Department of Commerce

The present study empirically verifies the potential determinants of capital flows into the emerging countries. The study mainly focuses on the role of recently proposed variables viz economic policy uncertainty, geopolitical risk, and environmental performance index. We use balanced panel data for 13 countries spanning from the year 2002 to 2021. The study employs recently developed Machado and Silva (2019) method of moments quantile regression analysis to examine the drivers of capital flows. The study also employs dynamic panel data estimators which contain fully modified ordinary least square (FMOLS), and dynamic ordinary least square (DOLS), models to check the robustness and consistency of the results. The overall results show that lagged FDIt-1, market size (GDPG), trade openness, economic freedom index, GPRC, and EPI have positive and significant effects on FDI inflows in the sample countries. The findings of the study bear significant implications for government, policy makers, and investors in several ways. The market size plays an important role in determining FDI inflows. Policymakers need to mainly focus on economic conditions of the developing countries. The findings also help to formulate the economic and monetary policies that can boost the FDI inflows. Finally, foreign investors (home countries) carefully look at the state-of-affairs of the economic policy uncertainty, geopolitical risk, and environmental sustainability before they park their money in the host countries.

Corporate social responsibility (CSR) has become a significant focus in the corporate world, emphasizing ethical practices and sustainable development. CSR is important because it ensures that businesses act ethically, contribute positively to economic growth, and improve societal well-being, addressing stakeholder interests while fostering trust and reputation. It is imperative in India due to legal mandates under the Companies Act, of 2013, requiring companies to allocate a portion of profits to CSR, thus aligning corporate goals with national priorities like education, healthcare, and sustainability. CSR's role in addressing climate change is crucial, especially in India, a country vulnerable to extreme weather, where companies contribute to reforestation, renewable energy, and community resilience projects, supporting India’s commitments to global climate goals such as the Paris Agreement and net-zero targets. This study explores the interplay between CSR and CFP within BSE 500 companies in India, offering insights into their interconnected impact on business sustainability and profitability. The study analyzed data from the annual reports of 204 Indian firms from 2016 to 2023, yielding a dataset of 1,632 observations. The research design was explanatory, and the results indicate that CSR has no significant impact on CFP. The findings that CSR has no significant impact on CFP suggest several policy implications. Policymakers should focus on creating frameworks that encourage companies to align CSR activities with their core business strategies, ensuring these initiatives are both impactful and economically beneficial. Additionally, there is a need to enhance stakeholder awareness and engagement, so that CSR efforts are more valued in the market. Regulatory bodies might also consider offering incentives for innovative and sustainable CSR projects that demonstrate measurable economic and social benefits. Lastly, fostering transparency and improved reporting standards for CSR activities could help bridge the gap between CSR investments and their perceived financial returns.

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.

In this paper, we examine the influence of ESG disclosure scores on firm performance of companies listed in the National Stock Exchange (NSE). The study uses 167 sample firms from 2010 to 2020. We capitalise overall ESG disclosure scores taken as a proxy to measure the effect of sustainability disclosure on firm performance. Further, we consider the return on assets (ROA), return on equity (ROE), Tobin's Q, and Price Earnings ratio (P/E ratio) as firm performance measures. We employ dynamic panel data regression analysis to examine the influence of ESG disclosures on performance of the firm. In order, to address the endogeneity issues, we apply Generalised Method of Moments (GMM) model. The study results show a positive relationship between ESG disclosure and firm performance. It suggests that companies’ desire to enhance their performance need to pay more attention towards sustainability disclosures.

We verify the effect of ESG disclosures on firm performance using NSE 500 index listed companies spanning from 2010 to 2020. The study employs a method-of-moments quantile regression approach to test whether ESG disclosures lead to superior firm performance. We find evidence that environmental, social, and governance disclosures positively influence firm performance. Higher quantiles of ESG disclosures are associated with better market performance (Tobin's Q), and the same lead to lower profitability (ROA). The present study suggests that companies aspiring to improve their financial performance may pay more attention to ESG disclosure practices.

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.

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.

Purpose: The present study aims to verify whether there is a positive (negative) role being played by the institutional investors on the loss-making companies' performance. Design/methodology/approach: The authors employ panel data regression and two-step system generalised method of moments (SYS-GMM) to test the above objective. Findings: The empirical results clearly show that no positive relation is found between institutional investors and loss-making companies' performance. Research limitations/implications: The findings of the study might have significant implications for firms to improve the firms' operational performance [return on assets (ROA)]. Also, the firm's financial performance [return on equity (ROE)] could be improved by increasing profitability which will reflect in the share prices of the firms whereby the performance can build the investors' confidence over the firm. Market performance (Tobin's Q) could be increased by providing more attractive offers and discounts to customers to capture the business opportunities available in the market. Practical implications: The overall findings might have for reaching implications in the manufacturing sector with regard to allowing (disallowing) institutional investors. Social implications: The results of the study may help both companies and institutional investors. Originality/value: This is the maiden attempt to study whether loss-making companies could be positively (negatively) impacted by the arrival of sophisticated institutional investors [foreign institutional investors (FIIs) and domestic institutional investors (DIIs)]. Further, this study is largely different from previous studies in terms of using new variables which are related to firm characteristics and valuation multiples. Further, seeing if the institutional investors tend to enhance the firm performance is curious.

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.