Designing a Credit Risk Management Model in the Network of after-sales service companies Using Financial Components of After-Sales Services and Metaheuristic Algorithms (Case study: Saipa's after-sales service company(Saipa Yadak))

Subject Areas : Financial engineering

Hamid reza  Radmannejad ¹ (PhD Student, Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran)
Mohammad Ebrahim  Mohammad Pourzarandi ² (Professor, Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran and member of Modern Financial Risk Research Group)
Mehrzad  Minouei ³ (Assistant Professor, Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.)

Received: 2021-05-12 Accepted : 2021-06-21 Published : 2021-09-23

Keywords: Firefly Algorithm, Bee Colony algorithm, After-Sales Service Agencies, Optimal Credit Risk Management,

Abstract :

The type of customer service during the warranty is crucial for each complex. The purpose of customer service will be to meet the satisfaction of customers. Many components can contribute to accomplish this goal. One of the most important components is financial components. Today's world is a world of wide developments in all dimensions. The majority of companies are, more than ever, aware that the delivery of after-sales service is very effective in the loyalty and repetition of customer purchases. The intense focus on the quality of service causes the product to be valuable in terms of customers and their loyalty. Therefore, in this study, designing a credit risk management model for the for the Saipa Yadak Company and its Representatives Network using financial components of after-sales service and meta-heuristic algorithms was discussed. The sample studied in this research is the representatives of Saipa Company.The results showed that using financial components including, service cost, performance, good accounting, the amount of collateral and the amount of after-sales service agents have an impact on optimal credit risk management. Also, firefly algorithm and bee colony algorithm have the ability to predict the optimal management of credit risk using financial components.