Francisca Arboh, Xiaoxian Zhu, Samuel Atingabili, Elizabeth Yeboah and Emmanuel Kwateng Drokow
The primary purpose of the study was to explore the impact of health workers’ awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in…
Abstract
Purpose
The primary purpose of the study was to explore the impact of health workers’ awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD–R) model, the study aimed to provide insights into how health workers’ perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study’s findings could inform strategies for supporting healthcare workers during technological transformations.
Design/methodology/approach
The study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling.
Findings
The study findings revealed that health workers’ AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers’ workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers’ AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour.
Research limitations/implications
While the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables.
Practical implications
The study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers’ AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives.
Originality/value
The study contributes to the existing literature by addressing a relatively unexplored area – the impact of AI awareness on healthcare workers’ well-being. While previous research has focused on the potential job displacement effects of AI, this study takes a unique perspective by examining how health workers’ perceptions of AI integration can shape their informal learning behaviour and, subsequently, their workplace well-being. By drawing on the JD–R model and incorporating employee learning orientation as a moderator, the study offers a novel theoretical framework for understanding the implications of AI adoption in healthcare organizations.
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Mirza Muhammad Naseer, Yongsheng Guo and Xiaoxian Zhu
This study aims to examine the relationship between environmental, social and governance (ESG) disclosure, firm risk and stock market returns within the Chinese energy sector…
Abstract
Purpose
This study aims to examine the relationship between environmental, social and governance (ESG) disclosure, firm risk and stock market returns within the Chinese energy sector. Using a variety of econometric techniques, the study seeks to uncover the impact of ESG disclosure on risk mitigation and its influence on stock market performance.
Design/methodology/approach
Benchmark regression models were used to explore the associations between ESG disclosure, firm risk and stock returns. To address potential endogeneity, a generalised method of moments estimator is used. Quantile regression was used for robustness analysis.
Findings
The study reveals a negative relationship between ESG disclosure and firm risk, indicating that companies with greater ESG disclosure tend to experience reduced risk exposure. In addition, a positive association is observed between ESG disclosure and stock market returns, suggesting that companies with more comprehensive ESG disclosure practices tend to perform better in the stock market.
Research limitations/implications
This study implies that investors appreciate sustainable investment and incorporate ESG practices and disclosure in decision-making. Policymakers can promote transparent ESG reporting through regulatory frameworks, fostering sustainable practices in the energy sector.
Originality/value
Despite the mounting concerns over carbon dioxide emissions and the energy industry’s environmental footprint, this study pioneers a comprehensive analysis of ESG disclosure within this critical sector. Delving into the relationship of ESG practices, firm risk and market returns, this research uniquely examines both risk mitigation and return enhancement, shedding new light on sustainable strategies in the energy domain.
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Mandella Osei-Assibey Bonsu, Yongsheng Guo and Xiaoxian Zhu
This paper examines the mediation role of green innovation in the relationship between corporate social responsibility and environmental performance of manufacturing firms in…
Abstract
Purpose
This paper examines the mediation role of green innovation in the relationship between corporate social responsibility and environmental performance of manufacturing firms in Ghana.
Design/methodology/approach
The paper chose African emerging markets and surveyed managers from manufacturing firms. With 301 questionnaires qualified for this study’s final analyses, the authors adopt the multiple regression with mediation models to estimates the nexus among study variables.
Findings
Results evidence that both corporate social responsibility and green innovation has a positive and significant impact on environmental performance. Interestingly, the authors find that corporate social responsibility significantly improves environmental performance through green innovation indicating that firms could essentially build their dynamic resource and innovation capabilities in sustainability leading to enhanced environmental performance.
Research limitations/implications
This paper develops a dynamic resource-based view of firm environmental performance illustrating how firms use resources to build strategic capabilities for competitive advantage, which leads to improved environmental performance. The paper highlights the mediation role of green innovation on corporate social responsibility and environmental performance relationships.
Practical implications
This study's results provide significant insights to owners and managers of manufacturing companies to integrate corporate social responsibility and green innovation to ensure environmental performance and sustainability. Furthermore, policy makers should encourage green innovation when design sustainable development systems in the manufacturing industry.
Originality/value
The paper provides a valuable model showing how green innovation mediates corporate social responsibility to improve environmental performance and build competitive advantages considering both small, medium, and large manufacturing enterprises in emerging countries.
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Muhammad Arsalan Nazir, Hadia Rizwan and Xiaoxian Zhu
This paper aims to examine the factors influencing the adoption of social media marketing by small and medium enterprises (SMEs) in Pakistan. By investigating the drivers and…
Abstract
Purpose
This paper aims to examine the factors influencing the adoption of social media marketing by small and medium enterprises (SMEs) in Pakistan. By investigating the drivers and challenges/barriers affecting the adoption of social media marketing tools among SMEs, this study provides practical guidance to SMEs seeking to utilize social media platforms for marketing purposes in a developing context such as Pakistan.
Design/methodology/approach
Utilizing the Technology-Organization-Environment (TOE) framework as a theoretical framework, qualitative data were collected through semistructured interviews with representatives of SMEs in Pakistan, followed by thematic analysis of the data.
Findings
The research identifies several key factors influencing the adoption of social media marketing by Pakistani SMEs. These factors include doubts regarding the benefits of social media, alignment with regulatory requirements, challenges related to tracking social media performance, resistance from senior management (older employees), the positive influence of competitive pressure and the Covid-19 pandemic, political instability and increased government taxes on digital services. Stakeholders such as marketing professionals, academics, policymakers, government authorities and SME owners and managers can benefit from these findings.
Originality/value
This research contributes to the academic literature on the adoption of social media marketing by SMEs, especially within emerging economies. It enriches theoretical understanding of adoption processes and factors, filling gaps in existing knowledge and laying a foundation for future research in this domain. Using the TOE framework, the study reveals that when all factors are adequately considered, SMEs can transition from traditional marketing methods and embrace social media as a digital marketing strategy to enhance performance, profitability, and gain a competitive advantage over their rivals.
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Xiaoxian Yang, Zhifeng Wang, Qi Wang, Ke Wei, Kaiqi Zhang and Jiangang Shi
This study aims to adopt a systematic review approach to examine the existing literature on law and LLMs.It involves analyzing and synthesizing relevant research papers, reports…
Abstract
Purpose
This study aims to adopt a systematic review approach to examine the existing literature on law and LLMs.It involves analyzing and synthesizing relevant research papers, reports and scholarly articles that discuss the use of LLMs in the legal domain. The review encompasses various aspects, including an analysis of LLMs, legal natural language processing (NLP), model tuning techniques, data processing strategies and frameworks for addressing the challenges associated with legal question-and-answer (Q&A) systems. Additionally, the study explores potential applications and services that can benefit from the integration of LLMs in the field of intelligent justice.
Design/methodology/approach
This paper surveys the state-of-the-art research on law LLMs and their application in the field of intelligent justice. The study aims to identify the challenges associated with developing Q&A systems based on LLMs and explores potential directions for future research and development. The ultimate goal is to contribute to the advancement of intelligent justice by effectively leveraging LLMs.
Findings
To effectively apply a law LLM, systematic research on LLM, legal NLP and model adjustment technology is required.
Originality/value
This study contributes to the field of intelligent justice by providing a comprehensive review of the current state of research on law LLMs.