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This study aims to examine competition between global professional service firms (GPSFs) and Chinese local audit firms (LAFs) over the past four decades, explaining the process and outcomes of this competition in relation to shifting economic policy priorities.

The authors analysed pertinent documents and media reports through the lens of strategic action field (SAF). The authors interpret the dynamics of the competition against the background of the shifting framing of Chinese economic policies.

The authors find that frame alignment with the state’s priorities in China enabled GPSFs and LAFs to secure stronger market positions relative to each other in different episodes of the Chinese policy landscape. The Chinese state’s marketisation reforms conditioned the outcome of the competition between GPSFs and LAFs. Initially, GPSFs gained access to the Chinese accounting field and achieved a strong market position by leveraging China’s “open-door” policy. This situation was reversed when China’s economic policy shifted to “going global” because Chinese LAFs pursued internationalisation framing thereby aligning with the state’s priority of internationalising the economy.

Using the lens of SAF, this study offers theorised insights into how transnational competition in the accounting field plays out in a non-Western state setting.

Drawing upon socio-technical system theory, this study intends to investigate the effects of the congruence and incongruence between artificial intelligence (AI) and explorative learning on supply chain resilience as well as the moderating role of organizational inertia.

Using survey data collected from 170 Chinese manufacturing firms, we performed polynomial regression and response surface analyses to test our hypotheses.

We find that the congruence between AI and explorative learning enhances firms’ supply chain resilience, while the incongruence between these two factors impairs their supply chain resilience. In addition, compared with low–low congruence, high–high congruence between AI and explorative learning improves supply chain resilience to a greater extent. Moreover, organizational inertia attenuates the positive influence of the congruence between AI and explorative learning on supply chain resilience, while it aggravates the negative influence of the incongruence between these two factors on supply chain resilience.

Our study expands the literature on supply chain resilience by demonstrating that the congruence between a firm’s AI (i.e. technical aspect) and explorative learning (i.e. social aspect) boosts its supply chain resilience. More importantly, our study sheds new light on the role of organizational inertia in moderating the congruent effect of AI and explorative learning, thereby extending the boundary condition for socio-technical system theory in the supply chain resilience literature.

This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

This study explores the role of human resource management (HRM) practices in advancing sustainable development goals (SDGs) within emerging markets. Specifically, we examine how HRM practices in financial institutions in the emerging markets of India and China promote SDGs 8 (decent work and economic growth), 10 (reduced inequalities) and 13 (climate action). We also propose a framework integrating these key SDG goals with core HRM functions.

Secondary data analysis was employed using data from sustainability reports of the top five Indian and Chinese banks listed in Forbes – the Global (2000) ranking for 2022–2023. These sustainability reports were analysed based on their reporting of indicators from the Global Reporting Initiative GRI 400 series, aligned with the SDGs 8, 10 and 13.

The result of the comparative analysis indicates that both Indian and Chinese banks use HRM practices of recruitment and selection, rewards and payments, workplace health and safety, and training and development to meet SDGs 8 (decent work and economic growth), 10 (reduced inequalities) and 13 (climate action). Regarding the reporting and disclosure of HRM practices in diversity, equity and inclusion, Indian banks outperform Chinese banks, and these practices contribute significantly to SDGs 8, 10 and 13. The dominance of state-owned initiatives in China dictates the alignment of HRM strategies with economic priorities at the national level, highlighting the challenge of balancing global sustainability initiatives with a centralised management system.

The study provides a comprehensive examination of sustainability reports with a specific focus on HRM practices and their role in advancing SDGs. It applies institutional theory to understand the differences in the reporting and implementation of HRM practices that contribute to the achievement of SDGs.

This study examines the relationship between corporate social advocacy (CSA) and employee trust and distrust, focusing on perceived employer support for the #StopAsianHate movement. We aim to explore how perceived CSA relates to employee perceptions and engagement in the workplace, answering for the following research questions: How do employees perceive their companies’ engagement in CSA, specifically the #StopAsianHate movement? To what extent do these perceptions influence trust and distrust toward their employers? How do trust and distrust, in turn, affect employees’ workplace engagement?

The study conducted an online survey of 798 full-time employees across various industries in the USA in March 2022. To ensure a diverse and representative sample, the survey targeted demographic representation based on the latest US census data.

CSA initiatives were found to be positively related to both trust and distrust by employees. Trust was significantly positively connected to employee engagement cognitively, emotionally and physically in the workplace, mediating the relationship between CSA and employee engagement.

This study adds to the empirical CSA research on employee–employer relations by incorporating a real-world context of the #StopAsianHate movement and illustrating the complexity of ambivalent CSA perceptions – both trust and distrust. It highlights the importance of understanding these dynamics within corporate advocacy efforts, offering an overview of CSA’s role in shaping workplace relations.

In the current competitive era of industrialization, a significant level of innovation is necessary to meet the growing competition. There are many economic forces that determine the pace of innovation within a country. Among others, this study aims to focus on exploring the relevant role of corruption control (CC) in determining the innovation level.

For empirical analysis, the authors sample the 24 years of data (1996–2019) of Asian economies and use the fully modified ordinary least square (OLS) and dynamic OLS models to check the regression among variables. The selection of both techniques is based upon the empirical suggestions offered by unit root testing and the Johansen cointegration test.

The empirical findings infer the positive and statistically significant role of CC in boosting innovation. Strengthening the corruption-free environment encourages innovation activities within the country. In addition, foreign direct investment has a negative relationship with CC while financial development, economic growth, export volume and government subsidies positively determine the innovation level.

Based on empirical analysis, it is suggested that the policy officials should do more focus on CC to enhance the competitiveness of the country through more innovation.

The empirical analysis robust the findings of existing literature in an alternative data set and offers innovative views regarding the role of other factors in boosting the innovation level.

This study examined whether job and personal resources could buffer the negative effects of technostrain and information and communication technology (ICT) availability demands on employee well-being.

The data were collected among Finnish comprehensive school teachers (n = 323) between December 2020 and February 2021 through an online questionnaire. Hierarchical multiple regression analyses were employed to analyse the main and moderating effects.

The results indicated that technostrain was positively associated with burnout and negatively associated with work engagement. These associations were stronger than those of ICT availability demands. The moderated regression analyses revealed that psychological detachment buffered the negative effects of technostrain on cynicism and a sense of inadequacy. School support acted as a moderator by buffering the negative impact of technostrain on emotional exhaustion and cynicism. Furthermore, school support was found to be an important job resource in terms of boosting work engagement when ICT availability demands were high.

This study provides insights into the role of resources in buffering possible burdening effects of technology on teacher well-being when adopting online teaching in the context of the Covid-19 pandemic.

The purpose of this study is to reveal the significant contribution of MXene on enhancing tribological properties and to obtain the influence mechanism of various factors on friction characteristics of rolling bearing under extreme conditions.

Under extreme working conditions, the friction characteristics of rolling bearings directly determine the safety and reliability of the transmission system. In this study, MXene is added to the origin lubricating grease (OLG) of rolling bearing to enhance their friction characteristics. Then, the effects of inner ring speed, radial load, grease filling volume and other factors on the friction coefficient of rolling bearing are analyzed using the Taguchi method.

The results indicate that the ranking of various factors affecting the friction coefficient is: radial load, inner ring speed, MXene additive content in grease and grease filling volume. Especially, the radial load and inner ring speed exhibit extremely significant effects, while the MXene additive content in grease (P < 0.05) has a significant influence on the friction coefficient of rolling bearing. The optimal condition for rolling bearing lubricated with MXene additives lubricating grease (MALG) achieves the lowest friction coefficient of 0.0049 under 1,000 rpm, 9 kN and 35% grease filling volume.

This study could offer reference solution for utilizing MXene nano-lubrication to fufill the demands of precision, heavy-load, or long-lifespan bearings. Furthermore, the lubrication approach has the potential to be expanded into aerospace, defense, and various industrial fields, thereby significantly promoting its practial engineering applications.

The purpose of this study is to map the intellectual structure of sustainable finance and accounting (SFA) literature by identifying the influential aspects, main research streams and future research directions in SFA.

The results are obtained using bibliometric citation analysis and content analysis to conduct a bibliometric review of the intersection of sustainable finance and sustainable accounting using a sample of 795 articles published between 1991 and November 2023.

The most influential factors in the SFA literature are identified, highlighting three primary areas of research: corporate social responsibility and environmental disclosure; financial and economic performance; and regulations and standards.

SFA has experienced rapid development in recent years. The results identify the current research domain, guide potential future research directions, serve as a reference for SFA and provide inspiration to policymakers.

SFA typically encompasses sustainable corporate business practices and investments. This study contributes to broader social impacts by promoting improved corporate practices and sustainability.

This study expands on previous research on SFA. The authors identify significant aspects of the SFA literature, such as the most studied nations, leading journals, authors and trending publications. In addition, the authors provide an overview of the three major streams of the SFA literature and propose various potential future research directions, inspiring both academic research and policymaking.

The purpose of this study is to address the critical need for patent value evaluation within patent management, particularly in the context of the digital economy. Recognizing the importance of utilizing historical data, this research aims to uncover effective methodologies that enhance the appraisal of patent value, which is vital for informed decision-making in the management of scientific and technological advancements.

This study introduces a comprehensive evaluation model by analyzing various factors that influence patent value. An index system is constructed that integrates technical, economic and legal aspects to facilitate a nuanced assessment of patents. The methodological core of this research is the development of an XGBoost patent value appraisal model, which incorporates Bayesian optimization to refine the evaluation process. The model’s validity is tested through empirical analysis of patents in the rapidly evolving sector of cloud computing.

The empirical results demonstrate that the XGBoost model, strengthened by Bayesian optimization, outperforms traditional categorization techniques. The proposed model shows superior performance in terms of accuracy, precision, recall rate and operational feasibility. These findings indicate a significant improvement in the precision of patent potential and value assessments, leading to more reliable and actionable insights for patent management.

This study introduces a novel patent evaluation model that combines XGBoost with Bayesian optimization. XGBoost enhances performance by integrating weak learners, ideal for complex, nonlinear problems like patent valuation. Bayesian optimization refines hyperparameters efficiently using prior distributions and known results. Its practical implications for patent management and technology exploration are substantial, offering a new tool for strategic decision-making.