IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v10y2022i7p139-d860919.html
   My bibliography  Save this article

Financing Cooperative Supply Chain Members—The Bank’s Perspective

Author

Listed:
  • Péter Juhász

    (Department of Finance, Corvinus University of Budapest, 1093 Budapest, Hungary)

  • Nóra Felföldi-Szűcs

    (Department of Finance, Corvinus University of Budapest, 1093 Budapest, Hungary)

Abstract

This paper contributes to the supply chain finance literature with an agent-based Monte Carlo simulation model focusing on the bank’s point of view. Our theoretical model assesses how a bank should screen a supply chain (SC) member and whether that requires different considerations and monitoring systems compared with traditional corporate loans. In the model, the SC members may cooperate, reducing their bankruptcy risk considerably; thus, the chance for and extent of inter-entity financial aid are critical to consider when assessing bankruptcy risk. A cooperative SC member cannot just be financed from debt taken by other members, but it may also offer protection to other SC members using its operating cash flow. Thus, based on our results, bankruptcy risk is SC-specific, rather than a characteristic of an individual firm. Therefore, to finance an SC member is a quasi-joint decision of its peers, so particular care should be paid to estimating and monitoring the correlations between the operational cash flows of cooperative SC members. One of the key results is that of edge default exposure of the bank; it might be optimal to limit the amount of the loan made available to a given collaborative SC member instead of charging higher rates or financing the most attractive SC member only. Another SC member offering an additional guarantee with its assets will provide the remaining need for financing. As this solution also reduces the total bankruptcy risk of the SC, the SC itself should prefer this financing structure.

Suggested Citation

  • Péter Juhász & Nóra Felföldi-Szűcs, 2022. "Financing Cooperative Supply Chain Members—The Bank’s Perspective," Risks, MDPI, vol. 10(7), pages 1-17, July.
  • Handle: RePEc:gam:jrisks:v:10:y:2022:i:7:p:139-:d:860919
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/10/7/139/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-9091/10/7/139/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jin, Wei & Zhang, Qinhong & Luo, Jianwen, 2019. "Non-collaborative and collaborative financing in a bilateral supply chain with capital constraints," Omega, Elsevier, vol. 88(C), pages 210-222.
    2. Wuttke, David A. & Blome, Constantin & Henke, Michael, 2013. "Focusing the financial flow of supply chains: An empirical investigation of financial supply chain management," International Journal of Production Economics, Elsevier, vol. 145(2), pages 773-789.
    3. He, Hua, 1990. "Convergence from Discrete- to Continuous-Time Contingent Claims Prices," The Review of Financial Studies, Society for Financial Studies, vol. 3(4), pages 523-546.
    4. Richard Bookstaber & Mark Paddrik & Brian Tivnan, 2018. "An agent-based model for financial vulnerability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(2), pages 433-466, July.
    5. Naveen Khanna & Sheri Tice, 2001. "The Bright Side of Internal Capital Markets," Journal of Finance, American Finance Association, vol. 56(4), pages 1489-1528, August.
    6. Camerinelli, Enrico, 2009. "Supply chain finance," Journal of Payments Strategy & Systems, Henry Stewart Publications, vol. 3(2), pages 114-128, April.
    7. WUTTKE, David A & BLOME, Constantin & HENKE, Michael, 2013. "Focusing the financial flow of supply chains: an empirical investigation of financial supply chain management," LIDAM Reprints CORE 2601, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Richard Bookstaber, 2012. "Using Agent-Based Models for Analyzing Threats to Financial Stability," Working Papers 12-03, Office of Financial Research, US Department of the Treasury.
    9. Srinivasa Raghavan, N.R. & Mishra, Vinit Kumar, 2011. "Short-term financing in a cash-constrained supply chain," International Journal of Production Economics, Elsevier, vol. 134(2), pages 407-412, December.
    10. Berger, Philip G. & Ofek, Eli, 1995. "Diversification's effect on firm value," Journal of Financial Economics, Elsevier, vol. 37(1), pages 39-65, January.
    11. Subramaniam, Venkat & Tang, Tony T. & Yue, Heng & Zhou, Xin, 2011. "Firm structure and corporate cash holdings," Journal of Corporate Finance, Elsevier, vol. 17(3), pages 759-773, June.
    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. Tseng, Ming-Lang & Lim, Ming K. & Wu, Kuo-Jui, 2019. "Improving the benefits and costs on sustainable supply chain finance under uncertainty," International Journal of Production Economics, Elsevier, vol. 218(C), pages 308-321.
    2. Wetzel, Philipp & Hofmann, Erik, 2019. "Supply chain finance, financial constraints and corporate performance: An explorative network analysis and future research agenda," International Journal of Production Economics, Elsevier, vol. 216(C), pages 364-383.
    3. 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.
    4. Zhang, Tiantian & Zhang, Cherry Yi & Pei, Qifan, 2019. "Misconception of providing supply chain finance: Its stabilising role," International Journal of Production Economics, Elsevier, vol. 213(C), pages 175-184.
    5. Yuting Li & Tong Chen & Baogui Xin, 2016. "Optimal Financing Decisions of Two Cash-Constrained Supply Chains with Complementary Products," Sustainability, MDPI, vol. 8(5), pages 1-17, April.
    6. Zhu, You & Zhou, Li & Xie, Chi & Wang, Gang-Jin & Nguyen, Truong V., 2019. "Forecasting SMEs' credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach," International Journal of Production Economics, Elsevier, vol. 211(C), pages 22-33.
    7. Zhang, Wen & Yan, Shaoshan & Li, Jian & Tian, Xin & Yoshida, Taketoshi, 2022. "Credit risk prediction of SMEs in supply chain finance by fusing demographic and behavioral data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    8. Jia, Fu & Blome, Constantin & Sun, Hui & Yang, Yang & Zhi, Bangdong, 2020. "Towards an integrated conceptual framework of supply chain finance: An information processing perspective," International Journal of Production Economics, Elsevier, vol. 219(C), pages 18-30.
    9. Chakuu, Sumeer & Masi, Donato & Godsell, Janet, 2019. "Exploring the relationship between mechanisms, actors and instruments in supply chain finance: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 216(C), pages 35-53.
    10. Pan, Ailing & Xu, Lei & Li, Bin & Ling, Runze, 2020. "The impact of supply chain finance on firm cash holdings: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 63(C).
    11. Hua Song & Sijie Chen & Anirban Ganguly, 2019. "Innovative Ecosystem In Enhancing Hi-Tech Sme Financing: Mediating Role Of Two Types Of Innovation Capabilities," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 24(02), pages 1-36, April.
    12. Ratri Parida & Manoj Kumar Dash & Anil Kumar & Edmundas Kazimieras Zavadskas & Sunil Luthra & Eyob Mulat‐weldemeskel, 2022. "Evolution of supply chain finance: A comprehensive review and proposed research directions with network clustering analysis," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(5), pages 1343-1369, October.
    13. Song, Hua & Yang, Xuan & Yu, Kangkang, 2020. "How do supply chain network and SMEs’ operational capabilities enhance working capital financing? An integrative signaling view," International Journal of Production Economics, Elsevier, vol. 220(C).
    14. Mou, W.M. & Wong, W.-K. & McAleer, M.J., 2018. "Financial Credit Risk and Core Enterprise Supply Chains," Econometric Institute Research Papers EI2018-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    15. Ferris, Stephen P. & Kim, Kenneth A. & Kitsabunnarat, Pattanaporn, 2003. "The costs (and benefits?) of diversified business groups: The case of Korean chaebols," Journal of Banking & Finance, Elsevier, vol. 27(2), pages 251-273, February.
    16. Lee, Sangwon, 2022. "Internal capital markets, corporate investment, and the COVID-19 pandemic: Evidence from Korean business groups," International Review of Financial Analysis, Elsevier, vol. 80(C).
    17. Kangning Zheng & Zuopeng Zhang & Jeffrey Gauthier, 2022. "RETRACTED ARTICLE: Blockchain-based intelligent contract for factoring business in supply chains," Annals of Operations Research, Springer, vol. 308(1), pages 777-797, January.
    18. Dekkers, Rob & de Boer, Ronald & Gelsomino, Luca Mattia & de Goeij, Christiaan & Steeman, Michiel & Zhou, Qijun & Sinclair, Scott & Souter, Victoria, 2020. "Evaluating theoretical conceptualisations for supply chain and finance integration: A Scottish focus group," International Journal of Production Economics, Elsevier, vol. 220(C).
    19. Murillo Campello, 2002. "Internal Capital Markets in Financial Conglomerates: Evidence from Small Bank Responses to Monetary Policy," Journal of Finance, American Finance Association, vol. 57(6), pages 2773-2805, December.
    20. João Silvestre, 2017. "Sovereign default contagion: an agent-based model approach," Working Papers Department of Economics 2017/08, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.

    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:jrisks:v:10:y:2022:i:7:p:139-:d:860919. 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.