http://localhost:8080/xmlui/handle/123456789/29 2026-06-13T20:39:32Z 2026-06-13T20:39:32Z Rani, Pooja http://localhost:8080/xmlui/handle/123456789/6099 2026-06-09T10:03:28Z 2025-06-01T00:00:00Z

Trading behaviour of Institutional investor in Indian stock market Rani, Pooja Institutional investors are key players in financial markets, executing large-scale and frequent trades that comprise a major portion of total market activity. Their substantial market presence allows them to have a major impact on stock prices and market indices through their purchasing and selling activity. Foreign institutional investors, by channeling capital into a country’s markets, enhance liquidity, promote financial innovation, and support integration with the global financial system. In contrast, domestic institutional investors act as internal stabilizing forces, with their investment strategies significantly shaping market dynamics and influencing investor confidence. The study seeks to analyze trends of institutional investors in the Indian stock market. It also aims to examine the impact of their trading behaviour on stock indices returns and stock market index volatility. Additionally, the study investigates the relationship between institutional investors’ trading behaviour and stock indices movements, and assesses the influence of macroeconomic variables on the investment behaviour of institutional investors. Financial data for this study are sourced from secondary sources, including Money Control, the National Stock Exchange, the Reserve Bank of India, and the Federal Reserve Economic Data. The compiled data are subsequently analyzed using statistical and econometric techniques to extract meaningful insights. The research design employed in this study is descriptive and analytical. Descriptive research follows comparative and correlational methods to yield useful results, while the analytical design utilizes existing facts and figures to conduct a critical evaluation. The research spans a considerable timeframe, focusing on recent years to ensure relevance and depth. Specifically, it examines the period from 2011 to 2020. The sample includes daily trading data on institutional investors and stock market indicators, along with monthly data on key macroeconomic variables such as interest rates, inflation, exchange rates, and GDP. Empirical analysis demonstrates the statistically significant impact of institutional investors on stock indices returns in the Indian economy. Although their behaviour exhibits predictive power, the historical momentum of the indices remains the primary driver of the fluctuations. The study also indicates that foreign and domestic institutional investors have a significant impact on the stock market index volatility. Foreign investors exert a negative impact while domestic Investors have a positive impact. In the short run, they adopt momentum trading strategies (knee–jerk reaction to market information, buy-low sell-high) and in the long run, follow value trading strategies (investing in stocks trading for less than their book value). The study introduces a novel perspective by examining how macroeconomic variables influence the investment behaviour of institutional investors. For foreign institutional investors, GDP and inflation emerge as the significant determinants, iv indicating a preference for investing in a growing economy and during inflationary periods, possibly due to the inflation-hedging nature of equities. However, the exchange rate does not show a statistically significant effect. In contrast, domestic institutional investors respond differently, with inflation and interest rates exerting a discouraging effect, consistent with risk-averse strategies during periods of economic uncertainty. GDP negatively influences the domestic institutional investor’s indicating intentional portfolio reallocation strategies. The study offers valuable insights for policymakers, investors, start-up companies, and growth-oriented organizations. The findings can also meaningfully contribute to the existing literature and identify the areas that require future research. Agrawal, Rachna and Ahmad Siddiqui,Taufeeque

2025-06-01T00:00:00Z Gupta, Riya http://localhost:8080/xmlui/handle/123456789/6098 2026-06-09T10:02:39Z 2025-04-01T00:00:00Z

Impact of HRM practices on employee engagement and retention A study of knowledge workers in healthcare sector Gupta, Riya The present study is aimed at examining the impact of HRM practices, employee engagement, person-organization (P-O) value fit on employee retention in the healthcare sector. It is an attempt to assess the relationship of key HRM practices namely recruitment and selection, compensation and reward, performance appraisal, training and development, and employee participation on the employee retention. Moreover, the research further investigates the mediating role of employee engagement and P-O value fit in the relationship between HRM practices and employee retention. To fulfill the research objectives based on identified research gaps, primary responses were collected from 311 registered medical allopathic doctors (knowledge workers) working in private hospitals in Delhi and National Capital Region (NCR). Respondents who have atleast completed their graduation in medicine (MBBS) are included for the research. Furthermore, the purposive selection of private hospitals is focused on institutions where HRM practices are systematically implemented, ensuring a relevant and accurate assessment of their impact on engagement and retention. A structured questionnaire has been designed based on the validated scales relevant to the study. The questionnaires were circulated both physically and online (via Google Forms). The primary data collection process is aimed towards obtaining firsthand insights into the influence of HRM practices on employee engagement and retention. The study has employed IBM SPSS Statistics for generating descriptive statistics, normality testing using Kolmogorov-Smirnov and Shapiro-Wilk tests and common method bias using Harman’s Single-Factor test. Additionally, PLS-SEM using Smart PLS 4 is applied to analyze theoretical model and test the hypothesized relationships. The PLS-SEM framework is advantageous for handling complex models with multiple constructs and latent variables. The analysis involved measurement model assessment including reliability testing, convergent validity and discriminant validity followed by formative model assessment. Final structural model is observed where bootstrapping procedure is followed for hypothesis testing. Overall, the bootstrapping results confirmed the robustness of the HRM Practices construct, validating the inclusion of all five first-order constructs in the model. The significant T-values and P-values reinforced that these dimensions meaningfully contribute to HRM Practices, with recruitment & selection and compensation & reward having the strongest influence. The findings of this study emphasize the crucial role of HRM practices in fostering employee engagement and enhancing employee retention in the healthcare sector. Effective recruitment, competitive compensation, structured training, and participatory decision-making significantly contribute to engagement and retention. However, performance appraisal systems require further iv refinement to maximize their impact on engagement. the insignificant impact of performance appraisal on engagement suggests that existing appraisal systems may require reassessment and refinement to better align with employee expectations and organizational goals. Additionally, mediation analysis is conducted to evaluate the mediating role of P-O value fit and engagement in the relationship between HRM practices and employee retention. The statistical significance of the indirect effect, combined with a strong mediation pathway, confirmed that Employee Engagement partially mediated the relationship between HRM Practices and Employee Retention. These findings emphasized the need for the healthcare organizations to not only implement effective HRM practices but also ensure that such practices enhance employee engagement to achieve workforce retention. Similarly, the results confirm that P-O value fit partially mediated the relationship between HRM Practices and employee retention. While HRM practices had a direct positive impact on retention, their effectiveness was further enhanced by ensuring that employees identified with the organization’s values. Finally, the research is concluded with theoretical contributions and practical implications. The theoretical contributions provide a robust conceptual foundation for understanding influence of HRM on healthcare organizations, integrating established theories to explain the dynamics of employee engagement and retention. Meanwhile, the practical implications offer actionable insights that can guide healthcare organizations, HR professionals, and policymakers in implementing HRM practices that enhance employee engagement and long-term retention. By focusing on these aspects, the study not only enriches academic literature but also provides a roadmap for healthcare organizations to optimize their HRM practices, ensuring a more engaged and dedicated knowledge workers. Agarwal, Rachna and Gupta, Arti

2025-04-01T00:00:00Z Mangla, Dolly http://localhost:8080/xmlui/handle/123456789/6096 2026-06-09T10:04:13Z 2026-01-01T00:00:00Z

Customer engagement strategies in health insurance industry Mangla, Dolly Health insurance is still underutilized, despite a rise in public awareness, interest, and consideration after the COVID-19 pandemic. It seems that a wide range of attractive plans are being offered to the general populace by both public and private companies. The reason Health Insurance (HI) companies are not succeeding in achieving the HI penetration has now becomes an area of study. A population’s attitude regarding health insurance may not be fully understood by stakeholders. According to a review of the literature, there are numerous problems with the health insurance market, including lack of trust, out-of-pocket expenses, and lack of knowledge about available facilities. Insurance market players can address these problems through CE in HI sector as CE has become strategic tool for facilitating satisfaction, repurchase intention, loyalty, co-creation, repatronage intention, and consequently firm performance in the service context. (Agyei et al., 2020; Dessart et al., 2015; Harrigan et al., 2017; Hollebeek, 2011a; Islam & Rahman, 2016). CE has been extensively researched across other service sectors such as banking (Islam et al., 2020), telecommunications (Mishra et al., 2020), and hospitality (Durna et al., 2015; Yen et al., 2020); however, its strategic role in the Indian health insurance industry domain remains underexplored. This study aims to fill that research gap by developing and validating a context-specific customer engagement model for the Indian health insurance sector. The research addresses four key objectives: (1) identifying the major issues in the Indian HI industry, (2) assessing the current level of CE, (3) determining the critical factors that influence CE, and (4) proposing an empirically validated CE framework tailored to India’s unique economic landscape. A descriptive and causal approach is adopted. Initially, expert opinions and a literature review informed the identification of CE dimensions. Fuzzy AHP was used to determine the level of customer engagement, while a structured survey of health insurance policyholders helped collect primary data. Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) techniques were employed to test hypotheses and validate the model. The present study seeks to examine, with the help of proposed model, the influence of various strategies (AI chatbots, gamification, innovation, and referral rewards) on CE which in turn leads to repurchase intention. The Stimulus-Organism-Response theory has been adopted as the theoretical background to justify the proposed model of the study. After carrying out an extensive literature review on CE and health insurance sector, this study adopted a quantitative cross-sectional survey design for empirically investigating the model. Two self-administered questionnaire surveys were conducted from experts and customers having health insurance respectively in NCR. Only those customers were taken as respondents who had HI from at least 3 years. A total of 396 valid responses were taken for statistical analysis (PLS-SEM) for the study and to study iv the level of CE, total of 25 responses were taken from HI industry experts for Analytical Hierarchy Process (Multi-Criteria Decision Making) technique. Findings of the study demonstrated that CE has a significant influence on repurchase intentions. Strategies such as digital interactivity (e.g., AI chatbots), referral reward programs, gamification, and service innovation emerged as key enablers of customer engagement. The study emphasizes the need for customized engagement strategies that reflect India’s cultural and demographic nuances. The key contribution of the present study is the formulation of a robust model that explains the CE concept in HI industry and explains that various strategies including AI chatbots, gamification, innovation, and referral rewards drive CE which in turn has a positive influence on repurchase intention. Moreover, the systematic literature review on CE and the various issues in health insurance sector provides insights for researcher regarding future research directions. By offering empirical evidence and managerial recommendations, the study contributes to both the academic literature, and industry practice, helping to solve the various issues in the health insurance industry. Aggrwal, Renu

2026-01-01T00:00:00Z Chopra, Neeraj http://localhost:8080/xmlui/handle/123456789/6080 2026-04-20T09:57:31Z 2025-04-01T00:00:00Z

Service quality Iinvestigation in massive open online courses Chopra, Neeraj Massive Open Online Courses (MOOCs) have become an important extension of formal education, spurred by the Open Educational Resources (OER) movement and supported by leading higher education institutions (HEIs). MOOCs offer lifelong learning opportunities to a wide and diverse audience with an aim at making education more accessible and inclusive. The adoption of MOOCs have significantly increased during the COVID-19 pandemic, as institutions and learners turned to online platforms to continue the learning process. Compared to traditional classroom learning, MOOCs offer notable advantages such as courses are free, flexible, widely accessible and have no strict entry requirements. These benefits have contributed to their growing popularity. However, the proliferation of MOOC platforms, coupled with the ease of switching between providers, has created a highly competitive environment. As learners frequently shift between platforms, providers face mounting pressure to distinguish themselves through enhanced service quality and user experience. Yet, a major concern persists that MOOCs have a consistently low completion rate i.e. below 10%. This high dropout rate not only undermines the value of MOOCs for learners but also leads to lost opportunities and reduced profitability for platform providers. Service quality has emerged as a key differentiator for MOOC platforms, offering a significant competitive advantage in an increasingly saturated market. Despite its importance, research on service quality in the context of MOOCs remains in its early stages. Today’s learners are highly discerning and exhibit low tolerance for subpar service experiences, often leading to high attrition rates. In contrast, delivering high-quality services can play a critical role in enhancing participant retention. Consequently, marketing and platform managers are increasingly focused on improving the quality of services offered through MOOCs. In response to this need, the present study seeks to identify and examine the dimensions that comprehensively capture service quality within the MOOC context. Specifically, the study conceptualizes MOOC service quality as a second-order construct, comprising multiple first-order dimensions that collectively define the overall learner experience. Service quality plays a pivotal role in shaping learner behavior, particularly by influencing engagement, satisfaction, and retention among MOOC participants. This underscores the importance of examining the relationship between service quality and learner retention within the MOOC environment. In response, the present study proposes a theoretical framework that explores the linkage between MOOC Service Quality (MOOCSQ) and MOOC Learner Retention (MLR). Recognizing that this relationship may be complex and not entirely direct, the study also considers the role of intervening and moderating variables in fostering learner retention. Specifically, it investigates MOOC Learner Engagement (MLE) and MOOC Learner Satisfaction iv (MLS) as mediating variables to gain deeper insight into the underlying mechanisms. In addition, the study examines the moderating effect of technostress (stress arising from the use of digital technologies in online learning) on the associations between service quality and learner engagement, satisfaction, and retention. This comprehensive approach aims to provide a nuanced understanding of how service quality influences learner outcomes in the MOOC context. The relationships between the first-order dimensions of MOOC Service Quality (MOOCSQ) and MOOC Learner Retention (MLR) are complex and not easily explained through linear analysis alone. When predictors are highly correlated, relying solely on linear models may fail to capture the true nature of their interactions. To address this limitation, the study employs Artificial Neural Networks (ANN) to uncover non-linear patterns among the first-order independent variables. The primary objective of this research is to identify and validate the key dimensions of MOOCSQ and to conceptualize it as a second-order construct. In addition, the study develops an integrated framework that captures both linear and non-linear relationships between MOOCSQ dimensions and learner retention, offering a more comprehensive understanding of the factors influencing retention in MOOCs. The five key first-order dimensions: Native Language MOOC Content, MOOC Learner Interface, Adaptive Learning Environment, Learner Support and Credit Mobility, and Functional Suitability and Performance Efficiency along with their respective measurement items relevant to the MOOC context, were identified through an extensive review of high-impact, highly cited empirical studies in the domains of both offline and online service quality. To collect primary data, a mixed-mode approach was employed, utilizing both paper-based and online survey methods. A total of 751 responses were gathered from Indian MOOC learners. The dataset was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the influence of MOOC Service Quality (MOOCSQ) on MOOC Learner Retention (MLR). Following this, Artificial Neural Network (ANN) analysis was conducted to detect non-linear patterns among the first-order dimensions of MOOCSQ and MLR. The study yielded three key findings. First, MOOCSQ demonstrated a direct and statistically significant positive effect on MOOC Learner Engagement (MLE), MOOC Learner Satisfaction (MLS), and MOOC Learner Retention (MLR). Second, complementary partial mediation was identified in the relationship between MOOCSQ and MLR via MLE and MLS. Third, technostress was found to negatively moderate the relationships between MOOCSQ and both MLE and MLS. The predictive accuracy and robustness of the model were further validated using the ANN technique. To further enhance the analysis, the study employed the Fuzzy Best Worst Method (FBWM) to rank the first order dimensions of MOOC Service Quality (MOOCSQ). v This research represents a pioneering effort in systematically evaluating service quality dimensions within the MOOC context. By integrating both quantitative and qualitative methodologies, the study presents a comprehensive research framework for assessing MOOCSQ. From an academic perspective, the study contributes to the existing literature by demonstrating how MOOC service quality influences learner retention, particularly through the inclusion of intervening and moderating variables. From a practical standpoint, the findings provide valuable insights for MOOC platform managers, highlighting specific dimensions of service quality that require greater attention in the design and delivery of services. The proposed framework enables providers to gain a competitive edge by focusing on the most influential aspects of service quality. Moreover, it supports the development of targeted strategies aimed at enhancing learner retention, improving market positioning, and increasing overall platform effectiveness. This study also offers a valuable diagnostic tool for assessing the current quality of service offerings, thereby guiding continuous improvement efforts across MOOC platforms. Dr. RAJIV SINDWANI and Dr. MANISHA GOEL

2025-04-01T00:00:00Z