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Environmental leadership has received continuous attention from the business sector in recent years, yet few studies have examined the internal mechanisms and contingent conditions that link environmental leadership to firm performance. The aim of this article is to advance research by investigating the relationship between environmental leadership and firm performance by considering the mediating role of green innovation practices and the moderating role of environmental knowledge learning. A questionnaire survey is used to collect data from 353 agricultural products corporations in China. Empirical results show that environmental leadership has a positive relationship with the two dimensions of firm performance, namely, environmental performance and financial performance. Results also indicate that green innovation practices (including green innovation strategy and actions) play a mediating role between environmental leadership and firm performance. Meanwhile, it is also found that environmental knowledge learning positively moderates the effect of environmental leadership on green innovation practices. This study adds value to the environmental management literature by introducing leadership style as an antecedent variable to examine the impact of environmental leadership on firm performance in China. And the study also highlights the important moderating effect of environmental knowledge learning on the relationship between environmental leadership and green innovation practices. The findings of this article could be important in terms of both management and policy implications.

The task of reducing carbon emission intensity is difficult for manufacturing firms in China under the national goal of “carbon peaking and carbon neutrality”. Numerous studies have confirmed the inhibitory impact of ESG performance on carbon emission intensity; nevertheless, the significance of ESG rating divergence as a derivative of ESG ratings has been neglected. Therefore, this study selects Chinese A-share listed manufacturing firms from 2011–2022 as a research sample and empirically examines the impact of ESG rating divergence on the carbon emission intensity of Chinese manufacturing firms via a higher-order fixed effects model. The study revealed that (1) ESG rating divergence creates disincentives for manufacturing firms to increase carbon emission intensity; (2) ESG rating divergence leads to an increase in corporate carbon emissions by inhibiting incentives for green innovation; and (3) mitigating financial constraints and enhancing digital transformation in enterprises diminishes the impact of ESG rating divergence on the carbon emissions of manufacturing firms. Furthermore, enterprise digital transformation can exert a moderating influence on both the initial and subsequent stages of the “ESG performance → green innovation → carbon emission intensity” pathway, predominantly in the initial phase. (4) The impact of ESG rating divergence on carbon emission intensity varies depending on the ownership, industry, geography, and level of competitiveness of manufacturing enterprises. The findings not only provide empirical evidence on the feasibility of expanding the standardization of ESG ratings within China’s regulatory framework but also provide useful inspiration for Chinese firms to reduce their carbon emission intensity and achieve sustainable development.

In the mammalian neocortex, projection neuron types are sequentially generated by the same pool of neural progenitors. How neuron type specification is related to developmental timing remains unclear. To determine whether temporal gene expression in neural progenitors correlates with neuron type specification, we performed single-cell RNA sequencing (scRNA-Seq) analysis of the developing mouse neocortex. We uncovered neuroepithelial cell enriched genes such as Hmga2 and Ccnd1 when compared to radial glial cells (RGCs). RGCs display dynamic gene expression over time; for instance, early RGCs express higher levels of Hes5, and late RGCs show higher expression of Pou3f2. Interestingly, intermediate progenitor cell marker gene Eomes coexpresses temporally with known neuronal identity genes at different developmental stages, though mostly in postmitotic cells. Our results delineate neural progenitor cell diversity in the developing mouse neocortex and support that neuronal identity genes are transcriptionally evident in Eomes-positive cells.

PurposeFollowing the rapid expansion of data volume, velocity and variety, techniques and technologies, big data analytics have achieved substantial development and a surge of companies make investments in big data. Academics and practitioners have been considering the mechanism through which big data analytics capabilities can transform into their improved organizational performance. This paper aims to examine how big data analytics capabilities influence organizational performance through the mediating role of dual innovations.Design/methodology/approachDrawing on the resource-based view and recent literature on big data analytics, this paper aims to examine the direct effects of big data analytics capabilities (BDAC) on organizational performance, as well as the mediating role of dual innovations on the relationship between (BDAC) and organizational performance. The study extends existing research by making a distinction of BDACs' effect on their outcomes and proposing that BDACs help organizations to generate insights that can help strengthen their dual innovations, which in turn have a positive impact on organizational performance. To test our proposed research model, this study conducts empirical analysis based on questionnaire-base survey data collected from 309 respondents working in Chinese manufacturing firms.FindingsThe results support the proposed hypotheses regarding the direct and indirect effect that BDACs have on organizational performance. Specifically, this paper finds that dual innovations positively mediate BDACs' effect on organizational performance.Originality/valueThe conclusions on the relationship between big data analytics capabilities and organizational performance in previous research are controversial due to lack of theoretical foundation and empirical testing. This study resolves the issue by provides empirical analysis, which makes the research conclusions more scientific and credible. In addition, previous literature mainly focused on BDACs' direct impact on organizational performance without making a distinction of BDAC's three dimensions. This study contributes to the literature by thoroughly introducing the notions of BDAC's three core constituents and fully analyzing their relationships with organizational performance. What's more, empirical research on the mechanism of big data analytics' influence on organizational performance is still at a rudimentary stage. The authors address this critical gap by exploring the mediation of dual innovations in the relationship through survey-based research. The research conclusions of this paper provide new perspective for understanding the impact of big data analytics capabilities on organizational performance, and enrich the theoretical research connotation of big data analysis capabilities and dual innovation behavior.

Innovation and entrepreneurship vitality, as a key factors in the development of the digital economy, significantly affects both regional economic development and residents’ consumption capacity. On the basis of the panel data of 31 provinces and cities in China from 2010 to 2022, this paper explores the impact of regional innovation and entrepreneurship vitality on residents’ leisure consumption potential and its internal mechanism. Research has shown that innovation and entrepreneurship vitality drives leisure consumption potential. Furthermore, regional innovation and entrepreneurship vitality can effectively increase educational investment, which in turn increases residents’ leisure consumption potential. Although scientific and technological investment can significantly increase innovation and entrepreneurship vitality, it curtails the development of residents’ leisure consumption potential. In addition, there are significant differences in the effect of regional innovation and entrepreneurial vitality on residents’ leisure consumption potential in different policy environments and demographic structure. Diverse policies help to better stimulate regional innovation and entrepreneurship influence on residents’ leisure consumption. The development of innovation and entrepreneurship vitality can effectively stimulate the leisure consumption potential of residents in areas with low population mobility, which compensate for the decrease of leisure consumption due to the lack of external population. On the basis of the inconsistency between economic development and residents’ spiritual needs in China’s major contradictions, this study further explores the coordination between scientific and technological development and individuals’ needs for a better life, and further complements and justifies the literature in the field of innovation and consumption.

Drawing on a perspective grounded in social information processing theory, this paper investigates the mechanism through which organizational innovative climate affects individual improvisational behavior. We developed a theoretical model for analyzing our hypotheses and conducted an empirical study by analyzing data from 356 employees who work for service enterprises. Our paper finds that organizational innovative climate impacts employees’ improvisational behavior by triggering their psychological safety perception. It is also found that employee’s creative self-efficacy plays a positive moderating role in the relationship between organizational innovative climate and employees’ improvisational behavior. The results of our study assert that improvisation is not just an inherently individual phenomenon. Rather, it is also affected by the characteristics of the organizations in which employees are embedded. We discuss the implications of these findings for understanding and promoting employees’ improvisational behaviors in the workplace.

The outbreak of COVID-19 at the beginning of 2020 had a significant impact on China’s economy, society, and citizens; it also had a negative impact on the development of the construction industry. In particular, small and medium-sized construction enterprises with low ability to withstand risk have been strongly impacted, aggravating a crisis of survival among these firms. The focus of this study is to analyze the impact of COVID-19 on the growth of small and medium-sized construction companies. Based on the characteristics of small and medium-sized construction enterprises, this paper establishes a growth evaluation index and builds a growth evaluation model based on factor analysis. Twenty-three construction enterprises listed on small and medium-sized enterprises board are selected as samples, and the quarterly data of 2019 and 2020 are used for empirical analysis. The results show that the epidemic has had a high short-term impact on construction enterprises, and the total output value of the construction industry in the first quarter of 2020 was 16% lower than that in the same period of last year. In the long run, the impact of the epidemic on the growth of small and medium-sized construction enterprises has been limited. In the first quarter of 2020, the growth score of enterprises decreased by only 1.95% year-over-year, and it was essentially flat in the second and third quarters. The epidemic has had little influence on solvency, tangible resources or intangible resources but a high short term influence on profitability, capital expansion and market expectations. The long-term impact is small; It is conducive to the improvement of enterprise operation ability. Finally, to both address the influence of the COVID-19 on small and medium-sized construction enterprises and to realize their transformation and upgrading, targeted suggestions are offered at the policy and enterprise levels. The results will help to understand the impact of the epidemic on the growth of construction enterprises, and provide decision support for the healthy and orderly development of the follow-up construction industry.

Despite the pivotal function of knowledge sharing for enterprises in today’s highly competitive and ever-changing economic environment, the mechanism about how ethical leadership impacts employees’ knowledge sharing remains a largely unexplored domain in the literature. Drawing on the social exchange theory and social learning theory, this study examines how ethical leadership helps to encourage followers’ knowledge sharing behavior considering the dual-mediating effects of positive reciprocity and moral efficacy. A questionnaire-based survey is used to collect data in China. And structural equation modeling techniques are used to analyze the collected data in order to test the proposed hypothesis. Results show that ethical leadership has positive impact on followers’ knowledge sharing. It is also found that both positive reciprocity and moral efficacy play significant mediating effects, and they are equally important in accounting for the impact of ethical leadership on followers’ knowledge sharing. Based on the analysis results, this paper further discusses theoretical and practical implications.

Balancing efficiency and equity within agricultural supply chains is crucial for rural revitalization and sustainable development. This study focuses on the three-tiered chain of ‘farmers–cooperatives–retailers’, constructing a joint decision-making model linking pricing, sales effort, and order volume. It compares the performance differences between decentralized and centralized decision-making structures. Methodologically, we introduce four corrective factors—risk-bearing capacity, cooperation level, capital investment, and information access—to the traditional Shapley value. By employing TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) to calculate proximity, we derive an enhanced Shapley–TOPSIS allocation coefficient. Furthermore, we design a secondary distribution rule of ‘effort-based value-added distribution according to labor contribution,’ tightly binding the marginal returns of sales effort to input intensity, thereby reconciling structural fairness with incentive compatibility. Empirical findings indicate that, compared with decentralized approaches, centralized decision-making significantly enhances overall system revenue and reduces retail prices. The refined distribution scheme outperforms the baseline Shapley value in fairness and stability, effectively mitigating the misalignment where effort contributors receive disproportionately low returns. The optimal sales effort level is approximately 0.35. Under the ‘distribution according to labor’ approach, retailers (the primary effort providers) see a marked increase in their value-added share, whereas farmers and cooperatives also gain positive benefits, enhancing alliance stability. Unlike existing studies that rely mainly on revenue-sharing contracts or a single Shapley allocation, this study, on the one hand, explicitly endogenizes sales effort into demand and profit functions and systematically characterizes the joint mechanism between effort and profit allocation under both centralized and decentralized structures. On the other hand, an improved Shapley–TOPSIS modeling procedure and an ‘effort added-value allocation according to contribution’ rule are proposed. By adjusting demand parameters and the weights of the adjustment factors, the proposed framework can be readily extended to other agricultural products and green supply chain settings, providing a replicable tool and managerial implications for designing sustainable profit allocation schemes.

In the context of financial support for rural revitalization, digital financial inclusion may become a new “gospel” to alleviate agricultural surface source pollution. Based on the panel data of 30 Chinese provinces from 2011 to 2020, the study constructs a fixed-effects model to test the mitigation effect of digital financial inclusion on agricultural non-point source pollution empirically. The study finds that: 1) Digital financial inclusion has a mitigating effect on agricultural non-point source pollution, and the abatement effect still exists after the robustness tests such as replacing the explanatory variables, reducing the sample size, and endogeneity treatment. 2) The moderating effect test shows that the income structure of farmers strengthens the mitigation effect of digital financial inclusion on agricultural non-point source pollution, i.e., the more the income structure of farmers tends to be “non-farmed”, the stronger the mitigation effect of digital financial inclusion. 3) The heterogeneity test found that all three dimensions of digital financial inclusion, including the breadth of coverage, depth of use, and degree of digitization, can mitigate agricultural non-point source pollution, but there are differences in the intensity of the effect. Compared with the northwestern part of the “hu huan yong” line, the mitigation effect of digital inclusive finance is more significant in the southeastern part of the “hu huan yong” line. 4) The threshold effect test shows that the mitigation effect of digital financial inclusion on agricultural non-point source pollution has non-linear characteristics, and there is a double threshold effect of digital financial inclusion, and the mitigation effect will be enhanced as the development level of digital financial inclusion increases.