Designing and Developing a Model for Distributing Financial Resources among Suppliers in a Single Producer Chain

Document Type : Research Paper

Authors

1 Ph.D. Candidate, Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran.

2 Assistant Prof., Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran.

3 Associate Prof., Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran.

Abstract

Objective: If important details such as sustainability and resilience are not taken into account in supply chains, the risk of potential threats increases. One of the crucial factors in increasing supply chain resilience is the management of cash flows, especially the management of payable accounts. Managing this factor will lead to better use of financial resources. This study creates a model to optimize the repayment schedules of payable accounts.
Methods: To optimize the model, a genetic algorithm was used and simulation was applied to calculate the suitability function. The objective function included the costs of stopping production lines, the costs of producing defective products, and the costs of borrowing for suppliers. The produced output determined the suppliers and the amount of payment to them in each period.
Results: Investigating the feasibility of applying the proposed method was the main finding of this study, and the obtained results proved the model as efficient.
Conclusion: The model used real data from the automotive industry and the results showed that the proposed model has the ability to reduce the costs up to 44.7%.

Keywords

References

Babich, V., & 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. Special Issue on Interface of Finance, Operations, and Risk Management, 20(1), 1-18.
Blackhurst, J., Dunn, K. S., & Craighead, C. W. (2011). An empirically derived framework of global supply resiliency. Journal of business logistics, 32, 374-391.
Chakuu, S., Masi, D., & 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.
Chakuu, S., Masi, D., & Godsell, J. (2020). Towards a framework on the factors conditioning the role of logistics service providers in the provision of inventory financing. International Journal of Operations & Production Management, 40(7/8), 1225-1241. https://doi.org/10.1108/IJOPM-06-2019-0502
Chen, X., & Wang, A. (2012). Trade credit contract with limited liability in the supply chain with budget constraints. Annals of Operations Research, 196(1), 153-165.
Dada, M., & Hu, Q. (2008). Financing newsvendor inventory. Operations Research Letters, 36, 569-573.
Devalkar, S. K., & Krishnan, H. (2019). The impact of working capital financing costs on the efficiency of trade credit. Production and Operations Management, 28(4), 878-889.
El Miloudi, F., Tchernev, N., & Riane, F. (2016). Scheduling payments optimization to drive working capital performance within a supply chain. In 6th International Conference on Information Systems, Logistics and Supply Chain ILS Conference.
Emtehani, F., Nahavandi, N., & Rafiei, F. M. (2021). A joint inventory–finance model for coordinating a capital-constrained supply chain with financing limitations. Financial Innovation, 7, 1-39.
Fallah Lajimi, H., Jafari Soruni, Z., Hoseini Dolatabad, A. (2020). Designing a Mathematical Optimizing Model of the Integrated Supply Chain Network at Strategic and Tactical Levels. Industrial Management Journal, 12(4), 545-577. (in Persian)
Farris, M. T., & Hutchison, P. D. (2003). Measuring cash‐to‐cash performance. The International Journal of Logistics Management, 14(283-92.
Fathollah, M., & Najafi, M. (2017). Development of Financial Supply Chain Management and Supply Chain Finance Model. Journal of Industrial Engineering Research in Production Systems, 4, 257-269.
Granja, C., Almada-Lobo, B., Janela, F., Seabra, J., & Mendes, A. (2014). An optimization based on simulation approach to the patient admission scheduling problem using a linear programing algorithm. Journal of Biomedical Informatics, 52, 427-437.
Guillen, G., Badell, M., & Puigjaner, L. (2007). A holistic framework for short-term supply chain management integrating production and corporate financial planning. International Journal of Production Economics, 106, 288-306.
Gupta, S. K., Kunnathur, A. S., & Dandapani, K. (1987). Optimal repayment policies for multiple loans. Omega, 15, 323-330.
Gupta, S., & Dutta, K. (2011). Modeling of financial supply chain. European journal of operational research, 211, 47-56.
Hausman, W. H. (2005). Financial flows & supply chain efficiency. Visa Commerical Solutions.
Hoad, K., Robinson, S., & Davies, R. (2010). Automated selection of the number of replications for a discrete-event simulation. Journal of the Operational Research Society, 61, 1632-1644.
Homayounfar, M., Baghersalimi, S., Nahavandi, B., Izadi Sheyjani, K. (2018). Agent-based simulation of national oil products distribution company’s supply network in the framework of a complex adaptive system in order to achieve an optimal inventory level. Industrial Management Journal, 10(4), 607-630. (in Persian).
Iskandarnejad, S., Hassanzadeh Baradaran, R., & Taheri, H. (2020). The impact of working capital management on Listed companies profitability in business cycles based on the output gap. Asset Management and Financing, 8, 31-48. (in Persian)
Jaber, M. Y., & Osman, I. H. (2006). Coordinating a two-level supply chain with delay in payments and profit sharing. Computers & Industrial Engineering, 50, 385-400.
Jahangiri, M. H., & Cecelja, F. (2014). Modelling financial flow of the supply chain. In 2014 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1071-1075): IEEE.
Johari, M., Hosseini-Motlagh, S. M., Nematollahi, M., Goh, M., & Ignatius, J. (2018). Bi-level credit period coordination for periodic review inventory system with price-credit dependent demand under time value of money. Transportation Research Part E: Logistics and Transportation Review, 114, 270-291.
Kouvelis, P., Chambers, C., & Wang, H. (2006). Supply chain management research and production and operations management: Review, trends, and opportunities. Production and Operations Management, 15, 449-469.
Krommyda, I.-P., Skouri, K., & Lagodimos, A. (2019). A unified EOQ model with financial constraints and market tolerance. Applied Mathematical Modelling, 65, 89-105.
Law, A. M., Kelton, W. D., & Kelton, W. D. (2000). Simulation modeling and analysis (Vol. 3): McGraw-Hill New York.
Lee, C. H., & Rhee, B.-D. (2011). Trade credit for supply chain coordination. European journal of operational research, 214, 136-146.
Lee, H.-H., Zhou, J., & Wang, J. (2018). Trade credit financing under competition and its impact on firm performance in supply chains. Manufacturing & Service Operations Management, 20, 36-52.
Longinidis, P., & Georgiadis, M. C. (2011). Integration of financial statement analysis in the optimal design of supply chain networks under demand uncertainty. International Journal of Production Economics, 129, 262-276.
Luo, W., & Shang, K. (2015). Joint inventory and cash management for multidivisional supply chains. Operations Research, 63, 1098-1116.
Mashud, A. H. M., Uddin, M. S., & Sana, S. S. (2019). A two-level trade-credit approach to an integrated price-sensitive inventory model with shortages. International Journal of Applied and Computational Mathematics, 5, 1-28.
Mohammadi, A. S., Alem Tabriz, A., Pishvaee, M. S. (2018). Designing green closed-loop supply chain network with financial decisions under uncertainty. Industrial Management Journal, 10(1), 61-84. (in Persian)
Moussawi-Haidar, L., & Jaber, M. Y. (2013). A joint model for cash and inventory management for a retailer under delay in payments. Computers & Industrial Engineering, 66, 758-767.
Moussawi-Haidar, L., Dbouk, W., Jaber, M. Y., & Osman, I. H. (2014). Coordinating a three-level supply chain with delay in payments and a discounted interest rate. Computers & Industrial Engineering, 69, 29-42.
Presutti, W. D., & Mawhinney, J. R. (2007). The supply chain-finance link. Supply Chain Management Review, 11(6), 32-38.
Rad, R. S., & Nahavandi, N. (2018). A novel multi-objective optimization model for integrated problem of green closed loop supply chain network design and quantity discount. Journal of cleaner production, 196, 1549-1565.
Razavi, S., Karimi, B., Rafeierad, D.(2017). Studying the Factors Affecting the Financing of Small and Medium Enterprises in Automotive Parts Supply Chains. Industrial Management Journal, 9(3), 435-454. (in Persian)
Sadeghi Rad, R., Nahavandi, N., Husseinzadeh Kashan, A., & Zegordi, S. (2018). An integrated closed-loop supply chain configuration model and supplier selection based on offered discount policies. International Journal of Engineering, 31, 440-449.
Sadigh, A. N., Fallah, H., & Nahavandi, N. (2013). A multi-objective supply chain model integrated with location of distribution centers and supplier selection decisions. The International Journal of Advanced Manufacturing Technology, 69, 225-235.
Taleizadeh, A. A., Lashgari, M., Akram, R., & Heydari, J. (2016). Imperfect economic production quantity model with upstream trade credit periods linked to raw material order quantity and downstream trade credit periods. Applied Mathematical Modelling, 40, 8777-8793.
Vintilă, G., & Nenu, E. A. (2016). Liquidity and profitability analysis on the Romanian listed companies. Journal of Eastern Europe research in business & economics, 2016, 1-8.
Xiao, S., Sethi, S. P., Liu, M., & Ma, S. (2017). Coordinating contracts for a financially constrained supply chain. Omega, 72, 71-86.
Xu, X., & Birge, J. R. (2006). Equity valuation, production, and financial planning: A stochastic programming approach. Naval Research Logistics (NRL), 53, 641-655.
Industrial Management Journal
Volume 13, Issue 4
2022
Pages 537-558

Files

Share

How to cite

Statistics