Empirical Analysis of the Impact of Industrial Internet Development Environment on Open Green Innovation of Manufacturing Enterprises

Double-edged sword of industrial internet of things: Empirical evidence from green transformation of enterprises

The industrial revolution based on the Internet of Things brings new opportunities and challenges for enterprises' green and sustainable development. Therefore, this study explores the relationship between the Industrial Internet of Things (IIOT) and the Green Transformation of Enterprises (GT) based on the data of China's A-share listed companies from 2009 to 2023 using two-way fixed, mediated effect, and moderated effect models. The results show that for every unit increase in IIOT, the GT increases by 28.89 percent on average, indicating that IIOT can break down information barriers and effectively promote GT. However, after disaggregating the GT, it was found that the IIOT guided companies to implement the Symbolic Green Transformation (SGT) instead of adopting the Realistic Green Transformation (RGT). This strategic choice preference is more pronounced among firms that are larger, in energy-intensive industries, in regions with weaker environmental regulations and higher levels of development. The intermediary mechanism test proved that the IIOT can drive firms to implement comprehensive GT through paths that enhance investment attractiveness, productivity, technological innovation, and pay gaps. In particular, the masking effect reminds us that smart technology is a "double-edged sword". The negative effects of smart technologies hinder the implementation of RGT. Further analysis reveals an inverted U-shaped relationship between IIOT and RGT preferences. In addition, in companies that focus on Environmental, Social and Governance (ESG) performance and avoid financial speculation, the dark side of intelligent technology is suppressed. The findings of this study enrich the research scope of smart technology, GT, and provide important insights for enterprises in emerging economies to rationally utilize IIOT to seek green and sustainable development under the wave of rapid development of smart technology.

Industrial co-agglomeration, Internet utilization, and the development of green and low-carbon cycle - based on the empirical study of 41 cities in the Yangtze River Delta of China

The construction of green and low-carbon circular (GLC) development economic system is conducive to the promotion of "carbon peaking and carbon neutral." The level of GLC development in the Yangtze River Delta (YRD) region is related to the realization of the ambitious goal of "carbon peaking and carbon neutrality" in the region. This paper use principal component analysis (PCA) to process GLC development level of 41 cities in the YRD from 2008 to 2020. Then, we constructed panel Tobit model and threshold model from the perspective of industrial co-agglomeration and Internet utilization and empirically tested the influence of the two key variables on GLC development of the YRD. We found that (1) the YRD's level of GLC development showed a dynamic evolution trend of "fluctuation, convergence, and rise." The four provincial-level administrative regions of the YRD are in the order of  GLC development level: Shanghai, Zhejiang, Jiangsu, and Anhui. (2) There is an inverted "U" Kuznets curve (KC) between industrial co-agglomeration and the development of GLC of the YRD. In the left segment of KC, the industrial co-agglomeration promotes GLC development of the YRD. In the right segment of KC, the industrial co-agglomeration inhibits GLC development of the YRD. Internet utilization enhances GLC development of the YRD. And the interaction of industrial co-agglomeration and Internet utilization cannot significantly enhance GLC development. (3) Double-threshold effect of opening-up is manifested as follows: industrial co-agglomeration on GLC development of the YRD goes through an insignificant-inhibited-improved evolutionary trajectory. Single-threshold effect of government intervention is manifested as follows: the impact of Internet utilization on GLC development of the YRD shifts from insignificant role to significant enhancement. In addition, there is an inverted-N type KC effect between industrialization and GLC development. Based on the above findings, we proposed suggestions in terms of industrial co-agglomeration, Internet-like digital technology application, anti-monopoly, and rational industrialization.

Identifying the factors affecting strategic decision-making ability to boost the entrepreneurial performance: A hybrid structural equation modeling – artificial neural network approach

This study builds a conceptual model of strategic decision-making ability that leads to entrepreneurial performance (EP) based on the two-system decision-making theory and logical analysis. An empirical approach using structural equation modeling – artificial neural network (SEM-ANN) was performed to describe the linear and nonlinear relationships in the proposed model. The empirical results reveal that strategic decision-making abilities are affected by five factors: attention, memory, thinking, emotion, and sentiment, and whose influence mechanisms and degrees are varied. Results also describe that these abilities have a positive effect on overall EP. Therefore, results suggest that businesses’ strategic decision-making is usually strengthened when entrepreneurs have a clear understanding of these influencing elements, and the interaction between them leads to improved performance.