IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i19p12808-d935824.html
   My bibliography  Save this article

Policy of Government Subsidy for Supply Chain with Poverty Alleviation

Author

Listed:
  • Haiyan Li

    (School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 611731, China
    School of Management, Chongqing University of Technology, Chongqing 400054, China)

  • Xingzheng Ai

    (School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 611731, China)

  • Han Song

    (School of Management, Chongqing University of Technology, Chongqing 400054, China)

  • Yi He

    (School of Management, Hainan University, Haikou 570228, China)

  • Xue Zeng

    (Kunming Shipbuilding Equipment Co., Ltd., Kunming 650236, China)

  • Jiafu Su

    (International College, Krirk University, Bangkok 10220, Thailand)

Abstract

Government subsidy is a common practice in poverty alleviation. We used game theory and the mathematical model of operations management to investigate the efficiency of subsidy with different poverty scales when the firm owns the decision power of the wholesale price. Comparative analysis of the equilibrium solutions demonstrated the following results: Exclusive subsidy has a significant effect on the payoff of the poor farmer, but the dilemma is that the increase in the payoff of the poor farmer is against the payoff decrease of the regular farmer. Sharing subsidy has a counterbalancing effect on the payoff of the poor and regular farmers. Co-subsidy is the best for consumer surplus and social welfare, but it has little effect on improving the poor farmer’s payoff. Generally, when the poor farmers are in the majority, sharing subsidies or co-subsidy is more reasonable than exclusive subsidy. When the poor farmers are in the minority, exclusive or sharing subsidies will be more economical for the government than co-subsidy. Our research helps the government recognize that spending more money may achieve a poor result in poverty alleviation and help the firm realize that it is better to give more subsidies to the poor farmer than to itself. The highlights of the paper are as follows. Firstly, our work provides a new perspective in supply chain operations management with poverty alleviation by considering the participation of the poor and regular farmers together; secondly, the poverty scale is introduced into the mathematical model; thirdly, we pay attention to the impact of government subsidy to enterprise on the payoff of the poor farmer.

Suggested Citation

  • Haiyan Li & Xingzheng Ai & Han Song & Yi He & Xue Zeng & Jiafu Su, 2022. "Policy of Government Subsidy for Supply Chain with Poverty Alleviation," Sustainability, MDPI, vol. 14(19), pages 1-22, October.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12808-:d:935824
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/19/12808/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/19/12808/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ma, Shigui & He, Yong & Gu, Ran & Li, Shanshan, 2021. "Sustainable supply chain management considering technology investments and government intervention," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    2. Zhen Li & Jiao Zhang & Qingfeng Meng & Wei Zheng & Jianguo Du, 2019. "Influence of Government Subsidy on Remanufacturing Decision under Different Market Models," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-16, July.
    3. Abhijit Barman & Rubi Das & Pijus Kanti De & Shib Sankar Sana, 2021. "Optimal Pricing and Greening Strategy in a Competitive Green Supply Chain: Impact of Government Subsidy and Tax Policy," Sustainability, MDPI, vol. 13(16), pages 1-20, August.
    4. Tang, Christopher S. & Zhou, Sean, 2012. "Research advances in environmentally and socially sustainable operations," European Journal of Operational Research, Elsevier, vol. 223(3), pages 585-594.
    5. Ying Wu & Haiyan Li & Qinglong Gou & Jibao Gu, 2017. "Supply chain models with corporate social responsibility," International Journal of Production Research, Taylor & Francis Journals, vol. 55(22), pages 6732-6759, November.
    6. Yang, Xiaolei & He, Lingyun & Xia, Yufei & Chen, Yufeng, 2019. "Effect of government subsidies on renewable energy investments: The threshold effect," Energy Policy, Elsevier, vol. 132(C), pages 156-166.
    7. Jaehyung An & Soo-Haeng Cho & Christopher S. Tang, 2015. "Aggregating Smallholder Farmers in Emerging Economies," Production and Operations Management, Production and Operations Management Society, vol. 24(9), pages 1414-1429, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jielin Jing & Jianling Wang & Qingjun Wu, 2022. "Litigation Risk and Corporate Social Responsibility—Evidence from a Poverty Alleviation Campaign in China," Sustainability, MDPI, vol. 14(22), pages 1-21, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chao Lu & Weilai Huang & Haifang Cheng, 2021. "Comparative Analysis of Government Subsidy Policies in a Dynamic Green Supply Chain Considering Consumers Preference," Sustainability, MDPI, vol. 13(21), pages 1-26, October.
    2. Qi Zhang & Yong Liu & Zhiyang Liu, 2022. "Decision Analysis of Manufacturer-Led Closed-Loop Supply Chain Considering Corporate Social Responsibility," IJERPH, MDPI, vol. 19(22), pages 1-23, November.
    3. ManMohan S. Sodhi & Christopher S. Tang, 2016. "Supply chain opportunities at the bottom of the pyramid," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 43(2), pages 125-134, June.
    4. Shihong Xiao & Ying-Ju Chen & Christopher S. Tang, 2020. "Knowledge Sharing and Learning Among Smallholders in Developing Economies: Implications, Incentives, and Reward Mechanisms," Operations Research, INFORMS, vol. 68(2), pages 435-452, March.
    5. Luyi Gui & Christopher S. Tang & Shuya Yin, 2019. "Improving Microretailer and Consumer Welfare in Developing Economies: Replenishment Strategies and Market Entries," Service Science, INFORMS, vol. 21(1), pages 231-250, January.
    6. Nur Sunar & Jayashankar M. Swaminathan, 2022. "Socially relevant and inclusive operations management," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4379-4392, December.
    7. Tiziana La Rocca & Maurizio La Rocca & Francesco Fasano & Alfio Cariola, 2023. "Does a country's environmental policy affect the value of small and medium sized enterprises liquidity in the energy sector?," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 30(1), pages 277-290, January.
    8. Shen, Jiayu & Shi, Jianxin & Gao, Lingceng & Zhang, Qiang & Zhu, Kai, 2023. "Uncertain green product supply chain with government intervention," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 208(C), pages 136-156.
    9. Belhadi, Amine & Kamble, Sachin S. & Mani, Venkatesh & Venkatesh, V.G. & Shi, Yangyan, 2021. "Behavioral mechanisms influencing sustainable supply chain governance decision-making from a dyadic buyer-supplier perspective," International Journal of Production Economics, Elsevier, vol. 236(C).
    10. David Benjamin Billedeau & Jeffrey Wilson & Naima Samuel, 2022. "From Responsibility to Requirement: COVID, Cars, and the Future of Corporate Social Responsibility in Canada," Sustainability, MDPI, vol. 14(11), pages 1-16, May.
    11. Yang, Jing & Zhang, Zhiyong & Hong, Ming & Yang, Mingwan & Chen, Jiayu, 2020. "An oligarchy game model for the mobile waste heat recovery energy supply chain," Energy, Elsevier, vol. 210(C).
    12. Tan, R.R. & Aviso, K.B. & Ng, D.K.S., 2019. "Optimization models for financing innovations in green energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    13. Tarun Jain & Jishnu Hazra & T. C. E. Cheng, 2023. "Analysis of upstream pricing regulation and contract structure in an agriculture supply chain," Annals of Operations Research, Springer, vol. 320(1), pages 85-122, January.
    14. Mahdi Mahmoudzadeh, 2020. "On the Non‐Equivalence of Trade‐ins and Upgrades in the Presence of Framing Effect: Experimental Evidence and Implications for Theory," Production and Operations Management, Production and Operations Management Society, vol. 29(2), pages 330-352, February.
    15. Choi, Tsan-Ming & Chow, Pui-Sze & Lee, Chang Hwan & Shen, Bin, 2018. "Used intimate apparel collection programs: A game-theoretic analytical study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 44-62.
    16. Hong, Zhaofu & Dai, Wei & Luh, Hsing & Yang, Chenchen, 2018. "Optimal configuration of a green product supply chain with guaranteed service time and emission constraints," European Journal of Operational Research, Elsevier, vol. 266(2), pages 663-677.
    17. Shuiwang Zhang & Qianlan Ding & Jingcheng Ding, 2023. "Return Strategy of E-Commerce Platform Based on Green and Sustainable Development," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
    18. Fan, Lurong & Xu, Jiuping, 2020. "Authority–enterprise equilibrium based mixed subsidy mechanism for carbon reduction and energy utilization in the coalbed methane industry," Energy Policy, Elsevier, vol. 147(C).
    19. Song, Yang & Zhang, Zhiyuan & Sahut, Jean-Michel & Rubin, Ofir, 2023. "Incentivizing green technology innovation to confront sustainable development," Technovation, Elsevier, vol. 126(C).
    20. Wanke, Peter Fernandes & Chiappetta Jabbour, Charbel José & Moreira Antunes, Jorge Junio & Lopes de Sousa Jabbour, Ana Beatriz & Roubaud, David & Sobreiro, Vinicius Amorim & Santibanez Gonzalez‬, Erne, 2021. "An original information entropy-based quantitative evaluation model for low-carbon operations in an emerging market," International Journal of Production Economics, Elsevier, vol. 234(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12808-:d:935824. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.