Carbon dioxide mainly comes from industrial economic activities. Industrial structure optimization is an effective way to reduce carbon dioxide emissions. This paper uses the panel data of 13 cities in the Beijing-Tianjin-Hebei urban agglomeration from 2006 to 2019, uses the Theil index to calculate the industrial structure rationalization index, and uses the proportion of industrial added value to calculate the industrial structure upgrade index. By constructing the STIRPAT model, this paper quantitatively analyzes the impact of industrial structure rationalization and upgrade on carbon emissions. The results show that the rationalization and upgrading of industrial structure in the Beijing-Tianjin-Hebei urban agglomeration significantly inhibit carbon emissions. Compared with the rationalization of the industrial structure, the upgrading of industrial structure in the Beijing-Tianjin-Hebei urban agglomeration has a better effect on carbon emission reduction. For the Beijing-Tianjin-Hebei urban agglomeration, government expenditure on science and technology can promote the upgrading of industrial structure to a certain extent, thereby reducing carbon emissions. There is a big gap between the industrial structure development level of Hebei province and that of Beijing and Tianjin. Finally, based on the conclusion, this paper puts forward the policy enlightenment of promoting the optimization process of industrial structure and reducing carbon emissions of the Beijing-Tianjin-Hebei urban agglomeration.

A good partnership is conducive to promoting the empowerment of manufacturing small- and medium-sized enterprises (SMEs) via industrial Internet platforms. By analyzing the factors influencing the cooperation motives of both parties and individual behavior, this paper puts forward the design of a cost-sharing and scale revenue-sharing mechanism and establishes an evolutionary game model. Then, the evolutionary stability strategies (ESSs) of individuals and the evolutionary equilibrium state of the system are analyzed. The results show that the key factors affecting the strategic choices of industrial Internet platforms and manufacturing SMEs are different and will change with the number of platform customers and the level of digitalization of enterprises. By sharing the access cost of SMEs and the scale revenue of the platform, mutual trust between the two parties can be enhanced, and SMEs will be more motivated to access the platform. Moreover, the platform network externality, customer churn risk, and cost-sharing ratio have different influences on the process of reaching evolutionary equilibrium in the system. Collaborative revenue expectations are critical to the behavioral strategies of both parties. In comprehensive consideration of the results of this study, it is recommended that industrial Internet platforms be subsidized in the initial stage of cooperation.

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With the continuous development of e-commerce, it has become normal for the manufacturer to sell products and to collect used products through e-commerce platforms (platform for short). We consider an electronic closed-loop supply chain (E-CLSC) where we composed a manufacturer with remanufacturing capability and a platform that can provide logistics services. The purpose of this paper is to address whether the manufacturer should directly collect used products from the consumer under the platform. Specifically, we have developed four game models, namely model N (no collection), model M (the manufacturer collects), model E (the platform collects), and model T (the third-party collects) and derived the optimal pricing decisions, logistics service level, and collection rate for E-CLSC members. We found that remanufacturing used products is conducive to increasing the profits of the manufacturer and the platform as well as to increasing the utility of the consumer. Under the same conditions, for the manufacturer, the platform, and the consumer, the optimal choice is that the manufacturer directly collects the used products from the consumer. If the manufacturer is unable to establish an effective collection channel, he should consider outsourcing to a contractor and should consider the platform to be under the same conditions. Numerical examples are also given to verify the proposed results.

Under the strategy of “Digital China” and “Sustainable Development,” the synergistic development of digital economy and green economy has become a crucial topic. Based on the panel data of 13 cities in the Beijing-Tianjin-Hebei (BTH) region from 2011 to 2019, this study investigates the direct effect, intrinsic mechanism, and spatial spillover effect of digital technology development (DTD) on urban green development efficiency (GDE). The empirical results show that (1) DTD significantly improves urban GDE in the BTH region, and it passes the endogeneity test, (2) DTD can enhance urban GDE by improving the environmental regulation intensity and technological innovation level in the BTH region; however, the industrial structure optimization weakens the promotion effect of DTD on urban GDE in the BTH region, which shows a “masking effect,” (3) the kernel density estimation method and ArcGIS technology reveal the existence of “digital divide” and GDE differences among cities in the BTH region. Moreover, the spatial distribution pattern of DTD gradually forms “H–H” and “L-L” clusters in the BTH region, and (4) DTD also increases the GDE of neighboring cities through spatial spillover effects in the BTH region, and it passes the robustness test of replacing the spatial weight matrix. This study is important for the BTH region to simultaneously solve economic development and environmental problems in the context of digitalization.