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This paper aims to examine the role of local/provincial government in influencing corporate social and environmental reporting (CSER) in China, and more specifically, how the underlying economic and political factors associated with local government have influenced the quality of CSER.

The authors used 234 environmentally sensitive companies listed on the Shanghai and Shenzhen Stock Exchanges during 2013 and 2015 as the research sample to test the relationship between CSER and local government’s political connection and economic prioritisation and the potential mediating effect of local economic prioritisation.

The analysis provides evidence that local/provincial government’s political geographical connectedness with the central government has directly and positively influenced the level of CSER, while local prioritisation of economic development has a direct but negative effect on CSER in China. In addition, local/provincial prioritisation of economic development has mediated the relationship between local–central political geographical connectedness and CSER.

While local/provincial governments are heavily influenced by the coercive pressure from the central government, they also act in their own political and economic interests in overseeing CSER at the local level. This study raises the question about the effectiveness of the top-down approach to improving CSER in China and suggests that the central government may need to focus more on coordinating and harmonising different local/provincial governments’ interests to enable achieving a common sustainability goal.

The authors provide evidence revealing how the economic and political contexts of local government have played a significant role in shaping CSER in China. More specifically, this paper addresses a gap in the literature by highlighting the importance of local government oversight power for CSER development and how such oversight is determined by local prioritisation of economic development and political geographical connectedness of local and central governments.

Malaysian rice wines (tapai) manufactured in small-scale industries are usually formulated based on personal experiences under minimally controlled conditions for generations, especially in Sabah, one of the East Malaysian states. However, the quality and safety of rice wines were receiving increased attention to ensure better quality control, particularly those produced on an industrial scale. Therefore, this research aims to determine the fermentation dynamics and consumers’ acceptance of Malaysian rice wines produced using different sasad (a local term for starter culture from Sabah).

The physicochemical [total soluble solids (TSS), alcohol content, total titratable acidity (TTA) and pH] and microbiological [total yeast and mould count (TYMC) and total lactic acid bacteria (LAB) count] changes in Malaysian rice wines were determined to better understand the fermentation process for future process optimisation. Additionally, sensory evaluations were conducted to determine the consumers’ preferences for the rice wines.

The overall fermentation dynamics of rice wines exhibited similar trends with slight variations between the samples, demonstrating the effect of microbial compositions of sasad on the quality of final rice wines. Additionally, consumer acceptance tests showed that rice wines with darker shades of yellow and a stronger alcoholic aroma were preferable.

This is the first research that provides important insights into both the fermentation dynamics and consumers’ acceptance of Malaysian traditional rice wines, enriching the rice wine literature from the academic perspective and contributing to the production of safe and high-quality rice wines.

This paper aims to examine the evolution of organizational identification (OI) research over the past five decades and its journey through various lenses, such as the collaborative network of authors, organizations and countries. The conceptual and intellectual structure of the construct is analysed via keywords and co-citation pattern mapping.

OI research is rising in popularity, with 118 papers published in 2019, 168 papers in 2020 and 15 publications till February 2021 in the Scopus database. The Scopus database is used to retrieve 55 years of OI studies published between 1965 and 2021. The free bibliometric tools Biblioshiny and VOSviewer are used to analyse 1,034 journal papers.

The result showed that R. Van Dick is the most influential author and the USA is the most involved country in OI research. As per the findings, the Journal of Organizational Behaviour published most of OI research and “corporate social responsibility” and “organizational commitment” seem to be the most used keywords alongside OI.

This study will be highly beneficial to OI researchers making their understanding about the construct better. It will also encourage social psychologists to understand the construct utility in workplace social welfare programmes. The research could also help governments and funding bodies to evaluate grant requests. Furthermore, researchers from countries with the lowest proportion of OI studies would be encouraged to spend more time and effort in this area. It will offer insight into international marketing and how individuals and stakeholders perceive and connect with an organization globally.

To the best of the authors’ knowledge, this study is one of the important research studies carried out in the domain of OI in the international context. This is also one of the few studies which is spread out across different disciplinary areas including international marketing and management. The success of this paper can open avenues and influence future researchers to study in the OI and related cross-disciplinary areas of international management.

The process of conveyance of solid–liquid mixtures poses a significant challenge due to the considerable wear and tear experienced by critical components. This issue not only affects the lifespan of the system but also jeopardizes its safe operation. The purpose of this study is to numerically and experimentally investigate the erosion wear behavior of impeller steels (SS-410 and S-317) using Computational Fluid Dynamics (CFD) and Design of Experiments (DOE) techniques, aiming to address the significant challenges posed by wear in slurry transportation systems.

In this study, a robust two-phase solid-liquid model combining CFD with Discrete Phase Modeling (DPM) was applied to simulate the effects of coal-ash slurries on impeller steel. Additionally, an experimental evaluation was conducted using the DOE approach to analyze the impact of various parameters on impeller steel. This integrated methodology enabled a comprehensive analysis of erosion wear behavior and the influence of multiple factors on impeller durability by leveraging CFD for fluid flow dynamics and DPM to model particle interactions with the steel surface.

Simulation results highlight a strong link between particle size and the wear life of impeller steel. Through simulations and experiments on SS-410 and SS-317 under varied conditions, it’s evident that SS-410 outperforms SS-317 due to its higher hardness and density. This is supported by Taguchi’s method, with SS-410 showing a higher Signal-to-Noise ratio. Notably, particle size emerges as the most influential parameter compared to others.

Current research primarily focuses on either CFD or experimentation to predict pump impeller steel erosion wear, lacking relevant erosion mechanism insights and experimental data. This study bridges this gap by employing both CFD and DPM methods to comprehensively investigate particle effects on pump impeller steel and elucidate erosion mechanisms.

Assembly action recognition plays an important role in assembly process monitoring and human-robot collaborative assembly. Previous works overlook the interaction relationship between hands and operated objects and lack the modeling of subtle hand motions, which leads to a decline in accuracy for fine-grained action recognition. This paper aims to model the hand-object interactions and hand movements to realize high-accuracy assembly action recognition.

In this paper, a novel multi-stream hand-object interaction network (MHOINet) is proposed for assembly action recognition. To learn the hand-object interaction relationship in assembly sequence, an interaction modeling network (IMN) comprising both geometric and visual modeling is exploited in the interaction stream. The former captures the spatial location relation of hand and interacted parts/tools according to their detected bounding boxes, and the latter focuses on mining the visual context of hand and object at pixel level through a position attention model. To model the hand movements, a temporal enhancement module (TEM) with multiple convolution kernels is developed in the hand stream, which captures the temporal dependences of hand sequences in short and long ranges. Finally, assembly action prediction is accomplished by merging the outputs of different streams through a weighted score-level fusion. A robotic arm component assembly dataset is created to evaluate the effectiveness of the proposed method.

The method can achieve the recognition accuracy of 97.31% and 95.32% for coarse and fine assembly actions, which outperforms other comparative methods. Experiments on human-robot collaboration prove that our method can be applied to industrial production.

The author proposes a novel framework for assembly action recognition, which simultaneously leverages the features of hands, objects and hand-object interactions. The TEM enhances the representation of dynamics of hands and facilitates the recognition of assembly actions with various time spans. The IMN learns the semantic information from hand-object interactions, which is significant for distinguishing fine assembly actions.

Turnover intention (TOI) has become a severe issue in Saudi Arabia’s health-care system as health professionals leave their organizations. Saudi Arabia’s health-care professionals’ TOI affects the organizations and the patients’ human rights. Therefore, this study aims to assess the factors that affected Saudi Arabia’s health-care professionals’ TOI.

This study based its findings on quantitative cross-sectional data. This study’s respondents were health-care professionals working in Saudi Arabia’s public and private health-care institutions.

By using path analysis, this study’s findings reveal that, on the one hand, job stress (JS), psychological distress (PD) and perceived work exhaustion (PWE) have positive and significant effects on TOI. On the other hand, perceived organizational support (POS) is a positive and significant predictor of TOI.

This study’s findings will help the Saudi Arabian Ministry and policymakers develop policies to encourage health professionals’ perseverance through reducing their JS, PD and PWE and by enhancing POS for health-care staff. Moreover, by controlling the increasing turnover ratio among Saudi Arabia’s health-care professionals, this study’s findings assist in overcoming the violations of human rights.

This study’s findings empirically confirm the development of TOI through JS, PD and PWE among Saudi Arabia’s health-care professionals.

This study examines the phenomenon of “knowledge influencers,” individuals who convey expert information to non-expert audiences and attract users to subscribe to their self-created knowledge products. It seeks to address two research questions: (1) What are the antecedents that promote perceived attractiveness of knowledge influencers? and (2) How does perceived attractiveness of knowledge influencers affect users’ willingness to subscribe to knowledge products?

Guided by self-branding theory, which suggests that individuals strategically shape user perceptions and interactions to create an appealing image, the study employed a sequential mixed-methods approach. Qualitative interviews were conducted with knowledge influencers and their subscribers, followed by a quantitative survey of users with knowledge subscription experience to validate the findings.

Results suggested that knowledge influencers could enhance their attractiveness to users by promoting perceived professionalism, perceived familiarity, and perceived connectedness. Perceived attractiveness of knowledge influencers could directly affect users’ willingness to subscribe or indirectly through the role of users’ attachment to knowledge influencers.

By understanding the factors driving users’ subscription intentions, platform operators and influencers can refine their strategies to enhance user attachment and optimize monetization opportunities through personalized interactions and tailored content offerings.

This study contributes to the literature by elucidating the relationship between perceived attractiveness and users’ subscription intentions, offering new insights into the dynamics of online knowledge consumption.

Artificial intelligence (AI) technologies have led to significant transformations across industries and society, including the field of education. The integration of AI in educational settings has the potential to improve students' learning experience and support their individual competencies when paired with non-AI methods. Despite the growing importance of AI in modern education, there remains a noticeable research gap regarding its use in entrepreneurship education and the effects of Chatbots on students' entrepreneurial competencies. To address this gap, an exploratory study was conducted on undergraduate students who were tasked with using ChatGPT to improve their business model canvas.

The chosen methodology aligned with the research purpose, aiming to explore the relationship between Generative AI and competencies. Due to the novel nature of the research problem, an exploratory study was conducted using a mixed methods approach. A survey with open- and closed-ended questions was designed, and statistical and text analyses were performed to interpret data and test identified propositions.

The findings of this study indicate that ChatGPT can enhance the types of students' entrepreneurial competencies considered in this study: spotting opportunities, creativity, vision, valuing ideas and ethical and sustainable thinking. The results show that ChatGPT can be particularly helpful to improve the ability of students of valuing ideas.

Overall, this study highlights the potential of adopting ChatGPT in experiential learning methodologies for enhancing students' entrepreneurial competencies and improving their learning outcomes.

The purpose of this paper is to analyze the effect and mechanism of platform incentives on users’ knowledge collaboration performance (KCP) and the configuration leading to high KCP in online knowledge communities (OKCs) in the post-COVID-19 pandemic era from a cross-culture perspective.

A survey method and a standard questionnaire were applied. The data was analyzed using multiple regression and fuzzy set qualitative comparative analysis.

The results indicate that, for both kinds of users, self-enhancement and communication positively affect the KCP. User engagement significantly mediates the relationship between communication and KCP and knowledge absorptive capacity moderates the relationship between user engagement and KCP. In contrast, material incentive positively affects the KCP of Chinese users, while hurting the cross-cultural sample. And the promotion of KCP for cross-cultural samples does not require a higher engagement and knowledge absorptive capacity, while paying more attention to short-term interests, such as communication and self-enhancement.

The study only divides users into Chinese and cross-cultural foreign users, without a distinction between foreign users in different countries. In addition, the research is based on cross-sectional data and failed to try to explore the long-term effects of these incentives from the time dimension.

This study explores the incentive mechanism and configuration of OKC platforms to achieve high KCP for different users from a cross-cultural perspective. It provides new ideas and solutions for precise incentives for users of OKC platforms.