Search results

This paper aims to investigate the relationship between corporate environmental, social and governance (ESG) ratings and leverage manipulation and the moderating effects of internal and external supervision.

The authors draw on a sample of Chinese non-financial A-share-listed firms from 2013 to 2020 to explore the effect of ESG ratings on leverage manipulation. Robustness and endogeneity tests confirm the validity of the regression results.

ESG ratings inhibit leverage manipulation by improving social reputation, information transparency and financing constraints. This effect is weakened by internal supervision, captured by the ratio of institutional investor ownership, and strengthened by external supervision, captured by the level of marketization. The effect is stronger in non-state-owned firms and firms in non-polluting industries. The governance dimension of ESG exhibits the strongest effect, with comprehensive environmental governance ratings and social governance ratings also suppressing leverage manipulation.

Firms should strive to cultivate environmental awareness, fulfil their social responsibilities and enhance internal governance, which may help to strengthen the firm’s sustainability orientation, mitigate opportunistic behaviours and ultimately contribute to high-quality firm development. The top managers of firms should exercise self-restraint and take the initiative to reduce leverage manipulation by establishing an appropriate governance structure and sustainable business operation system that incorporate environmental and social governance in addition to general governance.

Policymakers and regulators should formulate unified guidelines with comprehensive criteria to improve the scope and quality of ESG information disclosure and provide specific guidance on ESG practice for firms. Investors should incorporate ESG ratings into their investment decision framework to lower their portfolio risk.

This study contributes to the literature in four ways. Firstly, to the best of the authors’ knowledge, it is among the first to show that high ESG ratings may mitigate firms’ opportunistic behaviours. Secondly, it identifies the governance factor of leverage manipulation from the perspective of firms’ subjective sustainability orientation. Thirdly, it demonstrates that the relationship between ESG ratings and leverage manipulation varies with the level of internal and external supervision. Finally, it highlights the importance of governance in guaranteeing the other two dimensions’ roles by decomposing overall ESG.

How does a manager’s coaching behaviour encourage taking charge behaviour among subordinates? Although prior research has found a positive association between managerial coaching behaviour and employee performance, to date few studies have examined its effect on proactive behaviours in the workplace such as taking charge. Drawing on social exchange theory (SET) and social cognitive theory (SCT), this study develops a theoretical model to examine the mediating effects of work engagement and role breadth self-efficacy (RBSE) in the relationship between managerial coaching and subordinates taking charge. Additionally, drawing on social role theory (SRT), we test whether our proposed relationships are contingent on subordinates’ gender.

We tested our proposed moderated-mediation model using empirical data collected across two waves from 196 employees within a large Malaysian services enterprise. Partial least squares structural equation modelling was used to test the proposed hypotheses.

The results revealed that managerial coaching has a significant, positive relationship with taking charge, work engagement and RBSE. However, only work engagement was found to partially mediate the relationship between managerial coaching and taking charge. Subordinates’ gender was found to positively attenuate the direct effect between managerial coaching and taking charge among females. However, the mediating effects of work engagement and RBSE in managerial coaching and taking charge were found to be not contingent on subordinates’ gender.

Finding from this study reveals that managerial coaching is useful in shaping employees' taking charge behaviour through work engagement. Hence, organisations should focus on strategies aiming to enhance managers' coaching capabilities.

This study extends the nomological networks of managerial coaching by highlighting it as a predictor of taking charge. Moreover, drawing on SET and SCT to explain the mechanism of managerial coaching and taking charge, we provide a novel perspective on how managerial coaching can influence taking charge. Specifically, we highlight the critical role of work engagement as a key mechanism that influences the relationship between managerial coaching and taking charge. Finally, we demonstrate managerial coaching as a means through which organisations can improve individual functioning.

This study aims to investigate the influence of digital transformation on the overall financial performance of firms, with a specific focus on Chinese-listed companies from 2010 to 2021. It seeks to understand the impacts on various accounting and financial indicators in emerging economies such as China.

This study employs a text-mining approach to construct a digital transformation index based on the data sample of 11,814 firm-year observations from China’s A-share listed companies. This index serves as a proxy to measure the extent of digital transformation and its impact on financial performance and health.

The findings indicate that digital transformation significantly enhances overall financial performance and health, as evidenced by increased profitability, reduced operational costs, and lowered financial risks. The study reveals a time-lagged effect, where the benefits of digital transformation become more apparent after about one year. Further analysis shows that the value of digital transformation is more evident in a firm’s asset items. This raises the possibility of recognising the by-product, such as data resources, in the digital transformation process.

This research offers a unique contribution by linking digital transformation to financial performance using a large dataset from China's A-share listed firms. Doing so enhances our understanding of the tangible effects of digital transformation on corporate performance. Furthermore, this research provides valuable insights for the advancement of future accounting practices and the development of standards.

The paper aims to clarify the distribution of excess pore pressure during cone penetration in two-layered clay and its influence on penetrometer resistance.

An arbitrary Lagrangian–Eulerian scheme is adopted to preserve the quality of mesh throughout the numerical simulation. Simplified methods of layered penetration and coupled pore pressure analysis of cone penetration have been proposed and verified by previous studies. The investigation is then extended by the present work to study the cone penetration test in a two-layered clay profile assumed to be homogeneous with the modified Cam clay model.

The reduction of the range of pore pressure with decreasing PF will cause a decrease of the sensing distance. The PF of the underlying soil is one of the factors that determine the development distance. The interface can be obtained by taking the position of the maximum curvature of the penetrometer resistance curve in the case of stiff clay overlying soft clay. In the case of soft clay overlying stiff clay, the interface locates at the maximum curvature of the penetrometer resistance curve above about 1.6D.

The cone penetration analyses in this paper are conducted assuming smooth soil-cone contact.

A simplified method based on ALE in Abaqus/Explicit is proposed for layered penetration, which solves the problem of mesh distortion at the interface between two materials. The stiffness equivalent method is also proposed to couple pore pressure during cone penetration, which achieves efficient coupling of pore water pressure in large deformations.

In recent decades, emerging market multinational enterprises (EMNEs) have predominantly adopted a big step internationalization strategy to expand their business overseas. This study aims to examine the effect of big step internationalization on the speed of subsequent foreign direct investment (FDI) expansion for EMNEs. The authors also investigate the potential boundary conditions.

The authors use the random effects generalized least squares (GLS) regression following a hierarchical approach to analyze the panel data set conducted by a sample of publicly listed Chinese firms from 2001 to 2012.

The findings indicate that implementing big step internationalization in the initial stages accelerates the speed of subsequent FDI expansion. Notably, the authors find that this effect is more pronounced for firms that opt for acquisitions as the entry mode in their first big step internationalization and possess a board of directors with strong political connections to their home country’s government. In contrast, the board of director’s international experience negatively moderates this effect.

This study provides insights into our scholarly and practical understanding of EMNEs’ big step internationalization and subsequent FDI expansion speed, which offers important implications for firms’ decision-makers and policymakers.

This study extends the internationalization theory, broadens the international business literature on the consequences of big step internationalization and deepens the theoretical and practical understanding of foreign expansion strategies in EMNEs.

The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.

This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.

The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.

This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.

The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.