Organizational collaborations are important means for organizations to access new resources and enhance the sustainable performance. Recent examples of inter-organizational collaborations towards more sustainable production are synergy parks, such as eco-industrial parks and agroparks. Synergy parks are collaborations among organizations across different sectors, mainly from agriculture and industry, aiming at enhanced economic and environmental performance, sustainable agri-food and bio-energy production through exchanging waste and by-products, creating production synergies. Because synergy parks connect organizations in their non-core business activities, these organizations are not always keen in the realization of synergy parks. A synergy park consists of multiple organizations from various sectors linked through multiple ties, its coordination can be explained by means of organizational network theory (Van de Ven & Fery, 1980). Consequently, a synergy park can be seen as a network where companies are the nodes and their collaborations the ties. Companies with direct ties, can affect the behavior of one another (Rowley, 1997). Recently more and more scholars use network analysis in understanding firms, stakeholders, and their social and behavioral phenomena (Ahuja, 2000; Ahuja, et al., 2009; Corsaro, et al., 2012; Gulati, 2007; Gulati, et al., 2000). Theories that discuss organizational networks, however, pay more attention to relations at dyadic level. Network analysis use in understanding firms, stakeholders, and their social and behavioral phenomena beyond dyadic level is slowly increasing (Ackermann & Eden, 2011; Frooman, 1999; Rowley, 1997). It provides scholars new insights to develop the inter-organizational network theory, to further it from dyadic relationship and examine systems of dyadic interactions capturing the influence of multiple and interdependent relations on network development. The purpose of the study is to understand how the structure of inter-organizational networks impact the realization of synergy parks by analyzing network attributes. In this study we answer the following questions: What is the impact of the network structure attributes (size, type of relation, centrality, and density) on realization of inter-organizational collaborations, such as a synergy park? What alternative network structures are effective in different inter-organizational collaborations? We suggest the following propositions: 1) The relation between the size of the network and the potential of a synergy park realization has an inverse convex shape (n shape) 2) Companies connected with both formal and informal ties have stronger and enduring relationships than the ones connected with formal ties only. 3) Decentralized and dense network structures are more suited for the realization of a synergy park if the set of involved companies are more heterogeneous. We conducted cross-case analysis in three synergy parks through using mixed qualitative and quantitative methods. The unit of analysis is the exchange relationship among the organizations within the networks. We focus on formal, informal, and trust related relations. We identified the boundary spanners in each organization, and asked managers who are the most knowledgeable about the relation of other organizations in the parks. These persons are formally or informally responsible for managing the collaborative relationships with other organizations. The main method of data collection was semi-structured interviews. The network survey has complex design comparing to standard surveys, therefore, we decided to interview each respondent personally by using ONA online survey tools. Concerning to network ties, we gather value and binary data. Each tie among the same companies have been measured and analyzed separately, and compared with one another. The data is coded and analyzed by using UCINET network analysis software (Borgatti, et al., 2002; Hanneman & Riddle, 2005). Networks are framed and analyzed per synergy park separate, which is followed by the analysis across networks. The discussion and the conclusion will be presented in the full paper. Reference Ackermann, F., & Eden, C., 2011. Strategic Management of Stakeholders: Theory and Practice. Long Range Planning, 44(3): 179-196. Ahuja, G., 2000. Collaboration Networks, Structural Holes, and Innovation: A Longitudinal Study. Administrative Science Quarterly, 45(3): 425-455. Ahuja, G., Polidoro, F., & Mitchell, W., 2009. Structural homophily or social asymmetry? The formation of alliances by poorly embedded firms. Strategic Management Journal, 30(9): 941-958. Borgatti, S. P., Everett, M. G., & Freeman, L. C., 2002. UCINET for Windows, Version 6.59: Software for Social Network Analysis. Harvard, MA Analytic Technologies. Corsaro, D., Cantu, C., & Tunisini, A., 2012. Actors' Heterogeneity in Innovation Networks. Industrial Marketing Management, 41(5): 780-789. Frooman, J., 1999. Stakeholder influence strategies. Academy of Management Review, 24(2): 191-205. Gulati, R., 2007. Managing network resources: alliances, affiliations and other relational assets. Oxford: Oxford University Press. Gulati, R., Nohria, N., & Zaheer, A., 2000. Strategic networks. Strategic Management Journal, 21(3): 203-215. Hanneman, R. A., & Riddle, M., 2005. Introduction to Social Network Methods. Riverside CA: University of California. Rowley, T. J., 1997. Moving beyond dyadic ties: A network theory of stakeholder influences. Academy of Management Review, 22(4): 887-910. Van de Ven, A. H., & Fery, D. L., 1980. Measuring and Assessing Organizations: John Wiley & Sons, Inc.
|Publication status||Published - 2014|
|Event||Sustainability and Innovation in Chains and Networks, Capri, Italy - |
Duration: 4 Jun 2014 → 6 Jun 2014
|Conference||Sustainability and Innovation in Chains and Networks, Capri, Italy|
|Period||4/06/14 → 6/06/14|