Scholars have paid extensive attention to transformational leadership for decades. However, existing studies still lack ample discussions on the underlying mechanism and boundary conditions of its influence on employee job satisfaction. This study proposed a moderated mediation model based on social exchange theory. We collected survey data from 211 frontline employees to verify our hypotheses. The results showed that transformational leadership was positively associated with employee job satisfaction via the mediation role of the perceived employee relations climate. Furthermore, the relationship between transformational leadership and the employee relations climate, as well as the indirect relationship between the two, was demonstrated to be more significant for male employees. This study offered a new account of the mechanisms of transformational leadership and clarified a boundary condition for its effectiveness.

The transportation industry is a high carbon emission industry, and China has also put forward strict requirements for the transportation industry to achieve carbon emission reduction. By measuring the total factor carbon emission efficiency of the transportation industry, we can understand the change trend and the influencing factors of the total factor carbon emissions. To fully consider the problem of multiple inputs and outputs in the transportation industry and obtain a more accurate efficiency evaluation value, this paper adopted the slack-based model-data envelopment analysis method and global Malmquist—Luenberger index to study the change in the total factor carbon emission performance of the transportation industry. The combination of static analysis and dynamic analysis was used to calculate the TFP of the transportation industry and increase the content of output indicators. The results indicate that the average TFP and GML index values exhibited significant heterogeneity nationwide. The values in Anhui and Hebei Provinces were greater than 1, and the average GML index values in Shanxi, Guangxi, and Yunnan were greater than 1. The eastern region performed well in terms of technical efficiency and scale efficiency. The technical efficiency in the central, western, and northeastern regions was optimal. In terms of influencing factors, the influencing factors causing the different carbon emission efficiencies in the four regions varied. Finally, corresponding policy suggestions were proposed.

This paper explores the spatial spillover effect of shared mobility on urban traffic congestion by constructing spatial econometric models. Based on panel data of 94 Chinese cities from 2016 to 2019, this study analyses the spatial correlation of shared mobility enterprise layout and geographical correlation of urban transport infrastructure and examines their influence mechanism. From the perspective of geographic spatial distribution, congestion has positive spatial correlation among Chinese cities, and it has different directions and centripetal forces across regions. The shared mobility enterprises in a region have same direction distribution with traffic congestion, but the centripetal forces of the aggregation effect are different. The econometric results include the fact that bike-sharing has reduced congestion significantly, but the overall impact of car-sharing is not clear. Neither bike-sharing nor car-sharing can offset the traffic congestion caused by economic activities and income growth. From the perspective of spillover effects, congestion has been influenced by bike-sharing, economic development, population, and public passengers in surrounding areas. In terms of spatial heterogeneity, bike-sharing relieves congestion in the Pearl River Delta region while having no significant effect in other regions. Meanwhile, car-sharing has aggravated congestion in the Yangtze River Delta but eased traffic jams in the Pearl River Delta.