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Purpose: Significant structural changes are currently occurring in the Indian labour sector. Artificial intelligence (AI) and other emerging technologies are redefining the activities and skill requirements for various jobs in the healthcare sector. These adjustments have been accelerated by the economic crisis brought on by COVID-19, along with other considerations.

Need for the Study: Skills shortages, job transitions, and the deployment of AI at the company level are the three main challenges confronting the Indian labour market. This chapter aims to discuss policy alternatives to address a rising need for health workers and provide an overview of changes to the healthcare sector’s labour market.

Methodology: A review of the available literature was conducted to determine the causes of the widening skill gap despite a vibrant and prodigious young population. The background of the sustainable labour market is examined in this chapter, with a focus on workforce migration and mobility.

Findings: This chapter gives a comparative review of recent policy papers and evidence, as well as estimates of the health workforce and present Indian datasets. Furthermore, it highlights how important it is for all people concerned to invest in today’s workforce to close the skill gap and create better future opportunities.

Practical Implications: This chapter’s findings imply a severe shortage of human intellectual capital in India and a need to bridge this gap in the Indian labour market.

The imperative to conserve resources and minimize operational expenses has spurred a notable increase in the adoption of lean manufacturing within the context of the circular economy across diverse industries in recent years. However, a notable gap exists in the research landscape, particularly concerning the implementation of lean practices within the pharmaceutical industry to enhance circular economy performance. Addressing this void, this study endeavors to identify and prioritize the pivotal drivers influencing lean manufacturing within the pharmaceutical sector.

The outcome of this rigorous examination highlights that “Continuous Monitoring Process for Sustainable Lean Implementation,” “Management Involvement for Sustainable Implementation” and “Training and Education” emerge as the most consequential drivers. These factors are deemed crucial for augmenting circular economy performance, underscoring the significance of management engagement, training initiatives and a continuous monitoring process in fostering a closed-loop practice within the pharmaceutical industry.

The findings contribute valuable insights for decision-makers aiming to adopt lean practices within a circular economy framework. Specifically, by streamlining the process of developing a robust action plan tailored to the unique needs of the pharmaceutical sector, our study provides actionable guidance for enhancing overall sustainability in the manufacturing processes.

This study represents one of the initial efforts to systematically identify and assess the drivers to LM implementation within the pharmaceutical industry, contributing to the emerging body of knowledge in this area.

The purpose of this study is to discover the factors related to human resource (HR) digital transformation (DT) in Bahrain during coronavirus disease 2019 (COVID-19) and to analyze the impact of e-human resource management (e-HRM) on organizational performance. These factors are funding, information technology (IT) infrastructure, technical support, digital skills or talents, organizational culture, employee resistance and top management support. These factors were tested to determine whether they affected HR DT in Bahrain during COVID-19. There are no findings in the researched literature regarding the proposed factors that affect HR DT in Bahrain during COVID-19 in this study.

For data collection, a quantitative method was applied by conducting an online survey and distributing it to HR executives and employees from multiple organizations in Bahrain, both in the private and public sectors.

This study proposes a DT adoption model based on seven factors extracted from the literature review. A questionnaire was deployed, and accurate data were collected, processed and then analyzed. The logit model shows determinants factor to the DT adoption where all variables have a positive effect.

Using technology in an organization’s HR practices, known as e-HRM or HR DT, is becoming more crucial since the COVID-19 pandemic. Unlike European countries, the HR sector in Bahrain is not prepared to adopt the e-HRM process. This paper proposes a model that enables the HR sector to adopt digital technologies. This model is based on the key factors that enable an effective transition to the sector’s digitalization (e-HRM). Future research is sought to provide additional insights into the same factors and measure their effect on HR DT during COVID-19 in other countries.

This study aims to develop and test an original conceptual framework that examines the role of various factors borrowed from three theories (i.e. Institutional Theory, Resource-Based View and Diffusion of Innovation) in adopting Human Resource Analytics (HRA).

A new conceptual framework (research model) is developed based on previous research and coherent theoretical arguments. Its factors are classified using the Technology–Organization–Environment (TOE) framework. Research hypotheses are tested using primary data collected from 152 managers of Greek organizations. Empirical data are analyzed using the “Structural Equation Modelling” (SEM) technique.

The technological and organizational context proved extremely important in enhancing Organizational Analytics Maturity (OAM) and HRA adoption, while the environmental context did not. Relative advantage and top management support were found to significantly impact the adoption of HRA, while Information Technology (IT) infrastructure, human resource capabilities and top management support are crucial for increasing OAM. Overall, the latter is the most important factor in enhancing HRA adoption.

This study contributes to the limited published research on HRA adoption while at the same time it can be used as a guideline for future research. The novel findings offer insights into the factors impacting OAM and HRA adoption.

Upon the premises of social exchange theory (SET), this study aimed at hypothesizing and examining a serial mediation model that investigated the underlying mechanism through which a high-performance work system (HPWS) affects individuals’ future time perspective (FTP).

The hypothesized relationships were examined using responses collected from 275 employees from 15 local private banks and 40 established branches through a proportionate stratified sampling technique. The statistical package for social sciences (SPSS) PROCESS macro 3.0 and analysis of moment’s structure (AMOS) 24.0 were employed for data analysis purposes.

The study revealed that HPWS is indirectly related to the individuals’ FTP through workplace social courage (WSC) and employee well-being (EWB) sequentially. Prescriptions for theoretical and managerial implications were discussed, and future research viewpoints with limitations were acknowledged.

This study illuminated the underlying mechanism and theoretical logic linking HPWS and individuals’ FTP by proposing the serial mediating effect of WSC and EWB.

The purpose of this study is to investigate the impact of integrating “Licorice powder” into curd balls on their storage stability under refrigeration conditions. Through this examination, this study aims to evaluate the potential effects of licorice powder on extending the shelf life, maintaining quality attributes and preserving the overall stability of curd balls when stored at refrigeration temperatures.

Licorice powder, in varying quantities (1%, 2% and 3%), was incorporated into curd balls alongside a control group lacking licorice (0%). These batches were subsequently stored for 25 days under refrigeration at a temperature of 4 ± 1ºC, using aerobic packaging conditions. During this storage period, the samples were regularly monitored and analyzed for various parameters to assess changes in their properties and qualities.

The findings indicated that in the treatment groups, pH and titratable acidity were notably lower than those in the control group (p = 0.05). Curd balls enriched with licorice powder exhibited significantly higher levels of 2, 2-diphenyl-1-picrylhydrazyl, 2-2-azinobis-3ethylbenthiazoline-6-sulphonic acid and total phenolic contents compared to the control (p = 0.05). Furthermore, curd balls containing licorice powder displayed notably lower levels of peroxide, thiobarbituric acid reactive substances and free fatty acids in comparison to the control (p = 0.05). Among all samples, T3 (3%) demonstrated significantly less microbial growth (p = 0.05) than the other groups. Conversely, the sensory panel rated T2 significantly higher than T3 (p = 0.05).

The investigation highlights that curd balls enriched with 2.0% licorice powder demonstrated significant efficacy in preventing the deterioration of physicochemical attributes, enhancing antioxidant capacity, restraining lipid oxidation, curbing microbial growth and ultimately exhibiting the most favorable organoleptic properties among the tested variations. This finding underscores the potential of incorporating 2.0% licorice powder as an effective agent for bolstering the storage stability and overall quality of curd balls during refrigerated storage.

This study aims to test the market anomaly of herding behavior driven by the response to supply chain disruptions in extreme market conditions such as those observed during COVID-19. The authors empirically test the response of the capital market participants for B2B firms, resulting in herding behavior.

Using the event study approach based on the market model, the authors test the impact of supply chain disruptions and resultant herding behavior across six sectors and among different B2B firms. The authors used cumulative average abnormal returns (CAAR) and cross-sectional absolute deviation (CSAD) to examine the significance of herding behavior across sectors.

The event study results show a significant effect of COVID-19 due to supply chain disruptions across specific sectors. Herding was detected across the automotive and pharmaceutical sectors. The authors also provide evidence of sector-specific disruption impact and herding behavior based on the black swan event and social learning theory.

The authors examine the impact of COVID-19 on herding in the stock market of an emerging economy due to extreme market conditions. This is one of the first studies analyzing lockdown-driven supply chain disruptions and subsequent sector-specific herding behavior. Investors and regulators should take sector-specific responses that are sophisticated during extreme market conditions, such as a pandemic, and update their responses as the situation unfolds.

This article aims to optimise energy use and consumption by integrating Lean Six Sigma methodology with the ISO 50001 energy management system standard in an Irish dairy plant operation.

This work utilised Lean Six Sigma methodology to identify methods to measure and optimise energy consumption. The authors use a single descriptive case study in an Irish dairy as the methodology to explain how DMAIC was applied to reduce energy consumption.

The replacement of heavy oil with liquid natural gas in combination with the new design of steam boilers led to a CO₂ footprint reduction of almost 50%.

A further longitudinal study would be useful to measure and monitor the energy management system progress and carry out more case studies on LSS integration with energy management systems across the dairy industry.

The novelty of this study is the application of LSS in the dairy sector as an enabler of a greater energy-efficient facility, as well as the testing of the DMAIC approach to meet a key objective for ISO 50001 accreditation.

This study aims to explore the transformative potential of integrating artificial intelligence (AI) and the metaverse into academic libraries, envisioning a future where personalized, immersive and accessible user experiences redefine the traditional concept of libraries. The purpose is to analyse the synergy between AI and the metaverse in enhancing library services and user interactions.

The study uses a literature review approach to synthesize current knowledge on AI, the metaverse and their integration into academic libraries. It delves into the functionalities of AI in cataloguing, personalization and predictive analysis, coupled with the immersive experiences offered by the metaverse. The design envisions metaverse-infused academic libraries as digital spaces hosting AI-driven virtual assistants, personalized learning paths and collaborative environments.

The integration of AI and the metaverse in academic libraries presents opportunities for personalized learning experiences, efficient resource management and global collaboration. The findings suggest that the synergy enhances accessibility, inclusivity and efficiency in library services, albeit with challenges such as the digital divide, privacy concerns and technical complexities.

This study contributes to the discourse on the future of academic libraries by proposing a comprehensive vision of metaverse-infused libraries empowered by AI. It underscores the originality and value of the integration, emphasizing the potential for personalized, interactive and globally accessible learning and research environments.

This paper aims to present a summary of the green consumer behaviour (GCB) research conducted during the 2001–2021 period using the bibliometric analysis and to carry out a thematic and content analysis on the three clusters which comprise 57 articles resulting from the co-citation analysis and identify the significant green purchasing factors.

The three-pronged methodology applied to this research analysis includes performance analysis of the literature using biblioshiny and R Studio; network mapping analysis using VOSviewer and Gephi; thematic analysis using word clouds generated with R Software and content analysis of each paper with the aid of within and between-study analyses.

Cluster one acted as a base for the theoretical foundations of GCB which aids in understanding the basic concepts of green marketing, its evolution and the methodologies, whereas cluster two determined the predictors of everyday green behaviour, which helps in gaining knowledge about the everyday sustainable activities the consumers indulge and the factors motivating to do so. Cluster three mainly focused on the psycho-socio demographic determinants of GCB, which assists in segmentation and predicting the purchase behaviour of the various consumer segments.

The significant variables and major gaps in each of the clusters were identified and authors have drawn the implications for future researchers and marketing managers.