Abstract
Most scientific publications on the subject of value chain management only analyse which structures, processes and actions can contribute to value creation. How the distribution of added values that were collectively achieved in a network of autonomous actors can influence the stability of such a network is often disregarded. The distributive justice or the fair distribution of collectively created added values is one of the most important ways to secure the stability of networks. This paper therefore presents a proposal for an operationalization of the fairness term from an economic perspective. This proposal is specific to the distribution of cooperation gains in networks of autonomously acting companies and takes a cooperative game theory approach as its basis. With the aid of the τ-value, it is shown how intuitive and vague associations of fairness can be substantiated to give a concrete distribution proposal that can be perceived and communicated as fair by gradually establishing rational or at least plausible assumptions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bilbao, J. M., Jiménez-Losada, A., Lebrón, E., & Tijs, S. H. (2002). The τ-value for games on Matroids. Top, 10(1), 67–81.
Branzei, R., Dimitrov, D., & Tijs, S. (2005). Models in cooperative game theory: Crisp, fuzzy, and multi-choice games. Berlin: Springer.
Cachon, G. P., & Zipkin, P. H. (1999). Competitive and cooperative inventory in a two-stage supply chain. Management Science, 45(7), 936–953.
Curiel, I. (1997). Cooperative game theory and applications: Cooperative games arising from combinatorial optimization problems. Boston: Kluwer Academic Publishers.
Driessen, T. S. H. (1985). Contributions to the theory of cooperative games: The τ-value and k-convex games. Unpublished doctoral dissertation, University of Nijmegen, The Netherlands.
Driessen, T. (1987). The τ-value: A survey. In H. J. M. Peters & O. J. Vrieze (Eds.), Surveys in game theory and related topics (pp. 209–213). Amsterdam: Stichting Mathematisch Centrum.
Driessen, T., & Tijs, S. (1982). The τ-value, the nucleolus and the core for a subclass of games. In H. Loeffel & P. Stähly (Eds.), Methods of operations research 46 (pp. 395–406). Königstein: Verlagsgruppe Athenäum Hain Hanstein.
Driessen, T. S. H., & Tijs, S. H. (1983). Extensions and modifications of the τ-value for cooperative games (Rep. No. 8325). Nijmegen, The Netherlands: University of Nijmegen, Department of Mathematics.
Driessen, T. S. H., & Tijs, S. H. (1985). The τ-value, the core and semiconvex games. International Journal of Game Theory, 14(4), 229–247.
Fromen, B. (2004). Fair distribution in enterprise networks: Solution concepts stemming from cooperative game theory (in German). Doctoral dissertation, University of Duisburg-Essen, Germany. Wiesbaden: Gabler.
Gjerdrum, J., Shah, N., & Papageorgiou, L. G. (2001). Transfer prices for multienterprise supply chain optimization. Industrial & Engineering Chemistry Research, 40(7), 1650–1660.
Inderfurth, K., & Minner, S. (2001). Production and logistics (in German). In P.-J. Jost (Ed.), Spieltheorie in der Betriebswirtschaftslehre (pp. 307–349). Stuttgart: Schäffer-Poeschel.
Kuhn, H. W., Harsanyi, J. C., Selten, R., Weibull, J. W., van Damme, E., Nash, J. F., Jr., et al. (1996). The work of John Nash in game theory: Nobel seminar, December 8, 1994. Journal of Economic Theory, 69(1), 153–185.
Li, S., Zhu, Z., & Huang, L. (2009). Supply chain coordination and decision making under consignment contract with revenue sharing. International Journal of Production Economics, 120(1), 88–99.
Mahdavi, I., Mohebbi, S., Cho, N., Paydar, M. M., & Mahdavi-Amiri, N. (2008). Designing a dynamic buyer-supplier coordination model in electronic markets using stochastic Petri nets. International Journal of Information Systems and Supply Chain Management, 1(3), 1–20.
Minner, S. (2007). Bargaining for cooperative economic ordering. Decision Support Systems, 43(2), 569–583.
Saharidis, G. K. D., Kouikoglou, V. S., & Dallery, Y. (2009). Centralized and decentralized control policies for a two-stage stochastic supply chain with subcontracting. International Journal of Production Economics, 117(1), 117–126.
Sucky, E. (2004a). Coordination in supply chains: Game theoretical analysis for the determination of integrated procurement and production policies (in German). Doctoral dissertation, University of Frankfurt am Main 2003. Wiesbaden: Gabler.
Sucky, E. (2004b). Coordinated order and production policies in supply chains. OR Spectrum, 26(4), 493–520.
Sucky, E. (2005). Inventory management in supply chains: A bargaining problem. International Journal of Production Economics, 93–94, 253–262. Proceedings of the Twelfth International Symposium on Inventories.
Thun, J.-H. (2005). The potential of cooperative game theory for supply chain management. In H. Kotzab, S. Seuring, M. Müller, & G. Reiner (Eds.), Research methodologies in supply chain management (pp. 477–491). Heidelberg: Springer.
Tijs, S. H. (1981). Bounds for the core and the τ-value. In O. Moeschlin & D. Pallaschke (Eds.), Game theory and mathematical economics (pp. 123–132). Amsterdam: North Holland Publishing Company.
Tijs, S. H. (1987). An axiomatization of the tau-value. Mathematical Social Sciences, 13(2), 177–181.
Tijs, S. H., & Driessen, T. S. H. (1983). The τ-value as a feasible compromise between Utopia and disagreement (Rep. No. 8312). Nijmegen, The Netherlands: University of Nijmegen, Department of Mathematics.
Tijs, S. H., & Driessen, T. S. H. (1986). Game theory and cost allocation problems. Management Science, 32(8), 1015–1028.
Voß, S., & Schneidereit, G. (2002). Interdependencies between supply contracts and transaction costs. In S. Seuring & M. Goldbach (Eds.), Cost management in supply chains (pp. 253–272). Heidelberg: Physica.
Xiao, T., Luo, J., & Jin, J. (2009). Coordination of a supply chain with demand stimulation and random demand disruption. International Journal of Information Systems and Supply Chain Management, 2(1), 1–15.
Zelewski, S. (2009). Fair distribution of efficiency gains in supply webs: A game theoretic approach based on the τ-value (in German). Berlin: Logos.
Zhang, D. (2006). A network economic model for supply chain versus supply chain competition. Omega: The International Journal of Management Science, 34(3), 283–295.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jene, S., Zelewski, S. (2012). Fair Distribution of Added Values in Networks of Autonomous Actors. In: Jodlbauer, H., Olhager, J., Schonberger, R. (eds) Modelling Value. Contributions to Management Science. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2747-7_9
Download citation
DOI: https://doi.org/10.1007/978-3-7908-2747-7_9
Published:
Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-7908-2746-0
Online ISBN: 978-3-7908-2747-7
eBook Packages: Business and EconomicsBusiness and Management (R0)