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Consumption Coupons, Consumption Probability and Inventory Optimization: An Improved Minimum-Cost Maximum-Flow Approach

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  • Shunlin Wang

    (School of Business and Administration, Ningbo Polytechnic, Ningbo 315800, China)

  • Yifang Chen

    (The Dean’s Office, Ningbo Polytechnic, Ningbo 315800, China)

Abstract

The issuance of consumption coupons during the epidemic period to stimulate the economy must take full account of the level of probabilistic consumption and inventory optimization. In this paper, an improved minimum-cost maximum-flow model is constructed to dynamically adjust the inventory capacity of node enterprises with the change of probabilistic consumption level, and three scenarios are simulated by numerical assumptions. The results show that: (1) The model can better solve the problem of consumption coupons, probabilistic consumption and inventory optimization; (2) Consumer welfare remains unchanged, the largest number of government consumption coupons is issued, and the number of enterprise inventories reaches the lowest; (3) Enterprise inventories are minimized with different decisions on consumer probability consumption, and the government’s issuance of consumption coupons and the satisfaction of consumer demand have reached a dynamic balance. Corresponding suggestions are put forward, hoping to better help the government to implement the consumption coupons policy to stimulate the economy.

Suggested Citation

  • Shunlin Wang & Yifang Chen, 2022. "Consumption Coupons, Consumption Probability and Inventory Optimization: An Improved Minimum-Cost Maximum-Flow Approach," Sustainability, MDPI, vol. 14(13), pages 1-14, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7759-:d:847785
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    References listed on IDEAS

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    1. Weiwu Wang & Lingjun Liu & Yuxin Yang, 2022. "Spatial Matching Analysis and Development Strategies of County Night-Time Economy: A Case of Anning County, Yunnan Province," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
    2. Yifan Wu & Shibo Jin, 2022. "Joint pricing and inventory decision under a probabilistic selling strategy," Operational Research, Springer, vol. 22(2), pages 1209-1233, April.
    3. H. Dawid & P. Harting & M. Neugart, 2018. "Fiscal transfers and regional economic growth," Review of International Economics, Wiley Blackwell, vol. 26(3), pages 651-671, August.
    4. Jonathan Z. Zhang & Chun-Wei Chang, 2021. "Correction to: Consumer dynamics: theories, methods, and emerging directions," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 197-197, January.
    5. David Blake, 2022. "Nudges and Networks: How to Use Behavioural Economics to Improve the Life Cycle Savings-Consumption Balance," JRFM, MDPI, vol. 15(5), pages 1-17, May.
    6. Shahla Wunderlich & Kelsey Gatto & Marielle Smoller, 2018. "Consumer knowledge about food production systems and their purchasing behavior," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(6), pages 2871-2881, December.
    7. M. Palanivel & R. Uthayakumar, 2017. "A production-inventory model with promotional effort, variable production cost and probabilistic deterioration," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(1), pages 290-300, January.
    8. Anushri Maji & Asoke Kumar Bhunia & Shyamal Kumar Mondal, 2022. "A production-reliability-inventory model for a series-parallel system with mixed strategy considering shortage, warranty period, credit period in crisp and stochastic sense," OPSEARCH, Springer;Operational Research Society of India, vol. 59(3), pages 862-907, September.
    9. Jonathan Z. Zhang & Chun-Wei Chang, 2021. "Consumer dynamics: theories, methods, and emerging directions," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 166-196, January.
    10. John H. Roberts & Glen L. Urban, 1988. "Modeling Multiattribute Utility, Risk, and Belief Dynamics for New Consumer Durable Brand Choice," Management Science, INFORMS, vol. 34(2), pages 167-185, February.
    11. Fay, Scott, 2008. "Selling an opaque product through an intermediary: The case of disguising one's product," Journal of Retailing, Elsevier, vol. 84(1), pages 59-75.
    12. Kamhon Kan & Shin-Kun Peng & Ping Wang, 2017. "Understanding Consumption Behavior: Evidence from Consumers' Reaction to Shopping Vouchers," American Economic Journal: Economic Policy, American Economic Association, vol. 9(1), pages 137-153, February.
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