Saravanan Vellaiyan’s research while affiliated with Christ University and other places

This chapter investigates the influence of flexible working schedules affect the productivity and skill development of polyvalent workers. A thorough literature analysis guided the creation of a questionnaire that was given to 153 polyvalent workers as a sample. The gathered data was subjected to statistical analysis in order to determine how flexible work schedules affected worker productivity and skill development. The results show a strong correlation between flexible work schedules and increased productivity and skill development among employees. Furthermore, it was discovered that these results were significantly impacted by flexible working hours. Flexible schedules can help multitasking employees, who are skilled in a range of jobs, improve their productivity and further develop their skills. Companies that use polyvalent labour are encouraged to think about adopting flexible work schedules as a way to improve worker productivity and abilities.

The aim of this chapter is to investigate the influence of gender diversity and leadership style on team performance and innovation of potential teams in the information technology sector. A questionnaire was developed, and a sample of 403 responses were collected from the employees. The analysis of the collected data was done using statistical tests of correlation and logistical regression, in order to understand the relationship and impact of gender diversity and leadership style on team performance and innovation potential of teams. The following findings emerged from the analysis. The findings reveal that there is a positive and significant relationship between gender diversity, leadership style, team performance, and innovation. Also, the result from logistics regression evidence that gender diversity and communication have an impact on team performance, whereas organisational culture and communication have an impact on innovation potential within teams.

The educational system in most countries are moving toward Outcome-Based Education (OBE) which is a student-centric teaching and learning methodology. The basic idea behind the adoption of OBE model is that the graduates should possess a sound knowledge in their respective disciplines and also have global mobility and acceptance. The Outcome-Based Education (OBE) should be based on the vision and mission of the institution. The institutions should clearly spell out the learning objectives of the program and course. The Course Outcome (CO), Program Outcome (PO), Program Specific Outcome (PSO) and Program Educational Objectives (PEO) determine clearly what the students are expected to accomplish, post their course or program respectively. This study aims to provide the simplified approach on assessment, evaluation and calculating the attainment levels of students through COs and POs in a management program. To assess the CO attainment for management courses, the authors have identified the subject “Entrepreneurship Development” offered in the first semester from the 2018–2020 batch of 60 students from the MBA program of an autonomous institute. The Course Outcome (CO) and Program Outcome (PO) are mapped with the Continuous Internal Assessments (CIA) and Semester Exam End (SEE) and thus the attainment levels of each CO are measured.

Sustainable finance represents the next biggest transformation in the financial sector to aid the process of sustainable development. Sustainable finance comprises traditional investment which provides financial profits as well as financing the projects or investments that have social, economic and governance impact. The transition from traditional investment to sustainable finance is underway in different markets at different capacities. This study seeks to examine the performance of sustainability indices representing sustainable finance in the Indian and global markets by analysing returns. It was found that sustainable finance gained significant appreciation in the Indian market. In comparing the performance of sustainability indices in developing and developed markets, there was no development divide identified. In this path towards widespread adoption of sustainable finance, data science as a field also provides promising applications for facilitating this transformation.

Implied volatility (IV) is crucial in option pricing models and serves as an essential tool for volatility traders to make informed decisions. However, its effectiveness in predicting realized return volatility is still debated. This study investigates the efficiency of implied volatility in forecasting realized return volatility in the Indian financial markets, specifically using Bank Nifty index options and also assesses the predictive capability of implied volatility against the realised volatility estimator. Utilizing data spanning five years, from January 2018 to December 2022. Finding of this study reveal that implied volatility significantly forecasts realized volatility, highlighting its efficacy as a forecasting tool. Moreover, historical volatility fails to enhance predictive power when combined with implied volatility. Nonetheless, caution should be exercised in generalizing these results to other markets or time periods, as further research is warranted. The study contributes to the ongoing discourse on implied volatility efficiency, offering practical insights for options traders and adding to the body of knowledge in financial economics.

The Indian Foreign Exchange Market has experienced significant changes over the past decade, due to high degree of instability of the Indian Rupee leading to its devaluation against major global currencies. Exchange rate is considered as one of crucial indicators to determine the economic growth. Volatility of exchange rate of each day is influenced by various factors such as demand and supply, Gross Domestic Product, Interest rate, employment rate, public debt, balance of payments, inflation etc. Though there are multiple causes to determine the movement of exchange rate, but still the accurate level of causation is unpredictable. Keeping this in mind, this paper tries to attempt the relationship that exists between the exchange rate and select macroeconomic factors. To analyse the extent of influence of the selected variables on the exchange rate, the research paper uses 10 years of data spanning from Jan 2013 to Nov 2022. Further, the study uses monthly data of above-mentioned variables to bring out the analysis to meet the objectives. Descriptive statistics is used to find the characteristics of the data, correlation analysis and Ordinary Least Square method is used to find the relationship and impact level select macroeconomic factors on exchange rate. Autoregressive Distributed Lag (ARDL) model is used to find if any short run and long run association exists between the variables and the exchange rate.

Success and efficiency of today's business depends on many factors across various industries. Among the many factors, supply chain plays a crucial role. The well-functioning of distribution system may lead to customer satisfaction, cost reduction, risk management, competitive advantage, collaboration and integration, innovation and adoptability and sustainability. Adopting technology in supply chain systems is another way of increasing business growth in the present era. The technologies used in today's business organizations are blockchain, internet of things (IoT), cloud technology, etc. To what extent technology is used to improve supply chain visibility in business is a matter of concern. With this background, the study aims to explore the relationship and impact of different technology on supply chain visibility in fast moving consumer goods sector. To meet the objective of the study, the study chose the top 20 FMCG companies based on highest market share and collected the data from 20 supply chain managers. The variables considered for the study were internet of things (IoT), blockchain, artificial intelligence (AI), radio frequency identification (RFID), cloud technology and information technology. relevant statistical analysis was used to prove the results and it is evident that technology positively correlates with the supply chain visibility. Artificial Intelligence has the most significant impact on the supply chain visibility of a firm. Hence, there is a significant impact of technology on supply chain visibility and the extent impact is high.

The study tries to investigate the long run and short run relationship between trade openness (TO), political stability (PO), and FDI on sustainable development of select developed and developing nations. Time series data from 1995 to 2021 of about 25 economies—10 developed economies and 15 developing economies—was collected and analyzed using Phillips Perron Fisher panel unit root test, panel auto regressive distributed lag (PARDL) model, and panel fully modified least squares/fully modified OLS. From the result, it found that FDI and TO are positively contributing to sustainability development index (SDI) in developing countries rather than the developed countries in the long run. In addition to this, changes in the SDI score is significantly influenced by the present and past import and export activities in developed as well as developing economies in the short run.

India has seen a phenomenal growth in cumulative mutual fund investment from Rs 7.93 trillion in 2012 to Rs 40.38 trillion in 2022, which is more than a five-fold increase since last 10 years. Retail investors are now realizing the power of savings and Systematic Investment Plans (SIP) to build long term wealth. A financial literacy wave which is sweeping across India has projected mutual funds as a significant contributor and beneficiary of this phenomenon. The evolving economic landscape of India provides investors with excellent opportunities to capitalize on these fluctuations through systematic investment in safe investment vehicles like mutual funds. The market associated with mutual funds is always subjected to economic risks. The erratic fluctuations in macroeconomic variables can largely explain the Volatility in Net Asset Value (NAV) of equity oriented mutual fund schemes. With this background, this paper examines the impact of select macroeconomic variables on mutual funds’ performance in India. To analyse this, monthly observations of select macroeconomic variables, average NAV of large cap, mid cap, and small cap funds collected for a period of 10 years starting from January 2013 to November 2022. Descriptive statistics is used to probe the characteristics of the variable. In addition, correlation and ordinary least square method is applied to check the existing relationship and impact level of macroeconomic factors on NAV of select schemes. Lastly, short and long run relationship is analysed using Autoregressive Distributed Lag Model (ARDL).