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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

As the new frontier in online healthcare innovation, mobile health consultation (MHC) is transforming how traditional healthcare is delivered. Despite being known on a large scale for its benefits, MHC still faces consumer resistance. MHC is a technology-enabled service, so an in-depth analysis of consumer resistance from the perspective of technology is crucial to enhance service adoption. This study sought to determine the mechanism by which two information technology (IT)-specific traits – IT affordance and IT identity – influence consumer resistance to MHC during consumer–platform interactions.

We used the Credamo platform to gather data from 786 users with medical consulting experience to validate the resulting relationships.

Based on partial least squares structural equation modeling, three of the six IT affordances (visibility, searching and guidance shopping) exerted a significant positive influence on IT identity, while trigger attending and association affordance had no significant effect on IT identity. Persistence affordance was negatively associated with IT identity, and IT identity negatively influenced consumer resistance to MHC.

Academically, this empirical paper primarily contributes to the MHC literature and the theory of IT affordance and IT identity. Practically, several valuable guidance for MHC platforms is provided.

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.

This paper aims to obtain a calculation method by hand without iteration.

This paper adopts strains as known quantities to solve the internal forces and deformations of the section, simplifies the deflection curve of the column and obtains nomograms that can calculate the bearing capacity and reinforcement of circular reinforced concrete (RC) columns by hand.

Nomograms include five variables: mechanical reinforcement ratio, relative normal force, dimensionless bending moment, slenderness ratio and ultimate dimensionless curvature. Nomograms corresponding to all classes of concrete have been drawn, and their dimensionless form makes them widely applicable. The calculation results of nomograms are compared and analysed with numerical calculation results, and the difference is within 5%, meeting the engineering requirements.

Calculating the bearing capacity of compression bending components requires considering second-order effects. Therefore, the calculation of the bearing capacity of circular RC columns requires iterative calculation, as it includes dual nonlinearity of material and geometry, and the two are coupled with each other. To calculate the bearing capacity of the section adopting ordinary concrete, it is necessary to solve the transcendental equation iteratively. For high-strength concrete, it can only be solved by numerical integration. A fast calculation method by hand is proposed in this paper.

This study delves into the less-explored domain of teachers’ readiness for leadership roles by investigating the direct and indirect relationships between positive school culture and teachers' readiness for leadership roles through affective-identity motivation to lead, and teacher optimism.

This study employed partial least squares structural equation modelling (WPLS-SEM) for data analysis. The data were gathered from 424 elementary school teachers who do not hold any leadership positions in Xi’an, China. A total of 391 samples were used after sampling weight adjustments.

There is a significant and positive direct relationship between positive school culture and teachers’ readiness for leadership roles. Affective-identity motivation to lead and teacher optimism emerged as significant mediators in this dynamic.

This study complements and expands on the study of the relationship between positive school culture, affective-identity motivation to lead, teacher optimism and teachers' readiness for leadership role. This research has established a theoretical framework for school stakeholders to cultivate future teacher leaders.

These findings provide valuable theoretical insights into educational leadership literature and contribute to a more comprehensive understanding of the factors influencing teachers in assuming leadership roles, particularly in the context of Asian societies.

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.