Determinants of inter-organizational network formation in the cultural sector
Article Sidebar
Main Article Content
Abstract
In recent years, the number of studies applying Social Network Analysis to the formation of inter-organizational networks has increased. This paper analyzed a socio-centric network composed of 32 cultural organizations in Andalusia to measure this increase. Multiple Regression Quadratic Assignment Procedure (MR-QAP) at the dyadic level, showed that perceptions of affinity (i.e., homophily) and the possibility of establishing contacts in the future, can exert influence on the establishment of informal contacts. At the internal level, an organization’s brokerage position in collaboration project networks is related to the volume of business and the old in the sector. Finally, this article discusses applications for the management of inter-organizational networks in order to strengthen the implementation of public policies.
Downloads
Metrics
Article Details
A RAE compromete-se a contribuir com a proteção dos direitos intelectuais do autor. Nesse sentido:
- adota a licença Creative Commoms BY (CC-BY) em todos os textos que publica, exceto quando houver indicação de específicos detentores dos direitos autorais e patrimoniais;
- adota software de detecção de similaridades;
- adota ações de combate ao plagio e má conduta ética, alinhada às diretrizes do Committee on Publication Ethics (COPE)
References
Baker, W. (2014). Making pipes, using pipes: How tie initiation, reciprocity, positive emotions and reputation create new organizational social capital. In D. Brass, G. Labianca, A. Mehra, D. Halgin, & S. P. Borgatti (Eds.), Contemporary perspectives on organizational social networks (pp. 57-72). Bradford, UK: Emerald Group Publishing.
Baur, M., Benkert, M., Brandes, U., Cornelsen, S., Gaertler, M., Köpf, B. … Wagner, D. (2002). Visone software for visual social network analysis. In P. Mutzel, M. Jünger, & S. Leipert, Graph Drawing (pp. 463-464). Berlin, Germany: Springer.
Borgatti, S. P., Everett, M., & Freeman, L. C. (2002). UCINET VI Version 1.0. Natick, MA: Analytic Technologies.
Borgatti, S. P., & Halgin, P. (2011). On network theory. Organization Science, 22(5), 1168-1181. doi:10.1287/orsc.1100.0641
Brandes, U., Kenis, P., & Raab, J. (2005). La explicación a través de la visualización de redes. REDES-Revista Hispana para el Análisis de Redes Sociales, 9(6), 1-19.
Burt, R. S., Kilduff, M., & Tasselli, S. (2013). Social network analysis: Foundations and frontiers on advantage. Annual Review of Psychology, 64, 527-547. doi:10.1146/annurev-psych-113011-143828
Calanni, J. C., Siddiki, S. N., Weible, C. M., & Leach, W. D. (2015). Explaining coordination in collaborative partnerships and clarifying the scope of the belief homophily hypothesis. Journal of Public Administration Research and Theory, 25(3), 901-927. doi:10.1093/jopart/mut080
Capone, F., & Lazzeretti, L. (2017). Interorganisational networks and proximity: An analysis of R&D networks for cultural goods. Sinergie Italian Journal of Management, 34, 53-70.
Cheng, J., Romero, D., Meeder, B., & Kleinberg, J. (2011). Predicting reciprocity in social networks. In Privacy, security, risk and trust (passat), (pp. 49-56). IEEE Third International Conference on Social Computing. Boston, MA: IEEE.
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3ª Edición). Mahwah, NJ: Lawrence Erlbaum Associates.
Crispeels, T., Willems, J., & Brugman, P. (2015). The relationship between organizational characteristics and membership of a biotechnology industry board-of-directors-network. Journal of Business & Industrial Marketing, 30(3-4), 312-323. doi:10.1108/JBIM-11-2012-0222
Dekker, D., Krackhardt, D., & Snijders, T. A. B. (2007). Sensitivity of MRQAP tests to collinearity and autocorrelation conditions. Psychometrika, 72(4), 563-581. doi:10.1007/s11336-007-9016-1
Ebers, M. (1999). The formation of inter-organizational networks. Oxford, UK: Oxford University Press.
Everett, M., & Borgatti, S. P. (2014). Networks containing negative ties. Social Networks, 38, 111-120. doi:10.1016/j.socnet.2014.03.005
Freeman, L. C. (2000). Visualizing social networks. Journal of Social Structure, 1, 1-15.
Freeman, L. C. (1979). Centrality in social networks: Conceptual clarification. Social Networks, 1(3), 215-239. doi:10.1016/0378-8733(78)90021-7
Granovetter, M. (1985). Economic action and social structure: The problem of embeddedness. American Journal of Sociology, 91(3), 481-510. doi:10.1086/228311
Gulati, R. (1995). Social structure and alliance formation patterns: A longitudinal analysis. Administrative Science Quarterly, 40(4), 619- 652. doi:10.2307/2393756
Hermans, F., Sartas, M., Van Schagen, B., van Asten, P., & Schut, M. (2017). Social network analysis of multi-stakeholder platforms in agricultural research for development: Opportunities and constraints for innovation and scaling. PloS one, 12(2), 1-21. doi:10.1371/journal. pone.0169634
Hollstein, B., & Domínguez, S. (2012). Mixing methods in social network research. Cambridge, MA: Cambridge University Press.
Jansen, D. (2017). Networks, social capital, and knowledge production. In B. Hollstein, Wenzel Matiaske, & Kai-Uwe Schanpp (Eds.), Networked Governance (pp. 15-42). Cham, ZG: Springer International Publishing.
Kim, G. M. (2016). Collaborative innovation with suppliers in a turbulent market. Asian Journal of Technology Innovation, 24(2), 179-201. doi:10.1080/19761597.2016.1186557
Knoke, D., & Yang, S. (2008). Social network analysis. (2nd Ed.). California, CA. Sage Publications Thousand Oacks.
Krackhardt, D. (1988). Predicting with networks: Nonparametric multiple regression analysis of dyadic data. Social Networks, 10(4), 359-381. doi:10.1016/0378-8733(88)90004-4
Krackhardt (1987). QAP partialling as a test of spuriousness. Social Networks, 9(2), 171-186. doi:10.1016/0378-8733(87)90012-8
Labianca, G., & Brass, D. (2006). Exploring the social ledger: Negative relationships and negative asymmetry in social networks in organizations. Academy of Management Review, 31(3), 596-614.
Lange, D., Lee, P. M., & Dai, Y. (2011). Organizational reputation: A review. Journal of Management, 37(1), 153-184. doi:10.1177/0149206310390963
Lecy, J. D., Mergel, I. A., & Schmitz, H. P. (2014). Networks in public administration: Current scholarship in review. Public Management Review, 16(5), 643-665. doi:10.1080/14719037.2012.743577
Ma, X., Yao, X., & Xi, Y. (2009). How do inter-organizational and interpersonal networks affect a firm’s strategic adaptive capability in a transition economy?. Journal of Business Research, 62, 1087-1095. doi:10.1016/j.jbusres.2008.09.008
Martin-Rios, C., & Erhardt, N. (2017). Small business activity and knowledge exchange in informal interfirm networks. International Small Business Journal, 35(3), 285-305. doi:10.1177/0266242616667540
McPherson, M., Smith-Lovin, L., & Cook, J. (2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27, 415- 444. doi:10.1146/annurev.soc.27.1.415
Otte-Trojel, T., Rundall, T. G., de Bont, A., & van de Klundert, J. (2017). Can relational coordination help inter-organizational networks overcome challenges to coordination in patient portals?. International Journal of Healthcare Management, 10(2), 75-83. doi:10.1080/20479700.20 15.1101911
Provan, K. G., Huang, K., & Milward, B. (2009). The evolution of structural embeddedness and organizational social outcomes in a centrally governed health and human services network. Journal of Public Administration Research and Theory, 19(4), 873-893. doi:10.1093/ jopart/mun036
Ramos-Vidal, I. (2017). Detecting key actors in interorganizational networks. Cuadernos de Gestión, 17(2), 63-86. doi:10.5295/cdg.140512ir
Ramos-Vidal, I., & Maya-Jariego, I. (2013). Alianzas y redes de colaboración entre las agrupaciones culturales de las Artes Escénicas en Andalucía. Empiria. Revista de Metodología de Ciencias Sociales, (26), 15-34. doi:10.5944/empiria.26.7151
Sánchez, A. R. P., & Vega, M. Á. F. (2011). La industria cultural en Andalucía: Un estudio comparativo en el contexto de las regiones españolas (No. E2011/02). Sevilla, España: Centro de Estudios Andaluces.
Sytch, M., Tatarynowicz, A., & Gulati, R. (2012). Toward a theory of extended contact: The incentives and opportunities for bridging across network communities. Organization Science, 23(6), 1658- 1681. doi:10.1287/orsc.1110.0712
Tomasello, M. V., Perra, N., Tessone, C. J., Karsai, M., & Schweitzer, F. (2014). The role of endogenous and exogenous mechanisms in the formation of R&D networks. Scientific Reports, 4. doi:10.1038/srep05679
Uzzi, B. (1997). Social structure and competition in interfirm networks: The paradox of embeddedness. Administrative Science Quarterly, 42(1), 35-67. doi:10.2307/2393808
Uzzi, B., & Spiro, J. (2005). Collaboration and creativity: The small world problem. American Journal of Sociology, 111(2), 447-504. doi:10.1086/432782
Valente, T. (1995). Network models of the diffusion of innovations. Cresskill NJ: Hampton Press.
Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. New York, NY: Cambridge University Press.
Watts, D., & Strogatz, S. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393, 440-442. doi:10.1038/30918
Worrell, J., Wasko, M., & Johnston, A. (2013). Social network analysis in accounting information systems research. International Journal of Accounting Information Systems, 14(2), 127-137. doi:10.1016/j. accinf.2011.06.002
Zajocs, R., & Edwards, E. (2006). What explains community coalition effectiveness? A review of the literature. American Journal of Preventive Medicine, 30(4), 351-361. doi:10.1016/j.amepre.2005.12.004
