The incorporation of artificial intelligence (AI) into language education has created new opportunities for improving the instruction and acquisition of Chinese characters. Nevertheless, the cognitive difficulties linked to the acquisition of Chinese characters, such as their intricate visual features and lack of clear meaning, necessitate thoughtful deliberation when developing AI-supported learning interventions. The objective of this project is to explore the capacity of a collaborative method between humans and machines in teaching Chinese characters, utilising the advantages of both human expertise and AI technology. We specifically investigate the utilisation of ChatGPT, a substantial language model, for the creation of instructional materials and evaluation methods aimed at teaching Chinese characters to individuals who are not native speakers. The study utilises a mixed-methods approach, which involves both qualitative examination of lesson plans created by ChatGPT and quantitative evaluation of student learning outcomes. The results indicate that the suggested framework for human-machine collaboration can successfully tackle the cognitive difficulties associated with learning Chinese characters, resulting in enhanced learner involvement and performance. Nevertheless, the research also emphasises the constraints of AI-generated material and the significance of human involvement in guaranteeing the accuracy and dependability of educational interventions. This research adds to the expanding collection of literature on AI-assisted language learning and offers practical insights for educators and instructional designers who aim to use AI tools into Chinese language curriculum. The results emphasise the necessity of employing a multi-disciplinary strategy in AI-supported language learning, incorporating knowledge from cognitive psychology, educational technology, and second language acquisition.

The cars industry has undergone significant technological advancements, with data analytics and artificial intelligence (AI) reshaping its operations. This study aims to examine the revolutionary influence of artificial intelligence and data analytics on the cars sector, particularly in terms of supporting sustainable business practices and enhancing profitability. Technology-organization-environment model and the triple bottom line technique were both used in this study to estimate the influence of technological factors, organizational factors, and environmental factors on social, environmental (planet), and economic. The data for this research was collected through a structured questionnaire containing closed questions. A total of 327 participants responded to the questionnaire from different professionals in the cars sector. The study was conducted in the cars industry, where the problem of the study revolved around addressing artificial intelligence in its various aspects and how it can affect sustainable business practices and firms’ profitability. The study highlights that the cars industry sector can be transformed significantly by using AI and data analytics within the TOE framework and with a focus on triple bottom line (TBL) outputs. However, in order to fully benefit from these advantages, new technologies need to be implemented while maintaining moral and legal standards and continuously developing them. This approach has the potential to guide the cars industry towards a future that is environmentally friendly, economically feasible, and socially responsible. The paper’s primary contribution is to assist professionals in the industry in strategically utilizing Artificial Intelligence and data analytics to advance and transform the industry.

Since the onset of the COVID-19 pandemic, academic research has primarily focused on the challenges posed by flexible working arrangements. However, there has been a lack of exploration into managers’ intentions to either promote or reject remote work. This paper utilizes a TAM analysis to examine managers’ attitudes and motivations towards implementing telework in a sample of European companies. Our findings reveal that this intention is largely influenced by their perception of its usefulness. Additionally, telework is more likely to be accepted when managerial teams believe that those who hold significance to them also support the implementation of flexible work practices in their companies. Our research contributes to the existing literature by considering the impact of job performance, quality of output, and digital skills on telework adoption. The results confirm that skills related to communication and team building are crucial competencies for successfully implementing telework. The ability of leaders to effectively build, motivate, recognize, and hold accountable teams in virtual environments can make all the difference.

The sustainable development of the global economy and society necessitates the integration of environmental and socially responsible management, known as ESG (environmental, social, and corporate governance). Despite growing recognition of ESG’s importance, the strategic management of ESG factors in Kazakhstan’s telecommunications industry remains underexplored. This study bridges this gap by analyzing Kazakh telecom’s ESG strategies from 2019 to 2021 through a cross-sectional design and semi-structured interviews with 12 industry experts. Utilizing the National Rating Agency (NRA) methodology, the research evaluates environmental, social, and governance variables. Key findings reveal that Kazakh telecom excels in “Climate Change” and “Human Capital Management” but needs significant improvements in “Environmental Impact” and “Society.” The study offers specific recommendations such as enhancing corporate volunteering, responsible marketing, service quality, and integrating sustainable practices. The primary contributions of this research include actionable insights for improving ESG strategies in telecommunications companies and advocating for more systematic and standardized ESG assessment approaches. This study expands the understanding of how ESG principles can enhance competitiveness and sustainable development in the telecommunications industry, providing valuable guidance for industry practitioners and policymakers. It offers insights into effective ESG implementation practices and highlights critical areas requiring attention to drive sustainable development in telecommunications.

There is a growing emphasis on employee engagement in organizations and academia. It is reflected through an increasing number of academic publications that explores the link between human resource management practices and employee engagement. The present study investigates this relationship using bibliometric analysis. It is crucial to understand how human resource management practices influence employee engagement for creating a more productive and engaged workforce. The publications that focused on “human resource management” and “employee engagement” between 1996 and 2023 were analysed using the Biblioshiny package in R from the Web of Science (WoS) database. The analysis examined the existing research trends and also included comparative analysis across different geographic regions. It identified the emerging trends in human resource management research and the interconnectedness of various sub-disciplines within human resource management. This study offers a comprehensive analysis of the relationship between human resource management practices and employee engagement that revealed new avenues for future research and collaboration within the human resource management field. In other words, it will certainly provide valuable insights for future research agendas.

Payment for forest ecosystem services (PFES) policy is a prevalent strategy designed to establish a marketplace where users compensate providers for forest ecosystem services. This research endeavours to scrutinise the impact of PFES on households’ perceptions of forest values and their behaviour towards forest conservation, in conjunction with their socio-economic circumstances and their communal involvement in forest management. By incorporating the social-ecological system framework and the theory of human behaviours in environmental conservation, this study employs a structural equations model to analyse the factors influencing individuals’ perceptions and behaviours towards forest conservation. The findings indicate that the payment of PFES significantly increases forest protection behaviour at the household level and has achieved partial success in activating community mechanisms to guide human behaviour towards forest conservation. Furthermore, it has effectively leveraged the role of state-led social organisations to alter local individuals’ perceptions and behaviours towards forest protection.