• Energy Research

With the rapid popularization of online shopping, more and more enterprises adopt dual-channel supply chain structures, and information sharing plays an important role in the implementation of dual-channel supply chain management. Most of the existing literature has investigated one-way information sharing from the retailer to the manufacturer, whereas few studies on two-way information sharing between the manufacturer and retailer in a dual-channel supply chain have been explored. A dual-channel supply chain consisting of a manufacturer and a retailer, both of whom have private information about consumer preference and service cost was considered in this study. Game-theoretic models were developed to investigate the decision-making problem of dual-channel members in two information-sharing scenarios including non-information sharing and information sharing respectively. Furthermore, the impact of the manufacturer's information forecast capability on the sale price, service level, and profits were analyzed through numerical example. Results show that information sharing can increase the wholesale price, sale price, and online service level; furthermore, information sharing not always be beneficial for dual-channel supply chain members. When the information forecast capability of the manufacturer is relatively weak, information sharing can increase supply chain members' profits. On the contrary, information sharing may not always increase his profits. Additionally, the retailer cannot benefit from information sharing in any cases, which accounts for his weak willingness to share information with the manufacturer. This study provides a significant reference for decision-making. Keywords: dual-channel supply chain; information sharing; price decisions; service decisions

AbstractThis paper aims to estimate the spatial dynamic evolution of renewable energy development efficiency and justify the dimensions that impact renewable energy development efficiency. The study applies the following methods: the ultraefficient slack‐based model (SBM) (to measure the efficiency of renewable energy development); the Dagum‐Gini coefficient decomposition process (to measure the interregional differences in the development of renewable energy efficiency); nuclear density estimation (to measure the dynamic distribution); the Markov model (to forecast renewable energy development efficiency); and the Tobit model (to justify the influencing factors of renewable energy development efficiency). The empirical findings confirm that the overall regional gaps in renewable energy development efficiency in China are widening year by year. The average value of renewable energy development efficiency increased from 0.932 in 2006 to 1.078 in 2020. The mean Gini coefficient increased gradually from 0.028 in 2006 to 0.174, with mean differences exceeding the average growth trend after 2011 and slowly decreasing post‐2016. There is polarization in the eastern region, while there is no polarization in the northeast. The overall level of renewable energy development efficiency in the middle and western areas is improving and showing a trend of absolute difference narrowing. In addition, economic development, green finance, technological progress, urbanization rate, and economic openness are conducive to renewable energy development efficiency, and renewable energy development efficiency is in a rapid development trend. Considering the findings, China should implement targeted regional development strategies, enhance green finance mechanisms, promote technological innovation, and align urbanization policies with renewable energy goals to reduce regional disparities and accelerate sustainable renewable energy development.