Prioritizing Risk Factors in Supply Chain Finance for Logistics Company Using Analytic Hierarchy Process
Keywords:
Analytic Hierarchy Process (AHP), Logistics Company, Supply Chain Finance (SCF)Abstract
This study aimed to identify and rank the risk factors associated with logistics companies engaged in supply chain finance (SCF) operations using the Analytic Hierarchy Process (AHP). The target population consists of three distinct groups: staff of logistics companies, professionals from financial institutions, and researchers affiliated with academic institutes. This study used questionnaire and convenient sampling to collect data. The results showed that logistics operations management, pledge management, and supply chain environment were significant dimensions of risk factors for logistics companies in SCF. The risk factors were divided into three groups: high-risk, medium-risk, and low-risk factors. The study recommends that logistics companies in SCF prioritize risk management strategies on the high-risk factors to minimize potential losses and reputational damage. Based on AHP, those high-risk factors are pledge disposal capability, pledge quality, pledge ownership, and legal & regulation. The study suggests that goods and companies can mitigate these risks by implementing advanced inventory management systems, partnering with third-party logistics providers or liquidators, seeking third-party assistance to identify the quality of the pledged goods, and conducting thorough investigations into the qualifications of applicants and the ownership of goods before conducting business. Furthermore, complying with relevant laws and regulations is crucial for logistics companies to avoid potential legal issues and safeguard the success of the SCF business. These findings can provide insights into developing effective risk management systems for logistics companies engaged in SCF operations, enhancing their ability to operate successfully in this industry.
References
Abbasi, W. A., Wang, Z., Zhou, Y., & Hassan, S. (2019). Research on measurement of supply chain finance credit risk based on Internet of Things. International Journal of Distributed Sensor Networks, 15(9), 1-14.
Ali, Z., Gongbing, B., & Mehreen, A. (2018). Does supply chain finance improve SMEs performance? The moderating role of trade digitization. Business Process Management Journal, 26(1), 150-167.
Ali, Z., Gongbing, B., & Mehreen, A. (2019). Predicting supply chain effectiveness through supply chain finance: evidence from small and medium enterprises. The International Journal of Logistics Management, 30(2), 488-505.
Amin, H. M., & Shahwan, T. M. (2020). Logistics management requirements and logistics performance efficiency: the role of logistics management practices-evidence from Egypt. International Journal of Logistics Systems and Management, 35(1). https://doi.org/10.1504/IJLSM.2020.103859
Bai, W., Liu, Y., & Wang, J. (2022). An intelligent supervision for supply chain finance and logistics based on Internet of things. Computational Intelligence and Neuroscience, 2022, 1-9. https://doi.org/10.1155/2022/6901601
Chen, X., Liu, C., & Li, S. (2019). The role of supply chain finance in improving the competitive advantage of online retailing enterprises. Electronic Commerce Research and Applications, 33, 100821.
Deng, A., & Lu, X. (2017). A literature review on the study of chattel pledge supervision in logistics and supply chain finance of China. Journal of Financial Risk Management, 6(02), 93.
Deng, A., & Sen, M. (2017). A research review on pricing influencing factors of supply chain financial services. World Journal of Research and Review, 4(2), 16-20.
Du, Y., Zhong, J., Su, Z., Yang, X., & Yao, Y. (2019). Risk Evaluation and Control of Supply Chain Finance. Applied Economics and Finance, 6(1), 21-29. https://doi.org/10.11114/aef.v6i1.3831
Foisal, M. T. M., & Sagar, A. H. (2021). Factors Affecting Supply Chain Finance Decision for Actors in Agro-food Industry: A Study on Bangladesh Economy. IOSR Journal of Economics and Finance, 12(2), 1-13.
Gelsomino, L. M., Mangiaracina, R., Perego, A., & Tumino, A. (2016). Supply chain finance: a literature review. International Journal of Physical Distribution & Logistics Management, 46(4), 1-33.
Guo, L., Chen, J., Li, S., Li, Y., & Lu, J. (2022). A blockchain and IoT-based lightweight framework for enabling information transparency in supply chain finance. Digital Communications and Networks, 8(4), 576-587.
Hu, H., Chen, D., Sui, B., Zhang, L., & Wang, Y. (2020). Price volatility spillovers between supply chain and innovation of financial pledges in China. Economic Modelling 89, 397-413.
Huang, X., Sun, J., & Zhao, X. (2021). Credit risk assessment of supply chain financing with a grey correlation model: an empirical study on China’s home appliance industry. Complexity, 2021, 1-12.
Huo, X., Jasimuddin, S. M., Zheng, K., & Zhang, Z. (2022). Exploring the Risks of International Supply Chain Financial Warehouse Receipts Pledge Model: A Structural Equation Approach. Supply Chain Forum: An International Journal, 1-12. https://doi.org/10.1080/16258312.2022.2036076
Ioannou, I., & Demirel, G. (2022). Blockchain and supply chain finance: a critical literature review at the intersection of operations, finance, and law. Journal of Banking and Financial Technology, 6(1), 83-107.
Jia, F., Blome, C., Sun, H., Yang, Y., & Zhi, B. (2020). Towards an integrated conceptual framework of supply chain finance: An information processing perspective. International Journal of Production Economics, 219, 18-30.
Jia, F., Zhang, T., & Chen, L. (2020). Sustainable supply chain Finance: Towards a research agenda. Journal of Cleaner Production, 243, 118680.
Lam, H. K., Zhan, Y., Zhang, M., Wang, Y., & Lyons, A. (2019). The effect of supply chain finance initiatives on the market value of service providers. International Journal of Production Economics, 216, 227-238.
Li, S., & Chen, X. (2019). The role of supply chain finance in third-party logistics industry: a case study from China. International Journal of Logistics Research and Applications, 22(2), 154-171.
Li, G., Yang, J., & Huang, Y. (2020). Supply chain finance credit risk evolving intelligent analysis system based on system dynamic model. Journal of Intelligent & Fuzzy Systems, 38(6), 7837-7847.
Li, L., Wang, Z., & Zhao, X. (2022). Configurations of financing instruments for supply chain cost reduction: evidence from Chinese manufacturing companies. International Journal of Operations & Production Management, 42(9), 1384-1406. https://doi.org/10.1108/IJOPM-12-2021-0755
Liang, X., Zhao, X., Wang, M., & Li, Z. (2018). Small and medium-sized enterprises sustainable supply chain financing decision based on triple bottom line theory. Sustainability, 10(11), 4242.
Liao, Z. (2015). Criticality analysis on Value-at-Risk model of Loan-to-Value ratios decision in inventory financing of supply chain finance. Open Access Library Journal, 2(12), 1.
Lin, Q., Xiao, Y., & Zheng, J. (2021). Selecting the supply chain financing mode under price-sensitive demand: Confirmed warehouse financing vs. trade credit. Journal of Industrial and Management Optimization, 17(4), 2031-2049.
Liu, L., Zhang, J. Z., He, W., & Li, W. (2021). Mitigating information asymmetry in inventory pledge financing through the Internet of things and blockchain. Journal of Enterprise Information Management, 34(5), 1429-1451.
Liu, X., Arthanari, T., & Shi, Y. (2019). Making dairy supply chains robust against corruption risk: a systemic exploratory study. The International Journal of Logistics Management, 30(4), 1078-1100. https://doi.org/10.1108/IJLM-02-2018-0039
Liu, X., Wang, Y., Wang, J., & Xu, W. (2022). Supply chain financial logistics supervision system based on blockchain technology. Journal of Ambient Intelligence and Humanized Computing, 14(8), 11059-11069.
Lu, Q., Liu, B., & Song, H. (2020). How can SMEs acquire supply chain financing: the capabilities and information perspective? Industrial Management & Data Systems, 120(4), 784-809.
Lyu, P., Kang, S. H., Kang, Y., & Choi, M. S. (2021). Supply chain finance and financing constraints: Evidence from Chinese multinational manufacturing firms. Academic Journal Eurasian Studies, 18(3), 33-72.
Lyu, X., & Zhao, J. (2019). Compressed sensing and its applications in risk assessment for internet supply chain finance under big data. IEEE Access, 7, 53182-53187.
Marak, Z. R., & Pillai, D. (2018). Factors, outcome, and the solutions of supply chain finance: review and the future directions. Journal of Risk and Financial Management, 12(1), 3.
Meng, J., & Wang, S. (2022). The Performance Evaluation of Logistics Enterprises in Online Supply Chain Finance Based on Analytic Hierarchy Process. Mathematical Problems in Engineering, 2022. https://doi.org/10.1155/2022/8393223
Mou, W., Wong, W. K., & McAleer, M. (2018). Financial credit risk evaluation based on core enterprise supply chains. Sustainability, 10(10), 3699.
Mu, W. (2022). Analysis and warning model of logistics risks of cross-border E-commerce. Discrete Dynamics in Nature and Society, 2022, 1-10. https://doi.org/10.1155/2022/5140939
Pan, A., Xu, L., Li, B., & Ling, R. (2020). The impact of supply chain finance on firm cash holdings: Evidence from China. Pacific-Basin Finance Journal, 63(2020), 1-19.
Ronchini, A., Moretto, A., & Caniato, F. (2021). A decision framework for inventory-and equipment-based supply chain finance solutions. Journal of Purchasing and Supply Management, 27(4), 100712.
Saaty, T. L. (1970). Optimization in integers and related extremal problems. McGraw-Hill.
Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting, resource allocation (1st ed.). McGraw-Hill.
Saaty, T. L. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48(1), 9-26. https://doi.org/10.1016/0377-2217(90)90057-I
Saaty, T. L., & Vargas, L. G. (2006). Decision making with the analytic network process (Vol. 282). Springer Science+ Business Media, LLC.
Schleper, M. C., Gold, S., Trautrims, A., & Baldock, D. (2021). Pandemic-induced knowledge gaps in operations and supply chain management: COVID-19’s impacts on retailing. International Journal of Operations & Production Management, 41(3), 193-205.
Seuring, S., & Müller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16(15), 1699-1710.
Song, H., Yu, K., Ganguly, A., & Turson, R. (2016). Supply chain network, information sharing and SME credit quality. Industrial Management & Data Systems, 116(4), 740-758.
Soni, G., Kumar, S., Mahto, R. V., Mangla, S. K., Mittal, M. L., & Lim, W. M. (2022). A decision-making framework for Industry 4.0 technology implementation: The case of FinTech and sustainable supply chain finance for SMEs. Technological Forecasting and Social Change, 180, 121686.
Tseng, M. L., Wu, K. J., Hu, J., & Wang, C. H. (2018). Decision-making model for sustainable supply chain finance under uncertainties. International Journal of Production Economics, 205, 30-36.
Wang, Y., Jia, F., Schoenherr, T., Gong, Y., & Chen, L. (2020). Cross-border e-commerce firms as supply chain integrators: The management of three flows. Industrial Marketing Management, 89, 72-88.
Wang, Z., Wang, Q., Lai, Y., & Liang, C. (2020). Drivers and outcomes of supply chain finance adoption: an empirical investigation in China. International Journal of Production Economics, 220, 107453.
Wang, R., Yu, C., & Wang, J. (2019). Construction of supply chain financial risk management mode based on Internet of Things. IEEE access, 7, 110323-110332.
Yang, Y., Chu, X., Pang, R., Liu, F., & Yang, P. (2021). Identifying and predicting the credit risk of small and medium-sized enterprises in sustainable supply chain finance: evidence from China. Sustainability, 13(10), 5714-5733. https://doi.org/10.3390/su13105714.
Yu, H., Zhao, Y., Liu, Z., Liu, W., Zhang, S., Wang, F., & Shi, L. (2021). Research on the financing income of supply chains based on an E-commerce platform. Technological Forecasting and Social Change, 169, 120820.
Yu, W., Jacobs, M. A., Chavez, R., & Yang, J. (2019). Dynamism, disruption orientation, and resilience in the supply chain and the impacts on financial performance: A dynamic capabilities perspective. International Journal of Production Economics, 218, 352-362.
Zhang, L., Hu, H., & Zhang, D. (2015). A credit risk assessment model based on SVM for small and medium enterprises in supply chain finance. Financial Innovation, 1(1), 1-21.
Zhao, Y., & Wang, N. (2021). Research on Authors' Co-authorship Network in Supply Chain Finance in China Based on Social Network Analysis, WHICEB 2021 Proceedings (page 508-517). Wuhan International Conference on e-Business at AIS Electronic Library https://aisel.aisnet.org/whiceb2021/65
Zhou, L., Chen, M., & Lee, H. (2022). Supply Chain Finance: A Research Review and Prospects Based on a Systematic Literature Analysis from a Financial Ecology Perspective. Sustainability, 14(21), 14452.
Zhu, Y., Zhou, L., Xie, C., Wang, G. J., & Nguyen, T. V. (2019). Forecasting SMEs' credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach. International Journal of Production Economics, 211, 22-33.
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