A cooperative game network DEA model for circular economy performance eva‎luation of railway maintenance and repair companies in Iran

1/1/1900 12:00:00 AM

The railway industry in Iran is considered one of the oldest industries in the country. Over time, some important actions have been taken toward the growth and development of its infrastructure, including the connection of important cargo centers and destinations to the national railway network, the creation of branch lines, and the shift of freight transportation from road to rail. Despite the importance of the railway's role in the country's logistics, unfortunately, significant progress has not been made in modernizing the railway fleet and in mechanized and precise loading and unloading. This has led to resource waste and loss of transported cargo, ultimately resulting in the discouragement of traders and cargo owners from using rail transport. From an environmental perspective, there are also no proper structures in place for the treatment of waste and industrial wastewater, which may cause concerns and problems in the future. The concept of the circular economy seeks to create a balance between sustainable economic benefits, aiming to return recycled products into the production cycle and thereby reduce environmental pollution. One method for eva‎luating performance within the circular economy is Data Envelopment Analysis (DEA). In this study, by using a network DEA model that incorporates a centralized network and cooperative game strategy, the performance and productivity of the circular economy in the field of maintenance and repair of the railway fleet are eva‎luated and assessed. The performance of this system is based on the mutual interaction between two subsystems: the first, called the production subsystem, deals with the repair and washing of the railway fleet, and the second, the treatment subsystem, is responsible for the treatment of wastewater and industrial waste generated in the first subsystem. This model, through the implementation of a cooperative game strategy between these subsystems, aims to find the maximum efficiency level for both subsystems. Additionally, the Malmquist productivity index is used to eva‎luate the productivity of the units under review during the considered time period. In this research, the performance of railway fleet maintenance and repair companies in Iran’s railway network during the years 2020 to 2024 (1399 to 1403 in the Iranian calendar) has been studied. The average overall efficiency score during this five-year period is 0.53, indicating that, on average, these maintenance and repair companies have been inefficient. The efficiency of the production subsystem, which deals with washing and repairing the fleet, is 0.44, while the efficiency of the treatment subsystem, which pertains to waste and industrial wastewater recycling, is 0.63. The results of this study can assist in identifying efficient versus inefficient companies and provide solutions to help improve the performance of inefficient units toward reaching efficiency.

؛ارزيابي عملكرد؛ , ؛تحليل پوششي داده‌هاي شبكه‌اي؛ , ؛تئوري بازي همكاري؛ , ؛تعميرات و نگهداري ناوگان ريلي؛ , ؛راه‌آهن ايران.

؛Performance eva‎luation؛ , ؛Network Data Envelopment Analysis؛ , ؛Cooperative game theory؛ , ؛Railway fleet maintenance؛ , .Iranian railway؛

rojin vafaei

mohammadreza gholamian