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Supply disruption management under consumer panic buying and social learning effects

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  • Zheng, Rui
  • Shou, Biying
  • Yang, Jun

Abstract

This study investigates the impact of consumers’ social learning (SL) behavior on their purchase decisions under supply disruption risk, and accordingly, how retailers should take this into account and optimize their inventory ordering strategy. We develop a model with two batches of consumers. The first batch of consumers evaluates the potential supply disruption risk and decides whether to stockpile extra units for future consumption (i.e., panic buying). Their purchase decisions influence the second batch of consumers via social learning. We derive the optimal inventory ordering policy for the retailer and evaluate the retailer’s loss of profit if the impact of SL is not taken into consideration. We show that when the portion of panic buying consumers among the first batch (which we define as the initial panic intensity) is at a moderate level, consumer panic buying and SL behaviors can be beneficial for the retailer and the social welfare. In contrast, if the initial panic intensity is very low or very high, SL can hurt the retailer’s profit and the total social welfare.

Suggested Citation

  • Zheng, Rui & Shou, Biying & Yang, Jun, 2021. "Supply disruption management under consumer panic buying and social learning effects," Omega, Elsevier, vol. 101(C).
  • Handle: RePEc:eee:jomega:v:101:y:2021:i:c:s0305048319307959
    DOI: 10.1016/j.omega.2020.102238
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    6. Raktim Pal & Nezih Altay, 2023. "The missing link in disruption management research: coping," Operations Management Research, Springer, vol. 16(1), pages 433-449, March.
    7. Xu, Qingyun & He, Yi & Shao, Zhen, 2023. "Retailer's ordering decisions with consumer panic buying under unexpected events," International Journal of Production Economics, Elsevier, vol. 266(C).
    8. Choi, Tsan-Ming & Shi, Xiutian, 2022. "Reducing supply risks by supply guarantee deposit payments in the fashion industry in the “new normal after COVID-19”," Omega, Elsevier, vol. 109(C).
    9. Ekinci, Esra & Mangla, Sachin Kumar & Kazancoglu, Yigit & Sarma, P.R.S. & Sezer, Muruvvet Deniz & Ozbiltekin-Pala, Melisa, 2022. "Resilience and complexity measurement for energy efficient global supply chains in disruptive events," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    10. Li, Dong & Dong, Chuanwen, 2022. "Government regulations to mitigate the shortage of life-saving goods in the face of a pandemic," European Journal of Operational Research, Elsevier, vol. 301(3), pages 942-955.
    11. Yuanfang Lin & Xuezhu Wang & Tirtha Dhar, 2021. "Impact of Information on Food Stocking during Early Period of COVID-19 Outbreak: Survey Exploration between Canada and US Consumers," International Business Research, Canadian Center of Science and Education, vol. 14(2), pages 1-72, February.
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    13. Jhanghiz Syahrivar & Genoveva Genoveva & Chairy Chairy & Siska Purnama Manurung, 2021. "COVID-19-Induced Hoarding Intention Among the Educated Segment in Indonesia," SAGE Open, , vol. 11(2), pages 21582440211, May.
    14. Abu Elnasr E. Sobaih & Fatheya Moustafa, 2022. "Panic Food Purchasing amid COVID-19 Pandemic: Does the Impact of Perceived Severity, Anxiety and Self-Isolation Really Matter?," IJERPH, MDPI, vol. 19(22), pages 1-16, November.
    15. Mohammad Alamgir Hossain & Md. Maruf Hossan Chowdhury & Ilias O. Pappas & Bhimaraya Metri & Laurie Hughes & Yogesh K. Dwivedi, 2023. "Fake news on Facebook and their impact on supply chain disruption during COVID-19," Annals of Operations Research, Springer, vol. 327(2), pages 683-711, August.
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