlikely Technology modifiers A At least partly in-house No Not new to market National or International No Technology modifiers B At least partly in-house
No New to market National or
International
Regional or local only
Technology adopters
Out-house No New to market National or
International
Diffusion through innovation
Table 2.7 Innovation modes
Although the choice of variables underlying the above mentioned classification of innovation modes are not tested on validity, the establishment of a classification does provide an opportunity to distinguish firms based on their innovative capacity and gives an indication of the capacity of the sector in general. On average 11% of all energy sector firms are said to be technology adopters, an additional 11% are technology modifiers, 12% intermittent innovators and only 3% of all firms is said to be a strategic innovator. The innovative capacity of domestic energy sectors thrives mostly on the combined efforts of intermittent innovators and technology modifiers. Interestingly, intermittent innovators show the highest rates of employment- and export growth while strategic innovators tend to be relatively large firms (12 times larger then the average intermittent innovator) generating high turnovers (Kaloudis and Pedersen, 2008).
2.5 Conclusion
Energy Valley brings together individuals and organizations from all three helix spheres, in an effort to develop clean, reliable and durable energy solutions. In doing so it whishes to establish the Northern part of the Netherlands as the primary knowledge region for Europe’s energy based economy. These initiatives combined with the geographical and historical benefits of the region (e.g. large natural gas reserves, seaports, strong agricultural industry) have lead to the formation of a strong energy clusters. Members of Energy Valley, ranging from consultants and local governments to large producers of electricity, enjoy the benefits of increased
connectedness within the clusters which represents the significant contribution Energy Valley has made to the development of a reliable energy-economy.
The position of knowledge within the energy industry has been the subject of increased attention. Especially in relation to innovation, the development of knowledge is though to have significant value for long term innovation output (measured in patent application). Where short term output is equally dependent on investments in R&D and knowledge development. It is the long term that proves to have beneficial effects on the effectiveness of knowledge development in terms of innovative output.
Regarding typical energy industry innovation, it is possible to divide the different innovation challenges into technologically generic application issues focussing on greening existing technologies (expressed in terms of incremental innovation) and disruptive trends of technology (expressed in radical innovations). Both types of developments are important because they shape and fulfil fundamental human needs. Additionally, energy technology developments not only impact society, but effect the global environment. This causes the industry to be subjected to political pressures as it copes with many sources of complexity (e.g. dependency on oil, shrinking natural resource reserves). When these developments result in innovation, the complexity of the energy industry (dealing with political, societal, economical and environmental issues) causes some ambiguity in assessing the value of innovation. Innovative efforts of energy industry firms and organization are therefore continuously studied, built, demonstrated, and refined as widespread diffusion is pursued. When a certain degree of diffusion is achieved, production and consumption are simultaneous and still under pressure of uncertainty in value assignment. In this situation it becomes clear that durable energy innovation reflect complex, dynamic and socially interactive processes resulting in extremely diverse innovation goals and innovation paths.
4.
THEORETICAL BACKGROUND
This chapter will provide an elaborate overview of relevant theory constituting the foundation of this research report. The concepts of i. knowledge exchange; with its related concepts, ii. social network structure and iii. social interaction, will be further explored in this chapter. In describing the theory, some of the concepts will show to lack mutual exclusivity in describing relationships as they are relevant. We will limit the discussion on reasons for these different perspectives to a minimum, and will introduce further specification of the concepts in chapter four of this report. The following table summarizes the objectives of this chapter and identifies the main sources of literature used in its formation.
Concept Purpose Main Sources
3.1 Social networks
The main problem statement driving this study focuses on the effects of gift giving on network structures. In this part of the report, knowledge exchange is further linked to social embeddedness (reflected by network structure) and Social
Network Analysis theory is proposed as an appropriate tool to help further the empirical study of the concepts.
Wasserman and Faust, 1994; Borgatti, 2005 3.2 Knowledge transfer
Introduce the social perspective form which this study perceives the knowledge transfer process.
Lin, 2007
3.3 Gift exchange Discuss social structure that underlies the knowledge transfer process and identify the optimal circumstances for use of gift exchange to facilitate the knowledge transfer process. This is in accordance with the main problem statement addressed in this report.
Van der Eijk, 2008
3.4 Knowledge complexity
Discuss the effect of knowledge complexity on the knowledge transfer process, in accordance with sub-question 2.
n.a.
3.5 Social ties Discuss the effects of the strength of social ties on the knowledge transfer process, in accordance with sub-question 3.
n.a.
Gift Exchange Network Structure: Centrality Knowledge Complexity Tie Strength + + +
In an attempt to answer the main research question described in the introduction to this report we build a frame of reference based on a theoretical description off the underlying concepts of knowledge transfer through gift exchange and its relation to network structure centrality. In doing so, a conceptual model of the different research variables (concepts) is established. Please see figure 3.1 for this model.
Figure 3.2 Conceptual model
3.1 Social networks
Individuals may outperform rivals or benefit from knowledge exchange processes, based on the different structural characteristics of- and the relative position in the network to which the individual belongs (Burt, 1992; Podolny and Baron, 1997). Before we start the elaborate
discussion on the theoretical concepts addressed in this report, it should be clear that this report studies the structure of relationships that links nodes (e.g. actors or individuals) and creates interdependencies between nodes in a social network environment. In addition, it studies the attitudes and behavior that determine the configuration of these social relations. Based on this assumption, this study actually contains a social network analysis of the Energy Valley Platform network (O’Malley and Marsden, 2008). Thus considering the main problem addressed in this report, SNA should prove to be a good fit with our informational demands.
The increased division of labour, the resulting functional specialization within firms and industries has made firms as well as individuals become increasingly dependent on each other. Specialization is said to have lead to economic development but also reduced the stock of knowledge and skills actor’s posses. This creates a strong need for cooperation (Van der Eijk, 2008; Hayek, 1945; Schumpeter, 1934; Nahapiet and Goshal, 1998). It is these insights that underpin the arguments made earlier regarding the link between knowledge exchange and innovative performance. Because of co-creation and the increased interdependencies between highly specialized firms, innovative performance is considered to be the direct result of effective knowledge exchange while social networks play an crucial in this process.
The key elements of networks are nodes and ties. Nodes are the individuals (or actors) in the network and ties are formed by the relationships between them. Ad hoc relationships are seen as weak ties where close cooperation or interaction forms a so called strong tie. In addition, the amount of nodes a network comprises determines the size of the network (Dolfsma and Aalbers, 2008). As a consequence of the high degree of specialization, there exists a need to exchange (give, receive and reciprocate) information and knowledge between nodes. This is especially the case in mature markets where technological- and market uncertainty is high (Ferrary, 2003). Not confirming to such actions would lead to the exclusion from socially or economically meaningful exchanges, rejection from the social capital community and will affect organizational
to be actors constituting these social networks. They engage in social relationships and together form a cluster of relationships. Granovetter (1985; 1992) describes this phenomenon as “social embeddedness”. Individuals in highly dense networks posses different resources and cope with different constraints then individuals in less dense networks, due to their degree of social embeddedness which may facilitate or hamper their ability to exchange knowledge resources (Moody and White, 2003; Gulati, 1998).
Although a common need for exchange is recognized, different goals and interest are likely to exist among different actors in the exchange network. Consequently, exchange requires coordination. Where the coordination of tangible exchange is proven to be a difficult issue in the economic context, the exchange of intangible resources (e.g. knowledge, information) can be considered even more difficult. Social network theory provides a way to visualize and model connections and interdependencies that are involved in the knowledge exchange process within a particular contextual environment. In addition, it allows the analyses of observational data that captures exchange relationships at the level in which knowledge resides and facilitates inference on the effects of interaction on network structure (Enemark, McCubbins, Paturi and Weller, 2010).
In evaluating knowledge exchange, social theory provides theoretical and methodological guidance in the form of social network analysis (SNA) (Lin, 2007). Traditional social theory and data analysis perceives individuals to make choices without considering behavior of others and thereby ignores the social environment of the actor. In SNA, relational data are the prime focus of the investigation even though the characteristics of individual actors are necessary in order to fully understand social phenomena. It shows how structural regularities influence the actors’ behavior and allows an insight in how behavior structures a social environment (Otte and Rousseau, 2002). In other words: “Methods of social network analysis provide formal statements about social properties and processes” (Wasserman and Faust, 1994).
3.1.1 Characteristics of networks
network interaction is considered to start innovation processes (Muller and Doloreux, 2007; Kauffeld-Monz and Fritsch, 2007).
Coleman (1998) suggests that an optimal network environment is achieved when all nodes are tied to each other. He termed these types of networks “high-redundancy networks” (see figure 4.1). One of the main benefits these type of networks offer is that the interconnectedness between nodes prevent individual nodes from influencing the exchange of information (Dolfsma and Aalbers, 2008). Interconnectedness enables different actors to seek information through different channels which limits the need to influence the exchange in order to benefit an individual node. In this case, costs of influencing the transaction reflect a transaction cost and may prohibit the establishment of a deep-trust relationship (CITATION NEEDED, SBE).
Figure 3.3 High-redundancy network
(Coleman, 1988)
3.1.2 Centrality
The position of actors in networks and the degree of eminence they consequently posses reflects the centrality of an actor (node) in its network environment. As such, it indicates the influence one has over other actors in the network (Brass and Burckhardt, 2002). Centrality is one of the core concepts of SNA and is used to identify the most important or “powerful” actors (Wasserman and Faust, 1994; Kahler, Hafner-Burton and Montgomery, 2009).
This report aims to investigate the individual nodes of a network, their characteristics and their position in the network. We can differentiate a number of basic approaches (measures) used in social network studies to capture this value:
o In-degree: Reflects an actor’s popularity in the network and a presented by the amount of ties oriented towards an actor.
o Out-degree: Reflects an actor’s expansiveness and is measured by the amount of ties stemming from one actor to another. Greater expansiveness is associated with a prominent role in the network.
2. Closeness centrality: Defined by Freeman in 1979; the closeness centrality is the sum of graph-theoretic distances from all other nodes, where the distance from a node to another is defined as the length (in links) of the shortest path from one to the other. In other words, the measure focuses on how close one person is positioned to all other persons in the network and this is a function of the geodesics distance where direct as well as indirect relations are considered. As such, it is a relatively easily interpretable measure of the ease with which a particular actor may disseminate (send) knowledge on its network (Landherr, Friedl, Heidemann, 2010). It is simply calculated as the inverse of the average distances between nodes i and any other node (Enemark, et al., 2010).
3. Betweenness centrality: Is based on the idea that one actor is important when this actor lies on a path between two other actors. Where communication and interaction between two specific actors is dependent on a third actor, this specific actor is said to be able to control the interaction between two nonadjacent nodes (Landherr, Friedl, Heidemann, 2010; Enemark et al., 2010).
4. Eigenvector or actor degree: Describes the amount of actors one actor is directly connected to but adds additional insight by claiming that a node’s importance depends on the importance of other nodes it is connected to (Enemark et al., 2010). The asymmetry of the relation is important that means, if a node is a source or drain of a relation (Mueller, Gronau and Lembcke, 2008).
3.2 Knowledge transfer
Knowledge transfer can be defined as; the process of engaging action, for mutual benefit, with business, government or the community to generate, acquire, apply and make accessible the knowledge needed to enhance material, human, social and environmental wellbeing (Argote, 1999). The generation of new knowledge and innovation is said to be dependent on individuals inside an organization and commercialization through knowledge transfer, which actively uses social structures (Podolny, 2001; Tsai and Hoshal, 1998; Owen-Smith and Powell, 2004). In other words, knowledge transfer entails a process that is recognized to be highly interactive and
socially driven (Schumpeter, 1934). During this chapter, we will explain how organizations recreate complex, ambiguous sets of reciprocal routines that facilitate the process of knowledge transfer; while building on the development of social ties, altruism, reciprocal action, time and trust.
Before we start, we recognize that the process of knowledge transfer exists under pressures from markets, hierarchies and social interactions. Different approaches are available to elaborate on knowledge transfer issues in network environments. However, it is this last aspect of social interaction that forms the focal area of this report, in an attempt to identity the drivers that underlie knowledge transfer activity in social network environments. By adopting this focus, we “envision the transfer of knowledge as gift exchanges between actors” (Van der Eijk, 2009; 6) and additionally draw upon prior efforts to study these issues. This allows us to engage in a discussion regarding the social structures underlying complex or tacit knowledge transfer and the difficulties this brings. Eventually, gift exchange theory will allow us to test knowledge transfer issues in relation to its effect on network structure. Additionally, this study will also elaborate on the (mediating or moderating) effects of contextual factors influencing this process recognized to have received too little attention in prior studies (Lin, 2007; Bock and Kim, 2002).
Knowledge transfer on the individual level is perceived to be the central issue in post-industrial society (Styre, 2002). The causes and effects of more tacit levels of knowledge (constituting most valuable organizational resources) have received much attention in this light (e.g. Bock and Kim, 2002; Lin, 2007; Kerr, 1995). Remarkably, focus in these studies was often aimed solely on the exchange difficulties degrees of tacitness brings without elaborating on the contextual forces present in the social environment. Based on the idea that knowledge is embedded and holds particular value in a particular contextual environment; Lin (2007)
by the works of Manev and Stevenson (2001). His 2007 study was “first to enhance the
3.3 Gift exchange
The problem statement addressed in this research report focuses on gift exchange as an independent variable influencing network structure (discussed later in this chapter). Because gift exchange is often discussed in relation to both economic and social attributes, theoretical
discussions can prove to be quite comprehensive and confusing for the discussions often show to overlap with different theoretical concepts. This chapter attempts to introduce these different concepts in a clear and structured manner to improve linkage between the theoretical discussion presented in this chapter and the methodological discussion presented in chapter four.
For these reasons, we have chosen to address the concept of gift exchange in the form of what, where, why, when and how questions and thereby circumvent repeated discussion of similar concepts from different theoretical perspectives.
3.3.1 Gifts and gift exchange
Gift exchange entails a process of giving, receiving and reciprocating different kinds of resources (Dolfsma, Van der Eijk and Joling, 2008). In addition, it is said that any resource; material or immaterial, tangible or intangible, of high or low value can be transformed into a gift or favor (Blau, 1964; Heath, 1976; Homans, 1974; Sherry, 1983). During the subsequent
exchange, the gift can take any form (suggestions, information, services, flowers etc.) as long as it is presented within the proper ritual. Presenting a gift means inviting someone to enter your (social capital) community for as long as the exchange relationship holds. In addition, such a relationship can only withstand if the initial gift is not considered to be a bribe (depending on how obvious its value is).
In light of this report, we will limit the discussion on gifts to the exchange of valuable knowledge through social interaction between individuals. Reasons for this choice will be discussed later on in this chapter. At this point, further clarification of the theoretical context of gift exchange is necessary to fully understand the choices and relationships discussed later on in the report.
process. Put simply “gift exchange provides parties with a mechanism for the exchange of resources and provides an incentive to do so” (Dolfsma and Van der Eijk, 2008; 4).
Van der Eijk (2009) describes gift exchange as “the, in fulfillment of an obligation or spontaneous, conference of some material or intangible benefit that is, consciously or unconsciously, subject to expectations of reciprocity whereby the particulars of the return in terms of form and time are left unspecified at the time of transaction” (Van der Eijk, 2008; 4). He implies that valuable exchange facilitates the fulfillment of long-term self-interest but depends on altruistic action in the short term. Short-term action is however often solely focused on obtaining short-term returns. Van der Eijk (2009) thus elaborates on an existing paradox between altruistic behavior and long-term self-interest from a social network perspective. However, the length and complexity of this single definition is typical for the theory that is considered in this report. As Van der Eijk (2008) also notes; the concept of gift exchange is highly integrated in other theoretical concepts.
Although the discussion on the functioning of social capital is elaborate and often vague, to understand later choices in methodological issues an introduction to this concept in relation to gift exchange is considered necessary. Social capital may be loosely described as “the sum of actual or potential resources embedded within, available through, and derived from the social structure that facilitates exchange and social interaction” (Van der Eijk, 2008; 35). In addition, social capital is perceived to have structural, relational and cognitive dimensions (Nahapiet and Goshal, 1998) that need maintenance. Gift exchange does this by allowing individuals to be tied to each other and in doing so provides access to social capital (resources) (Van der Eijk, 2008).
The theoretical value of gifts is founded on the idea that when exchange becomes a continuous social effort positive emotions will overtake uncertainty and generate commitment to the relationship (Lawler et al. 2000). In order for such relationships to develop initial knowledge exchange should be reinforced by incentives or rewards. The expected gains from future
3.3.2 Gift giving incidence
Gift exchange offers solutions to problems that market exchange and hierarchy have in coordinating knowledge transfer. It allows personal and impersonal sources of coordination, driven by both egoistic and altruistic motivations, to cooperatively facilitate exchange (Ferrary, 2003; Smart, 1993). Markets are said to be an imperfect coordinating mechanism for knowledge transfer for they take a de-socialized perspective in value creation and recognize knowledge actors as being motivated by extrinsic benefits. Under market pressures, actors would thus engage in opportunistic behavior, rendering valuable knowledge transfer impossible (Le Grand, 2003; Granovetter, 1985; Grant, 1996).
Based on the idea of transaction cost theory, hierarchy is also unable to coordinate transfer of knowledge because it depends on a high degree of confirmation. Rules and directives are unable to support novel ways of thinking and are not suited to deal with degree of tacitness (intangibility) that is said to characterize valuable knowledge (explained later in this chapter) for any form of new knowledge creation going beyond minor adaptations of existing goods and processes requires a more socially driven form of coordination (Van der Eijk, 2009).
Gift exchange has both economic and social purposes (Belk, 1979; Cheal, 1988; Larsen and Watson, 2001) and always takes place between individuals from within one- or representing different organizations (Flynn, 2003; Bouty, 2000); Child and Faulkner, 1998; Ferrary, 2003). Because the social aspect of gift giving is able to handle tacitness it facilitates the exchange of valuable knowledge. In addition it is considered an economic transaction ,but also reflects social interaction, embedded in a social structure (Gulati, 1998). As such it offers process benefits (Cheal, 1988). It is this social component that allows gift exchange to circumvent opportunistic behavior and effectively handle the intangibility associated with valuable knowledge exchange.
sense of obligation to return favors. Shared ideology, culture, norms and values are thus highly important for these types of relationships to work properly (Coleman, 1998; Ferrary, 2003; Field, 2003; Laumann and Pappi, 1976; Portes, 1998; Putnam, 1993; Sandefur and Laumann, 1998). This report will accept these truths without further analyzing the underlying conditions for reasons stated in chapter 1.3.
3.3.3 Gift giving occurrence
The concept of gift giving focuses on the beneficial effects of so called voluntary actions. Although gifts might sometimes be considered as selfless acts of generosity in the short-term, such actions tend to have positive effects on reputation, gratitude and return gifts in the long run (Blau, 1964; Mauss, 1954; Putnam, 2000). As a consequence, the “Matthew effect” suggests (the rich get richer) that these reputational benefits will lead to even more advantages as generously perceived individuals can expect to become an even more appreciated party in their environment (Merton, 1968).
These statements are all based on the idea that connectedness will lead to performance improvements of firms. To remain competitive and take advantage of new entrepreneurial opportunities, entrepreneurs are in need of resources that they actually already possess. This causes entrepreneurs to form both formal and informal relationships with other firms (Welbourne and Pardo-del-Val, 2008) reflected by the establishment of formal and informal networks.
Most valuable knowledge exchange takes place in informal networks and social ties that form these so called social capital “communities” (Brown and Duguit, 1991; Cohendet et al, 2004; Freeman, 1991; Cross et al, 2002; Madhaven and Grover, 1998). These communities are
established where horizontal (informal) linkage between experts facilitates knowledge creation (Galbraith, 1973; Grant, 1996; Hansen, 1999; Kogut and Zander, 1992). In such communities gift exchange offers a way to deal with problems “by curbing the effects of opportunism and goal incongruence using social and/ or cultural mechanism such as trust, common values and beliefs or network and reputation effects” (Van der Eijk, 2008; 21).
3.3.4 Gift giving prerequisites
In general and as stated earlier, gift exchange can coordinate processes by offering a social dimension that effectively deals with complexities in a way that market- and hierarchical coordination can not. Gift exchange differs from other coordination mechanism in specific ways:
environments coordination takes place without the help of centralized structures capable of binding decisions to actors. Actors within the organization (on the individual level) are however able to see through the ambiguous roles in the process of knowledge exchange and are better able to monitor and value each others performance. The acceptance of a gift creates the informal obligation to reciprocate and thereby drives both parties to form a lasting relationship (Gouldner, 1960; Levi-Strauss, 1996; Malinowski, 1996; Mauss, 1954; Sahlins, 1996; Schwartz, 1996; Simmel, 1996; Schein, 1965; Larsen and Watson, 2001; Carrier, 1991).
• The value, form and timing of gift return is not specified beforehand (Bouldier, 1977; Gouldner, 1960; Mauss, 1954; Deckop, Cirka and Andersson, 2003) and should be different from the gift that was exchanged first. This is known as homeomorphic reciprocity (Schwarz, 1996) and provides direct incentives for knowledge transfer. Despite the costs of uncertainty, time, energy and vulnerability of the sharing actors, knowledge is still being shared (Reagans and McEvily, 2003; Wenger and Snyder, 2000; Wenger, 1998; Brown and Duguid, 1991; 2001) because gift exchange provides a context as well as a socially embedded informal enforcement mechanism in absence of complete contracts. Gift giving will initiate a social relationship based on a sense of obligation to the giver while establishing a reputation of generosity or trustworthiness that will help to access resources from others (Coleman, 1988; Mauss, 1954; Bourdieu, 1977).
In line with these remarks, gift reciprocity takes place at a later point in time. This obligates individuals to each other and creates social debt (Mauss, 1954; Bourdieu, 1977; Ferrary, 2003; Deckop et al., 2003; Van der Eijk, 2008).
