A behavioral experiment on inventory management with supply chain disruption

Sourish Sarkar, Sanjay Kumar

Research output: Contribution to journalArticle

34 Scopus citations

Abstract

Various operational strategies for mitigating supply chain disruption have been studied theoretically, but few studies have investigated behavioral decision-making in multi-echelon supply chains experiencing disruptions. We explore the effects of communicating disruption information in real-time to supply chain members using the beer distribution game in a controlled laboratory setting. Both upstream (manufacturer) and downstream (retailer) disruptions are independently considered, and in each of these scenarios, the difference between sharing and not sharing the disruption information is investigated. We find that supply chain disruptions may cause higher order variability when compared to the base case (no disruption). For a disruption at an upstream echelon, sharing the disruption information is found beneficial in reducing order variability and supply chain cost - upstream echelons experience more benefits from information sharing than downstream echelons. Therefore, we advocate that manufacturers share supply disruption information in real-time in order to benefit from a reduced bullwhip effect and its associated costs. For a disruption at a downstream echelon, sharing disruption information does not appear to have a significant benefit. Past studies have shown the importance of sharing downstream inventory information with upstream supply chain members. In the event of disruptions, our results demonstrate that sharing upstream disruption information with downstream members is beneficial.

Original languageEnglish (US)
Pages (from-to)169-178
Number of pages10
JournalInternational Journal of Production Economics
Volume169
DOIs
StatePublished - Nov 1 2015

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Economics and Econometrics
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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