IDEAS home Printed from https://ideas.repec.org/a/ags/aareaj/338512.html
   My bibliography  Save this article

Optimal financing and operation strategy of fresh agricultural supply chain

Author

Listed:
  • Yan, Bo
  • Liu, Gaodi
  • Zhenyu, Zhang
  • Chang, Yan

Abstract

Increased market demand and expanded scales of production of fresh agricultural products by small and medium-sized enterprises (SMEs) have highlighted the challenge of funding sufficient infrastructure. Additional costs to improve the freshness of produce makes the optimal financial and operational policies different for these enterprises. On the basis of the characteristics of the fresh agricultural supply chain, this paper analyses the financing strategies adopted by SMEs and obtains optimal operational and financing strategies for SMEs in six different situations. The analysis shows that the optimal level of financing by SMEs is not only affected by the financing rate, but also negatively related to the freshness effort cost coefficient, and is positively related to the sensitivity coefficient of market freshness. Moreover, although the cost of improving the freshness level of the producte is only borne by the SME, the supply chain cannot maximise profit from the optimal financial strategies of SMEs. Shouldering the fresh effort cost also lessens the optimal financing requirement of the SME compared with that of the entire supply chain. The difference is affected by the fresh effort cost coefficient.

Suggested Citation

  • Yan, Bo & Liu, Gaodi & Zhenyu, Zhang & Chang, Yan, 2020. "Optimal financing and operation strategy of fresh agricultural supply chain," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(3), July.
  • Handle: RePEc:ags:aareaj:338512
    DOI: 10.22004/ag.econ.338512
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/338512/files/ajar12375.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.338512?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Qin, Yiyan & Wang, Jianjun & Wei, Caimin, 2014. "Joint pricing and inventory control for fresh produce and foods with quality and physical quantity deteriorating simultaneously," International Journal of Production Economics, Elsevier, vol. 152(C), pages 42-48.
    2. Xiaoheng Zhang & Ping Qing & Xiaohua Yu, 2019. "Short supply chain participation and market performance for vegetable farmers in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(2), pages 282-306, April.
    3. Onur Boyabatlı & L. Beril Toktay, 2011. "Stochastic Capacity Investment and Flexible vs. Dedicated Technology Choice in Imperfect Capital Markets," Management Science, INFORMS, vol. 57(12), pages 2163-2179, December.
    4. Kate Ambler & Alan de Brauw & Susan Godlonton, 2018. "Measuring postharvest losses at the farm level in Malawi," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(1), pages 139-160, January.
    5. Onur Boyabatlı & Paul R. Kleindorfer & Stephen R. Koontz, 2011. "Integrating Long-Term and Short-Term Contracting in Beef Supply Chains," Management Science, INFORMS, vol. 57(10), pages 1771-1787, October.
    6. Wang, Xiaojun & Li, Dong, 2012. "A dynamic product quality evaluation based pricing model for perishable food supply chains," Omega, Elsevier, vol. 40(6), pages 906-917.
    7. Zhao, Lima & Huchzermeier, Arnd, 2015. "Operations–finance interface models: A literature review and framework," European Journal of Operational Research, Elsevier, vol. 244(3), pages 905-917.
    8. Duan, Qinglin & Liao, T. Warren, 2013. "A new age-based replenishment policy for supply chain inventory optimization of highly perishable products," International Journal of Production Economics, Elsevier, vol. 145(2), pages 658-671.
    9. Longinidis, Pantelis & Georgiadis, Michael C., 2011. "Integration of financial statement analysis in the optimal design of supply chain networks under demand uncertainty," International Journal of Production Economics, Elsevier, vol. 129(2), pages 262-276, February.
    10. Li, Bo & Arreola-Risa, Antonio, 2017. "Financial risk, inventory decision and process improvement for a firm with random capacity," European Journal of Operational Research, Elsevier, vol. 260(1), pages 183-194.
    11. Anderson, Edward & Monjardino, Marta, 2019. "Contract design in agriculture supply chains with random yield," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1072-1082.
    12. Li, Xiang & Li, Yongjian & Cai, Xiaoqiang, 2013. "Double marginalization and coordination in the supply chain with uncertain supply," European Journal of Operational Research, Elsevier, vol. 226(2), pages 228-236.
    13. Peng, Juan & Zhou, Zhili, 2019. "Working capital optimization in a supply chain perspective," European Journal of Operational Research, Elsevier, vol. 277(3), pages 846-856.
    Full references (including those not matched with items on IDEAS)

    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. Bo Yan & Gaodi Liu & Zhenyu Zhang & Chang Yan, 2020. "Optimal financing and operation strategy of fresh agricultural supply chain," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(3), pages 776-794, July.
    2. Janssen, Larissa & Claus, Thorsten & Sauer, Jürgen, 2016. "Literature review of deteriorating inventory models by key topics from 2012 to 2015," International Journal of Production Economics, Elsevier, vol. 182(C), pages 86-112.
    3. Ni, Jian & Chu, Lap Keung & Li, Qiang, 2017. "Capacity decisions with debt financing: The effects of agency problem," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1158-1169.
    4. Onur Boyabatlı, 2015. "Supply Management in Multiproduct Firms with Fixed Proportions Technology," Management Science, INFORMS, vol. 61(12), pages 3013-3031, December.
    5. Yong He & Hongfu Huang & Dong Li, 2020. "Inventory and pricing decisions for a dual-channel supply chain with deteriorating products," Operational Research, Springer, vol. 20(3), pages 1461-1503, September.
    6. Buisman, M.E. & Haijema, R. & Bloemhof-Ruwaard, J.M., 2019. "Discounting and dynamic shelf life to reduce fresh food waste at retailers," International Journal of Production Economics, Elsevier, vol. 209(C), pages 274-284.
    7. Zhangwei Feng & Peng Jin & Guiping Li, 2023. "Investment Decision of Blockchain Technology in Fresh Food Supply Chains Considering Misreporting Behavior," Sustainability, MDPI, vol. 15(9), pages 1-19, April.
    8. Pan, Fei & Zhou, Wei & Fan, Tijun & Li, Shuxia & Zhang, Chong, 2021. "Deterioration rate variation risk for sustainable cross-docking service operations," International Journal of Production Economics, Elsevier, vol. 232(C).
    9. Dilupa Nakandala & Henry Lau & Paul K.C. Shum, 2017. "A lateral transshipment model for perishable inventory management," International Journal of Production Research, Taylor & Francis Journals, vol. 55(18), pages 5341-5354, September.
    10. Nilanjan Dutta & Arshinder Kaur, 2023. "Enabling socially responsible operations: A decision-making model for a firm contracting with decision-biased smallholders," Annals of Operations Research, Springer, vol. 320(1), pages 509-533, January.
    11. Yiping Jiang & Liangqi Chen & Yan Fang, 2018. "Integrated Harvest and Distribution Scheduling with Time Windows of Perishable Agri-Products in One-Belt and One-Road Context," Sustainability, MDPI, vol. 10(5), pages 1-13, May.
    12. Xu, Xinhan & Chen, Xiangfeng & Jia, Fu & Brown, Steve & Gong, Yu & Xu, Yifan, 2018. "Supply chain finance: A systematic literature review and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 204(C), pages 160-173.
    13. Kouki, Chaaben & Jouini, Oualid, 2015. "On the effect of lifetime variability on the performance of inventory systems," International Journal of Production Economics, Elsevier, vol. 167(C), pages 23-34.
    14. Asl-Najafi, Javad & Yaghoubi, Saeed & Zand, Fatemeh, 2021. "Dual-channel supply chain coordination considering targeted capacity allocation under uncertainty," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 187(C), pages 566-585.
    15. Sim, Jaehun & Prabhu, Vittaldas, 2017. "A microcredit contract model with a Black Scholes model under default risk," International Journal of Production Economics, Elsevier, vol. 193(C), pages 294-305.
    16. Palsule-Desai, Omkar D., 2021. "Multi-product supply networks: Implications of intermediaries," European Journal of Operational Research, Elsevier, vol. 292(3), pages 909-929.
    17. Abdelrahman Ali & Chunping Xia & Moustafa Ismaiel & N’Banan Ouattara & Irfan Mahmood & Dessalegn Anshiso, 2021. "Analysis of determinants to mitigate food losses and waste in the developing countries: empirical evidence from Egypt," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 26(6), pages 1-26, August.
    18. Hezarkhani, Behzad & Demirel, Guven & Bouchery, Yann & Dora, Manoj, 2023. "Can “ugly veg” supply chains reduce food loss?," European Journal of Operational Research, Elsevier, vol. 309(1), pages 117-132.
    19. Jiao Wang & Lima Zhao & Arnd Huchzermeier, 2021. "Operations‐Finance Interface in Risk Management: Research Evolution and Opportunities," Production and Operations Management, Production and Operations Management Society, vol. 30(2), pages 355-389, February.
    20. Jing He & Ting Yang, 2022. "Differential Game Analysis of Emission Reduction and Preservation in the Tertiary Food Supply Chain under Different Government Subsidy Models," Sustainability, MDPI, vol. 15(1), pages 1-16, December.

    More about this item

    Keywords

    Industrial Organization;

    Statistics

    Access and download statistics

    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:ags:aareaj:338512. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaresea.html .

    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.