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This paper reviews 105 Scopus-indexed articles to identify the degree, scope and purposes of machine learning (ML) adoption in the core functions of human resource management (HRM).

A semi-systematic approach has been used in this review. It allows for a more detailed analysis of the literature which emerges from multiple disciplines and uses different methods and theoretical frameworks. Since ML research comes from multiple disciplines and consists of several methods, a semi-systematic approach to literature review was considered appropriate.

The review suggests that HRM has embraced ML, albeit it is at a nascent stage and is receiving attention largely from technology-oriented researchers. ML applications are strongest in the areas of recruitment and performance management and the use of decision trees and text-mining algorithms for classification dominate all functions of HRM. For complex processes, ML applications are still at an early stage; requiring HR experts and ML specialists to work together.

Given the current focus of organizations on digitalization, this review contributes significantly to the understanding of the current state of ML integration in HRM. Along with increasing efficiency and effectiveness of HRM functions, ML applications improve employees' experience and facilitate performance in the organizations.

The primary purpose of this study is to examine the factors leading to shopping cart abandonment and construct a model depicting interrelationship among them using interpretive structural modeling (ISM) and Matriced Impact Croises Multiplication Appliquee an un Classement (MICMAC).

Initially, 20 factors leading to shopping cart abandonment were extracted through a systematic literature review and expert opinions. Fifteen factors were finalized using the importance index and CIMTC method, for which consistency has been checked in SPSS software through a statistical reliability test. Finally, ISM and MICMAC approach is used to develop a model depicting the contextual relationship among finalized factors of shopping cart abandonment.

The ISM model depicts a technical glitch (SC8), cash on delivery not available (SC4), bad checkout interface (SC9), just browsing (SC11), and lack of physical examination (SC12) are drivers or independent factors. Additionally, four quadrants have been formulated in MICMAC analysis based on their dependency and driving power. This facilitates technical managers of e-commerce companies to focus more on factors leading to shopping cart abandonment according to their dependency and driving power.

Taking an expert’s opinion as a base may affect the results of the study due to biases based on subjectivity.

This study’s outcomes would accommodate practitioners, researchers, and multinational or national companies to indulge in e-commerce to anticipate factors restricting the general public from online shopping.

For the successful running of an e-commerce business and to retain the confidence of e-shoppers, every e-commerce company must make a strategy for controlling factors leading to shopping cart abandonment at the initial stage. So, this paper attempts to highlight the main factors leading to shopping cart abandonment and interrelate them using ISM and MICMAC approaches. It provides a clear path to technical heads, researchers, and consultants for handling these shopping cart abandonment factors.

Utilising componential theory of creativity the study aims to examines the roles of green transformational leadership, organizational culture and green mindfulness as antecedents of green creativity.

A three-wave data collection method was used to collect data from the 304 hotel employees belonging to hotels located in the tourist’s location of India. The study used PROCESS macro to test the hypothesized model.

The results found a significant serial mediating effect of green organizational culture and green mindfulness for strengthening the association between green transformational leadership and green creativity.

The study establishes that a transformational leadership can bring about a much-needed green turnaround and thus makes significant practical contribution. As customers are becoming environmentally conscious, the industry can translate the green practices and motivate their subordinates by exhibiting the environmentally conscious behaviour and exhibit the same in their actions at work.

The current research work expands the body of literature on green transformational leadership and green creativity nexus in tourism and hospitality industry by exploring the boundary condition that increases the strength of this relationship.

Fashion brands are one of the strongest means of expressing consumers identity. This study explores and empirically validates the concepts of brand love and hate for masstige fashion brands from the purview of emerging markets. This study deciphers three components of masstige fashion brand promise through the lens of hedonic identity, uniqueness and expected social gains for the affluent middle-class consumers. The model is complemented by the impact of environmental and society’s well-being.

Empirical evidence was obtained through an online survey in India. Total of 222 complete responses were used to test hypotheses by fitting a model with the partial least squares algorithm.

Fashion brand love is triggered by consumers’ hedonic identity and expected social gains. Brand hate is fuelled by environmental and societal well-being concerns, expected social gains and uniqueness. Theoretical contribution is threefold: First, the relevance of social and environmental consequences reflecting consumers’ accepted responsibility for their masstige consumption is introduced. Second, the study deciphers the emotions related to masstige brand love and brand hate for emerging market’s affluent middle-class. Third, empirical results contribute to the ongoing discussion on whether brand hate and love are two distinct concepts or collapse to be two extremes of one and the same continuum.

Middle-class consumers in India are strict in their avoidance and rejection of the lower classes’ preferred fashion brands. Targeting must consider the social classes hierarchy. Marketing-mix design, particularly prices and distribution networks, need to enable a distinction between the social classes.

Masstige fashion brand love and hate turn out to be two distinct constructs that co-exist rather than being two extremes of one and the same dimension.

Indian middle-class consumers satisfy their need of environmental and social caretaking by avoidance and brand hate but continue to choose masstige brands to demonstrate social status and are not modernizing their traditional accumulative materialism.

The purpose of this paper is to examine the impact of transformational leadership (TL) on building trust and hence, its influence on the commitment level of the employees to achieve the desired work outcomes. It also examined whether transformational leaders were able to psychologically empower employees so as to increase their commitment level and thus reduce the employee turnover intentions (TIs) in the small- and medium-sized (SME) IT companies operating in Delhi NCR, India.

Data were collected from 420 employees (168 females and 252 males) of SME IT companies operational in Delhi NCR, India. They responded to questions about their leader’s TL and their own psychological empowerment (PE), commitment and trust.

The findings of the study show that transformational leaders were able to create a higher level of PE and trust amongst their employees. Further, it was also found that this led to an increase in their commitment level and hence, a decrease in their TI. The findings of the study also suggest that trust, commitment and PE act as mediators.

Limited sample size is a possible limitation of the study. One more limitation of the study is the data collection method, i.e. through survey. It was self-reported, taking only the perspective of the employees; it may not be a completely accurate response.

With TL, leaders can psychologically empower followers to do things in a better way and can develop trust in employees resulting in high commitment; highly committed employees in turn reduce the TIs. If followers do not have faith in their own capability, it may not be possible for them to complete their job effectively.

This study adds to the existing literature; it clarifies the process by which transformational leaders enhance followers’ meaning in life through PE and develop trust resulting in high commitment.

The behavioural decision-making process of individuals highlights the importance of investors’ sentiment and their correlation with the real economy. This paper aims to contribute to the literature of behavioural finance by examining the influence of contextual factors on investment decision-making.

Using a questionnaire, a total of 445 valid responses were collected from March to May 2021 through online sources. The current study uses a technique of Fuzzy-analytical hierarchical process (AHP) to assign relative weights to various contextual factors influencing investment decision-making. Harman’s single factor test was used to check common method bias.

Results of the study reveal that accounting information, self-image/firm-image coincidence, and neutral information as the top-ranked factors in influencing investment decisions, whereas advocate recommendation and personal financial needs emerged as less important factors in influencing investment decisions.

The current study collects data from Indian stock market investors, which may limit the generalization of the study to India only. Moreover, this study is cross-sectional in nature, and there are numerous factors that are not part of the study but might significantly influence the investors’ decision-making process.

The research has implications for both academicians working in the area of behavioural finance and practitioners’ who are active in stock markets, more specifically dealing with retail investors and in the domain of personal finance. Also, the current study will accommodate different groups, i.e. policy makers, financial advisors, investors, investment professionals, etc. in carrying out their professional work.

The current study will provide a comprehensive overview of individual investor behaviour. To the best of the authors’ knowledge, the present study is one of its kind to use the Fuzzy-AHP technique for evaluating the relative ranks of contextual factors influencing investment decision-making.

Grounding on the goal-setting theory and flow theory, this study explored the mechanism underlying the association between transfer design (TD); identical elements and training transfer (TT). Specifically, the authors explored a moderated mediation process of trainer performance and motivation to improve work through learning (MTIWL) that has received less consideration in the TT literature.

Data were collected using the retro-perspective survey method. The first survey was administered offline (t1: the day when leadership intervention was completed. Subsequently, trainees were requested to participate in an online survey (t2: 12–14 weeks later). In all, 355 executives participated.

The results of structural equation modeling (SEM) analyses suggested that trainees’ MTIWL mediational impact between leadership intervention triggers (transfer design and identical elements), and TT was supported. In addition, the indirect impact of these variables on TT was found to be significant when the trainer had high performance than when it was low. This confirmed the trainer’s performance as a potential moderator in the TT process.

This study is limited to the exploration of leadership intervention variables on TT. The findings have implications for leadership professionals and scholars who use leadership intervention and motivation metrics to predict TT.

This study offers a moderated mediation mechanism for enhancing TT through leadership intervention triggers. The proposed conceptual model included MTIWL as mediator and trainer performance during leadership intervention as moderator.

Artificial Intelligence (AI) is one of the newest technology that is quickly advancing and can be utilised to improve human resource competence in the age of rapid digital transformation. The present competitive scenario demands accurate data that need to be collected and analysed for organisational growth.

Purpose: The research examines the applications and usage of AI in performance management and further analyses the future of PM from the perspectives of AI.

Methodology: The study is conceptual and relies on secondary data from research papers, publications, HR blogs, survey reports and other sources. Employee performance and attitudes were monitored using digital technologies, big data analytics and AI. The quality of employee performance continues to increase with the integration of AI, enabling predictive analytics to increase employee performance.

Research Implication: In employee performance appraisal, a digital performance management system leads to openness and honesty with time, effort and sincerity. It is based on the performance management system’s practical usefulness.

Theoretical Implication: The study’s findings provide HR managers, academics, IT professionals and practitioners with an understanding of how AI may be used for performance management and its consequences on their operations. In addition, the connection between the HR devolution theory on performance management and AI is discussed.

Recently, blockchain technology (BT) has resolved healthcare data management challenges. It helps healthcare providers automate medical records and mining to aid in data sharing and making more accurate diagnoses. This paper attempts to identify the critical success factors (CSFs) for successfully implementing BT in healthcare.

The paper is methodologically structured in four phases. The first phase leads to identifying success factors by reviewing the extant literature. In the second phase, expert opinions were solicited to authenticate the critical success factors required to implement BT in the healthcare sector. Decision Making Trial and Evaluation Laboratory (DEMATEL) method was employed to find the cause-and-effect relationship among the third phase’s critical success factors. In phase 4, the authors resort to validating the final results and findings.

Based on the analysis, 21 CSFs were identified and grouped under six dimensions. After applying the DEMATEL technique, nine factors belong to the causal group, and the remaining 12 factors fall under the effect group. The top three influencing factors of blockchain technology implementation in the healthcare ecosystem are data transparency, track and traceability and government support, whereas; implementation cost was the least influential.

This study provides a roadmap and may facilitate healthcare professionals to overcome contemporary challenges with the help of BT.

This study aims to comprehend the ambidexterity and organizational learning capability construct in the Indian E-commerce industry context.

The survey method was adopted for this study. A survey was circulated among the personnel working in E-commerce companies in India. The focus was on people working in managerial positions and had at least three years of experience in the same industry.

This paper investigates the link between two dimensions of ambidexterity, i.e., exploration, exploitation and learning capability in firm performance. The paper also establishes the moderating effect of the learning capability on the two dimensions of ambidexterity and firm’s performance.

Our focus was to cover most of the E-commerce companies, yet to generalize the research the analysis needs to be conducted with even more E-commerce companies. Although we took extraordinary care to gather data from multiple resources and discarded the data that was incomplete or was from lower level employees yet, we need a larger sample to establish the causal claim of our model.

We reason that learning capability of a firm impacts the two dimensions and firms should focus both on external and internal knowledge to benefit from the ambidexterity efforts.

Learning capability influences a firm’s performance and has managerial implications. The analysis’ results on the India based ecommerce companies differs from prior research done in more developed countries and other industries.

No prior research has been done from this perspective in the Indian context, and thus our work opens up new avenues for researchers to look at.Keywords Ambidexterity, Firm performance, Learning capability