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One of the most decisive objectives of human resource management (HRM), essential for business performance, is to attract, maintain and engage a qualified workforce. This study aims to identify and prioritize the antecedents of employer branding, which are considered extremely important by potential applicants when they choose to join a particular employer.

The authors have adopted a popular multicriteria decision-making technique fuzzy analytical hierarchy process, to prioritize the identified antecedents. The modified Delphi techniques with the 22 experts have been conducted to validate the identified antecedents. Structured questionnaires were discussed, and their reliability was assessed using the expert’s opinion.

Results of this study indicate that potential applicants consider career advancement opportunities as the most important enabler that persuades them to join a particular employer. Future employees are also motivated to join if they are offered attractive compensation packages, which are distinct from competitors. Furthermore, corporate social responsibility is evolving as an antecedent of employer branding as potential candidates are attracted to employers who are socially responsible.

Employer branding can serve as a strategic HRM technique for any business seeking to attract, recruit, retain and involve outstanding employees, as the success of the organization is determined by how its image is built, communicated and promoted. This study provides insights for HR managers and practitioners who can think of developing an effective employer brand communication that offers a distinct and in-imitable image and reputation as an employer of choice.

This study is unique, as it offers meaningful visions to HR practitioners and experts for designing employer branding strategies for attracting potential applicants to join their organizations.

The purpose of this study is to explore and prioritize the factors that determine the social insurance contribution of unorganized workers.

A two-stage procedure was adopted to recognize and prioritize factors influencing the social insurance participation of unorganized workers: first, crucial factors influencing unorganized workers’ contribution towards social insurance were identified by employing exploratory factor analysis, and in the second phase, the fuzzy analytical hierarchal process was applied to rank the specified criteria and then sub-criteria by assigning weights.

Four broad factors were identified, namely, economic, political, operational and socio-psychological, that significantly influence unorganized workers’ contribution towards social insurance. Later findings revealed that the prime influencer of unorganized workers’ contribution is employment contracts followed by average earnings, delivery of quality services, eligibility and accessibility.

The research findings are feasible as the basic propositions are based on real-world scenario. The identification and ranking of factors have the potential to be used as a checklist for policymakers when designing pension and social insurance for unorganized workers. If it is not possible to consider all, the criteria and sub-criteria assigned upper rank can be given priority to extend pension coverage for a large group of working poor.

The key factors driving social insurance contributions have been highlighted by studying the stakeholders’ perceptions at a micro level. By comprehending the challenges, there is a possibility of covering a large section of the working poor into social insurance coverage.

This paper is believed to be one of its kinds to acknowledge a combination of factors that determine the contribution of unorganized workers to social insurance. This study is an empirical investigation to prioritize the essential drivers of social insurance participation by low-income cohorts in the context of emerging countries. The present approach of employing fuzzy logic has also very limited use in social insurance literature yet.

This paper aims to investigate the relationship between employer branding (EB) and talent retention. The paper also analyses the mediating role of employee engagement in the association between EB and talent retention.

Partial least square structural equation modelling has been applied to carry out the analysis. The findings are based on the perceptions of IT professionals (n = 397) to assess the interrelationship between EB, employee engagement and talent retention.

The paper gives empirical insights on how employee engagement helps promote employer value offerings to the employee, which helps in the successful retention of employees. The results indicate that employee engagement partially mediates the association between EB and talent retention.

This study provides a clear direction to a diversity of practitioners working in IT firms. Building and maintaining sympathetic and emotional connections with co-workers, team leaders and higher managerial employees can help increase employee engagement. The findings can help business planners and managers focus their efforts on employer brand elements for successfully involving their workforce.

Authors believe this study is one of its kind to test the association between EB and talent retention mediated by the engagement level of employees. The present research study will help future academia delve into how EB can significantly impact the engagement and retention of existing employees.

Sustainability has become the topic of the era, and the world is moving toward a circular economy. As part of it, companies are also integrating sustainability in supply chain management. Therefore, this study conducts a technology-empowered systematic literature review to examine the state of the literature on the technologies in the sustainable supply chain. The review reveals that limited studies have been conducted in the area. There is still scope for the researchers to explore new innovative technologies, many clusters in author collaboration, and involve more sectors in the study. Future studies can enrich the field by employing other methodologies like meta-analysis review.