**2.1 Inter-organizational collaboration and ecosystem**

Business today is based on networks and collaboration within and between organizations. As, knowledge is dispersed among different actors and organizations [11, 12] a most relevant motivation of organizations is the access to new ideas and complementary knowledge resources [13, 14]. In fact, knowledge diversity resulting of these collaborations enhance innovation as it is seen to expand the range of ideas that individual can use. Increasingly, literature on innovation considers industrial clusters [15, 16], national system of innovation [5], business ecosystem [17] and ecosystem of innovation [18–20] as territorial systems that facilitates and drive collaboration. Whatever name they are given, these concepts are widely analyzed to better understand the nature of relation between space industry and innovation [6]. For both researchers and practitioners, much of this intense interest is driven by the recognition that co-location allows the generation of a learning process, following the externalities of knowledge generated by geographical proximity, thus leading to innovation [15, 21, 22]. Mostly based on the success of certain highly innovative regions such as Silicon Valley and Route 128 of Boston, the unanimity about the virtues of these forms of territorial agglomeration has been reinforced. Local production system is here referred to under the generic term of «ecosystem» which is defined as *« an economic community supported by a foundation of interacting organizations and individuals-the organisms of the business world. This economic community produces goods and services of value to customers, who are themselves members of the ecosystem» ([*1*7]*:26). As Moore [17] states, the ecosystem refers primarily to notions of interdependence, leadership, and coevolution around innovative ideas.

More and more, innovation is seen as a collective action, which involves many different actors operating in a cluster context [23]. Furthermore, cluster enhances interorganizational relationship among the actors by facilitating networking and socialization through the geographic proximity [24, 25]. This socialization, facilitated by the possibility of frequent face-to-face contacts, helps foster knowledge exchange by building trust [26, 27]. As Cohendet et al. [28] argued, what are matters in the socio-economic approach of networks is the quality of the relationship between firms rather than the quality of the transaction. This social dimension's interest in the relationship between the partners has led to more and more in-depth research on the notion of social proximity. As it is increasingly recognized that the knowledge economy is a relational economy [29], much of research on networks

**161**

*Managing Inter-Organizational Knowledge Sharing: Integrating Macro, Meso and Micro...*

and collaboration [30, 31] knowledge management [26] has stressed the benefit of social proximity to facilitate collaboration and knowledge sharing. As suggested by the literature of sociology [32], social proximity fosters trust and builds a mutual commitment and consequently facilitates collaboration and interactive learning. In other words, it is often highlighted that the network partners may generate new solutions by joint-problem solving arrangements facilitated by ties embedded in the network [31]. As Boschma et al. [33] and Boschma [34] explain, an innovative performance at the firm follows an inverted «U» relationship between embeddedness and firm's innovative performance. Boschma [34] uses the embededness literature [32, 35] to define social proximity as a micro level' socially embedded relationships that includes trust based on friendship, kinship, and experience. This social proximity fosters the interactive learning by reducing the risk of opportunistic behavior and facilitating the sharing of tacit knowledge [26], which requires frequent interactions. However, Boschma [34] argue that as well as too much social distance, too much social proximity may be harmful for learning and innovation as it could lead to a closed community and consequently impedes innovation by limiting the

Knowledge creation and innovation processes have become increasingly complex due to a wide variety of sources of knowledge and the growing need for collaboration [7, 36]. The main purpose of theses collaboration is to maintain a sustainable advantage [37] by creating and sharing knowledge. Corno et al. [38] present three levels of knowledge transfer. The level of «initiation» that allows the sharing of explicit knowledge, the «encounter» level in which the actors seek to understand the tacit knowledge of their partners, to convert them into explicit knowledge, to integrate and to use them, and the level of «intimacy», in which the interaction between partners becomes deeper and characterizes a more developed level of cooperation between them. In this phase, the partners exchange their tacit knowledge by sharing their experiences, exchanging their culture and adopting a common language.

Different factors can influence the success of knowledge sharing. The overview of the literature highlights these main factors in [18] the characteristics of the units involved in the sense of their motivation and their cognitive and absorption capacity [19, 39–42] the attributes of knowledge [11, 39, 40, 42, 43] the relationships between partners [7, 38, 39, 42] the organizational context [41, 44] and [39] the network properties [45]. However, most of these researches examine the factors facilitating the knowledge transfer and sharing by using one level of analysis such

The present qualitative interpretative research seek to better understand interorganizational knowledge sharing process. It adopts an interactionist approach as stipulated by Strauss [46] is divided into three main elements: [18] the society as a collective production resulting from the interaction between different actors [19] the competences the knowledge and the rules are essentially elaborated in inter-subjective relations that evolve over time and [11] the human being must be seen as an active, reflective and creative being. The review of literature shows that the knowledge sharing between ecosystem partners needs a deeper understanding of the factors and determinants that enhance the knowledge sharing and how that affect it. Little is known about the determinants of successful knowledge sharing [47]. The present qualitative research seeks to better understand interorganizational knowledge sharing process between interorganizational projects partners by answering those two main questions: what are the factors that bolster knowledge sharing between partners? How these factors emerge during the collaborative project?

*DOI: http://dx.doi.org/10.5772/intechopen.97830*

access to the innovative ideas and diversity.

**2.2 Ecosystem and knowledge sharing**

individual or team or organization.

*Managing Inter-Organizational Knowledge Sharing: Integrating Macro, Meso and Micro... DOI: http://dx.doi.org/10.5772/intechopen.97830*

and collaboration [30, 31] knowledge management [26] has stressed the benefit of social proximity to facilitate collaboration and knowledge sharing. As suggested by the literature of sociology [32], social proximity fosters trust and builds a mutual commitment and consequently facilitates collaboration and interactive learning. In other words, it is often highlighted that the network partners may generate new solutions by joint-problem solving arrangements facilitated by ties embedded in the network [31]. As Boschma et al. [33] and Boschma [34] explain, an innovative performance at the firm follows an inverted «U» relationship between embeddedness and firm's innovative performance. Boschma [34] uses the embededness literature [32, 35] to define social proximity as a micro level' socially embedded relationships that includes trust based on friendship, kinship, and experience. This social proximity fosters the interactive learning by reducing the risk of opportunistic behavior and facilitating the sharing of tacit knowledge [26], which requires frequent interactions. However, Boschma [34] argue that as well as too much social distance, too much social proximity may be harmful for learning and innovation as it could lead to a closed community and consequently impedes innovation by limiting the access to the innovative ideas and diversity.

#### **2.2 Ecosystem and knowledge sharing**

*Occupational Wellbeing*

**2. Literature review**

knowledge sharing. However, despite the widespread expansion of research on concepts of cluster, recent studies emphasize the current analytical shortcomings and the failure of conceptualizing innovation in contemporary societies [6], the lack of understanding the dynamics of collaboration within the cluster [7–9], and the little known in the explanation of the link between knowledge ties and proximity within the cluster [10]. As cluster enhances innovation by facilitating knowledge creation, the aim of this research is to shed light in the factors that bolster knowledge sharing between partners. To do so, we draw from research on cluster and knowledge management to analysis the factors that enhance and impeded the interorganizational knowledge sharing. In the sections that follow, we first review research on collaboration, cluster and knowledge sharing highlighting the factors that foster or impede the interorganizational knowledge sharing within a cluster. Section 2 explains the methodological framework used for this research and in the final section we sum-

Business today is based on networks and collaboration within and between organizations. As, knowledge is dispersed among different actors and organizations [11, 12] a most relevant motivation of organizations is the access to new ideas and complementary knowledge resources [13, 14]. In fact, knowledge diversity resulting of these collaborations enhance innovation as it is seen to expand the range of ideas that individual can use. Increasingly, literature on innovation considers industrial clusters [15, 16], national system of innovation [5], business ecosystem [17] and ecosystem of innovation [18–20] as territorial systems that facilitates and drive collaboration. Whatever name they are given, these concepts are widely analyzed to better understand the nature of relation between space industry and innovation [6]. For both researchers and practitioners, much of this intense interest is driven by the recognition that co-location allows the generation of a learning process, following the externalities of knowledge generated by geographical proximity, thus leading to innovation [15, 21, 22]. Mostly based on the success of certain highly innovative regions such as Silicon Valley and Route 128 of Boston, the unanimity about the virtues of these forms of territorial agglomeration has been reinforced. Local production system is here referred to under the generic term of «ecosystem» which is defined as *« an economic community supported by a foundation of interacting organizations and individuals-the organisms of the business world. This economic community produces goods and services of value to customers, who are themselves members of the ecosystem» ([*1*7]*:26). As Moore [17] states, the ecosystem refers primarily to notions

of interdependence, leadership, and coevolution around innovative ideas.

More and more, innovation is seen as a collective action, which involves many different actors operating in a cluster context [23]. Furthermore, cluster enhances interorganizational relationship among the actors by facilitating networking and socialization through the geographic proximity [24, 25]. This socialization, facilitated by the possibility of frequent face-to-face contacts, helps foster knowledge exchange by building trust [26, 27]. As Cohendet et al. [28] argued, what are matters in the socio-economic approach of networks is the quality of the relationship between firms rather than the quality of the transaction. This social dimension's interest in the relationship between the partners has led to more and more in-depth research on the notion of social proximity. As it is increasingly recognized that the knowledge economy is a relational economy [29], much of research on networks

marize the findings as well as future research directions.

**2.1 Inter-organizational collaboration and ecosystem**

**160**

Knowledge creation and innovation processes have become increasingly complex due to a wide variety of sources of knowledge and the growing need for collaboration [7, 36]. The main purpose of theses collaboration is to maintain a sustainable advantage [37] by creating and sharing knowledge. Corno et al. [38] present three levels of knowledge transfer. The level of «initiation» that allows the sharing of explicit knowledge, the «encounter» level in which the actors seek to understand the tacit knowledge of their partners, to convert them into explicit knowledge, to integrate and to use them, and the level of «intimacy», in which the interaction between partners becomes deeper and characterizes a more developed level of cooperation between them. In this phase, the partners exchange their tacit knowledge by sharing their experiences, exchanging their culture and adopting a common language.

Different factors can influence the success of knowledge sharing. The overview of the literature highlights these main factors in [18] the characteristics of the units involved in the sense of their motivation and their cognitive and absorption capacity [19, 39–42] the attributes of knowledge [11, 39, 40, 42, 43] the relationships between partners [7, 38, 39, 42] the organizational context [41, 44] and [39] the network properties [45]. However, most of these researches examine the factors facilitating the knowledge transfer and sharing by using one level of analysis such individual or team or organization.

The present qualitative interpretative research seek to better understand interorganizational knowledge sharing process. It adopts an interactionist approach as stipulated by Strauss [46] is divided into three main elements: [18] the society as a collective production resulting from the interaction between different actors [19] the competences the knowledge and the rules are essentially elaborated in inter-subjective relations that evolve over time and [11] the human being must be seen as an active, reflective and creative being. The review of literature shows that the knowledge sharing between ecosystem partners needs a deeper understanding of the factors and determinants that enhance the knowledge sharing and how that affect it. Little is known about the determinants of successful knowledge sharing [47]. The present qualitative research seeks to better understand interorganizational knowledge sharing process between interorganizational projects partners by answering those two main questions: what are the factors that bolster knowledge sharing between partners? How these factors emerge during the collaborative project?
