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This study aims to conduct a bibliometric analysis of knowledge sharing during COVID-19 and highlight prominent contributors, diverse trends and themes followed with provisions of future research avenues.

The study through scientific procedures and rationales for systematic literature reviews framework analyses 148 peer-reviewed journal publications and conference proceedings indexed in Scopus and WoS databases from 2020 to 2022. It uses general statistics and diverse bibliometric techniques, including co-occurrence analysis for trend and cluster identification in the literature.

The findings reveal an exponential annual growth rate of 150% in the domain, highlighting the global research focus. With regards to domain contribution, the Journal of Knowledge Management and China leads with ten publications in their respective categories. The co-occurrence analysis further highlights four diverse clusters in the domain, which are further discussed in detail. The study highlights significant contributions from developed economies, thus providing scope for future research from developing or transitioning economies in the Middle East, Central Asia or Africa. The study concludes by presenting the elementary role of knowledge sharing in response to external crises.

The interest in the knowledge sharing domain has grown exponentially during the COVID-19 pandemic. This research is the first bibliometric analysis with comprehensive and rigorous analytic techniques to unearth critical developments and insights for a holistic understanding.

The organizational environment can influence how employees experience meaningfulness. This study examines the mediating role of meaningful work between organizational ethical climates and the affective well-being of employees. We also test for the moderating role of self-regulatory traits in this relationship.

Partial least squares – structural equation modelling (PLS-SEM) was employed to test the hypothesized model using responses from 430 working professionals. Recommended robustness checks were conducted before model assessment and hypotheses testing.

The findings suggest that a caring ethical climate is positively related to affective well-being. Meaningful work dimensions, i.e. unity with others, inspiration and balancing tensions partially mediate the relationship between the caring climate and affective well-being. Integrity with self and balancing tensions fully mediate the negative effect of an instrumental climate on affective well-being. Positive mediation of unity with others and negative mediation of reality were observed between a law and code climate and affective well-being. Moderating effects of self- and other-orientation and self-monitoring were also observed.

The study presents significant insights, however, a few limitations must be discussed. The study has relied on cross-sectional data which may be addressed in future studies.

In times when organizations are spending in large amounts in ensuring meaningful work and employee well-being, this study suggests internal mechanisms that can bring positive impact in employees' work life. Leaders should assess how employees perceive the ethical climate of the organization in order to provide better meaningful work opportunities to the workforce.

Having meaningful work and experiencing affective well-being are significant for a collective betterment of society. Meaningful work encourages individuals in identifying how their work if affecting the society. A affectively happy workforce is essential in building a mentally healthy society.

This study contributes to the investigation of organizational factors that help employees find meaning in their work. Based on ethical climate theory, this study highlights how organizations can redesign and modify their ethical climates to provide opportunities for employees to experience meaningful work and improve their affective well-being.

This research focuses on suggesting an optimized model for selecting best employees using advanced multi-criteria decision making method to a supply chain firm, who is planning to start a new cold chain business vertical.

Study has been conducted in a supply chain firm in North India, who wants to expand its business with the help of efficient team members. In total 38 applicants were considered for the study, as selected by the firm after initial screening from pool of talent. AHP-LP and TOPSIS-LP integrated approach were applied separately for evaluation and implementation of personnel selection model. Further, both the approaches were compared to find the best fit and optimized model.

As per the findings, both AHP and TOPSIS can be used to select the best candidate among the alternatives available. TOPSIS was found easier to implement as it involves ranking of applicants with respect to each skills required for respective job profile only once, whereas AHP involves pair-wise comparison among candidates with respect to each skills required for respective job profile and normalization of each comparison, resulting in the formation of number of comparison matrices. However, AHP is more reliable as it considers consistency check for each level of pair-wise comparison. Hence, there is a chance to avoid or revise the human judgment error. Integrated ranking and optimization approach minimizes the cost by suggesting the relevant positions to be filed to make an efficient team.

Group of interviewers are involved in the decision-making process, hence there are chances of biasness in ranking method which can influence the group decision. Research is limited to a particular geography of North India therefore needs to be tested for other regions also in order to generalize. The research will help the third party logistics (3PL) and other related firms in efficient team selection.

The researcher focuses on formalizing a method for potential candidate selection by considering the constraints of the organization. It has been observed that limited researches have been done on the application of AHP-LP or TOPSIS-LP integrated approach for selection process. Hence, this research proposes two integrated ranking-optimization method and suggests the best fit by comparing both the approaches.