Development of a structural-functional model for the implementation of the methodological approach to assessing the business network effectiveness
-
DOIhttp://dx.doi.org/10.21511/ed.18(4).2019.05
-
Article InfoVolume 18 2019, Issue #4, pp. 41-49
- Cited by
- 438 Views
-
86 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
During the economic crisis, to ensure sustainable development, the use of network forms of business organization in Ukraine is one of the most effective. However, given that business networks are hierarchical organizations, the problem of continuous monitoring of economic activity is updated to make the necessary effective management decisions. In this paper, using the structural and functional modeling method, a model is developed, which is an integral part of the methodological approach to assessing the business network effectiveness. The model combines empirical, theoretical and mathematical approaches to assessing the effectiveness of the network-based business organization and is based on a combination of qualitative and quantitative characteristics of business network activity. This approach ensures the objectivity of evaluating the properties of its functioning. A system of factors for a qualitative assessment of the effectiveness of a business network functioning was determined by an expert assessment method involving 40 managers of four companies in Ukraine. Determining the result deviations, in comparison with the accepted factors of the qualitative characteristics of networks, reveals the existing trends in the development of future events in terms of the risk of certain types of the business network activity. The results obtained are practical and will be useful for business network managers in developing an effective management strategy.
- Keywords
-
JEL Classification (Paper profile tab)L2, L51, M10, M10
-
References20
-
Tables0
-
Figures1
-
- Figure 1. Структурно-логічна модель методичного підходу до оцінювання ефективності функціонування бізнес-мережі
-
- Anderson, H., Havila, V., Andersen, P., & Halinen, A. (1998). Position and role-conceptualizing dynamics in business networks. Scandinavian Journal of Management, 14(3), 167-186.
- Ansoff, I. (2009). Strategicheskiy menedzhment [Strategic management] (344 p.). Sankt-Peterburg: Piter. (In Russian)
- Bosovska, M. (2015). Methodological approaches to assessing the performance of the networks based on multi approaches. Investytsiyi: praktyka ta dosvid - Investment: practice and experience, 3, 23-26. (In Ukrainian).
- Cheremnykh, S., Semenov, I., & Ruchkin, V. (2006). Modelirovaniye i analiz sistem. IDEF-tekhnologii [Modeling and analysis of systems. IDEF technology] (188 р.). Moskva: Finansy i statistika. (In Russian)
- Cowan, R., & Jonard, N. (2004). Network structure and the diffusion of knowledge. Journal of Economic Dynamics and Control, 28(8), 1557-1575.
- Coyne, K., & Dye, R. (1998). The competitive dynamics of network-based businesses. Harvard Business Review, 76(1), 99-109
- Danylovych-Kropyvnytska, M. (2014). Analiz rozvytku merezhevykh struktur na osnovi teoretyko-ihrovoho pidkhodu [Analysis of the development of network structures on the basis of theoretical and game approach]. Socio-Economic Research Bulletin, 1, 13-17. (In Ukranian).
- Fayol, A., Emerson, G., Teylor, F., & Ford, G. (1992). Upravleniye - eto nauka i iskusstvo [Management is science and art] (349 р.). Moskva: Respublika. (In Russian) 9. Hakansson, H., & Ford, D. (2002). How should companies interact in business networks? Journal of Business Research, 55(2), 133-139.
- Hellin, J., & Meijer, M. (2006). Guidelines for value chain analysis (24 p.).
- Izhevskyy, P. (2017). Business model of integration of agricultural enterprises on the basis of a network. Ekonomichnyi visnyk Zaporizkoi derzhavnoi inzhenernoi akademii - Economic Bulletin of Zaporizhzhya State Engineering Academy, 5(1), 139-144. (In Ukranian).
- Kastels, M. (2000). Informatsionnaya epokha: ekonomika, obshchestvo i kultura [The Information Age: Economics, Society and Culture] (608 p.). Moskva: HU VShE. (In Russian)
- Mason, K., & Leek, Sh. (2008). Learning to build a supply network: an exploration of dynamic business models. Journal of Management Studies, 45(4), 774-799.
- Menke, W. (2018). Geophysical Data Analysis. Discrete Inverse Theory (4th Edition) (pp. 207-222). Academic Press.
- Plyuta, V. (1980). Sravnitelnyy mnogomernyy analiz v ekonomicheskikh issledovaniyakh: metody taksonomii i faktornogo analiza [Comparative multivariate analysis in economic research: taxonomy and factor analysis methods] (151 р.). Moskva: Statistika. (In Russian)
- Reagans, R., & McEvily, B. (2003). Network structure and knowledge transfer: the effects of cohesion and range. Administrative Science Quarterly, 48(2), 240-267.
- Rousseau, R., Egghe, L., & Guns, R. (2018). Becoming Metric-Wise. A Bibliometric Guide for Researchers (1st Edition) (pp. 67-97). Chandos Publishing.
- Schilling, M., & Phelps, C. (2007). Interfirm collaboration networks: the impact of large-scale network structure on firm innovation. Management Science, 53(7), 1113-1126.
- Straub, D., Rai, A., & Klein, R. (2004). Measuring firm performance at the network level: a nomology of the business impact of digital supply networks. Journal of Management Information Systems, 21(1), 83-114.
- Tsai, W. (2001). Knowledge transfer in intraorganizational networks: effects of network position and absorptive capacity on business unit innovation and performance. Academy of Management Journal, 44(5), 996-1004.
- Viner, N. (2001). Chelovek upravlyayushchiy [Human leadership]. Sankt-peterburg: Piter. (In Russian)