Teachers need to replace the traditional approach of the teaching and learning (TL) process by the integration of Information and Communication Technology (ICT)-based education to meet the global requirement. This paper aims to map the role of technology in the teaching and learning and the challenges associated with the technology implementation in the domain of language education. Therefore, the study has conducted a systematic literature review to synthesize the knowledge in this field based on the documents from the Scopus database. Fifty-three documents were finalized for the systematic review based on the SPAR 4 SLR protocol and inclusion and exclusion criteria. The study identified four technological themes such as virtual reality, multimedia and digital tools, online learning, and information and communication technology. This review has implications for the students, teachers, educators, EdTech companies, and regulators.

This paper’s objective is to scientifically identify the present research trends for future research agenda in Human Resource Analytics (HRA) domain by conducting a comprehensive literature study. Our proposed article applied the existing SPAR-4-SLR protocol for the systematic assessment of the HRA literature. Based on search parameters including subject, function, and language, the authors discovered 226 publications from the Scopus database. We performed a systematic literature review by considering the top 60 highly cited publications and identified five key themes such as HR analytics, Training and Development, Performance Management, Big Data, AI and ML, and Human Resource Information System and Organisation Development. This study extends the HRA research by incorporating systematic assessment to build a systematic grasp of the field of study and highlights the emerging relevance of HRA for effective, objective, and transparent Human Resource Development (HRD).

This study investigates the impact of financial and other factors, including profitability, firm value, board size, firm size, and the influence of COVID, on the quality of integrated reporting (IR). The sample comprises 46 listed Indian corporates observed over a three-year period (2019–2021). A scoring system was devised to assess IR quality through content analysis of annual reports. Empirical estimation employed pooled ordinary least square, fixed effect, and random effect models. The findings revealed no significant relationship between profitability, firm value, and IR quality. However, board size, firm size, and the COVID dummy variable exhibited a positive impact on IR quality. Robustness checks provided further support to the panel regression estimates.

Purpose – The objective of this study is to analyse the integration of technology in Human Resources Management (HRM) with a special focus on Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT) and Big Data. Design/methodology/approach – This study aims to contribute to the understanding of these trends by conducting a thorough bibliometric analysis using the Scopus database, encompassing research on HRM and Technology from 1991 to 2022. By employing citation analysis, co-citation analysis and co-word analysis, the study uncovers key patterns and trends in the field. Findings – The findings indicate that AI, Big Data and ML are the focal points of research when exploring the intersection of Technology and HRM. These technologies offer promising prospects for enhancing Human Resource processes, such as Talent Acquisition, Performance Management and Employee Engagement. Research limitations/implications – In our study, we showcase the practical implications that offer guidance for HR researchers and professionals, enabling them to make informed decisions regarding the adoption and implementation of Information Technology. Practical implications – This research can provide valuable insights to HR managers on the use of cutting-edge technology in HRM. It aims to enhance the manager’s awareness of how technology-enabled HRM can improve HR performance. Originality/value – This study adds to the existing body of knowledge on how Modern Technology empowers HRM. It also proposes a conceptual framework for the use of Modern Technology along with Strategic Management and Knowledge Management to improve Human Resource Performance.

The research on integrated reporting (IR) has grown swiftly over the past decade, and specific attention is given to the disclosure quality of IR information across the globe. The objective of this study is to investigate the association between board characteristics and integrated reporting quality. The analysis selected 46 Indian listed companies with 138 firm-year observations over three years. The study found a positive impact of board size, CEO duality, non-executive board members, financial leverage, the COVID-19 crisis and firm size on IR quality. The study found a negative effect of gender diversity, board activity and profitability on IR quality. This study is the first to examine the effect of board features on the implementation and adoption of IR in the Indian context. Moreover, the study offers key insights for researchers, practitioners, accounting bodies, government agencies, investors and policymakers into the use of integrated reporting and sound decision-making.

This research paper addresses the gap in FinTech and banking literature and offers insightful analysis into the area by conducting an extensive bibliometric review of 523 articles published between 1980 and 2022. The review includes a performance analysis that identifies the key authors, documents, journals, nations, and institutions in the area of research. Additionally, a science mapping approach using the VOS viewer software is employed to explore prevalent keywords, keyword clusters, and the most frequently co-cited sources. The results contribute significantly to the academic knowledge by offering insights into the trends within this domain. The study identifies and assesses five major thematic clusters: technology networking, FinTech innovation, FinTech disruption, business model growth, and risk and soundness. Our findings include implications for researchers in the FinTech and Banking sectors and for top-level management within banks. In essence, this research analysis aids as a valuable guide for researchers looking for upcoming opportunities in the ever-evolving area of FinTech and its applications in Banking.

Information is one of the elementary and important tools assessed by the corporate stakeholders for strong decision making. Further, providing accurate, transparent, and concise report is always a challenging task. In this context, this groundwork explores the advancement of integrated reporting (IR) in India. Moreover, the exploration also focuses on the level of disclosure and quality of reporting through individual parameters of IR, i.e., four guiding principles (GP), eight content elements (CE), and six capitals of the IR system. The analysis selected annual reports of 81 Indian companies for 2020 and 2021 and examined 162 integrated annual reports by employing a scoring system for converting qualitative information in the integrated reports to quantitative data. The study constructed the capital disclosure index (CDI) and integrated reporting index (IRI) to measure the overall quality of IR. Wilcoxon signed ranks test, the sign test and paired sample t-test were employed to capture the trend of the IR. This study found that quality of IRI improved in 2021 compared to 2020; however, the individual items did not show much variation. This research has practical implications for the top management, market regulators and policy makers.

Introduction: The application of artificial intelligence (AI) can substantially enhance both short- and long-term decision-making in human resource management (HRM) practices. However, academic research fails to address the dark side of AI in confluence with HRM and primarily paints a bright picture of the advantages of AI. Purpose: The current research emphasises the challenges faced in the HRM domain in applying AI in HRM practices and further discusses the future path to maximise the effect of AI on HRM. Methodology: The study rigorously surveyed secondary sources like the journal papers, consultant reports and other databases to critically examine the challenges encountered in applying AI in HRM practices. Findings: Analysis of the above-mentioned sources shows that AI algorithm might bring routinisation of work. HRM ethics, data safety and integrity, biased algorithm from the programmer, fewer data to train the AI model, lack of technical skills of HR executive, neglecting values, and ignoring the creative thinking by employees are a few aspects that might cause difficulty in the adaptation of AI in the HRM domain. As a consequence, there could be unnecessary extra monitoring of employee behaviour, which in turn could lead to loss of workplace well-being and trimming of the human element in HRM. Practical Implications: This study adds value by focusing on the challenges and suggests the path for robust HRM practices; because, the biased decision-making by AI could potentially lead to improper decision-making by the top management, and in turn, the sustainability of a firm could be at stake.