PURUSHARTHA - A journal of Management, Ethics and Spirituality

Leadership in Gen Z: Exploring Constructs, Traits, and Challenges through the Lens of the Indian Knowledge System

Murugan Paramaguru — 2025-06-28

This study explores leadership in Gen Z through the lens of the Indian Knowledge System (IKS), adopting a constructivist approach to leadership theory. As Gen Z enters the workforce with a strong entrepreneurial mindset, this research examines their leadership constructs, core traits, and the challenges they face as both entrepreneurs and professionals. By integrating principles from IKS, the study investigates how indigenous wisdom, philosophical traditions, and historical leadership models influence Gen Z's leadership perspectives. It delves into generational leadership differences, workplace competencies, motivation, and development opportunities while assessing the impact of traditional Indian leadership values on their decision-making and problem-solving abilities. The study aims to provide a comprehensive understanding of how Gen Z’s leadership preferences and competencies shape their professional and entrepreneurial performance within the modern workplace.

Integrating Ancient Indian Wisdom in Modern Business: The Role of Spiritual Leadership, Workplace Spirituality, Ethical Governance, and Corporate Social Responsibility in Organizational Transformation

Satyendra Pratap Singh — 2025-06-28

The growing complexities of organizational sustainability have intensified the demand for leadership models that emphasize values[1]driven decision-making, meaningful purpose, and human-cantered management. Drawing on the profound insights of ancient Indian wisdom, this study explores the influence of spiritual leadership, workplace spirituality, ethical governance, and corporate social responsibility (CSR) on organizational transformation. Adopting a quantitative research methodology, the study employed a structured questionnaire to collect primary data from 407 professionals across Tier-1 cities in India. The instrument incorporated validated scales to measure spiritual leadership, workplace spirituality, inner wisdom, innate human qualities, CSR, and organizational transformation. Correlation and regression analyses were conducted to evaluate the predictive relationships between these constructs in the context of responsible and sustainable business practices. The findings highlight the potential of integrating ancient Indian philosophical perspectives with modern management approaches to strengthen leadership, enhance employee engagement, and promote long-term organizational development. The study offers valuable insights for both practitioners and scholars on fostering trust, commitment, and resilience by aligning leadership practices with enduring ethical and cultural principles.

The Influence of Currency Fluctuations on NSE Market Capitalization: An Econometric Analysis

Suraj Prakash Singh — 2025-06-28

Purpose: This study looks at how currency fluctuations affect the NSE's market capitalization. This study examines historical data from 2013 to 2023 to identify trends, underlying causes, and potential implications for investors and policymakers. The study employs econometric modelling techniques to investigate the relationship between currency exchange rate fluctuations and stock market capitalization.

Design/methodology/approach: To assess the impact of currency fluctuations on the NSE market capitalization, a quantitative research methodology was used, which included regression analysis. The study used secondary data sources such as official financial statements, exchange rate repositories, and stock market indices. The data were statistically analysed using econometric models, ensuring robust and reliable results. The selection of principal explanatory variables was guided by literature and empirical research, ensuring a thorough assessment of currency exchange rate effects.

Findings: The analysis revealed that exchange rate fluctuations had a significant impact on the NSE's market capitalization. There was a strong correlation between the movement of the INR against primary global currencies and changes in the NSE's overall market valuation. The findings show that instances of INR depreciation are frequently associated with increased market volatility and fluctuations in investor sentiment. The study also emphasizes how macroeconomic variables such as inflation, interest rates, and foreign direct investment (FDI) influence the relationship between exchange rate fluctuations and stock market capitalization.

Practical Implications: The study provides valuable insights for investors, policymakers, and financial analysts into the impact of currency fluctuations on stock market trends. The findings emphasize the importance of exchange rate risk management strategies for investors seeking to minimize potential losses. Policymakers may use the findings to develop regulatory frameworks that promote market stability and foreign investment.

Originality/value: This study adds to the current knowledge base by conducting an empirical analysis of the effects of currency exchange rate fluctuations on NSE market capitalization. In contrast to previous studies, which primarily focus on short-term fluctuations, this study takes a decade-long perspective. The findings improve understanding of market dynamics, allowing stakeholders to make informed investment and policy decisions.

Investigating Determinants of Customers’ Channel Switching Intentions: An Integrated Structural Model Approach

Anuradha Yadav — 2025-06-28

The purpose of this study is to explore at how consumers switch from traditional shopping to online shopping and vice versa in the apparel industry. It begins by identifying the factors driving consumer buying behaviour, then identifies the influencing variables that effect shopping behaviour individually (traditional and online shopping behaviour) and then identifies the factors responsible for switching behaviour across modes. The study also looked at the socio-demographic characteristics that influence conventional and internet purchasing habits. The statistics came from a study of 520 online buyers in three Indian metropolises (Delhi, NCR, Mumbai, and Bangalore). All constructs were evaluated using a modified version of well-known scales, and data was analysed using AMOS through CFA (Confirmatory Factor Analysis), Path Analysis, and MGA (Multi Group Analysis) of SEM (Structural Equation Modelling), and Stepwise Regression from Linear Regression. Our findings contribute to the body of research on consumers' switching intentions for traditional and online services, which has been consolidated and formalized into a complete model of factors influencing customers' switching behaviour (Gupta & Sahu, 2015). The study will assist marketers in learning about the elements and aspects that are more essential in customers' switching behaviour.

Corporate Divestitures around Mergers and Acquisitions: A Bibliometric Study

Aditya Pratap Singh — 2025-06-28

Even though studies have found that divestitures around Mergers and Acquisitions (M&A) are a common occurrence (13%-45% across studies), this topic hasn’t been studied enough. This bibliometric study reviews the research themes and publication pattern of papers on divestitures around M&A. An initial extract of 537 research papers listed on SCOPUS till 2023 on relevant keywords was identified of which 170 papers were shortlisted to identify research work which was contributing to the research area in a meaningful way. This study identifies top contributors to the area across authors, journals and countries. Several key research sub-themes emerged. While there are papers focusing on divestitures as an indicator of failure of prior M&A, a different group of papers have studied divestitures in more positive light such as it being a tool to improve performance. One of the most important themes is to identify reasons and estimate likelihood of divestiture of previously acquired units.

Machine Learning Models for Software Defect Detection: A Strategic Management Approach

Sripriya Roy Chowdhuri — 2025-06-28

Businesses are at serious risk from software flaws, which can affect consumer trust, security, and operational effectiveness. Proactive quality assurance is made possible by machine learning's (ML) creative approaches to software defect detection and prediction. From the standpoint of strategic management, companies can manage the allocation of resources efficiently, increase decision-making, and improve overall software quality by incorporating machine learning (ML) models into defect detection procedures. This study examines the business ramifications of AI-driven quality assurance as well as the different machine learning models used for software defect identification and their incorporation into IT management plans. The paper emphasizes ML's significance in long-term strategic planning and operational efficiency along with highlighting the difficulties, advantages, and potential future directions of using it for defect management in organizational settings.