Dynamic supply chain decisions based on networked sensor data: An application in the chilled food retail chain

Dong Li, Xiaojun Wang

Research output: Contribution to journalArticle (Academic Journal)peer-review

64 Citations (Scopus)
656 Downloads (Pure)


With large volume of product flows and complex supply chain processes, more data than ever before is being generated and collected in supply chains through various tracking and sensory technologies. The purpose of this study is to show a potential scenario of using a prototype tracking tool that facilitate the utilisation of sensor data, which is often unstructured and enormous in nature, to support supply chain decisions. The research investigates the potential benefits of the chilled food chain management innovation through sensor data driven pricing decisions. Data generated and recorded through the sensor network are used to predict the remaining shelf-life of perishable foods. Numerical analysis is conducted to examine the benefit of proposed approach under various operational situations and product features. The research findings demonstrate a way of modelling pricing and potential of performance improvement in chilled food chains to provide a vision of smooth transfer and implementation of the sensor data driven supply chain management. The research finding would encourage firms in the food industry to explore innovation opportunities from big data and develop proper data driven strategies to improve their competitiveness.
Original languageEnglish
Pages (from-to) 5127-5141
Number of pages15
JournalInternational Journal of Production Research
Issue number17
Early online date27 May 2015
Publication statusPublished - 2017

Structured keywords

  • Smart Networks for Sustainable Futures


  • sensor data
  • food supply chain
  • tracking and monitoring
  • shelf-life prediction


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