en pl
en pl

Central European Management Journal

Zobacz wydanie
Rok 3/2021 
Tom 29 
Numer 1

Supply Chain Finance Factors: An Interpretive Structural Modeling Approach

Zericho Marak
Symbiosis International University, Symbiosis School of Banking and Finance

Deepa Pillai
Symbiosis International University, Symbiosis School of Banking and Finance

3/2021 29 (1) Central European Management Journal

DOI 10.7206/cemj.2658-0845.42

Abstrakt

Purpose: The present study aims to identify the critical factors of supply chain finance and the interrelationship between the factors using interpretive structural modeling.

Methodology: Factors of supply chain finance were identified from the literature and experts from both industry and academia were consulted to assess the contextual relationships between the factors. Then, we applied interpretive structural modeling to examine the interrelationships between these factors and find out the critical factors.

Findings: The model outcome indicates information sharing and workforce to be the most influential factors, followed by the automation of trade and financial attractiveness.

Originality/value: Previous literature identified various factors that influence supply chain finance. However, studies showing interrelationships between these factors are lacking. This study is unique in the field as it applies total interpretive structural modeling for assessing the factors that affect supply chain finance. Our model will aid practitioners’ decision-making and the adoption of supply chain finance by providing a necessary framework.

Powiązania

  1. Ahmad, M., Tang, X.W., Qiu, J.N., and Ahmad, F. (2019). Interpretive structural modeling and MICMAC analysis for identifying and benchmarking significant factors of seismic soil liquefaction. Applied Sciences, 9(2), 233. https://doi.org/10.3390/app9020233. [Google Scholar]
  2. Ando, N., and Rhee, D.K. (2009). Antecedents of interorganizational trust: joint decision-making, cultural adaptation, and bargaining power. Journal of Asia Business Studies, 3(2), 16–29. https://doi.org/10.1108/15587890980001513. [Google Scholar]
  3. Angerhofer, B.J., and Angelides, M.C. (2006). A model and a performance measurement system for collaborative supply chains. Decision support systems, 42(1), 283–301. https://doi.org/10.1016/j.dss.2004.12.005. [Google Scholar]
  4. Agarwal, A., Shankar, R., and Tiwari, M.K. (2007). Modeling agility of supply chain. Industrial marketing management, 36(4), 443–457. https://doi.org/10.1016/j.indmarman.2005.12.004. [Google Scholar]
  5. Ali, Z., Gongbing, B., and Mehreen, A. (2018). Does supply chain finance improve SMEs performance? The moderating role of trade digitization. Business Process Management Journal. https://doi.org/10.1108/BPMJ-05-2018-0133. [Google Scholar]
  6. Al-Muftah, H., Weerakkody, V., Rana, N.P., Sivarajah, U., and Irani, Z. (2018). Factors influencing e-diplomacy implementation: Exploring causal relationships using interpretive structural modelling. Government Information Quarterly, 35(3), 502–514. https://doi.org/10.1016/j.giq.2018.03.002 [Google Scholar]
  7. Asian Development Bank (2017). Trade Finance Gaps, Growth, and Jobs Survey. [Google Scholar]
  8. Attri, R., Dev, N., and Sharma, V. (2013). Interpretive structural modelling (ISM) approach: an overview. Research Journal of Management Sciences, 2(2), 3–8. [Google Scholar]
  9. Babich, V., and Kouvelis, P. (2018). Introduction to the special issue on research at the interface of finance, operations, and risk management (iFORM): Recent contributions and future directions. Manufacturing & Service Operations Management, 20, 1–160. https://doi.org/10.1287/msom.2018.0706 [Google Scholar]
  10. Baykasoğlu, A., and Gölcük, İ. (2017). Development of a two-phase structural model for evaluating ERP critical success factors along with a case study. Computers & Industrial Engineering, 106, 256–274. https://doi.org/10.1016/j.cie.2017.02.015 [Google Scholar]
  11. Blackman, I.D., and Holland, C. (2006). The management of financial supply chains: from adversarial to co-operative strategies. In: Project E-Society: Building Bricks (pp. 82–95). Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39229-5_8. [Google Scholar]
  12. BSR. (2018). Win-Win-Win: The Sustainable Supply Chain Finance Opportunity, 2019. [Google Scholar]
  13. Buzacott, J.A., and Zhang, R.Q. (2004). Inventory management with asset-based financing. Management Science, 50(9), 1274–1292. https://doi.org/10.1287/mnsc.1040.0278. [Google Scholar]
  14. Camerinelli, E. (2009). Supply chain finance. Journal of Payments Strategy & Systems, 3(2), 114–128. [Google Scholar]
  15. Caniato, F., Gelsomino, L. M., Perego, A., and Ronchi, S. (2016). Does finance solve the supply chain financing problem? Supply Chain Management: An International Journal, 21(5), 534–549. https://doi.org/10.1108/SCM-11-2015-0436. [Google Scholar]
  16. Casey, E., and O’Toole, C.M. (2014). Bank lending constraints, trade credit and alternative financing during the financial crisis: Evidence from European SMEs. Journal of Corporate Finance, 27, 173–193. https://doi.org/10.1016/j.jcorpfin.2014.05.001. [Google Scholar]
  17. Chakuu, S., Masi, D., and Godsell, J. (2019). Exploring the relationship between mechanisms, actors and instruments in supply chain finance: A systematic literature review. International Journal of Production Economics, 216, 35–53. https://doi.org/10.1016/j.ijpe.2019.04.013. [Google Scholar]
  18. Chandramowli, S., Transue, M., and Felder, F.A. (2011). Analysis of barriers to development in landfill communities using interpretive structural modeling. Habitat International, 35(2), 246–253. https://doi.org/10.1016/j.habitatint.2010.09.005. [Google Scholar]
  19. Chen, Q. (2016). A Supply Chain Financial Service Management Model of Chinese Logistics Enterprises. International Journal of Simulation Systems, Science & Technology, 17. [Google Scholar]
  20. Chen, C., and Kieschnick, R. (2018). Bank credit and corporate working capital management. Journal of Corporate Finance, 48, 579–596. https://doi.org/10.1016/j.jcorpfin.2017.12.013. [Google Scholar]
  21. Chen, J., Zhou, Y.W., and Zhong, Y. (2017). A pricing/ordering model for a dyadic supply chain with buyback guarantee financing and fairness concerns. International Journal of Production Research, 55(18), 5287–5304. https://doi.org/10.1080/00207543.2017.1308571. [Google Scholar]
  22. Crook, T.R., Giunipero, L., Reus, T. H., Handfield, R., and Williams, S. K. (2008). Antecedents and outcomes of supply chain effectiveness: an exploratory investigation. Journal of Managerial Issues, 161–177. [Google Scholar]
  23. Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319–340. https://doi.org/10.2307/249008. [Google Scholar]
  24. Ding, Z. (2017). Research on the Framework of Supply Chain Finance Operation Model of E-commerce Enterprises by Taking JD as An Example. Boletín Técnico, 55(15). [Google Scholar]
  25. Dwivedi, Y.K., Janssen, M., Slade, E. L., Rana, N. P., Weerakkody, V., Millard, J., and Snijders, D. (2017). Driving innovation through big open linked data (BOLD): Exploring antecedents using interpretive structural modelling. Information Systems Frontiers, 19(2), 197–212. https://doi.org/10.1007/s10796-016-9675-5. [Google Scholar]
  26. Farrell, H. (2004). Trust, distrust, and power. Distrust, 85105. [Google Scholar]
  27. Fairchild, A. (2005). Intelligent matching: integrating efficiencies in the financial supply chain. Supply Chain Management: An International Journal, 10(4), 244–248. https://doi.org/10.1108/13598540510612703. [Google Scholar]
  28. Gelsomino, L. M., Mangiaracina, R., Perego, A., and Tumino, A. (2016). Supply chain finance: a literature review. International Journal of Physical Distribution & Logistics Management, 46(4), 348–366. https://doi.org/10.1108/IJPDLM-08-2014-0173. [Google Scholar]
  29. Global Supply Chain Finance Forum. (n.d). In Brief Standard Definition. Global Supply Chain Forum. http://supplychainfinanceforum.org/ accessed on 20 June 2019. [Google Scholar]
  30. Gomm, M.L. (2010). Supply chain finance: applying finance theory to supply chain management to enhance finance in supply chains. International Journal of Logistics: Research and Applications, 13(2), 133–142. https://doi.org/10.1080/13675560903555167. [Google Scholar]
  31. Gynther, R.S. (1969). Some “conceptualizing” on goodwill. The accounting review, 44(2), 247–255. [Google Scholar]
  32. Herath, G. (2015). Supply-chain finance: The emergence of a new competitive landscape. McKinsey. [Google Scholar]
  33. Hofmann, E. (2005). Supply chain finance: some conceptual insights. Beiträge Zu Beschaffung Und Logistik, 203–214. https://doi.org/10.1007/978-3-322-82165-2_16. [Google Scholar]
  34. Hofmann, E., and Belin, O. (2011). Supply chain finance solutions. Springer-Velag Berlin Heidelberg. https://doi.org/10.1007/978-3-642-17566-4. [Google Scholar]
  35. Hofmann, E., and Kotzab, H. (2010). A supply chain‐oriented approach of working capital management. Journal of business Logistics, 31(2), 305–330. https://doi.org/10.1002/j.2158-1592.2010.tb00154.x. [Google Scholar]
  36. Hofmann, E., Strewe, U.M., and Bosia, N. (2017). Supply chain finance and blockchain technology: the case of reverse securitization. Springer. https://doi.org/10.1007/978-3-319-62371-9. [Google Scholar]
  37. Hofmann, E., and Zumsteg, S. (2015). Win-win and no-win situations in supply chain finance: the case of accounts receivable programs. Supply Chain Forum: An International Journal, 16(3), 30–50. https://doi.org/10.1080/16258312.2015.11716350. [Google Scholar]
  38. Hudnurkar, M., Jakhar, S., and Rathod, U. (2014). Factors affecting collaboration in supply chain: a literature review. Procedia-Social and Behavioral Sciences, 133(1), 189–202. https://doi.org/10.1016/j.sbspro.2014.04.184. [Google Scholar]
  39. Iacono, U.D., Reindorp, M., and Dellaert, N. (2015). Market adoption of reverse factoring. International Journal of Physical Distribution & Logistics Management, 45(3), 286–308. https://doi.org/10.1108/IJPDLM-10-2013-0258. [Google Scholar]
  40. Inkpen, A. C., and Currall, S. C. (2004). The coevolution of trust, control, and learning in joint ventures. Organization science, 15(5), 586–599. https://doi.org/10.1287/orsc.1040.0079. [Google Scholar]
  41. Ivashina, V., and Scharfstein, D. (2010). Bank lending during the financial crisis of 2008. Journal of Financial Economics, 97(3), 319–338. https://doi.org/10.1016/j.jfineco.2009.12.001. [Google Scholar]
  42. Jiang, J., Jin, Y., and Dong, C.Y. (2016). Research on the e-business logistics service mode based on branch storage and warehouse financing. International Journal of Services Technology and Management, 22(3–5), 203–217. https://doi.org/10.1504/IJSTM.2016.078537. [Google Scholar]
  43. Kailash, Saha, R.K. and Goyal, S. (2019) ‘Benchmarking of internal supply chain management: factors analysis and ranking using ISM approach and MICMAC analysis’, International Journal of Productivity and Quality Management, 27(4), 394–419. https://doi.org/10.1504/IJPQM.2019.101933. [Google Scholar]
  44. Klapper, L. (2006). The role of factoring for financing small and medium enterprises. Journal of Banking and Finance, 30, 3111–3130. https://doi.org/10.1016/j.jbankfin.2006.05.001. [Google Scholar]
  45. Lamoureux, J.F., and Evans, T.A. (2011). Supply chain finance: a new means to support the competitiveness and resilience of global value chains. https://doi.org/10.2139/ssrn.2179944. [Google Scholar]
  46. Lee, J. D., and Gao, J. (2005, January). Trust, information technology, and cooperation in supply chains. Supply Chain Forum: An International Journal, 6(2), 82–89. https://doi.org/10.1080/16258312.2005.11517150. [Google Scholar]
  47. Lee, J., Palekar, U.S., and Qualls, W. (2011). Supply chain efficiency and security: Coordination for collaborative investment in technology. European Journal of Operational Research, 210(3), 568–578. https://doi.org/10.1016/j.ejor.2010.10.015. [Google Scholar]
  48. Lee, N., Sameen, H., and Cowling, M. (2015). Access to finance for innovative SMEs since the financial crisis. Research Policy, 44(2), 370–380. https://doi.org/10.1016/j.respol.2014.09.008. [Google Scholar]
  49. Lee, H., and Whang, S. (2000). Information sharing in a supply chain. International Journal of Technology Management, 20(3/4), 373–387. https://doi.org/10.1504/IJTM.2000.002867. [Google Scholar]
  50. Li, Y., Wang, S., Feng, G., and Lai, K.K. (2011). Comparative analysis of risk control in logistics and supply chain finance under different pledge fashions. International Journal of Revenue Management, 5(2–3), 121–144. https://doi.org/10.1504/IJRM.2011.040305. [Google Scholar]
  51. Liebl, J., Hartmann, E., and Feisel, E. (2016). Reverse factoring in the supply chain: objectives, antecedents and implementation barriers. International Journal of Physical Distribution & Logistics Management, 46(4), 393–413. https://doi.org/10.1108/IJPDLM-08-2014-0171. [Google Scholar]
  52. Lotfi, Z., Mukhtar, M., Sahran, S., and Zadeh, A.T. (2013). Information sharing in supply chain management. Procedia Technology, 11, 298–304. https://doi.org/10.1016/j.protcy.2013.12.194. [Google Scholar]
  53. Malone, D.W. (1975). An introduction to the application of interpretive structural modeling. Proceedings of the IEEE, 63(3), 397–404. https://doi.org/10.1109/PROC.1975.9765. [Google Scholar]
  54. Maloni, M., and Benton, W.C. (2000). Power influences in the supply chain. Journal of business logistics, 21(1), 49–74. [Google Scholar]
  55. Mandal, A., and Deshmukh, S.G. (1994). Vendor selection using interpretive structural modelling (ISM). International Journal of Operations & Production Management, 14(6), 52–59. https://doi.org/10.1108/01443579410062086. [Google Scholar]
  56. Marak, Z., and Pillai, D. (2019). Factors, outcome, and the solutions of supply chain finance: review and the future directions. Journal of Risk and Financial Management, 12(1), 3. [Google Scholar]
  57. Martin, J. (2017). Suppliers' participation in supply chain finance practices: predictors and outcomes. International Journal of Integrated Supply Management, 11(2–3), 193–216. https://doi.org/10.1504/IJISM.2017.086242. [Google Scholar]
  58. More, D., and Basu, P. (2013). Challenges of supply chain finance: A detailed study and a hierarchical model based on the experiences of an Indian firm. Business Process Management Journal, 19(4), 624–647. https://doi.org/10.1108/BPMJ-09-2012-0093. [Google Scholar]
  59. Pellegrino, R., Costantino, N., and Tauro, D. (2019). Supply Chain Finance: A supply chain-oriented perspective to mitigate commodity risk and pricing volatility. Journal of Purchasing and Supply Management, 25(2), 118–133. https://doi.org/10.1016/j.pursup.2018.03.004. [Google Scholar]
  60. Pfohl, H.C., and Gomm, M. (2009). Supply chain finance: optimizing financial flows in supply chains. Logistics Research, 1(3–4), 149–161. https://doi.org/10.1007/s12159-009-0020-y. [Google Scholar]
  61. Pfohl, H. C., Gallus, P., and Thomas, D. (2011). Interpretive structural modeling of supply chain risks. International Journal of Physical Distribution & Logistics Management, 41(9), 839–859. https://doi.org/10.1108/09600031111175816. [Google Scholar]
  62. Popa, V. (2013). The financial supply chain management: a new solution for supply chain resilience. Amfiteatru Economic Journal, 15(33), 140–153. [Google Scholar]
  63. Protopappa-Sieke, M., and Seifert, R.W. (2017). Benefits of working capital sharing in supply chains. Journal of the Operational Research Society, 68(5), 521–532. https://doi.org/10.1057/s41274-016-0009-2. [Google Scholar]
  64. Randall, W.S., and Theodore Farris, M. (2009). Supply chain financing: using cash-to-cash variables to strengthen the supply chain. International Journal of Physical Distribution & Logistics Management, 39(8), 669–689. https://doi.org/10.1108/09600030910996314. [Google Scholar]
  65. Roberts, S. (2003). Supply chain specific? Understanding the patchy success of ethical sourcing initiatives. Journal of Business Ethics, 44(2–3),159–170. https://doi.org/10.1023/A:1023395631811. [Google Scholar]
  66. Rogers, E.M. (2010). Diffusion of innovations. Simon and Schuster. [Google Scholar]
  67. Saxena, J.P., Sushil., and Vrat, P. (1990). Impact of indirect relationships in classification of variables—a micmac analysis for energy conservation. Systems Research, 7(4), 245–253. https://doi.org/10.1002/sres.3850070404. [Google Scholar]
  68. Shankar, R., Gupta, R., and Pathak, D.K. (2018). Modeling critical success factors of traceability for food logistics system. Transportation Research Part E: Logistics and Transportation Review, 119, 205–222. https://doi.org/10.1016/j.tre.2018.03.006. [Google Scholar]
  69. Shinozaki, S. (2014). A new regime of SME finance in emerging Asia: Enhancing access to growth capital and policy implications. Journal of International Commerce, Economics and Policy, 5(03), 1440010. https://doi.org/10.1142/S1793993314400109. [Google Scholar]
  70. Silvestro, R., and Lustrato, P. (2014). Integrating financial and physical supply chains: the role of banks in enabling supply chain integration. International journal of operations & production management, 34(3), 298–324. https://doi.org/10.1108/IJOPM-04-2012-0131. [Google Scholar]
  71. Simatupang, T.M., Wright, A.C., and Sridharan, R. (2004). Applying the theory of constraints to supply chain collaboration. Supply Chain Management: An International Journal. https://doi.org/10.1108/13598540410517584. [Google Scholar]
  72. Singh, R.K., Garg, S.K., and Deshmukh, S.G. (2007). Interpretive structural modelling of factors for improving competitiveness of SMEs. International Journal of Productivity and Quality Management, 2(4), 423–440. https://doi.org/10.1504/IJPQM.2007.013336. [Google Scholar]
  73. Sommer, M., and O’Kelly, R. (2017). Supply Chain Finance: Riding the Waves. Oliver Wyman. [Google Scholar]
  74. Sopranzetti, B.J. (1998). The economics of factoring accounts receivable. Journal of Economics and Business, 50(4), 339–359. https://doi.org/10.1016/S0148-6195(98)00008-3. [Google Scholar]
  75. Soufani, K. (2002). The decision to finance account receivables: the factoring option. Managerial and Decision Economics, 23(1), 21–32. https://doi.org/10.1002/mde.1046. [Google Scholar]
  76. Wandfluh, M., Hofmann, E., and Schoensleben, P. (2015). Financing buyer–supplier dyads: an empirical analysis on financial collaboration in the supply chain. International Journal of Logistics Research and Applications, 19(3), 200–217. https://doi.org/10.1080/13675567.2015.1065803. [Google Scholar]
  77. Wuttke, D.A., Blome, C., and Henke, M. (2013a). Focusing the financial flow of supply chains: An empirical investigation of financial supply chain management. International Journal of Production Economics, 145(2), 773–789. https://doi.org/10.1016/j.ijpe.2013.05.031. [Google Scholar]
  78. Wuttke, D.A., Blome, C., Foerstl, K., and Henke, M. (2013b). Managing the innovation adoption of supply chain finance – Empirical evidence from six European case studies. Journal of Business Logistics, 34(2),148–166. https://doi.org/10.1111/jbl.12016. [Google Scholar]
  79. Wuttke, D.A., Blome, C., Heese, H.S., and Protopappa-Sieke, M. (2016). Supply chain finance: Optimal introduction and adoption decisions. International Journal of Production Economics, 178, 72–81. https://doi.org/10.1016/j.ijpe.2016.05.003. [Google Scholar]
  80. Wuttke, D.A., Rosenzweig, E.D., and Heese, H. S. (2019). An empirical analysis of supply chain finance adoption. Journal of Operations Management, 65(3), 242–261. https://doi.org/10.1002/joom.1023. [Google Scholar]
  81. Xiao, Y., and Zhang, J. (2017). Preselling to a retailer with cash flow shortage on the manufacturer. Omega, 80, 43–57. https://doi.org/10.1016/j.omega.2017.09.004. [Google Scholar]
  82. Xu, X., Chen, X., Jia, F., Brown, S., Gong, Y., and Xu, Y. (2018). Supply chain finance: A systematic literature review and bibliometric analysis. International Journal of Production Economics, 204, 160–173. https://doi.org/10.1016/j.ijpe.2018.08.003. [Google Scholar]
  83. Yan, N., Dai, H., and Sun, B. (2014). Optimal bi‐level Stackelberg strategies for supply chain financing with both capital‐constrained buyers and sellers. Applied Stochastic Models in Business and Industry, 30(6), 783–796. https://doi.org/10.1002/asmb.2021. [Google Scholar]
  84. Ye, Fei, and Zhang. (2010). Impact of resource dependence, trust and relationship commitment among supply chain partners on information system alignment. Industrial Engineering and Management, 15(6), 7–15. [Google Scholar]
  85. Yu, J., and Zhu, D. (2018). Study on the Selection Strategy of Supply Chain Financing Modes Based on the Retailer’s Trade Grade. Sustainability, 10(9), 3045. https://doi.org/10.3390/su10093045. [Google Scholar]
  86. Zhang, C. (2016). Small and medium-sized enterprises closed-loop supply chain finance risk based on evolutionary game theory and system dynamics. Journal of Shanghai Jiaotong University (Science), 21(3), 355–364. https://doi.org/10.1007/s12204-016-1733-0. [Google Scholar]
  87. Zhang, M., and Huo, B. (2013). The impact of dependence and trust on supply chain integration. International Journal of Physical Distribution & Logistics Management. https://doi.org/10.1108/IJPDLM-10-2011-0171. [Google Scholar]
  88. Zheng, J., and Zhang, J. (2017). 18. Analysis on Coordination Mechanism of Supply Chain Finance for B2C Cross-border Ecommerce. Revista de la Facultad de Ingeniería, 32(14), 103–109. [Google Scholar]
  89. Zhou, Q., Chen, X., and Li, S. (2018). Innovative financial approach for agricultural sustainability: A case study of Alibaba. Sustainability, 10(3), 891. https://doi.org/10.3390/su10030891. [Google Scholar]

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Cytowanie zasobu

APA style

Supply Chain Finance Factors: An Interpretive Structural Modeling Approach. (2021). Supply Chain Finance Factors: An Interpretive Structural Modeling Approach. Central European Management Journal, 29(1), 88–111. https://doi.org/10.7206/cemj.2658-0845.42 (Original work published 3/2021n.e.)

MLA style

„Supply Chain Finance Factors: An Interpretive Structural Modeling Approach”. 3/2021n.e. Central European Management Journal, t. 29, nr 1, 2021, ss. 88–111.

Chicago style

„Supply Chain Finance Factors: An Interpretive Structural Modeling Approach”. Central European Management Journal, Central European Management Journal, 29, nr 1 (2021): 88–111. doi:10.7206/cemj.2658-0845.42.