Digital capability and green innovation: The perspective of green supply chain collaboration and top management's environmental awareness.

The emergence of the digital economy has accelerated digital transformation, and digitalization has shown new potential and solutions to increasingly severe environmental challenges. Based on the resource-based view, dynamic capability view, synergy effect and upper echelons theory, the connotation and measurement dimensions of digital capability and green supply chain collaboration are defined and improved. Then, a theoretical model of "digital capability-green supply chain collaboration-green innovation performance" is constructed. The influence mechanism and transmission process of digital capability on green innovation performance from the perspective of green supply chain collaboration is discussed. Meanwhile, the boundary condition of the influence of digital capability on green innovation performance in the view of top management's environmental awareness is explored. Finally, an empirical test is conducted based on the Chinese manufacturing corporates. The results indicate that green innovation performance is significantly and favorably impacted by digital capability, green supply chain collaboration plays a partial mediating role between digital capability and green innovation performance, and top management's environmental awareness can positively moderate the effect of digital capability on green innovation performance. This study offers valuable theoretical and practical enlightenments for manufacturing companies to foster the growth of green innovation through digital capability more effectively.

Multi-scale analysis of China's transportation carbon emissions based on nighttime light data.

This study explores the spatial and temporal evolution characteristics of transportation carbon emissions from multiple scales. Based on the integrated DMSP/OLS-NPP/VIIRS nighttime light data, a transportation carbon emission estimation model was constructed, and the spatial and temporal evolution characteristics of transportation carbon emissions in 30 provinces and some counties in China from 2000 to 2019 were analyzed. The main findings are as follows: (1) The goodness-of-fit of the estimation model improved from 51.2 to 87.15% by introducing the GDP variables. (2) At the provincial scale, the provinces with high carbon emissions from transportation were mainly distributed in the eastern region, with the highest value increasing from 19,171.6 million tons in 2000 to 71,545.98 million tons in 2019. The spatial distribution has a significant and positive spatial spillover effect, and the H-H aggregation was mainly distributed in the east-central region, showing a trend of expansion from the coast to the inland. Trend analysis showed that Shandong, Guangdong, Shanghai, and Jiangsu were areas with a rapid growth of high carbon emissions. (3) The county scale displayed a northeast-southwest evolutionary pattern, with the center of gravity in Henan. The spatial distribution showed a significant spatial agglomeration phenomenon. Trend analysis indicated that the transportation carbon emissions in 184 counties need to be controlled urgently, which was the focus of carbon emission reduction. This paper theoretically enriches the measurement method of transportation carbon emissions and overcomes the problem of insufficient spatial information of statistical data. In practice, it provides a scientific basis for accurate emission reduction and low-carbon development of transportation.

A novel bi-level programming model for structure sustainability optimization of passenger transport corridor.

The transportation industry has entered a new stage from quantity expanding to structure optimization, quality and efficiency improvement, and from respective governance to integrative development. This indicates that the traditional corridor mode allocation dominated by quantity equilibrium can no longer meet the requirements of the new stage. In this paper, we propose a multi-entity programming model based on the economic equilibrium between supply and demand. It not only ensures the economic equilibrium in the market, but also maximizes the social benefits of the whole system, thereby realizing the sustainable development of the transportation system. Also, the Globalsearch algorithm and intlinprog algorithm are designed to solve the problem. The actual case of Beijing-Shanghai corridor shows that the model and algorithms are effective, providing decision support for the optimal allocation of regional transport network resources.

A panel analysis of the sustainability of logistics industry in China: based on non-radial slacks-based method.

Previous studies have primarily targeted at positive causal linkages between the logistics industry and economic benefits, resulting in biased findings without the consideration of undesirable social and environmental problems. Therefore, this paper aims to develop a holistic approach to the assessment of logistics efficiency, through considering comprehensive inputs and desirable and undesirable outputs. In specific, contextualized in China, this paper comprehensively examined the spatiotemporal variations of China logistics efficiency and further investigated the impact of some exogenous factors. Results indicate that the overall logistics efficiency of China was low, but temporally showed a trend of increase. Spatially, the logistics efficiency followed the pattern of Eastern > Central > Western > Northeastern. Moreover, for the spatial interaction among adjacent provinces, there occurred high-high patterns in the Eastern, and low-low aggregation in the Western and Northeastern regions. However, along with time, the spatial interaction among adjacent provinces was weakening. For exogenous factors, level of economic development, urbanization level, utilization rate of logistics resources, and location advantage had a significant positive impact on SLE, while the effect of labor quality was not significant. Overall, this paper enriches the theoretical understandings of sustainable logistics efficiency evaluation and unbiasedly inform central and local governments with approaches to optimizing logistics efficiency.

A Normal Distribution-Based Methodology for Analysis of Fatal Accidents in Land Hazardous Material Transportation.

The deaths of accident occurring in land hazardous material transport (rail and road) is a scale standard for judging accident severity in safety programmes. The f-N curve is a common practice to express the results from past scattered accident data through curve fitting method, which only estimate the overall trend. For this reason, this paper proposed a simple methodology by combination of normal distribution and f-N curve. To verify the method, the following three sets of statistical data were selected and analysed in this study: 1932 accidents in over 95 countries (1931⁻2004) and 322 accidents in China (2000⁻2008) available in the literature, and 2046 accidents investigated in China (2013⁻2017). It was found that the mean value curve is almost identical or even better than the best-fitted curve, while the predicted upper and lower limits with 96% reliability (±2σ) covering nearly all the statistical data are beyond the scope of common curve fitting. The result explains the inherent relation between accumulated frequency and deaths in different transport mode, in different country and at different period. This study also provides insights on the evolution of accident severity with the development of social economy and the requirement of safety.