Network interactions of global supply chain members
Abstract
Supply chain structure of global enterprises tend to develop dramatically. These lead to more difficulty for enterprises in managing and building information sharing systems. Thus, it is a necessary for enterprises to limit the scope of the information sharing system by selecting essential partners. The aims of this study are to quantify the cooperation of each supply chain member, and evaluate and visualize their effects in information sharing systems in order to support policymakers in making their decisions in supply chain management. The network analytical method in network science is applied to indicate the relationship between supply chain members and present a comprehensive supply chain visually. Moreover, Motor Corporation’s topology in Japan is used as a representation of global enterprise features to analyze the relationships between supply chain members. The data for Motor Corporation is secondary data which includes the number of suppliers, manufacturers, and dealers, and the interaction among them. Data is collected and verified from reputable websites such as www.marklines.com, or www.statista.com. As a result, this study contributes by applying a new method for not only determining the impact levels of supply chain members but also giving visual descriptions of impact levels on the large-scale information sharing system.
Keyword : information systems, sharing information, supply chain management, network science, network analysis, global enterprises
How to Cite
Le, T. D. C., Oláh, J., & Pakurár, M. (2021). Network interactions of global supply chain members. Journal of Business Economics and Management, 22(6), 1593-1613. https://doi.org/10.3846/jbem.2021.14965
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Jeong, K., & Hong, J. D. (2019). The impact of information sharing on bullwhip effect reduction in a supply chain. Journal of Intelligent Manufacturing, 30(4), 1739–1751. https://doi.org/10.1007/s10845-017-1354-y
Jiang, Q., & Ke, G. (2019). Information sharing and bullwhip effect in smart destination network system. Ad Hoc Networks, 87, 17–25. https://doi.org/10.1016/j.adhoc.2018.07.006
Jozwiak, A., Milkovics, M., & Lakner, Z. (2016). A network-science support system for food chain safety: A case from Hungarian cattle production. International Food and Agribusiness Management Review, 19(A), 1–26. https://doi.org/10.22004/ag.econ.240694
Kot, S., Haque, A. U., & Kozlovski, E. (2019). Strategic SCM’s mediating effect on the sustainable operations: Multinational Perspective. Organizacija, 52(3), 219–235. https://doi.org/10.2478/orga-2019-0014
Kot, S., Onyusheva, I., & Grondys, K. (2018). Supply chain management in SMEs: Evidence from Poland and Kazakhstan. Engineering Management in Production and Services, 10(3), 23–36. https://doi.org/10.2478/emj-2018-0014
Kovács, Z. (2016). Moral hazard in producer organizations – Some experiences of an empirical survey. Applied Studies in Agribusiness and Commerce, 10(4–5), 77–83. https://doi.org/10.19041/APSTRACT/2016/4-5/10
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Ledwoch, A., Yasarcan, H., & Brintrup, A. (2018). The moderating impact of supply network topology on the effectiveness of risk management. International Journal of Production Economics, 197, 13–26. https://doi.org/10.1016/j.ijpe.2017.12.013
Lei, H., Wang, J., Shao, L., & Yang, H. (2019). Ex post demand information sharing between differentiated suppliers and a common retailer. International Journal of Production Research, 58(3), 703–728. https://doi.org/10.1080/00207543.2019.1600758
Li, G., Lin, Y., Wang, S., & Yan, H. (2006). Enhancing agility by timely sharing of supply information. Supply Chain Management, 11(5), 425–435. https://doi.org/10.1108/13598540610682444
Li, Y., Ye, F., & Sheu, C. (2014). Social capital, information sharing and performance. International Journal of Operations & Production Management, 34(11), 1440–1462. https://doi.org/10.1108/IJOPM-03-2013-0132
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