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Given the widespread adoption of empowerment in the workplace, increasing research has investigated the influences of empowering leadership. However, previous research has found confounding effects of it. This study aims to examine how and when empowering leadership exhibits “double-edged sword” effects on followers’ work outcomes.

The authors used a three-wave survey with a final sample of 215 full-time employees to test the research model.

The results indicate that followers’ role-breadth self-efficacy (RBSE) interacted with empowering leadership to predict their hindrance-related stress, subsequently influencing their turnover intention. Specifically, empowering leadership is found to elicit hindrance-related stress among followers with low RBSE. Furthermore, empowering leadership indirectly affects turnover intention by eliciting hindrance-related stress only among followers with low RBSE.

This study broadens the exploration of the “dark side” of empowering leadership, offering a more nuanced explanation of how it can lead to both beneficial and detrimental outcomes. It refines the understanding of empowering leadership’s effectiveness by highlighting the role of followers’ RBSE rather than focusing solely on the degree of empowerment. In addition, by contributing to the stress theory, this research demonstrates how individual differences influence followers’ cognitive appraisal of stress, shaping distinct stress experiences and driving the adoption of varying work-related coping strategies.

Smart manufacturing (SM) capitalizes on big data analytics (BDA) advancements by enhancing current capabilities such as defect identification and enabling supporting capabilities such as preventive maintenance (PM). The previous literature fails to investigate the comprehensive associations between SM, BDA and PM. Therefore, this study aims to investigate the relationship among SM, BDA and PM.

The present research implements a multi-analytical PLS-SEM-ANN approach to investigate the relationships among BDA, PM and SM.

This investigation indicates that BDA is an effective digital technology that positively affects the operations of SM and PM. Furthermore, the results suggest that PM has a positive influence on SM and that it also positively mediates the relationship between BDA and SM, where PM cannot be treated as an auxiliary practice and plays an important role in SM as a primary operation. Furthermore, implementing the BDA enhances the performance of SM and PM.

The role of PM in the context of BDA and SM has been ignored in past research, and this study offers novelty by examining this relationship.

To deepen the structural reform of the financial system on the supply side and mitigate associated risks in the economic and financial fields, with significant practical implications for FinTech development.

Based on microdata of listed companies, this paper constructs multi-level indicators of FinTech development. Robustness tests include alternative measures of the degree of long-term use of short-term debts, sample adjustments and heterogeneity in firm characteristics and regional differences.

FinTech can significantly alleviate the long-term use of short-term corporate debt, although there are heterogeneous effects. The alleviation effect is more pronounced for state-owned enterprises, non-technology-intensive enterprises and other companies with lower levels of short-term debt maturity. Additionally, in regions with high capital mismatch and high levels of financial development, FinTech exhibits a significant suppressive effect on the long-term use of short-term corporate debt.

The paper suggests promoting the diversification of FinTech products, emphasizing the importance of inclusive finance through FinTech, and driving China’s economic transformation and high-quality development.

By constructing a theoretical analysis framework of “FinTech—corporate investment and financing term mismatch,” this paper provides a multi-level estimation of the factors influencing FinTech’s impact on the long-term use of short-term corporate debt. This framework aids in developing a more dialectical and objective understanding of the economic effects of FinTech’s development.

This study aims to develop a novel self-powered monitoring system that uses radio frequency (RF) energy harvesting and ultra-low-power management technologies for real-time condition monitoring of switch rails.

The system is designed for integration within the jump wire holes of switch rails, ensuring structural integrity and aesthetic appeal. It features a highly efficient energy harvesting mechanism combined with optimized power management for wireless sensor nodes. An on-board antenna captures ambient RF energy, managed by high-efficiency circuits to ensure stable wireless sensor operation. An ultra-low-power system-on-chip is used to acquire and transmit multimodal data on vibration and temperature from the switch rails. The data collection is enhanced through a two-threshold approach, adapting to harvested energy levels for self-energy balancing.

Testing revealed that the energy harvesting subsystem operated stably at distances up to 2.9 m from the RF source, charging a 200 µF capacitor to 4.2 V in just 220 s. The monitoring subsystem’s average power consumption is in the low microwatt range. Continuous operation over 30 days in real conditions resulted in only a 5 mV reduction in battery voltage, indicating successful self-powered operation and validating long-term reliability in unattended scenarios.

This research presents an innovative solution, integrating RF energy harvesting with ultra-low-power technology, which addresses the power and stability challenges faced by traditional monitoring systems.

Face is the most intuitive and representative feature at the individual level. Many studies show that beautiful faces help individuals and enterprises obtain economic benefits and form a high economic premium, but the discussion of their potential social value is insufficient. This study aims to focus on the impact of the personal characteristics of executives. It mainly analyzes the impact mechanism of CEO facial attractiveness on corporate social responsibility (CSR) decision-making, clarifying the social value of beauty from the perspective of CSR.

The authors use the regression model to analyze the panel data set, which was conducted by a sample of Chinese publicly listed firms from 2016 to 2018.

The study found that CEOs with high facial attractiveness are more active in fulfilling CSR, which can usually bring higher social benefits. CEOs with beautiful faces are prone to overconfidence, are optimistic about their ability and the future development of the enterprise and are more willing to increase their investment in CSR. CEO duality can positively regulate the positive correlation between a CEO’s facial attractiveness and CSR.

Based on the perspective of upper echelons theory, this paper explores the mechanism of CEO facial attractiveness on CSR. This study enriches the perspective of the upper echelon’s theoretical research and has essential enlightenment for CEO selection and training practice.

This paper aims to examine the impact of corporate environmental transparency (CET) on corporate financial performance under a mandatory environmental disclosure policy in China, the largest carbon-emitting country. It aims to clarify the concept of CET and investigate its short-term financial implications for key pollutant-discharging entities (KPEs).

A multidimensional model is used to construct a comprehensive CET index for KPEs in China. Empirical tests are conducted to assess the relationship between CET and corporate financial performance.

The study finds a negative relationship between CET and corporate financial performance in the short term. Increased environmental transparency necessitates higher environmental resource allocation, adversely affecting profits. The results remain unchanged from a battery of robustness tests. Despite mandatory disclosure, companies tend to provide general and vague information rather than specific and meaningful environmental data.

The findings provide rich practical implications for policymakers to improve a mandatory environmental disclosure policy. The paper also contributes to the existing knowledge by developing a measure of CET and presenting new evidence to the debate on whether corporate environmental disclosure can be regarded as transparency.

Policymakers are advised to refine mandatory environmental disclosure regulations to ensure genuine transparency and to implement policy measures that alleviate the financial burdens of companies with high CET levels, thereby encouraging sustainable practices.

This paper contributes to the existing knowledge by developing a measure of CET and providing new evidence on the debate over whether environmental, social and governance (ESG) disclosure equates to transparency. It emphasizes the complexity of transparency and the inadequacy of current environmental disclosure practices among KPEs. The study underscores the need for financial support for companies with high CET levels to alleviate short-term financial strains and promote long-term sustainability.

Motivated by the significant role of uncertainty in affecting investment decisions and China's economic leadership in Asia, this paper investigates the predictive role of exposure to Chinese economic policy uncertainty at the individual stock level in large Asian markets.

We estimate the monthly uncertainty exposure (beta) for each stock and then employ the portfolio-level sorting analysis to investigate the relationship between the China’s uncertainty exposure and the future returns of major Asian markets over multiple trading horizons. The raw returns of the high-minus-low portfolios are then adjusted using conventional asset pricing models to investigate whether the relationship is explained by common risk factors. Finally, we check the robustness of the portfolio-level results through firm-level Fama and MacBeth (1973) regressions.

Applying portfolio-level sorting analysis, we reveal that exposure to Chinese uncertainty is negatively related to the future returns of large stocks over multiple trading horizons in Japan, Hong Kong and India. We discover this is unexplained by common risk factors, including market, size, value, profitability, investment and momentum, and is robust to the specification of stock-level Fama and MacBeth (1973) regressions.

Our analysis demonstrates the spillover effects of Chinese economic policy uncertainty across the region, provides evidence of China's emerging economic leadership, and offers trading strategies for managing uncertainty risks.

The findings of the study significantly improve our understanding of stock return predictability in Asian markets. Unlike previous studies, our results challenge the leading role of the US by providing a new intra-regional return predictor, namely, China’s uncertainty exposure. These results also evidence the continuing integration of the Asian economy and financial markets. However, contrary findings for some Asian markets point toward certain market-specific features. Compared with market-level research, our analysis provides deeper insights into the performance of individual stocks and is of particular importance to investors and other market participants.

The purpose of this study is to examine the impact of customers' environmental concern on corporate green innovation and its underlying mechanisms.

This study empirically examines the impact of customer environmental concern on corporate green innovation using 967 company-customer-year observations of Chinese A-share listed companies over the period 2012–2022.

The empirical results show that customer environmental concern significantly enhances corporate green innovation. Furthermore, executive environmental awareness and research and development (R&D) investment play a partial mediating role in this relationship. The heterogeneity analysis reveals that state-owned customers, customers located in the same province with the corporate and the intellectual property model cities contribute to strengthening this relationship. Moreover, corporate performance analysis shows that customer environmental concern can significantly increase corporate financial performance and sustainable performance.

This study innovatively proposes a measure of customer environmental concern and examines its impact on corporate green innovation and its underlying mechanisms. In addition, this study also proposes some insights for policymakers.

Innovation resilience, which refers to firms’ ability to consistently innovate and recover from disruptions, has recently gained increasing attention. Digital transformation plays a crucial role in the innovation of manufacturing firms. This paper aims to investigate the impact mechanisms of manufacturing firms’ innovation resilience in the context of digital transformation.

Using panel data from Chinese A-share listed manufacturing firms spanning from 2017 to 2022 as an example, this research examines the impact of digital transformation on innovation resilience. It also tests the moderating effect of innovation network embeddedness and the mediation effect of absorptive capacity.

It is found that digital transformation can enhance the innovation resilience of manufacturing firms. Furthermore, the structural embeddedness and relational embeddedness of manufacturing firms within innovation networks moderate the relationship between digital transformation and innovation resilience. The absorptive capacity of manufacturing firms acts as a mediator in the relationship between digital transformation and innovation resilience.

This paper is one of the first studies that investigates the impact mechanisms of digital transformation on the innovation resilience of manufacturing firms based on network embeddedness theory and dynamic capability theory.

Although many countries are focusing on the management of construction and demolition waste (CDW) resource utilization, the effect of risk aversion of the green innovation-led enterprise on the performance of the CDW resource utilization supply chain is unclear when considering different green innovation contexts (green innovation led by the building materials remanufacturer or by the construction waste recycler). This study aims to investigate how the level of risk aversion of the green innovation-led enterprise affects CDW resource utilization under different green innovation contexts based on contingency theory.

Using Stackelberg game theory, this study establishes a decision model consisting of a building materials remanufacturer, construction waste recycler and CDW production unit and investigates how the level of risk aversion of the green innovation-led enterprise under different green innovation contexts influences the performance level of the supply chain.

The conclusions are as follows. (1) For the green innovation-led enterprise, the risk-averse behaviour is always detrimental to his own profits. (2) For the follower, the profits of the construction waste recycler are negatively correlated with the level of risk aversion of the green innovation-led enterprise in the case of a small green innovation investment coefficient. If the green innovation investment coefficient is high, the opposite result is obtained. (3) When the green innovation investment coefficient is low, the total supply chain profits decrease as the level of risk aversion of the green innovation-led enterprise increases. When the green innovation investment coefficient is high, total supply chain profit shows an inverted U-shaped trend with respect to the degree of risk aversion of the green innovation-led enterprise.

(1) This study is the first to construct a green innovation context led by different enterprises in the CDW resource utilization supply chain, which provides a new perspective on green management and operation. (2) This study is the first to explore the operation mechanism of the CDW resource utilization supply chain based on contingency theory, which provides new evidence from the CDW resource utilization supply chain to prove contingency theory. At the same time, this study examines the interactive effects of the green innovation cost coefficient and the degree of risk aversion of green innovation-led enterprises on the performance of supply chain members, expanding the contingency theory research on contingencies affecting enterprise performance. (3) This study will guide members of the CDW resource utilization supply chain to rationally face risks and achieve optimal supply chain performance.