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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.

The proliferation of health misinformation on social media has increasingly engaged scholarly interest. This research examines the determinants influencing users’ proactive correction of health misinformation, a crucial strategy in combatting health misbeliefs. Grounded in the elaboration likelihood model (ELM), this research investigates how factors including issue involvement, information literacy and active social media use impact health misinformation recognition and intention to correct it.

A total of 413 social media users finished a national online questionnaire. SPSS 26.0, AMOS 21.0 and PROCESS Macro 4.1 were used to address the research hypotheses and questions.

Results indicated that issue involvement and information literacy both contribute to health misinformation correction intention (HMCI), while misinformation recognition acts as a mediator between information literacy and HMCI. Moreover, active social media use moderated the influence of information literacy on HMCI.

This study not only extends the ELM into the research domain of correcting health misinformation on social media but also enriches the perspective of individual fact-checking intention research by incorporating dimensions of users’ motivation, capability and behavioral patterns.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2023-0505

The purpose of this paper assess the impact of the green finance pilot reform on corporate green innovation, leveraging the establishment of the China green finance pilot reform in 2018 as a quasi-natural experiment.

This study investigates the effects of environmental policies on green innovation, utilising a substantial data set from Chinese A-share listed firms over the 2015–2019 period. Employing both double and triple difference models, it focuses on how tax reforms influence green patent filings among these firms.

The study confirms that environmental tax policies and green finance initiatives significantly boost green patent filings in pollution-intensive industries. Findings from the regression analysis show robust positive effects from these policies, supporting the idea that stringent environmental regulations can spur innovation by offsetting regulatory costs. Financial health indicators like asset logs and return on assets positively correlated with innovation, emphasising the importance of financial stability. In addition, increased RandD spending is linked to enhanced green innovation, highlighting that financial investment in research is crucial for overcoming innovation barriers. These insights are crucial for shaping policies that integrate sustainability into corporate practices.

This research contributes to the literature by highlighting traditional views on the economic burden of environmental taxes and demonstrating their role as significant drivers of innovation. It deepens insights into strategically optimising fiscal tools to promote environmentally sustainable economic activities. In addition, it offers a practical framework for policymakers to improve ecological outcomes through effective fiscal strategies.

Unhealthy diets are associated with an increased risk of non-communicable diseases and present a significant public health challenge. When developing effective interventions and policies, consideration must be given to the unique social culture in which food choice is embedded. Health vulnerabilities to poor nutrition exist throughout life but may be influenced by socio-cultural factors such as age. This study aimed to assess the attitudes of older or younger Chinese consumers towards healthy eating and explore the factors influencing their food choices.

Semi-structured interviews were conducted in Wuhan, China, with 20 consumers aged 18–25 (Group A) and 20 consumers aged 65 and over (Group B).

Thematic analysis revealed that the two groups had positive attitudes towards healthy eating, although Group A participants were more knowledgeable. Time pressure, food prices and social networks differentially influence healthy eating practices across age groups.

Given China’s economic and cultural context, healthy eating interventions should consider the individual characteristics and food preferences of the different age groups. This approach can optimize targeted healthy eating interventions, and media communications related to healthy eating.

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.

To overcome the shortcomings of traditional dynamic parameter identification methods in accuracy and efficiency, this paper aims to propose a dynamic parameter identification method based on improved iterative reweighted least squares (IIRLS) algorithm.

First, Newton–Euler method is used to establish the dynamic model of the robot, which is linearized and reorganized. Then, taking the improved Fourier series as the excitation trajectory, the optimization model with objective function is established and optimized. Then, the manipulator runs the optimized trajectory and collects the running state of the joint. Finally, the iterative process of iterative reweighted least squares (IRLS) algorithm is improved by combining clustering algorithm and matrix inversion operation rules, and the dynamic model of robot is identified by using the processed collected data.

Experimental results show that, compared with the IRLS algorithm, the root mean square of the proposed IIRLS algorithm is reduced by 4.18% and the identification time is reduced by 94.92% when the sampling point is 1001. This shows that IIRLS algorithm can identify the dynamic model more accurately and efficiently.

It effectively solves the problem of low accuracy and efficiency of parameter identification in robot dynamic model and can be used as an effective method for parameter estimation of robot dynamic model, which is of great significance to the research of control method based on robot model.

Metaverse is one of the technologies that has the most promise for the future. However, there is less discussion about teaching using the metaverse. It is possible that most of the educators are ignorant of the metaverse’s features and its potential uses. The objective of this chapter is to define the metaverse precisely and discusses the various applications, characteristics, and challenges of metaverse in Education. This chapter explores the pioneering efforts in leveraging the metaverse for educational purposes, highlighting key examples and their impact on the learning experience. The possible applications of metaverse and research encounters in context to education are further reviewed and then explained and included the Artificial Intelligence (AI) functions in the world of metaverse along with learning based on metaverse. Researchers in the domains of educational technology and computer science shall advance an inclusive insight of the metaverse and its potential applications in education using various metaverse techniques like gamified learning, virtual learning, etc. Also, the metaverse role in education starting from the perception of AI has been covered.

In recent years, the frequency of emergencies, such as natural disasters and public health crises, has markedly increased globally. These occurrences have introduced new challenges to national public security systems and emergency management capabilities. Post-disaster humanitarian logistic operations involve the collection of emergency relief resources to mitigate the impact of disasters in affected areas. Effective coordination among governments, enterprises and charities is essential to enhance the efficiency of these operations. This study employs evolutionary game theory to explore the strategic interactions and behavioral patterns among these key stakeholders during the collection of emergency materials.

A tripartite evolutionary game model involving governments, enterprises and charities is developed. Subsequently, to validate the theoretical findings, a scale-free network is constructed for the purpose of numerical simulations. As this network evolves, both the edges between nodes and the strategy choices of the nodes also change. Numerical simulations are conducted using the network to examine the sensitivity of factors influencing strategic choices among game stakeholders.

According to the model simulation results, penalties significantly influence government regulation strength, while enterprise philanthropic behavior is mainly affected by penalties, profit transfer benefits and trust loss. For charities, strategic choices are primarily driven by penalties, tax subsidies, illegal operation benefits and charitable costs. The findings provide a theoretical basis for governments, enterprises and charities to select the sensible strategy.

Our study establishes a dynamic network of edges and nodes evolving over time to analyze the strategic evolutionary paths of governments, enterprises and charities from a micro perspective. The results assist governments, enterprises and charities in making more strategic decisions.

Corporations are confronted with growing demands to take a stand on socio-political issues, i.e. corporate social advocacy (CSA), which affects their reputation in the public. Companies use different CSA message strategies, including calling the public to support and act on the issue they advocate. Using reactance theory, the authors investigate the impact of CSA messages with a call to action on corporate reputation in the case of a company's gender equality initiative.

A one-factorial (CSA message with or without a call to action) between-subjects experiment was conducted by surveying 172 individuals living in Switzerland. The CSA messages were created in the context of gender equality.

The authors' study indicates that CSA messages with a call to action compared to those without overall harmed corporate reputation due to individuals' reactance, which is higher for CSA messages with a call to action, negatively affecting corporate reputation. The impact of the CSA message strategy with a call to action on corporate reputation remains significant after controlling for issue alignment and political leaning.

Communicating about socio-political issues, especially taking a stand, is a significant challenge for corporations in an increasingly polarized society and has often led to backlash, boycotts and damage to corporate reputation. This study shows that the possible adverse effects of advocating for socio-political issues can be related to reactance. It emphasizes that companies advocating for contested issues must be more cautious about the message strategy than the issue itself.