Joint decision on service level of chain electricity retailers. (November 2022)

• Record Type: Journal Article
• Authors: Yao, Jingyuan; Shu, Lingli; Jian, Xianzhong; Xiao, Erliang
• Is Part Of: Computers & industrial engineering. Volume 173(2022)
• Publication Date: 2022-11
• Subjects: Electricity retailing -- Service level -- Chain operation -- Optimization algorithm; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108678
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A decision-making model of chain electricity retailers on service levels is developed. A combined algorithm with selection mechanism is proposed to solve the model. The profits are compared when the service is provided or not. The service level significantly affects the profits of chain electricity retailers. Abstract: Nowadays, price competition in the electricity retailing industry is increasingly fierce. In the future, providing characteristic and suitable services to attract customers is an effective way. After gaining a certain market recognition by providing services, most decision makers will choose to establish subsidiary retailers to implement the chain operation. With the increase of subsidiary retailers, how to make joint decision on service level for all subsidiary retailers has become an issue faced by decision makers. To this end, this paper develops a model and designs a combined algorithm. Taking the Chinese electricity retailing as an example, we carry out parameter hypothesis and experimental simulation. Experiments verify that the proposed combined algorithm can effectively get the feasible and satisfactory price, service level and overall profit. The results can provide some theoretical guidance for decision-makers. Secondly, we find service levels significantly affected the overall profits of chain electricity retailer. The subsidiary retailers that provide the services can improve their own profits, and further can improve the overall profit. Through sensitivity analysis, we obtain some methods that can help decision makers adjust pricing and service levels in time to adapt to changes of uncertain parameters.