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Concerned with the rising social, economic and technological disruption in the world, the impact of the technological disruption had a significant impact on the future of work and it has been tremendously increased in past five years. Further, with the rising uncertainties and COVID-19 in the picture, the trends suggested by earlier literature might not hold. The purpose of this paper is to understand the evolution of technology in the workplace in the past five years, how does it stand during COVID-19, will the trend continue in light of disruption caused by COVID-19, the impact of COVID-19 on the future of work.

The paper uses bibliometric techniques to identify the conceptual and intellectual structure of the studies. The programming language named after authors Robert and Ross (R) software and Biblioshiny were used to identify the structures and the themes underlying those structures, which further helped in forecasting the trends of the studies.

The paper shows the drastic evolution of the studies in past few years and different technologies implemented at the workplace in the same period. It further identified the influential papers, authors, journals in the area with an emphasis on the various collaboration network among authors and countries. It also paints a picture of the impact of COVID-19 on the future of work. The paper finally concluded with future directions for the emerging trends and themes in the area in aftermath of COVID-19.

This paper takes the microscopic view of the studies carried out in the past five years as during the past five years, the studies related to this topic have grown tremendously and accordingly many trends have been identified but with the COVID-19 pandemic in the picture, the trend is likely to get accelerated. This paper takes this view and identifies the trends in the future by identifying the themes based on periods and at different levels – organizational, managerial, individual.

The study intends to examine the generational differences between GenY and GenZ Indian generational cohorts on the study variables, i.e. core self-evaluations (CSE), team cohesion, organizational culture and team performance. Further, the present research aims to analyze the impact of CSE, team cohesion and organizational culture on team performance as antecedents.

The study has adopted a descriptive cross-sectional survey method where the data were collected from Indian working professionals who belonged to GenY and GenZ generational cohorts. Further, a total of 370 responses were received, and thereafter, the data were analyzed by employing significant statistical tests such as exploratory factor analysis (EFA), confirmatory factor analysis (CFA), structural equation modeling (SEM) and an independent samples t-test.

The study results revealed that GenY and GenZ cohorts significantly differ on CSE, team cohesion and organizational culture. However, no significant difference was reported in team performance between these two generational cohorts. Also, the study results disclosed that CSE, team cohesion and organizational culture positively influence team performance by acting as its determinants.

The study reports differences between GenY and GenZ that would assist managers in effectively dealing with these generational cohorts and formulating human resource (HR) policies that can accommodate the needs of these two cohorts. Additionally, the study benefits managers by highlighting the importance of core-self evaluations, team cohesion and organizational culture to enhance team performance.

Existing research depicts that there lies a paucity of generational studies in the Indian context. The present study attempts to address this lacuna by putting pioneering efforts into this field. The main contribution of the study lies in empirically investigating the Indian generational cohorts (GenY and GenZ) in the organizations. Further, the study has also conceptualized and examined a team performance model by considering factors at three levels (individual, team and organization).

The study aims to define the term “generation” by proposing an integrated design based on age-period-cohort effects and by proposing an Indian generational cohort framework categorizing Indian generational cohorts into four categories, namely, Baby Boomers, GenX, GenY, and GenZ. The study further aimed to capture the existing generational differences between GenY and GenZ cohorts in the Indian teams on team climate, transactive memory system, and team leader humility.

For the first two objectives a literature review methodology along with the author's proposition was adopted. An integrated design was proposed by reviewing the relevant sociological literature to define generations. Thereafter, an Indian cohort framework was proposed categorizing them into four groups Baby Boomers, GenX, GenY, and GenZ. Following that, for the last objective, i.e. to identify the differences between cohorts, empirical data were collected by a structured questionnaire that was disseminated to GenY and GenZ Indian working professionals. A total of 229 responses were used for observing the differences or similarities between GenY and GenZ cohorts on the study variables by employing an independent samples t-test.

The study proposed an integrated design (age, period, and cohort effect). Following that, an Indian generational cohort's framework has been outlined categorizing Indian cohorts based on their birth years, age groups, developmental stages, formative years, major Indian historical events, and various characteristics possessed by them. Moreover, the empirical findings support the existing generational disparities and depict that GenZ holds a higher inclination towards transactive memory systems and team climate whereas GenY holds more inclination toward leader humility.

The study put forth its contribution to research scholars by categorizing Indian generational cohorts in a rationalized manner based on an integrated design (age-period-cohort) effect. The study would further assist concerned authorities and managers in formulating HR policies to deal with the underlying generational differences highlighted by the study.

As there lies a paucity of generational frameworks in the Indian context, this study is the first attempt in this direction which categorizes Indian generational cohorts based on a unique integrated design including age-period-cohort effects. In addition, the study also investigated these cohorts in Indian organizations to observe the existing variations.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

A study of Indian working professionals showed GenY and GenZ cohorts differed significantly in their approaches to core self-evaluations (CSE), team cohesion and organisational culture, but no significant difference was found in team performance. Meanwhile, the study also showed that CSE, team cohesion and organisational culture had a positive effect on team performance

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The already-strained vaccine supply chain (VSC) of the expanded program for immunization (EPI) require a more robust and structured distribution network for pandemic/outbreak vaccination due to huge volume demand and time constraint. In this paper, a lean-agile-green (LAG) practices approach is proposed to improve the operational, economic and environmental efficiency of the VSC.

A fuzzy decision framework of importance performance analysis (IPA)–analytical hierarchy process (AHP)–technique for order for preference by similarity in ideal solution (TOPSIS) has been presented in this paper to prioritize the LAG practices on the basis of the influence on performance indicators. Sensitivity analysis is carried out to check the robustness of the presented model.

The derived result indicates that sustainable packaging, coordination among supply chain stakeholders and cold chain technology improvement are among the top practices affecting most of the performance parameters of VSC. The sensitivity analysis reveals that the priority of practices is highly dependent on the weightage of performance indicators.

This study's finding will help policymakers reframe strategies for sustainable VSC (SVSC) by including new management practices that can handle regular immunization programs as well as emergency mass vaccination.

To the best of the authors' knowledge, this is the first study that proposes the LAG framework for SVSC. The IPA–Fuzzy AHP (FAHP)–Fuzyy TOPSIS (FTOPSIS) is also a novel combination in decision-making.

An integrated intuitionistic fuzzy (IF) modelling-based framework for examining the performance analysis of a packaging unit (PU) in three different stages has been proposed.

For the series and parallel configuration of PU, a mathematical model based on the intuitionistic fuzzy Lambda–Tau (IFLT) approach was developed in order to calculate various reliability parameters at various spreads. For determining membership and non-membership function-based reliability parameters for the top event, AND/OR gate transitions expression was employed.

For 15%–30% spread, unit’s availability for the membership function falls by 0.006442%, and it falls even more by 0.014907% with an increase in spread from 30% to 45%. In contrast, for 15%–30% spread, the availability of non-membership function-based systems reduces by 0.007491% and further diminishes. Risk analysis has presented applying an emerging approach called intuitionistic fuzzy failure mode and effect analysis (IFFMEA). For each of the stated failure causes, the output values of the intuitionistic fuzzy hybrid weighted Euclidean distance (IFHWED)-based IFFMEA have been tabulated. Failure causes like HP1, MT6, FB9, EL16, DR23, GR27, categorized under subsystems, namely hopper, motor, fluidized bed dryer, distributor, grader and bin, respectively, with corresponding IFFMEA output scores 1.0975, 1.0190, 0.8543, 1.0228, 0.9026, 1.0021, were the most critical one to contribute in the system’s failure.

The limitation of the proposed framework lies in the fact that the results obtained for both reliability and risk aspects mainly depend on the correctness of raw data provided by the experts. Also, an approximate model of PU is obtained from plant experts to carry performance analysis, and hence more attention is required in constructing the model. Under IFLT, reliability parameters of PU have been calculated at various spreads to study and analyse the failure behaviour of the unit for both membership and non-membership function in the IFS of [0.6,0.8]. For both membership- and non-membership-based results, availability of the considered system shows decreasing trend. To improve the performance of the considered system, risk assessment was carried using IFFMEA technique, ranking all the critical failure causes against IFHWED score value, on which more attention should be paid so as to avoid sudden failure of unit.

The livelihood of millions of farmers and workers depends on sugar industries. So perpetual running of these industries is very important from this viewpoint. On the basis of findings of reliability parameters, the maintenance manager could frame a correct maintenance policy for long-run availability of the sugar mills. This long-run availability will generate revenue, which, in turn, will ensure the livelihood of the farmers.

Mathematical modelling of the considered unit has been done applying basic expressions of AND/OR gate. IFTOPSIS approach has been implemented for ranking result comparison obtained under IFFMEA approach. Eventually, sensitivity analysis was also presented to demonstrate the stability of ranking of failure causes of PU.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.

In the last 10 years, India has amended its laws dealing with sexual offences against women with the changes ranging from increasing terms of imprisonment for the offence of rape to state-funded compensation schemes for women and child victims. In this regard, challenges persist for the agencies of the criminal justice system in India especially the courts to realise the vision of restorative justice as these forums have to navigate the relevant statutory provisions and binding precedents. This chapter seeks to analyse the challenges faced by courts in proper reintegration of victims and offenders of sexual offences, the institutional responses of the courts and suggests reforms to the criminal justice system in India in consonance with the principles of restorative justice acknowledged in the restorative justice movement in the international discourse.

The purpose of the present work is to improve the industry performance by identifying and quantifying the risks faced by the Indian pharmaceutical industry (IPI). The risk values for the prominent risks and overall industry are determined based on the four risk parameters, which would help determine the most contributive risks for mitigation.

An extensive literature survey was done to identify the risks, which were also validated by industry experts. The finalized risks were then evaluated using the fuzzy synthetic evaluation (FSE) method, which is the most suitable approach for the risk assessment with parameters having a set of different risk levels.

The three most contributive sub-risks are counterfeit drugs, demand fluctuations and loss of customers due to partners' poor service performance, while the main risks obtained are demand, financial and logistics. Also, the overall risk value indicates that the industry faces medium to high risk.

The study identifies the critical risks which need to be mitigated for an efficient industry. The industry is most vulnerable to the demand risk category. Therefore, the managers should minimize this risk by mitigating its sub-risks, like demand fluctuations, bullwhip effect, etc. Another critical sub-risk, the counterfeit risk, should be managed by adopting advanced technologies like blockchain, artificial intelligence, etc.

There is insufficient literature focusing on risk quantification. Therefore, this work addresses this gap and obtains the industry's most critical risks. It also discusses suitable mitigation strategies for better industry performance.

The Agri-Food supply chain (AFSC) conventionally suffers from multifaceted transparency, integration, traceability, product quality, and many more. Recently, various digital technologies have emerged, which reflect the potential to address the majority of such concerns. This chapter is an effort toward developing a vision for the future of the agri-food supply chain through digitalization. The technologies prominently covered in the chapter are the internet of things (IoT), blockchain, and artificial intelligence (AI). Different challenges the agri-food supply chain participants perceived in implementing digital technologies were identified through literature review and primary survey. The significant challenges are trained workforce, funds availability, and clarity on economic gains from digitalisation. In conclusion, few strategies toward the implementation of digital technologies in agri-food supply chains are discussed.