Retailer inventory data sharing in a fresh product supply chain

Michael Ketzenberg, Rogelio Oliva, Yimin Wang, Scott Webster

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

This research explores the value of data sharing in a two-echelon, fresh product supply chain consisting of a retailer and manufacturer. Demand is stochastic and price sensitive. Decision-making is decentralized and the supply chain operates with a simple linear wholesale price contract. We employ a game theoretic model in which the manufacturer is a Stackelberg leader. Although fresh product supply chains are ubiquitous in the marketplace, academic guidance is limited, particularly in the context of data sharing and when price is determined endogenously. Our analysis shows that although data sharing helps to improve product freshness and reduce waste, sufficiently improved product freshness is the key for both suppliers and retailers to benefit financially. Otherwise, either party or the entire supply chain can be worse off. We demonstrate that data sharing is most valuable when product is somewhat perishable and demand is volatile. For highly perishable or non-perishable products, the manufacturer benefits but the retailer is harmed. Our results suggest that the drivers that motivate retailers to share inventory data in a fresh product supply chain are distinct from extant knowledge. The results provide insight into strategies that not only improve both parties’ performance, but also reduce food waste at the same time.

Original languageEnglish (US)
JournalEuropean Journal of Operational Research
DOIs
StateAccepted/In press - 2022

Keywords

  • Data sharing
  • Inventory
  • Perishable
  • Pricing

ASJC Scopus subject areas

  • General Computer Science
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management
  • Industrial and Manufacturing Engineering

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