Identifying contributing factors to China's declining share of renewable energy consumption: no silver bullet to decarbonisation.

Renewable energy consumption (REC) holds the key to sustainable development. Therefore, many studies have considered the role of REC. However, the factors influencing the REC share in total energy usage (SREC) are not well investigated. Especially, the factors of China's fast-shrinking SREC are understudied. This research void on the world's largest renewable energy producer and consumer, i.e., China's decreasing SREC, is alarming and requires thorough investigation. Our study intends to fill this gap by analyzing the factors of China's decreasing SREC. The study uses both the conventional (descriptive and directional correlational analyses) and some unconventional (automatic linear modeling (ALM) and Artificial neural network (ANN) multilayer perceptron (MLP)) approach to investigate the factors of China's decreasing SREC. The initial hypothesis testing and most reliable model validation were achieved via directional correlational (Pearson and Spearman) and ALM analyses. The ANN MLP (two hidden layers) indicated that the most critical factor is "Combustible renewables and waste," with a 100% normalized importance. It was followed by "urbanization (64.2%), gross savings (56.1%), and alternative and nuclear energy (38%)," respectively. It is suggested that the Chinese government and private investors prioritize their investments based on factors' importance ranking.

A methodologically sound survey of Chinese consumers' willingness to participate in courier, express, and parcel companies' green logistics.

The environmental footprint of courier, express, and parcel (CEP) logistics is significant and growing, owing to increased e-commerce. Consumer willingness to participate in the green logistics of CEPs, however, has been understudied. This study addresses this knowledge gap by surveying 155 Chinese consumers about their willingness to participate in CEP green logistics. Additionally, this research identifies some technical issues with previous survey research. Three main factors were extracted after the data were tested for reliability and validity using exploratory factor analysis with principal axis factor extraction and confirmatory factor analysis with diagonally weighted least squares. Consumer willingness is positively correlated with economic (8 items), operational (3 items), and social (3 items) factors, with a statistical significance of p < 0.001. Of all the factors, the strongest correlation, 0.67 (95% CI = 0.57, 0.75; p < 0.001; N = 155), exists between economic factors and consumer willingness. The results of a multinomial logistic regression analysis suggest that all consumers are highly unlikely to participate in economic factors, while they are highly likely to positively commit to operational and social factors. Therefore, it is recommended that the government provides monetary incentives to CEP companies to adopt green logistics, such as tax reductions and subsidies, to reduce the costs of green logistics. Meanwhile, the CEP industry could provide some direct and indirect incentives to consumers to re-use, recycle, and share materials, and to spend time learning about express enterprises' green logistics, to increase consumer participation in economic factors.