PurposeThis 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.Design/methodology/approachA 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.FindingsBased 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.Research limitations/implicationsThe evolution and the current state of the HR analytics literature are presented. Some specific research questions are also provided to help future research.Originality/valueThis 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.
PurposeAn 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.Design/methodology/approachFifty-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.FindingsA 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.Research implications/limitationsAn 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.Originality/valueThis 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.
Purpose 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. Design/methodology/approach 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. Findings 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. Practical implications Managers should strive to balance sustainability reporting to reap its desired benefits on firm performance. Originality/value 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.
PurposeThis study aims to identify the present research trends and streamline future research possibilities in luxury brands by a systematic review of the existing literature.Design/methodology/approachA 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.FindingsA 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.Originality/valueThis 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.
PurposeThe 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.Design/methodology/approachBased 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.FindingsIt 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.Research limitations/implicationsThe 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.Practical implicationsThe 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.Originality/valueThis 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.
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