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The paper focuses on bridging the existing literature gap on the role of leadership in influencing employee engagement considering the advancement in technologies. With this, the author explores how the three critical elements of service-based companies' business environment-artificial intelligence (AI) success, employee engagement, and leadership are interlinked and are valuable for raising the engagement level of employees.

A purposive sampling strategy was used to select the employees working in the respective companies. The survey was distributed to 150 senior management employees but responses were received from only 56 employees making the response rate 37.33%. Consequently, an empirical examination of these 56 senior management employees belonging to service-based companies based in Delhi NCR using a survey questionnaire was conducted.

The PLS-SEM (partial least squares structured equation modelling) revealed that AI has a positive role in affecting employee engagement levels and confirmed the mediation of leadership. The magnitude of the indirect effect was negative leading to a reduction in total effect magnitude; however, as the indirect effect model has a higher R square value, the inclusion of a mediating variable made the model more effective.

This study contributes to extending the existing knowledge of the academicians about the relationship theory of leadership, AI implementation in organizations, AI association with leadership and AI impact on employee engagement. The author extends the theoretical understanding by showing that more integration of AI-supported leadership could enable organizations to enhance employee experience and motivate them to be engaged. Despite its relevance, due to the limited sample size, focus on a specific geographic area (Delhi NCR) and the constraint of only using quantitative analysis, the findings open the scope for future research in the form of qualitative and longitudinal studies to identify AI-supported leadership roles.

The study findings are beneficial majorly for organizations to provide them with more in-depth information about the role of AI and leadership style in influencing employee engagement. The identified linkage enables the managers of the company to design more employee-tailored strategies for targeting their engagement level and enhancing the level of productivity of employees. Moreover, AI-supported leadership helps raise the productivity of employees by amplifying their intelligence without making technology a replacement for human resources and also reducing the turnover rate of employees due to the derivation of more satisfaction from existing jobs. Thus, given the economic benefit and societal benefits, the study is relevant.

The existing studies focused on the direct linkage between AI and employee engagement or including artificial intelligence as a mediating variable. The role of leadership is not evaluated. The leadership enables supporting the easy integration of AI in the organization; therefore, it has an important role in driving employee engagement. This study identifies the contribution of leadership in organizations by providing the means of enhancing employee satisfaction without hampering the social identity of the company due to the integration of AI.

The relationships between transformational leadership (TL), organizational climate (OC) and project performance have been investigated by previous studies, but no review of existing studies has systematically analyzed the effects of TL and OC on project performance in the industrial revolution (IR) 5.0 era. Therefore, this study aims to conduct a systematic literature review on the effects of TL and OC on project performance in IR 5.0, and to identify mainstream research topics, research gaps and future research directions.

To do this, a total of 53 included journal articles were obtained after initially retrieving 648 documents from the Scopus database by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. It consists of four main steps, namely, identification of documents, screening, eligibility and included articles. In addition, science mapping analyses were conducted for keyword co-occurrence and document analyses, which aided in identifying the mainstream research topics, research gaps and future research directions.

The results report the annual publication trends, keywords and document analyses. Furthermore, a detailed qualitative discussion highlighted four mainstream research topics including TL in project management; the relationship between TL, OC and innovation; safety climate; and OC in project management. Moreover, this review study identified four research gaps and future research directions aligned with the mainstream research topics. They include: longitudinal investigations and multinational corporation surveys in TL; scope and longitudinal data in innovation; mono-method bias and universality of safety climate; and more comprehensive analyses of OC.

This review study would contribute to not only advancing the effects of TL and OC on project performance in IR 5.0, but also enabling project managers to understand TL or OC issues to improve project performance.

This study aims to develop a talent selection model for learning organizations capable of connecting two groups, candidates in a talent hiring process and managers of the hiring company, in a reliable process, promoting organizational learning and increasing employee satisfaction.

This paper integrates egalitarian principles, an artificial intelligence mechanism founded on stable matching algorithms, and evaluating critical soft skills to enhance recruitment practices within learning organizations. The authors conduct a numerical real-world application in Python to showcase the model’s effectiveness. Five candidates were evaluated for five job positions. Moreover, 26 soft skills were analyzed by the five company leaders, relating them to the requirements of each job position and by all candidates, as a self-assessment process.

The model promoted egalitarian talent management because it motivates the candidates to choose the preferred position in a company, and the employers hire the best candidate. It is satisfactory for all participants in a company’s hiring process if the parties intend to be fair and egalitarian. The benefits of the process can be considered isolated (parties’ satisfaction) or a part of a company’s effort to stimulate an egalitarian culture in organizational values.

The information generated by the model is used to refine its selection process and improve its understanding of the job requirements and candidate profiles of the company. The model supports this idea, using the concepts of indifference, stability, egalitarianism and the soft skills required and identified to be more effective and learn about themselves.

This paper discusses an egalitarian point of view in the recruitment process. It is satisfactory for all participants in a company’s hiring process if the parties intend to be fair and egalitarian. The process’s benefits can be considered part of a company’s effort to stimulate an egalitarian culture in organizational values.

This paper brings an excellent future perspective and points to the company’s development of talent retention. The model simultaneously solves the evolution of talent management processes through new technologies and soft skills emerging in the postpandemic scenario.

The determination of human behaviours due to individual characteristics (personality traits) or situational factors has long remained inconclusive. Although the literature stream on personality as the determinants of behaviour is voluminous, the interest of researchers is also growing towards organisational situational cues as the determinant of behaviours. According to situation strength theory (SST), behaviours are determined by situations in strong situations and by personality in weak situations. This study aims to propose a theoretical model of intrapreneurial behaviour (IB) emanation from empowering leadership (EL) by extending the epistemology of SST under the influence of organisational strong situations of job autonomy (JA) and perceived organisational support (POS).

Using SST, the present study argues that strong situations play a key role in determining human behaviours, and the same can be viewed deductively to assess IB.

The study attempts to propose whether EL is capable of predicting IB under the strong situation effect of JA and POS while dampening the impact of human personality characteristics.

The current study offers a significant departure from current human resource practices in person-situation dialectics, moving away from personality assessments and toward the creation of cues from strong situations for fostering human behaviour. As a result, personality researchers are being encouraged to conduct a reality check on the extensive personality research conducted in occupational settings. Considering organisational situational cues can impact human resource scope in areas such as talent management, selection, promotion and employment.

The purpose of this study is to provide an overview of artificial intelligence (AI) in the talent management sphere. The study seeks to contribute to the body of knowledge with respect to human resource management and AI by conducting a literature review on the integration of AI in talent management, synthesising existing approaches and frameworks, as well as emphasising potential benefits.

The study adopts desk research, computational literature review (CLR) and uses topic modelling [with bidirectional encoder representations from transformers (BERTopic)] to throw light on the diffusion of AI in talent management.

The study’s main finding is that the area of AI in talent management is on the verge of gradual development and is in tandem with the growth of AI. We deduced that there is a link between talent management practices (planning, recruitment, compensation and rewards, performance management, employee empowerment, employee engagement and organisational culture) and AI. Though there are some known fears with regards to using the innovation, the benefits outweigh the demerits.

The current study has some limitations. The scope and size of the sample are the primary limitations of this study. No form of qualitative analytics was used in this study; as a result, the information obtained was limited. The study provides a snapshot of AI in talent management and contributes to the lack of literature in the joint fields. Also, the study provides practitioners and experts an overview of where to target investments and resources if need be.

The originality of this study comes from the combination of CLR methods and the use topic modelling with BERTopic which has not been used by previous reviews. In addition, the salient machine learning algorithms are identified in the study, which other studies have not identified.

In today’s highly competitive world, the purpose of this research is to emphasize the increasing significance of management education and advocate for the adoption of innovative teaching approaches, specifically focusing on artificial intelligence (AI)-driven personalized learning (PL). This study aims to explore the integration of self-determination theory (SDT) principles into management education, with a primary focus on enhancing student motivation, engagement and academic performance (AP).

This interdisciplinary research adopts a multifaceted approach, combining perspectives from AI, education and psychology. The design and methodology involve a thorough exploration of the theoretical foundations of both AI-driven education and SDT. The research demonstrates how these two elements can synergize to create a holistic educational experience. To substantiate the theoretical claims, empirical data-driven analyses are employed, showcasing the effectiveness of AI-enabled personalized learning (AIPL). The study integrates principles from SDT, such as autonomy, competence and relatedness, to create an environment where students are intrinsically motivated, receiving tailored instruction for optimal outcomes.

The study, rooted in SDT, demonstrates AIPL’s transformative impact on management education. It positively influences students’ autonomy, competence and relatedness, fostering engagement. Autonomy is a key driver, strongly linked to improved AP. The path analysis model validates these relationships, highlighting AI’s pivotal role in reshaping educational experiences and intrinsically motivating students.

This study holds substantial significance for educators, policymakers and researchers. The findings indicate that the AIPL model is effective in increasing student interest and improving AP. Furthermore, this study offers practical guidance for implementing AI in management education to empower students, enhance engagement and align with SDT principles.

Contribute original insights through an interdisciplinary lens. Synthesize AI and SDT principles, providing a roadmap for a more effective educational experience. Empirical data-driven analyses enhance credibility, offering valuable contributions for educators and policymakers in the technology-influenced education landscape.

The aim of this article is to produce alternative solution suggestions at a conceptual level, by utilizing technologies in the field of Augmented Reality (AR) and Artificial Intelligence (AI), to address the increasing personnel shortages encountered in the tourism and hospitality industry. The discussion is based on a review of the literature.

This article presents a qualitative study investigating the impact of Artificial Intelligence (AI) and Augmented Reality (AR) technologies on the workforce turnover rate in the tourism and hospitality industry in general.

Although Artificial Intelligence (AI) and Augmented Reality (AR) technologies have both positive and negative aspects for the hospitality and tourism industry and its employees, these technologies can be used to reduce the factors that cause employee turnover. In particular, it leads to improvements in job satisfaction, job commitment and career opportunities of sector employees, reduction of job stress, and selection and retention of the right employees.

This study examines the factors that tourism sector employees encounter in the sector and that cause the workforce turnover rate to increase, and emphasizes the importance of the possible benefits of the use of Artificial Intelligence (AI) and Augmented Reality (AR) technologies in reducing these factors that cause the workforce turnover rate.

The present study aimed to explore the socio-psychological linkages between perceived job insecurity, loneliness, social support, depression, and interpersonal misconduct among hotel workers during a global crisis. The primary motivation behind this research was the significant problem of increased occupational stress resulting from the negative consequences of the pandemic on all hotel employees, including frontline workers and management personnel. This study aimed to investigate the impact of the pandemic on occupational stress within the hotel sector.

This research obtained 269 original survey data from employees in the Indian hotel industry by distributing a questionnaire and employing a convenience sampling method. Subsequently, the data were examined using (SEM).

The research findings suggest that there is a positive correlation between interpersonal deviance and depression. Additionally, this study demonstrated that social support can alleviate loneliness but has no significant association with depression.

This study can help hotel managers create guidelines that address the perceived insecurity and psychological issues faced by employees.

By understanding the psychological position of their employees, hoteliers can implement strategies to mitigate the negative impacts of the pandemic on their workforces.

The purpose of this paper spans twofold. Firstly, to investigate Human Resource Management practices (HRMP) adopted by organisations during the pandemic. Secondly, to bundle similar HRMP into Human Resource Management (HRM) bundles that provided unhindered organisational support to employees during the crisis.

The authors conducted 39 in-depth interviews across industries using a semi-structured interview schedule. Thereafter, the authors transcribed the interviews verbatim and analysed them thematically using MAXQDA 2021.

The study identifies effective practices during times of uncertainty and how soft HRM practices helped organisations survive during a crisis. When bundled together, these practices enabled organisations to continue operations during the pandemic, keeping their employees engaged and motivated.

Based on the learnings from the COVID-19 pandemic, the study provides a toolkit of HRMP bundles that organisations can adopt for future crisis management, enhancing the organisations’ absorptive capacity.

The study investigates the practices incorporated during COVID-19, leading to the identification of soft HRM bundles. The study adds value to the existing domain of HRM by including a unique set of soft HRMP bundles that have not been discussed in earlier studies and could be of high utility to organisations during the crisis.

With the goal to indicate the importance of human–nature connection in designing workplaces, the authors investigated the effects of direct and indirect biophilic indicators on the well-being and performance of employees of an organization. The main question is what is the effect of biophilic components on the well-being and performance of employees.

To answer the research questions, the authors designed and validated an instrument to evaluate correlation between biophilic components with well-being and performance. The participants include 160 employees of one organization. For the data analysis, both descriptive statistical and inferential statistics were used. Pearson's correlation test and ANOVA were conducted to explain the relationship between variables.

The results indicated that biophilic components have significant positive relationships with the well-being of the employees, but no significant relationship was found between biophilic components and the performance of the employees. Using the ANOVA test, biophilic indicators that have a positive and significant effect on the well-being and performance of employees were determined. The natural scenery and warm colors has significant positive effects on social well-being, and the usage of natural landscape posters in the working rooms has a positive and significant relationship with psychological well-being. The natural lighting has a positive and significant relationship with the employees' counterproductive work behavior.

Most of the questionnaires of this research were filled electronically because of the health protocols during pandemic. Almost 70% of the organization's employees had less than 5 years of work experience, which can be considered one of the interfering factors. In addition, the authors only used the questionnaire as a tool for collecting information in this study. There are other forms of information that can be explored through observations, interviews or experiments. Another limitation of this study is the lack of significant diversity in the investigated environments. Finally, the numbers of male and female participants of this study were not equal. The authors suggest studying both genders with an almost equal ratio so that the differences and needs of both groups can be understood.

The designed questionnaire is a validated instrument that can be used by other researchers to evaluate the biophilic design of workplace. These findings can also be useful for managers, companies and organizations in making decisions to improve the working environment and increase the well-being and performance of their employees.

The social effects of biophilic design in the workplace are significant as well. The use of biophilic components can foster a sense of connection between employees and their workplace, creating a positive social environment that supports collaboration and communication. Additionally, a biophilic workplace can promote a positive company culture that values the health and well-being of its employees, which can contribute to employee retention and satisfaction.

In this study, to determine the effects of the biophilic indicators on dimensions of employees' well-being and performance, an instrument is designed and validated.