article

Supply chain performance assessment and supplier and component importance identification in a general competitive multitiered supply chain network model

Authors:

Anna NagurneyAuthors Info & Claims

Journal of Global Optimization, Volume 67, Issue 1-2

Pages 223 - 250

https://doi.org/10.1007/s10898-015-0371-7

Published: 01 January 2017 Publication History

Abstract

In this paper, we develop a multitiered competitive supply chain network game theory model, which includes the supplier tier. The firms are differentiated by brands and can produce their own components, as reflected by their capacities, and/or obtain components from one or more suppliers, who also are capacitated. The firms compete in a Cournot---Nash fashion, whereas the suppliers compete a la Bertrand since firms are sensitive to prices. All decision-makers seek to maximize their profits with consumers reflecting their preferences through the demand price functions associated with the demand markets for the firms' products. We construct supply chain network performance measures for the full supply chain and the individual firm levels that assess the efficiency of the supply chain or firm, respectively, and also allow for the identification and ranking of the importance of suppliers as well as the components of suppliers with respect to the full supply chain or individual firm. The framework is illustrated through a series of numerical supply chain network examples.

References

[1]

Bertrand, J.: Theorie mathematique de la richesse sociale. Journal des Savants, 67, 499---508 (1883)

[2]

Bertsekas, D.P., Tsitsiklis, J.N.: Parallel and Distributed Computation--Numerical Methods. Prentice Hall, Englewood Cliffs, New Jersey (1989)

Digital Library

[3]

Chen, Z., Teng, C., Zhang, D., Sun, J.: Modelling inter-supply chain competition with resource limitation and demand disruption. Int. J. Syst. Sci. (2014).

Digital Library

[4]

Chopra, S., Sodhi, M.S.: Managing risk to avoid supply-chain breakdown. MIT Sloan Manag. Rev. 46(1), 53---61 (2004)

[5]

Clendon, L., Bird, L.: 5th Annual Survey Supply Chain Resilience. Business Continuity Institute, Caversham, United Kingdom (2013)

[6]

Cournot, A.A.: Researches into the Mathematical Principles of the Theory of Wealth, English translation. MacMillan, London, England (1838)

[7]

Cruz, J.M.: Dynamics of supply chain networks with corporate social responsibility through integrated environmental decision-making. Eur. J. Oper. Res. 184, 1005---1031 (2008)

[8]

Cruz, J.M.: The effects of network relationships on global supply chain vulnerability. In: Wu, T., Blackhurst, J. (eds.) Managing Supply Chain Risk and Vulnerability: Tools and Methods for Supply Chain Decision Makers, pp. 113---140. Springer, Berlin, Germany (2011)

[9]

Cruz, J.M., Nagurney, A., Wakolbinger, T.: Financial engineering of the integration of global supply chain networks and social networks with risk management. Nav. Res. Logist. 53, 674---696 (2006)

[10]

Dupuis, P., Nagurney, A.: Dynamical systems and variational inequalities. Ann. Oper. Res. 44, 9---42 (1993)

[11]

Gabay, D., Moulin, H.: On the uniqueness and stability of Nash equilibria in noncooperative games. In: Bensoussan, A., Kleindorfer, P., Tapiero, C.S. (eds.), Applied Stochastic Control in Econometrics and Management Science. North-Holland, Amsterdam, The Netherlands, pp. 271-294 (1980)

[12]

Gupta, D.: The $$(Q, r)$$(Q,r) inventory system with an unreliable supplier. INFOR 34, 59---76 (1996)

[13]

Kinderlehrer, D., Stampacchia, G.: An Introduction to Variational Inequalities and their Applications. Academic Press, New York (1980)

[14]

Lee, D., Pierson, D.: Disaster in Japan exposes supply chain flaw. Los Angeles Times, (2011)

[15]

Liu, Z., Cruz, J.M.: Supply chain networks with corporate financial risks and trade credits under economic uncertainty. Int. J. Prod. Econ. 137, 55---67 (2012)

[16]

Liu, Z., Nagurney, A.: An integrated electric power supply chain and fuel market network framework: theoretical modeling with empirical analysis for New England. Nav. Res. Logist. 56, 600---624 (2006)

[17]

Liu, Z., Nagurney, A.: Supply chain networks with global outsourcing and quick-response production under demand and cost uncertainty. Ann. Oper. Res. 208(1), 251---289 (2013)

[18]

Mukherjee, A.S.: The Spider's Strategy: Creating Networks to Avert Crisis, Create Change, and get Ahead. FT Press, Upper Saddle River, New Jersey (2008)

[19]

Nagurney, A.: Network Economics: A Variational Inequality Approach. Kluwer Academic Publishers, Dordrecht, The Netherlands (1999)

[20]

Nagurney, A.: Supply Chain Network Economics: Dynamics of Prices, Flows, and Profits. Edward Elgar Publishing, Cheltenham, England (2006)

[21]

Nagurney, A.: Formulation and analysis of horizontal mergers among oligopolistic firms with insights into the merger paradox: a supply chain network perspective. Comput. Manag. Sci. 7, 377---410 (2010)

[22]

Nagurney, A., Cruz, J., Dong, J., Zhang, D.: Supply chain networks, electronic commerce, and supply side and demand side risk. Eur. J. Oper. Res. 26, 120---142 (2005)

[23]

Nagurney, A., Dhanda, K.K.: Marketable pollution permits in oligopolistic markets with transaction costs. Oper. Res. 48(3), 424---435 (2000)

Digital Library

[24]

Nagurney, A., Dong, J., Zhang, D.: A supply chain network equilibrium model. Transp. Res. E 38, 281---303 (2002)

[25]

Nagurney, A., Dupuis, P., Zhang, D.: A dynamical systems approach for network oligopolies and variational inequalities. Ann. Reg. Sci. 28, 263---283 (1994)

[26]

Nagurney, A., Li, D.: A supply chain network game theory model with product differentiation, outsourcing of production and distribution, and quality and price competition. Ann. Oper. Res. 228(1), 479---503 (2015)

[27]

Nagurney, A., Li, D., Nagurney, L.S.: Pharmaceutical supply chain networks with outsourcing under price and quality competition. Int. Trans. Oper. Res. 20(6), 859---888 (2013)

[28]

Nagurney, A., Qiang, Q.: A network efficiency measure with application to critical infrastructure networks. J. Glob. Optim. 40, 261---275 (2008)

Digital Library

[29]

Nagurney, A., Qiang, Q.: Fragile Networks: Identifying Vulnerabilities and Synergies in an Uncertain World. Wiley, Hoboken, New Jersey (2009)

Digital Library

[30]

Nagurney, A., Zhang, D.: Projected Dynamical Systems and Variational Inequalities with Applications. Kluwer Academic Publishers, Boston, Massachusetts (1996)

[31]

Nash, J.F.: Equilibrium points in n-person games. Proc. Natl. Acad. Sci. USA 36, 48---49 (1950)

[32]

Nash, J.F.: Noncooperative games. Ann. Math. 54, 286---298 (1951)

[33]

Parlar, M.: Continuous review inventory problem with random supply interruptions. Eur. J. Oper. Res. 99, 366---385 (1997)

[34]

Parlar, M., Perry, D.: Inventory models of future supply uncertainty with single and multiple suppliers. Nav. Res. Logist. 43, 191---210 (1996)

[35]

Payne, J.W., Bettman, J.R., Luce, M.F.: When time is money: decision behavior under opportunity-cost time pressure. Organ. Behav. Hum. Decis. Process. 66(2), 131---152 (1996)

[36]

Qiang, Q.: The closed-loop supply chain network with competition and design for remanufactureability. J. Clean. Prod. 105, 346---356 (2015)

[37]

Qiang, Q., Ke, K., Anderson, T., Dong, J.: The closed-loop supply chain network with competition, distribution channel investment, and uncertainties. Omega 41(2), 186---194 (2013)

[38]

Qiang, Q., Nagurney, A.: A bi-criteria indicator to assess supply chain network performance for critical needs under capacity and demand disruptions. Transp. Res. A 46(5), 801---812 (2012)

[39]

Qiang, Q., Nagurney, A., Dong, J.: Modeling of supply chain risk under disruptions with performance measurement and robustness analysis. In: Wu, T., Blackhurst, J. (eds.) Managing Supply Chain Risk and Vulnerability: Tools and Methods for Supply Chain Decision Makers, pp. 91---111. Springer, Berlin, Germany (2009)

[40]

Sandoval-Chavez, D.A., Beruvides, M.G.: Using opportunity costs to determine the cost of quality: a case study in a continuous-process industry. Eng. Econ. 43, 107---124 (1998)

[41]

Stevenson, A., Lindberg, C.A. (eds.): New Oxford American Dictionary, 3rd edn. Oxford University Press, England (2010)

[42]

Tang, C.S., Zimmerman, J.D., Nelson, J.I.: Managing new product development and supply chain risks: The Boeing 787 case. Supply Chain Forum 10(2), 74---86 (2009)

[43]

Tomlin, B.T.: On the value of mitigation and contingency strategies for managing supply chain disruption risks. Manag. Sci. 52, 639---657 (2006)

Digital Library

[44]

Toyasaki, F., Daniele, P., Wakolbinger, T.: A variational inequality formulation of equilibrium models for end-of-life products with nonlinear constraints. Eur. J. Oper. Res. 236, 340---350 (2014)

[45]

Wu, T., Blackhurst, J. (eds.): Managing Supply Chain Risk and Vulnerability: Tools and Methods for Supply Chain Decision Makers. Springer, Berlin, Germany (2009)

[46]

Wu, T., Blackhurst, J., Chidambaram, V.: The model for inbound supply risk analysis. Comput. Ind. 57, 350---365 (2006)

Digital Library

[47]

Yang, J.: Worst Thai floods in 50 years hit Apple, Toyota supply chain. Bloomberg (2011)

Cited By

Ghahremani Nahr JMahmoodi AGhaderi A(2022)Modeling the leader–follower supply chain network under uncertainty and solving by the HGALO algorithmSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-022-07364-626:24(13735-13764)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s00500-022-07364-6
Bu M(2021)Performance Evaluation of Enterprise Supply Chain Management Based on the Discrete Hopfield Neural NetworkComputational Intelligence and Neuroscience10.1155/2021/32507002021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/3250700
Wang YWang HGuo SMontoya F(2019)Research on Dynamic Game Model and Application of China’s Imported Soybean Price in the Context of China-US Economic and Trade FrictionComplexity10.1155/2019/60481862019Online publication date: 12-Nov-2019
https://dl.acm.org/doi/10.1155/2019/6048186
Show More Cited By

Supply chain performance assessment and supplier and component importance identification in a general competitive multitiered supply chain network model
1. Applied computing
  1. Law, social and behavioral sciences

Recommendations

Supply Chain Competition: A Market Game Approach
We study supply chains where multiple suppliers sell to multiple retailers through a wholesale market. In practice, we often observe that both suppliers and retailers tend to influence the wholesale market price that retailers pay to suppliers. However, ...
Supply chain network capacity competition with outsourcing: a variational equilibrium framework

This paper develops a supply chain network game theory framework with multiple manufacturers/producers, with multiple manufacturing plants, who own distribution centers and distribute their products, which are distinguished by brands, to demand markets, ...
Consumer Returns Policies and Supply Chain Performance

This paper develops a model of consumer returns policies. In our model, consumers face valuation uncertainty and realize their valuations only after purchase. There is also aggregate demand uncertainty, captured using the conventional newsvendor model. ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Journal of Global Optimization

Journal of Global Optimization Volume 67, Issue 1-2

January 2017

440 pages

ISSN:0925-5001

Issue’s Table of Contents

Copyright © Copyright © 2017 Springer Science+Business Media New York.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 January 2017

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

5
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 04 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Ghahremani Nahr JMahmoodi AGhaderi A(2022)Modeling the leader–follower supply chain network under uncertainty and solving by the HGALO algorithmSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-022-07364-626:24(13735-13764)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s00500-022-07364-6
Bu M(2021)Performance Evaluation of Enterprise Supply Chain Management Based on the Discrete Hopfield Neural NetworkComputational Intelligence and Neuroscience10.1155/2021/32507002021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/3250700
Wang YWang HGuo SMontoya F(2019)Research on Dynamic Game Model and Application of China’s Imported Soybean Price in the Context of China-US Economic and Trade FrictionComplexity10.1155/2019/60481862019Online publication date: 12-Nov-2019
https://dl.acm.org/doi/10.1155/2019/6048186
Nagurney ABesik DNagurney L(2019)Global supply chain networks and tariff rate quotas: equilibrium analysis with application to agricultural productsJournal of Global Optimization10.1007/s10898-019-00794-x75:2(439-460)Online publication date: 1-Oct-2019
https://dl.acm.org/doi/10.1007/s10898-019-00794-x
Nagurney AYu MBesik D(2017)Supply chain network capacity competition with outsourcingJournal of Global Optimization10.1007/s10898-017-0497-x69:1(231-254)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1007/s10898-017-0497-x

View Options

View options

Figures

Tables

Media

View Issue’s Table of Contents