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This study aims to explore the impact of green inclusive leadership (GIL) on green creativity (GCRY) within the context of higher education institutions (HEIs) in China. Specifically, it aims to examine the mediating roles of green intrinsic motivation (GIM), environmental knowledge (EK) and green thinking (GT) according to the componential theory of creativity (CTC).

The study employed a series of questionnaire surveys to collect data at three different time points from various sources. A total of 583 leader-faculty matched samples were obtained from two universities in China. The hypothesized relationships were tested using PROCESS macro in SPSS.

The findings indicate a beneficial influence of GIL on GCRY, mediated by GIM, EK and GT. Noteworthy interaction effects were observed, with GIM fostering EK and GT, and EK laying the groundwork for GT.

This research contributes to the existing literature by confirming the implementation of GIL and supporting the CTC, offering insights into the motivational processes driving GCRY and with practical implications discussed for the effective management of GIL and GCRY in higher education settings.

The novelty of this research model lies in its operationalization of environmental sustainability within the CTC. This study is the initial investigation highlighting the role of GIL in fostering GCRY within HEIs. The key contribution of the study is the investigation of GIM, EK and GT as potential mediators in the relationship between GIL and GCRY. This expands the theoretical boundaries of the CTC framework.

This study draws on the conservation of resources logic to theorize the role of firm resilience in explaining variations in entrepreneurial well-being under varying conditions of supply chain disruption and dependency ratio.

The study uses ex-post survey data from 373 women entrepreneurs in diverse agricultural supply chains in Ghana, a sub-Saharan African country. Moderated regression analysis is employed to test the research hypotheses.

The results indicate that firm resilience has both positive and negative relationships with economic and subjective well-being, depending on the level of supply chain disruption and dependency ratio women entrepreneurs face. Notably, the findings suggest that firm resilience contributes more to economic and subjective well-being of women entrepreneurs when dependency ratio is low and supply chain disruption is high.

The study integrates firm resilience research and entrepreneurial well-being literature to provide new insights into theorizing and analyzing the benefit of firm resilience for women entrepreneurs’ well-being.

In the era of the digital economy, higher demands are placed on versatile talents, and the cultivation of students with innovative and entrepreneurial abilities has become an important issue for the further development of higher education, thus leading to extensive and in-depth research by many scholars. The study summarizes the characteristics and patterns of dual-innovation education at different stages of development, hoping to provide a systematic model for the development of dual-innovation education in China and make up for the shortcomings.

This paper uses Citespace software to visualize and analyze the relevant literature in CNKI and Web of Science databases from a bibliometric perspective, focusing on quantitative analysis in terms of article trends, topic clustering, keyword co-linear networks and topic time evolution, etc., to summarize and sort out the development of innovation and entrepreneurship education research at home and abroad.

The study found that the external characteristics of the literature published in the field of bi-innovation education in China and abroad are slightly different, mainly in that foreign publishers are more closely connected and have formed a more stable ecosystem. In terms of research hotspots, China is still in a critical period of reforming its curriculum and teaching model, and research on the integration of specialization and creative education is in full swing, while foreign countries focus more on the cultivation of students' entrepreneurial awareness and the enhancement of individual effectiveness. In terms of cutting-edge analysis, the main research directions in China are “creative education”, “new engineering”, “integration of industry and education” and “rural revitalization”.

Innovation and entrepreneurship education in China is still in its infancy, and most of the studies lack an overall overview and comparison of foreign studies. Based on the econometric analysis of domestic and foreign literature, this paper proposes a path for domestic innovation and entrepreneurship education reform that can make China's future education reform more effective.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

In large-scale environments, LIO-SAM (Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping) exhibits poor robustness due to the accumulation of errors caused by factors such as the prevalence of similar surroundings and the lack of features in certain open areas. Therefore, the purpose of this study is to optimize the loop detection module of LIO-SAM to reduce error accumulation and enhance mapping and localization performance.

Based on the LIO-SAM framework, the LinK3D (Linear Keypoints Representation for 3D LiDAR Point Cloud) feature extraction algorithm is integrated in the front end, while the BoW3D (Bag of Words for Real-Time Loop Closing in 3D LiDAR SLAM) loop detection algorithm is integrated in the back end. The features extracted by LinK3D serve as the range factors for the LiDAR, the BoW3D generates loop closure factors and these, along with inertial measurement unit (IMU) preintegration factors and global positioning system (GPS) factors, are added to the factor graph of LIO-SAM. This addition of constraints enhances the mapping and localization effects, optimizing the overall mapping and localization performance.

Based on the electrically controlled car, experiments were conducted in the experimental scenario proposed in this paper. Compared to LIO-SAM, the method presented in this paper significantly reduces cumulative errors. While ensuring real-time performance, it demonstrates superior mapping and localization effects.

This paper proposes and validates a method that integrates LinK3D, BoW3D and LIO-SAM, named LB-LIOSAM, which enhances the accuracy of feature extraction, optimizes the loop detection module of LIO-SAM and improves its mapping and localization performance in specific environmental scenarios.

This paper believes that while implementing the gradual delay retirement age policy in China, the impact should be considered comprehensively; we should pay attention to impacts brought by the delayed retirement policy and introduce policies to deal with the impacts in a timely manner.

This paper aims to explore the delayed retirement’s impact on women’s labor supply and to clarify the elderly care’s role in it.

The results found that the delayed retirement has a positive effect on the women’s overall and young women’s labor supply, with a more significant promotion for young women’s labor supply. The mediation results suggest that delayed retirement promotes women’s labor supply by affecting elderly care. Therefore, we believe that while implementing the gradual delay retirement policy in China, it is important to implement it on the correct estimation basis so as to reduce the volatility in the labor market.

This paper may produce marginal contributions in the following two aspects: From the research perspective, we construct a model containing delayed retirement, elderly care and women’s labor supply and illustrate how the delayed retirement promotes women’s labor supply by affecting elderly care. Secondly, from the research content, this paper expands the delayed retirement on macro-employment and further explores the micro-impact on employment.

Based on upper echelons theory and social contagion theory, we investigate how environmental leadership affects GIC via green human resource management (GHRM) and examine the moderating role of environmental climate.

We conduct hierarchical regression and use the bootstrap method to analyze the two-waved data from 317 Chinese manufacturers in order to verify the hypotheses.

The results indicate that GHRM mediates the impacts of environmental leadership on green human capital, structural capital and relational capital. In addition, environmental climate strengthens the positive impact of environmental leadership on GHRM.

Our study enriches the literature on GIC by uncovering the “black box” between environmental leadership and GIC, providing a logical framework opposite to mainstream GIC research, and expanding the boundary condition for GIC accumulation. This study provides more logical paths for enterprises and governments to increase the accumulation of GIC and promote green intellectual economy development.