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This paper aims to present a hybrid approach to measure the efficiency of virtual contact centers (VCCs) started during the pandemic and benchmark them for service performance. The results are used to plot the VCC's efficiency score (performance) and customer perception (Importance) to propose appropriate strategies.

Using the survey method, 854 responses were collected from customers who used VCC services during the pandemic. This data was then employed to assess the performance of VCCs using SERVPERF and DEA methods, followed by the development of the model for performance analysis.

Results reveal the ranking of different VCCs started during the pandemic for the telecom company using SERVPERF and DEA methods. Further, the performance analysis model highlighted the strategies appropriate for each VCCs.

The findings add to the body of knowledge on how multiple service units of a large organization can assess service efficiency utilizing a combination of SERVPERF-DEA. The present work also contributes to the performance analysis field by proposing a model to assess the service centers and provide improvement guidelines.

The work is one of the first to assess the service efficiency of the VCCs started during the pandemic by using a unique hybrid approach of SERVPERF and DEA. This approach provides a direction to whom to benchmark and to what degree service quality should be improved. Further, the study proposes a unique performance analysis model based on performance scores and customer perception.

This paper aims to identify the current research trends and set the future research agenda in the area of human resource (HR) analytics by an extensive review of the existing literature. The paper aims to capture state of the art and develop an exhaustive understanding of the theoretical foundations, concepts and recent developments in the area.

A portfolio of 125 articles collected from the Scopus database was systematically analyzed using a two-tier method. First, the evolution, current state of the literature and research clusters are identified using bibliometric techniques. Finally, using content analysis, the research clusters are studied to develop the future research agenda.

Based on the bibliometric analysis, network analysis and content analysis techniques, this study provides a comprehensive review of the existing literature. The study also highlights future research themes by identifying knowledge gaps based on content analysis of research clusters.

The evolution and the current state of the HR analytics literature are presented. Some specific research questions are also provided to help future research.

This study enriches the literature of HR analytics by integrating bibliometric analysis and content analysis to develop a more systematic and exhaustive understanding of the research area. The findings of this study may assist fellow researchers in furthering their research in the identified research clusters.

An original systematic review of the academic literature on applications of artificial intelligence (AI) in the human resource management (HRM) domain is carried out to capture the current state-of-the-art and prepare an original research agenda for future studies.

Fifty-nine journal articles are selected based on a holistic search and quality evaluation criteria. By using content analysis and structural concept analysis, this study elucidates the extent and impact of AI application in HRM functions, which is followed by synthesizing a concept map that illustrates how the usage of various AI techniques aids HRM decision-making.

A comprehensive review of the AI-HRM domain’s existing literature is presented. A concept map is synthesized to present a taxonomical overview of the AI applications in HRM.

An original research agenda comprising relevant research questions is put forward to assist further developments in the AI-HRM domain. An indicative preliminary framework to help transition toward ethical AI is also presented.

This study contributes to the literature through a holistic discussion on the current state of the domain, the extent of AI application in HRM, and its current and perceived future impact on HRM functions. A preliminary ethical framework and an extensive future research agenda are developed to open new research avenues.

The main purpose of this study is to explore the presence of the EKC hypothesis in emerging economies. Additionally, the present study also explores the existence of the “resource curse hypothesis” (RCH), and the causal relationship among the variables that are considered for testing the presence of EKC and RCH hypothesis for a panel of selected emerging economies for the time period between 1990 and 2014.

The authors performed unit root test followed by cointegration test to test the existence of cointegrating relationship among the variables. Dynamic ordinary least square (DOLS) and fully modified ordinary least square (FMOLS) methods are used to obtain long-run estimates of considered variables, and the Granger causality test is performed to test the directional causality.

The long-run estimates obtained from DOLS and FMOLS techniques support the presence of the EKC (inverted U-shape) and the RCH.

To the best of the authors’ knowledge, the present work is the pioneer study for EKC and RCH investigation in the context of emerging economies. The policy implication is that these economies should look forward to drafting new policies to reduce environmental degradation and promote sustainable development.

The authors originally explore the factors for blockchain technology (BCT) adoption in agricultural supply chains (ASCs) to enhance circularity and understand the dependencies, hierarchical structure and causalities between these factors.

Based on an extant literature review and expert opinion, the present study identified ten enablers for adopting BCT to leverage the circular economy (CE) practices in the ASCs. Then, using an integrated interpretive structural modeling and decision-making trial and evaluation laboratory (ISM-DEMATEL) approach, hierarchical and cause–effect relationships are established.

It was observed that traceability is the most prominent enabler from the CE perspective in ASCs. However, traceability, being a net effect enabler, will be realized through the achievement of other cause enablers, such as seamless connectivity and information flow and decentralized and distributed ledger technology. The authors also propose a 12 Rs framework for enhancing circularity in ASC operations.

The paper identifies enablers to BCT adoption that will enhance circularity in ASC operations. The ISM hierarchical model is based on the driving and dependence powers of the enablers, and DEMATEL aids in identifying causal relationships among the enablers.

The study's findings and proposed 12 Rs framework may help the practitioners and policymakers devise effective BCT implementation strategies in ASCs, thereby empowering sustainability and circularity.

This study enriches the literature by identifying and modeling enablers for BCT adoption in ASCs. The study also proposes a new 12 Rs framework to help enhance ASC circularity.

This study aims to provide a convincing argument behind the mixed findings on the association between sustainability reporting and firm performance by investigating the possibility of a non-linear relationship through a threshold model.

This study used (Hansen’s 1999) threshold framework to investigate the relationship between firm performance and sustainability reporting using a sample of 210 Bombay Stock Exchange-listed firms spanning over 10 years from March 2010 to March 2019. This framework helps to test the threshold effect’s presence, estimate the threshold value and check the authenticity of the estimated threshold value.

Sustainability reporting has a differential threshold impact on the different indicators of firm performance. On the one hand, the authors’ results illustrate that the firms’ operating performance is positively impacted if and only if the sustainability reporting crosses a certain threshold. On the other hand, sustainability reporting positively impacts firms’ market performance only up to a cut-off point.

Managers should strive to balance sustainability reporting to reap its desired benefits on firm performance.

This study explores the possible non-linearity in the association between firm performance and sustainability reporting and explains the relationship’s inconclusive results. Further, this study explores the field in the novel emerging economy with unique institutional settings that mandate spending on sustainability activities.

This study aims to identify the present research trends and streamline future research possibilities in luxury brands by a systematic review of the existing literature.

A portfolio of 552 articles published between 1996 and 2020 in the luxury brands domain is collected from the Scopus database and analyzed using an integrated approach comprising bibliometric and content analyses.

A comprehensive review of the available literature was done by identifying emerging topics, keywords and research themes. The study's findings indicate that the luxury brand is an exponentially growing theme; seven representative research clusters are identified and analyzed.

This study enriches the literature of luxury brand by presenting a holistic view of the academic literature using an integrated research methodology comprising bibliometric and content analysis techniques.

No fault found (NFF) in maintenance has been a frequently observed problem in industrial sectors, but very few academic contributions are devoted to reviewing and summarizing the related research. Considering the growing interest of academicians in NFF during the last decade, there is a critical need to examine theme evolution in this field, most influential authors, contemporary practices, research gaps and proposed solutions.

A portfolio of 169 articles published between 1982 and 2020 was collected from the Scopus database and was systematically analyzed using a two-tier method. First, the evolution, current state of literature and research clusters are identified using bibliometric techniques. Finally, the research clusters are studied to understand the literature's main themes and develop the future research agenda using content analysis.

The results indicate that publications on NFF are rising quickly in the last decade, especially after 2010. The previous NFF research primarily focuses on system design, fault diagnostics, reliability engineering, data management and human factors, but the criticality of economic and risk analysis has not been significantly represented.

The study resulted in developing an inclusive framework and identifying six research clusters that will help in granular understanding, benefit the researchers, practitioners and policy formulators in NFF.

This study examines the NFF's current research direction and calls for further research in integrating NFF economics on its stakeholders like manufacturers, supply chain, customers and risk analysis during the product life cycle.

While the world grappled with the COVID-19 pandemic and its externalities, scientists have recommended that the global community brace against potential future pandemics. The need to build resilient systems has never been this urgent. The world, especially emerging economies, faces acute food insecurity, high food prices, failing health infrastructure and rampant misinformation spread, among others. Since blockchain technology (BCT) has been discussed in the supply chain resilience context, and it offers the potential to develop resilient systems, we aim to outline the potential of BCT to help build resilience against ongoing and future pandemics. Mainly, we focus on BCT for healthcare management, disruption management of food supply chains, human resource management, modern education and certification and governance and administration.