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In the dynamic landscape of the modern business world, the pursuit of employee well-being and satisfaction with life (SWL) has gained prominence. Yet, few studies exist on SWL among Indian working professionals. This study aims to investigate the impact of inclusive leadership (IL) on the employees’ SWL. Moreover, employing a mediation approach, the study also reveals the mediating role of workplace inclusion (WI) and career satisfaction (CS) in the relationship between IL and SWL.

The study involves a cross-sectional quantitative approach, drawing upon a sample of 279 professionals belonging to the Indian IT sector by administering standardized questionnaires. Data were analyzed using PLS through SmartPLS4.0 software.

The findings reveal a fully complementary mediating role of WI and CS in the IL–SWL relationship, supporting the hypothesized mediation model.

This finding implies that leaders, with their inclusive behavior, can significantly influence employees’ SWL when accompanied by a sense of inclusiveness and CS among employees. The study offers valuable insights for organizations and leaders seeking to enhance employee satisfaction in the IT sector, emphasizing the significance of career-focused and inclusive practices in the workplace through leadership to promote a fulfilling workplace.

This study represents a pioneering effort to integrate the relationship between IL and SWL within the Indian context, going beyond the existing literature on WI and SWL. Additionally, the research model explores the influence of WI and CS in the IL–SWL relationship, a novel approach that has not been previously investigated.

This paper examines to what extent blockchain creates legitimacy and trust in different modes of public governance. It posits that while blockchain aims for political legitimacy through decentralising, immutable and consensus-based mechanisms, the execution of these mechanisms is limited in legitimating governance, which has knock-on effects on trust. It provides an original contribution by recontextualising and reframing blockchain as a governance mechanism that should, and must, perform a legitimating function in order to engender trust.

The research adopts a comprehensive framework for understanding the legitimacy of blockchain governance, positioning it in terms of co-governance, self-governance and hierarchical governance modes. It systematically analyses blockchain whitepapers, legislation, government documents and other sources in three paradigmatic case studies where blockchain governance failed. These cases are then used to assess blockchain according to three key characteristics of decentralisation, immutability and consensus.

The research finds that blockchain’s use in governance settings still relies on legitimacy conferred from other sources – namely state – in order to generate trust. Significant limitations in its de facto political decentralisation, immutability and consensus protocols can create failures in co-governance, self-governance and hierarchical-governance applications, thus limiting the legitimation function of blockchain in facilitating political trust.

These findings are significant in highlighting blockchain’s limitations as a decentralised, immutable and consensus-driven legitimating tool, which has knock-on effects on trust in technology and governance more broadly. It also has broader implications in more clearly highlighting the interconnectedness of political trust and legitimacy in governance processes.

Grounded on the distributed theory and the social exchange theory, the current study investigates the determinants that positively influence job performance among educators within the realm of higher education in India. It particularly assesses the impact of perceived academic leadership on performance and explores the mediating and moderating effects of organizational citizenship behavior and informal institutional leadership.

Employing a descriptive research design, this study encompasses a broad cross-section of faculty members from various higher educational institutions across India. Data were gathered from 826 educators using a snowball sampling technique, with questionnaires administered online. Each variable was measured using prevalidated scales.

The findings from the moderated mediation model indicate a significant indirect relationship between perceived academic leadership and job performance, which is mediated by organizational citizenship behavior. Furthermore, informal institutional leadership demonstrates significant conditional indirect effects, enhancing the link between academic leadership and job performance up to a threshold, beyond which its influence diminishes.

This study pioneers the exploration of academic dynamics beyond mere titles and ranks in the Indian educational sector. It delineates both the direct and indirect roles these dynamics play in enhancing faculty performance, providing a novel insight into the complexities of academic leadership.

The purpose of this study is to highlight and demonstrate how the study of stress and related responses in construction can best be measured and benchmarked effectively.

A range of perceptual and physiological measures are obtained across different time periods and during different activities in a fieldwork setting. Differences in the empirical results are analysed and implications for future studies of stress discussed.

The results of this study strongly support the use of multiple psychometrics and biosensors whenever biometrics are included in the study of stress. Perceptual, physiological and environmental factors are all shown to act in concert to impact stress. Strong conclusions on the potential drivers of stress should then only be considered when consistent results apply across multiple metrics, time periods and activities.

Stress is an incredibly complex condition. This study demonstrates why many current applications of biosensors to study stress in construction are not up to the task and provides empirical evidence on how future studies can be significantly improved.

To the best of the author’s knowledge, this is the first study to focus explicitly on demonstrating the need for multiple research instruments and settings when studying stress or related conditions in construction.

Violence and aggression against mental health professionals is a global concern with well-documented consequences. In the UK, mental health care is increasingly delivered in the community, yet little research has explored practitioner experiences of workplace violence (WPV) outside of inpatient settings. This study aimed to explore how mental health professionals in a UK community mental health team (CMHT) perceive, experience and cope with WPV.

Face-to-face semi-structured interviews were conducted with ten multidisciplinary professionals based in a CMHT in a UK city. Data was analysed using interpretative phenomenological analysis.

Three interconnected themes emerged. WPV was accepted as inevitable: participants carried on working despite its impact, and feeling unheard by management they gave up on change, perpetuating the perceived inevitability of WPV. Peer support and organisational resources like debriefing, counselling and occupational health improved coping. Stigma and ideas of professional responsibility were barriers to access.

To mitigate against the negative consequences of WPV, CMHTs could offer peer support initiatives, improve communication and availability of organisational resources and involve staff in post-incident decision-making. Recommendations are made to shift the attitude of acceptance of WPV and encourage help-seeking.

The study presented healthcare service quality, lean thinking and Six Sigma to enhance patient satisfaction. Moreover, the notion of machine learning is combined with lean service quality to bring about the fundamental benefits of predicting patient waiting time and non-value-added activities to enhance patient satisfaction.

The study applied the define, measure, analyze, improve and control (DMAIC) method. In the define phase, patient expectation and perception were collected to measure service quality gaps, whereas in the measure phase, quality function deployment (QFD) was employed to measure the high-weighted score from the patient's voice. The root causes of the high weighted score were identified using a cause-and-effect diagram in the analysis phase.

The study employed a random forest, neural network and support vector machine to predict the healthcare patient waiting time to enhance patient satisfaction. Performance comparison metrics such as root-mean-square error (RMSE), mean absolute error (MAE) and R2 were accessed to identify the predictive model accuracy. From the three models, the prediction performance accuracy of the support vector machine model is better than that of the neural network and random forest models to predict the actual data.

Lean service quality improvement using DMAIC, QFD and machine learning techniques can be generalized to predict patient waiting times. This study provides better realistic insights into patient expectations by announcing waiting times to enable data-driven service quality deliveries.

Prior studies lack lean service quality, Six Sigma and waiting time prediction to reduce healthcare waste. This study proposes lean service quality improvement through lean Six Sigma (LSS), i.e. DMAIC and machine learning techniques, along with QFD and cause-and-effect diagram.

Companies are increasingly benefiting from artificial intelligence (AI) applications in various domains, but also facing its negative impacts. The challenge lies in the lack of clear governance mechanisms for AI. While documentation is a key governance tool, standard software engineering practices are inadequate for AI. Practitioners are unsure about how to document AI, raising questions about the effectiveness of current documentation guidelines. This review examines whether AI documentation guidelines meet regulatory and industry needs for AI applications and suggests directions for future research.

A structured literature review was conducted. In total, 38 papers from top journals and conferences in the fields of medicine and information systems as well as journals focused on fair, accountable and transparent AI were reviewed.

This literature review contributes to the literature by investigating the extent to which current documentation guidelines can meet the documentation requirements for AI applications from regulatory bodies and industry practitioners and by presenting avenues for future research. This paper finds contemporary documentation guidelines inadequate in meeting regulators’ and professionals’' expectations. This paper concludes with three recommended avenues for future research.

This paper benefits from the insights from comprehensive and up-to-date sources on the documentation of AI applications.

A wide gap exists between the innovation and development of self-monitoring, analysis and reporting technology (SMART) technologies and the actual adoption by older adults or those caring for them. This paper aims to increase awareness of available technologies and describes their suitability for older adults with different needs. SMART technologies are intelligent devices and systems that enable autonomous monitoring of their status, data analysis or direct feedback provision.

This is a scoping review of SMART technologies used and marketed to older adults or for providing care.

Five categories of SMART technologies were identified: (1) wearable technologies and smart tools of daily living; (2) noninvasive/unobtrusive technology (i.e. passive technologies monitoring the environment, health and behavior); (3) complex SMART systems; (4) interactive technologies; (5) assistive and rehabilitation devices. Technologies were then linked with needs related to everyday practical tasks (mainly applications supporting autonomous, independent living), social and emotional support, health monitoring/managing and compensatory assistance rehabilitation.

When developing, testing or implementing technologies for older adults, researchers should clearly identify concrete needs these technologies help meet to underscore their usefulness.

Older adults and caregivers should weigh the pros and cons of different technologies and consider the key needs of older adults before investing in any tech solution.

SMART technologies meeting older adult needs help support both independent, autonomous life for as long as possible as well as aiding in the transition to assisted or institutionalized care.

This is the first review to explicitly link existing SMART technologies with the concrete needs of older adults, serving as a useful guide for both older adults and caregivers in terms of available technology solutions.