Managing disruptions in decentralized supply chains with endogenous supply process reliability

Sammi Y. Tang, Haresh Gurnani, Diwakar Gupta

Research output: Contribution to journalArticlepeer-review

77 Scopus citations

Abstract

Supply disruptions are all too common in supply chains. To mitigate delivery risk, buyers may either source from multiple suppliers or offer incentives to their preferred supplier to improve its process reliability. These incentives can be either direct (investment subsidy) or indirect (inflated order quantity). In this study, we present a series of models to highlight buyers' and suppliers' optimal parameter choices. Our base-case model has deterministic buyer demand and two possibilities for the supplier yield outcomes: all-or-nothing supply or partial disruption. For the all-or-nothing model, we show that the buyer prefers to only use the subsidy option, which obviates the need to inflate order quantity. However, in the partial disruption model, both incentives - subsidy and order inflation - may be used at the same time. Although single sourcing provides greater indirect incentive to the selected supplier because that avoids order splitting, we show that the buyer may prefer the diversification strategy under certain circumstances. We also quantify the amount by which the wholesale price needs to be discounted (if at all) to ensure that dual sourcing strategy dominates sole sourcing. Finally, we extend the model to the case of stochastic demand. Structural properties of ordering/subsidy decisions are derived for the all-or-nothing model, and in contrast to the deterministic demand case, we establish that the buyer may increase use of subsidy and order quantity at the same time.

Original languageEnglish (US)
Pages (from-to)1198-1211
Number of pages14
JournalProduction and Operations Management
Volume23
Issue number7
DOIs
StatePublished - Jul 2014

Keywords

  • dual sourcing
  • incentive mechanism
  • process improvement
  • supply disruption

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Management of Technology and Innovation

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