This study develops a framework consisting of normative, leadership, and sustainable capabilities to evaluate corporate green governance capabilities (CGGC) in supply chains. The Fuzzy Best-Worst Method (FBWM) is used to determine indicator weights, and the Combined Compromise Solution (CoCoSo) method is applied to rank firm performance in the Yangtze River Delta from 2014 to 2022. Results show low but improving governance levels with notable differences across regions and enterprise types. Leadership capabilities are more affected by external shocks. State-owned and high-pollution firms perform better, while non-state and labor-intensive firms improve more rapidly. The study contributes methodological and practical insights.

This study investigated the impact of corporate financial strategies-(CFSs) on the performance of companies listed on the Shanghai Stock Exchange-(SSE) from 2010-2023, analyzing data from 2,269 firms, yielding 31,766 balanced firm-year observations. Utilizing a mixed-methods approach with a quasi-experimental design grounded in pragmatism, the inquiry employed two-step System-GMM technique to address endogeneity, simultaneity, heteroscedasticity, reverse causality and Nickell bias. Fixed effects-(FE) and random effects-(RE) models were applied to handle unobserved heterogeneity, omitted variable bias and guarantee robustness. The results revealed that, total-debt-to-assets-ratio-(TDTAR) and dividend yield-(DY) significantly and negatively impacted firm performance-(FP), measured by return on assets-(ROA) and Tobin’s Q-(TQ). Contrary, cash conversion cycle-(CCC), current ratio-(CR), total-assets-turnover-(TAT), tangibility-(TANG), total-equity-to-total-assets ratio-(TETAR), dividend payout ratio-(DPR), firm size-(SIZE), and firm age-(AGE) had a significantly positive effect on FP-(ROA and TQ). The study emphasizes the importance of effective CFSs in improving FP and offers insights for policymakers, investors, and managers, highlighting the need for corporate deleveraging, capital structure optimization and efficient asset and working capital management. Although focused on China, the study’s framework is applicable to other emerging markets, providing valuable theoretical, conceptual, and methodological insights as it integrates CFS metrics into the resource-based view theory-(RBVT), extending the theory’s scope making it more robust and generalizable.

This research examines how artificial intelligence (AI) integration has affected employment in China’s construction industry. This research builds on the theories of skill-biased technological change and creative destruction to study how AI influences both positive and negative employment effects that later influence overall employment. The report confirms, based on the survey data and by using PLS-SEM, that AI introduction results in both job growth and job losses for managerial-level employees. In addition, whether an organization is ready greatly affects how these relationships play out, improving good outcomes and reducing the bad ones. It is clear from the findings that preparing a strategy helps make the most of AI and alleviate its risks. The study contributes to a more detailed view of AI’s effects on jobs and supplies ideas for sustaining both innovation and employment.

This study investigates the impact of cross-Border E-commerce development on China’s foreign trade. The software SPSS is used to calculate the value of each independent variable CBEC transaction volume, business infrastructure, professional talents, and development potential, and the software STATA version 18 is used to perform all the regression analyses. The findings reveal that efficient CBEC business infrastructure, including electronic payments, logistics, and digital support systems advancements, significantly enhances trade facilitation. Additionally, developing and cultivating professional CBEC talents are critical in sustaining trade growth, though there remains a significant talent gap in high-end, composite skills. Furthermore, the study highlights the immense potential of CBEC to broaden trade channels, improve global competitiveness, and foster innovation in small and medium-sized enterprises (SMEs). The analysis indicates steady growth in CBEC transactions and infrastructure, alongside an increasing internet penetration rate, supporting the sector's expansion. The study concludes with recommendations for policymakers and businesses, emphasizing the need to enhance infrastructure, cultivate professional talents, and strengthen market potential to ensure sustainable CBEC development and boost foreign trade. These insights provide a comprehensive understanding of the mechanisms CBEC influences foreign trade, offering a valuable reference for future research and policy formulation.

The purpose of this paper was to examine the relationships among work overload (WO), compensation (COM), organizational identification (OI) and organization embeddedness (OE) in the context of manufacturing industry in China through social identity theory. A 37-item questionnaire was filled by 384 new generation of rural migrant workers. Data were examined through a two-stage of first-order of reflective model and second-order reflective-formative hierarchical model using PLS-SEM. The empirical results indicate that COM and OI positively and significantly predicted OE, while WO was found to have no direct effect on OE. In addition, COM positively and significantly was associated with OI, whereas WO affected OI, negatively. Further examination of the mediation effects of OI revealed that OI could fully mediate the relationship between WO and OE. Moreover, OI also had a partial mediator role in the relationship between COM and OE. The study concluded with several implications and recommendations for future research.

This research applies TOPSIS, which stands for Technique for Order of Preference by Similarity to Ideal Solution, to evaluate and rank the performance of telemedicine in the seven Chinese cities—Hangzhou, Wuhan, Chengdu, Shanghai, Beijing, Guangzhou, and Shenzhen. The evaluation was based on five major criteria: Infrastructure, Healthcare System Integration, Accessibility & Equity, Service Breadth & Quality and Regulatory Environment. In a noteworthy finding, Hangzhou was at the top all the time, while Shenzhen was at the bottom despite its technological might. The result was very strong, being the same even when the cost criterion was given 50% weight which showed that the price factor alone does not overpower other performance disparities. The outcomes are a surprise to the common understanding that very high-quality medical institutions in a city and very good technology infrastructure are the only factors that determine the success of telemedicine. Rather, a city’s ability to build an integrated, user-centered digital ecosystem determines the leadership in telemedicine. The first position of Hangzhou indicates the benefit of unrestricted healthcare accessibility through a platform-based system whereas the last position of Shenzhen points out the drawbacks of an expensive and inequitable system. This study shifts the paradigm for future telemedicine cities from "Medical Resource" to "Integrated Ecosystem" model, thus, posing significant implications for the decision makers who strive to ensure effective and equal access to digital health services.