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Use of twitter data for waste minimisation in beef supply chain

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  • Nishikant Mishra

    (University of East Anglia)

  • Akshit Singh

    (University of East Anglia)

Abstract

Approximately one third of the food produced is discarded or lost, which accounts for 1.3 billion tons per annum. The waste is being generated throughout the supply chain viz. farmers, wholesalers/processors, logistics, retailers and consumers. The majority of waste occurs at the interface of retailers and consumers. Many global retailers are making efforts to extract intelligence from customer’s complaints left at retail store to backtrack their supply chain to mitigate the waste. However, majority of the customers don’t leave the complaints in the store because of various reasons like inconvenience, lack of time, distance, ignorance etc. In current digital world, consumers are active on social media and express their sentiments, thoughts, and opinions about a particular product freely. For example, on an average, 45,000 tweets are tweeted daily related to beef products to express their likes and dislikes. These tweets are large in volume, scattered and unstructured in nature. In this study, twitter data is utilised to develop waste minimization strategies by backtracking the supply chain. The execution process of proposed framework is demonstrated for beef supply chain. The proposed model is generic enough and can be applied to other domains as well.

Suggested Citation

  • Nishikant Mishra & Akshit Singh, 2018. "Use of twitter data for waste minimisation in beef supply chain," Annals of Operations Research, Springer, vol. 270(1), pages 337-359, November.
    • Handle: RePEc:spr:annopr:v:270:y:2018:i:1:d:10.1007_s10479-016-2303-4
    DOI: 10.1007/s10479-016-2303-4
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    1. Tanya Roberts & Jean C. Buzby & Michael Ollinger, 1996. "Using Benefit and Cost Information to Evaluate a Food Safety Regulation: HACCP for Meat and Poultry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(5), pages 1297-1301.
    2. Unnevehr, Laurian J. & Bard, Sharon K., 1993. "Beef Quality: Will Consumers Pay For Less Fat?," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 18(2), pages 1-8, December.
    3. Singh, Akshit & Mishra, Nishikant & Ali, Syed Imran & Shukla, Nagesh & Shankar, Ravi, 2015. "Cloud computing technology: Reducing carbon footprint in beef supply chain," International Journal of Production Economics, Elsevier, vol. 164(C), pages 462-471.
    4. Mena, Carlos & Terry, Leon A. & Williams, Adrian & Ellram, Lisa, 2014. "Causes of waste across multi-tier supply networks: Cases in the UK food sector," International Journal of Production Economics, Elsevier, vol. 152(C), pages 144-158.
    5. Jensen, Helen H. & Unnevehr, Laurian J. & Gomez, Miguel I., 1998. "Costs Of Improving Food Safety In The Meat Sector," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 30(1), pages 1-12, July.
    6. Tan, Kim Hua & Zhan, YuanZhu & Ji, Guojun & Ye, Fei & Chang, Chingter, 2015. "Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph," International Journal of Production Economics, Elsevier, vol. 165(C), pages 223-233.
    7. Chae, Bongsug (Kevin), 2015. "Insights from hashtag #supplychain and Twitter Analytics: Considering Twitter and Twitter data for supply chain practice and research," International Journal of Production Economics, Elsevier, vol. 165(C), pages 247-259.
    8. Hazen, Benjamin T. & Boone, Christopher A. & Ezell, Jeremy D. & Jones-Farmer, L. Allison, 2014. "Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications," International Journal of Production Economics, Elsevier, vol. 154(C), pages 72-80.
    9. Cicatiello, Clara & Franco, Silvio & Pancino, Barbara & Blasi, Emanuele, 2016. "The value of food waste: An exploratory study on retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 30(C), pages 96-104.
    10. Kaplan, Andreas M. & Haenlein, Michael, 2011. "Two hearts in three-quarter time: How to waltz the social media/viral marketing dance," Business Horizons, Elsevier, vol. 54(3), pages 253-263, May.
    11. Cox, Andrew & Chicksand, Dan, 2005. "The Limits of Lean Management Thinking:: Multiple Retailers and Food and Farming Supply Chains," European Management Journal, Elsevier, vol. 23(6), pages 648-662, December.
    12. Nicholas E. Piggott & Thomas L. Marsh, 2004. "Does Food Safety Information Impact U.S. Meat Demand?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(1), pages 154-174.
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