Modeling and analysis of the multiperiod effects of social relationship on supply chain networks

Jose M. Cruz, Zugang Liu

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

In this paper, we analyze the effects of levels of social relationship on a multiperiod supply chain network with multiple decision-makers (suppliers, manufacturers, and retailers) associated at different tiers. The model incorporates the individual attitudes towards disruption and opportunism risks and allows us to investigate the interplay of the heterogeneous decision-makers and to compute the resultant network equilibrium pattern of production, transactions, prices, and levels of social relationship over the multiperiod planning horizon. In our analysis, we focus on the following questions: (1) how do the evolving relationships affect the profitability and risks of supply chain firms as well as the prices and demands of the product in the market? (2) how do the relationships with the upstream supply chain firms affect the relationships with the downstream firms, and how these relationships influence the profitability and risks of the supply chain firms? (3) how do the supply disruption risks interact with the opportunism risks through supply chain relationships, and how these risks influence the profitability of the firms? The results show that high levels of relationship can lead to lower supply chain overall cost, lower risk, lower prices, higher product transaction and therefore higher profit.

Original languageEnglish (US)
Pages (from-to)39-52
Number of pages14
JournalEuropean Journal of Operational Research
Volume214
Issue number1
DOIs
StatePublished - Oct 1 2011

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

Fingerprint Dive into the research topics of 'Modeling and analysis of the multiperiod effects of social relationship on supply chain networks'. Together they form a unique fingerprint.

Cite this