This study aims to investigate how FinTech evolved over time in research using bibliometric analysis. First, 1359 publications particularly related to the field of FinTech, from 2010 to 2021, were collected from the Scopus database. This study analyzed the fundamental issues and characteristics of FinTech in research, such as the annual contribution of publication, hot in the press, and foci, using theme analysis, concurrence analysis, and timeline analysis of authors’ keywords. Second, prolific objects, such as journals, authors, institutions, countries, regions, and corresponding pivotal cooperative relationship mapping were used to present who leads considerable attention in FinTech research. Third, the citation structures of authors and journals were investigated, and presented the burst detection analysis of cited authors, journals, and references. Finally, combining the analysis results with the current financial environment, the challenges and future development opportunities are discussed further. This bibliometric analysis revealed an increasing annual publication trend, a shifting focus on financial inclusion, a dominance of authors from the USA, and a growing number of international collaborations and publications from different sources, indicating FinTech as a lively field with potential for further scientific enrichment. Accordingly, this comprehensive study of the FinTech documents not only reviews the current research characteristics and trajectories, but also helps scholars find the appropriate research entry-point and conduct in-depth research.

Globally, artificial intelligence (AI) occupies a burgeoning space among recruiters as it replaces many of the recruitment and selection tasks while hiring the talents. Despite the existence and acceptance of AI being unprecedented among savvy recruiters, the study of it in developing countries’ contexts is still at a fancy stage. Particularly, the extant literature documented that very little is known about the intention and actual use (AU) of AI to hire talents with the intervening effects of voluntariness of usage (VU), tenure, and education of the recruiters elsewhere. Hence, using the doctrine of the extended unified theory of acceptance and use of technology (UTAUT), the present study aims to unpack the intention and AU of AI among hiring professionals in the context of Bangladesh, a developing country in the South Asian region. A multi-item questionnaire survey was employed to collect the data of recruiters from talent acquisition departments in both manufacturing and service organizations with a convenience sampling technique. We used partial least square-based structural equation modeling (PLS-SEM) version 4.0.8.9 to analyze the data. Results showed that performance expectancy (PE), facilitating conditions (FC), and hedonic motivation (HM) have a significant influence on the intention to use (IU) AI (p < 0.05), and IU also predicts AU of AI significantly (p < 0.05). The moderating influence of VU has an insignificant effect on the positive influence of IU on AU. Moreover, the multi-group analysis showed that there is no significant difference between young adults and old adults and highly educated and lowly educated on the association between IU and AU. The findings in this study showed important notations that contributed to advancing the knowledge and filling the gap in the extant literature. Additionally, it also provides fresh insights for developing policy interventions to hire professionals for thriving AI adoption in the context of developing countries effectively.

Despite the recent, yet rapid advancements in the scholarly field of Digital Human Resource Management (DHRM), comprehensive studies mapping the field’s evolution and current knowledge breadth remain limited. To address this gap, the present research aims to comprehend the existing theoretical underpinning, interdependencies, models, and evolving concepts through a rigorous review of the existing literature and identify the current state of development and future research directions. Thus, bibliometric information from 532 documents, published between January 1, 1984, and September 6, 2024, was retrieved from the Scopus and Web of Science Databases. These documents were then systematically analyzed using a two-tier method. The bibliometric analysis revealed a robust annual growth rate in DHRM research, with significant contributions from a diverse range of authors and a notable increase in publications post-2015. Authors from developed countries contributed significantly to the field’s development. The content analysis conducted on bibliographic-coupling-based clusters suggests that research in this scholarly area highlights the integration of digital technologies and data-driven strategies in HR processes, emphasizes the strategic use of data analytics in decision-making, and shows the adaptation of HR functions through digital interfaces, along with the alignment of HRM with organizational strategies through comprehensive resource management. From the literature synthesis, this research offers an integrated socio-technical definition of DHRM and a three-layer definition framework (operational, relational, and transformational) that explains how digital technologies reshape HR processes and strategic value creation. However, the study is limited by its selection of keywords that might not capture all relevant DHRM literature, potentially impacting the comprehensiveness and depth of the findings. Regardless, this study complements the existing literature on DHRM by systematically reviewing the area and rigorously implementing the bibliometric and content analysis techniques to comprehensively understand the field. The findings are intended to facilitate future researchers to develop a congenial underpinning of the theories and concepts while harmonizing the development of identified less-developed research clusters.

There is a scarcity of research exploring how the major aspects of Green Human Resource Management (GHRM) influence individual and organizational performance. To fill this gap in the GHRM literature, the researchers undertook a systematic review of 66 articles to examine the ways in which different dimensions of organizational performance are influenced by various facets of GHRM. This systematic review identified prevalent themes in the literature centered on the five key aspects of GHRM: Green Performance Management, Green Compensation and Rewards, Green Recruitment and Selection, and Green Training and Development, and their impact on both sustainable employee and organizational performance. The review further revealed that Green Compensation and Rewards has been the subject of limited investigation, whereas Green Training and Development has received the most attention. Finally, a set of potential future research areas was identified, including various dimensions of organizational and individual performance and their relationship with GHRM practices.

Despite noticeable research interest, the labor-intensive Readymade Garments (RMG) industry has rarely been studied from the perspective of workers’ productivity. Additionally, previous studies already generalized that rewards and organizational commitment lead to employee productivity. However, extant research focused on the RMG industry of Bangladesh, which consists of a different socio-cultural, economic, and political environment, as well as profusion dependency on unskilled labor with an abundance supply of it, hardly considered job satisfaction as a factor that may affect the dynamics of compensations or rewards, commitment, and employee productivity. To address this research gap, this study analyzes the spillover effect of compensation, organizational commitment, and job satisfaction on work productivity in Bangladesh’s readymade garments (RMG) industry. Besides, it delves into the analysis of job satisfaction as a mediator among these relationships. We examined the proposed model by analysing cross-sectional survey data from 475 respondents using the partial least squares-structural equation model in Smart PLS 4.0. The findings show that higher compensation and organizational commitment levels lead to higher levels of job satisfaction, leading to greater productivity. This research also discovered that job satisfaction is a mediator between compensation and productivity and commitment and productivity, respectively. Results further show that increased organizational commitment and competitive wages are the two keyways to boost job satisfaction and productivity in the RMG industry. Relying on the findings, this study outlines pathways for organizational policymakers to improve employee productivity in the labor-intensive industry in developing countries.