In this paper, we firstly investigate issues of low carbon supply chain including one retailer and one manufacturer in the context of joint information asymmetry and cap-and-trade mechanism, where the retailer is a leader and faces a stochastic demand, and the manufacturer is a follower and keeps private information in carbon emissions. Our aim is to design an incentive contract to make the manufacturer disclose the carbon information. Furthermore, we quantify the effects of the carbon price, the carbon emissions and the carbon quota on the supply chain model and design an incentive contract for improving supply chain performance. Finally, we give a couple of numerical examples and undertake sensitivity analysis to illustrate the proposed model and provide some managerial inferences in the conclusions.

Industrial-technological innovation (ITI) has far-reaching significance for China’s sustainable development. In this study, we construct an ITI model to analyze the impact of communication barrier and spillover effects in ITI system from the perspective of system by means of system dynamics. Statistical data of smartphone industry were collected to verify the authenticity of the model, which show that the model has higher goodness of fit with the real-world. Simulation experiments were carried out and the results showed that: (1) Spillover effects have obvious effects on ITI in both positive and negative radiation directions, and deeper exchanges and cooperation should be encouraged to carry out among firm. (2) Communication barrier play an important role in regulating ITI. Under the condition of non-barrier and complete-barrier, the completion time of the whole process has increased by 76.5%, it is urgent to reduce communication carrier. The research puts forward suggestions to help improve ITI from institutional, market, and government.

Understanding the efficiency of green innovation in the logistics industry can drive sustainable development in China. However, there is a lack of evolutionary patterns and drivers of green innovation efficiency in the logistics industry. We examine the evolutionary patterns of green innovation efficiency in the logistics industry and identify its drivers across 30 provinces and cities in China from 2012-2021. This study examines the evolutionary patterns of green innovation efficiency in the logistics industry and identifies its drivers across 30 provinces and cities in China. It was discovered that there has been a consistent upward trend in the logistics sector's degree of green innovation efficiency. The eastern region exhibits the greatest average values across three indices of green innovation efficiency, with significant regional differentiation that decreases gradually from east to west. The overall spatial network displays an uneven pattern, with the central east showing higher efficiency and the west showing lower efficiency. Drivers such as spatial proximity, industrial structure, scientific and technological levels, and energy utilization significantly affect green innovation efficiency (P < 0.05). We underscore the importance of promoting regional cooperation and exchange, strengthening industrial restructuring and upgrading, and enhancing science, technology, and energy utilization to unleash the logistics industry's potential for green innovation.