Pawan Pant
@cuchd.in
Associate Professor
Chandigarh University
Dr. Pawan Pant is working as an Associate Professor of Management at the University School of Business, Chandigarh University, Mohali, Punjab. He has published two research papers, one in a national and one in an international journal, and two Book Chapters in a Scopus-indexed journal. He has 10 years of teaching experience and worked as an Assistant Manager (Purchase) at Pacific Industries Ltd., Udaipur (Rajasthan) for one year. His area of specialisation is Management Economics. email: pawanpant04@.
EDUCATION
Ph D in Commerce
RESEARCH, TEACHING, or OTHER INTERESTS
Multidisciplinary, Economics, Econometrics and Finance, Business, Management and Accounting, Finance
Scopus Publications
Scopus Publications
Pawan Pant
IGI Global Scientific Publishing
The global transition to sustainable practices requires a fundamental rethink of how societies, economies, and industries operate. Digital transformation with cutting-edge technology—namely, artificial intelligence (AI), the Internet of Things (IoT), blockchain, big data analytics, and cloud computing—herein termed 'digital tools'—is a powerful enabler of this transition. This chapter outlines the interdependence of digital transformation and sustainability, explaining how digital tools can support not only more efficient practices but also transformative shifts in thinking and behaviour across various sectors. Through conceptual analysis and examples from four sectors—energy, manufacturing, agriculture, and urbanisation- we delineate the myriad ways in which digital innovation is fostering a commitment to environmental stewardship, social equity, and continuity of economic activity.
Kaushal Kishore Mishra, Pawan Pant, Azmee Zaheer, and Pushpak Sharma
IGI Global Scientific Publishing
Product design has revolutionised the way businesses integrate innovative and sustainable technologies into product development, bridging the gap between innovation and environmental responsibility. This chapter explores the convergence of advanced technologies, including IoT, AI, and digital twins, with principles of sustainability, such as the circular economy, eco-design, and lifecycle management. It demonstrates how synergies are creating innovative, efficient, and environmentally responsive products, highlighting the need to address material choice, energy use, and waste reduction in material production and usage. Cases and frameworks illustrate best practices that stakeholders can use to apply such systems. Finally, it analyses emergent trends and ethical concerns that highlight implications for policy innovation in the pursuit of a sustainable future.
Azmee Zaheer, Pawan Pant, Kaushal Kishore Mishra, and Pratibha Gupta
IGI Global Scientific Publishing
Neuromarketing explores the use of neuroscientific techniques to study and shape consumer behaviour. Through the analysis of brain activity, eye movements, and other physiological responses, companies can uncover valuable insights into consumer preferences that conventional marketing approaches may overlook. The objective of this research paper is to analyse neuromarketing with the aim of identifying ethical concerns that give rise to criticism in this field and propose strategies to address these concerns. The present study is undertaken in the format of a critical literature review. Following an analysis of the history, nomenclature, methodology, findings, and implications of neuromarketing for consumer research, this paper concludes with an overview of the primary ethical considerations. The study's results suggest that neuromarketing has significant promise for consumer research, as it effectively acquires more precise data and novel insights on human behaviour that were previously unachievable.
Kaushal Kishore Mishra, Pawan Pant, Azmee Zaheer, and Swati Priya
IGI Global Scientific Publishing
The paradigm shift initiated in the mining industry has potential for much broader application. Making supply chains more sustainable, efficient and resilient is now a necessity. This chapter addresses the transformation in the mining supply chains through digitalisation; specifically, through the implementation of emerging technologies. We first define what “emerging technologies” includes including things like Artificial Intelligence (AI), Internet of Things (IoT), blockchain, cloud computing, multimedia tools and much more that can support real-time visibility, predictability and analytics, automated decision making and improved traceability, across all aspects of the mining value chain. The chapter then provides a planning framework for undertaking the digitalisation process to transform supply chains, with important elements such as technology enablers, organisational structure, and other planning aspects, through to investment planning.
Pawan Pant and Diksha Gandhi
IGI Global
This chapter analyzes how businesses can incorporate sustainability into their economic strategy in order to increase profitability and create long-term resilience. It analyses the financial logic behind sustainable business models that can achieve cost efficiency, revenue growth through green innovations, and operational and regulatory risk mitigation. Using this chapter, firms can get tools for setting sustainability-based financial metrics such as carbon ROI and environmental profit and loss accounts. Some of the essential strategies are optimized resource utilization, reduction in waste via principles of the circular economy, and effective use of digital technologies in increasing the efficiency of sustainability measures. It also talks about the regulatory landscape, discussing the economic benefits of proactive compliance and alignment with global standards. New funding sources such as green bonds and impact investing are also explored.
Pawan Pant
IGI Global
Blended learning has emerged as a teaching method in the age of digital transformation, combining digital learning with face-to-face learning. Though screen tools have never been matched for ready access to information, student-centred learning, or developing digital literacy, over-reliance on them can deprive learners of social exposure, critical thinking, or emotional growth. Thus, equilibrium should be kept between hours of screen-gazing and genuine human connections so as to enliven and sustain education. The discussion of the overuse of screens touches on cognitive, social and emotional impacts. It develops practical frameworks to aid teachers in designing and implementing blended learning with balance and technology to enrich, not replace, human contact. Case studies and action recommendations thus highlight how educators may find a balance between the digital and interpersonal elements of education and pave the way toward resilient and adaptive learning ecosystems.
Pawan Pant, Kaushal Kishore Mishra, and Animesh Singh
IGI Global
The chapter focuses on artificial intelligence to support sustainable personal finance and green lifestyles. With rising global awareness of the environmental dimension of sustainability, innovative potential is required to shift financial practices and personal lifestyles onto a more ecosystem-compatible pathway. AI technologies offer significant potential to address these needs through enhanced financial planning tools, green banking initiatives, and innovative consumption applications. The chapter sets the broader context of sustainable personal finance against the need for green lifestyles. The case studies illustrate the practical application of AI in these areas. They demonstrate how AI-driven financial planning tools, green banking applications, and intelligent consumption technologies can create an environment encouraging sustainable behaviours and a low carbon footprint. The chapter also deals with related implementation strategies, which include AI incorporation, user engagement, and supportive policies and regulations.
Pawan Pant
IGI Global
As global trends increasingly favour renewable energy sources, the challenges of stability, reliability, and efficiency in integrating intermittent sources like solar and wind into existing grids become more pronounced. However, AI is a promising solution, offering advanced predictive capabilities, optimisation algorithms, and real-time decision-making support. This chapter will revisit the case study of AI in renewable energy grid management and storage, presenting a structured framework of methodologies, case studies, and comparative analysis. The insights gained from this study will address current challenges and inspire optimism for the future of renewable energy.
Pawan Pant, Azmee Zaheer, Kaushal Kishor Mishra, and Abdullah
IEEE
Kaushal Kishor Mishra, Pawan Pant, Azmee Zaheer, and Abdullah
IEEE
Rinku Raghuvanshi, Pawan Pant, Kaushal Kishor Mishra, Azmee Zaheer, and Abdullah
IEEE
Azmee Zaheer, Kaushal Kishor Mishra, Pawan Pant, Abdullah, and Rinku Raghuvanshi
IEEE
Abhimanyu Sandhu, Akriti Gupta, Ranjeet Verma, Abdullah, and Pawan Pant
IEEE
Pawan Pant, Kaushal Kishore Mishra, Azmee Zaheer, Lucius J. S. Botes, and Wynand C. J. Grobler
Springer Nature Switzerland
Kaushal Kishore Mishra, Pawan Pant, Harvinder Singh, and Sunil Kant Mishra
Emerald Publishing Limited
Pawan Pant
IGI Global
In the context of public administration management within higher education institutions, this chapter explores the crucial elements of capacity building and skills development. It examines how academic and administrative staff members must continually learn and develop their skills to adapt to the ever-changing world of education. This chapter looks at ways to help staff, administrators, and faculty members enhance their skills and capacities by using theoretical frameworks and real-world examples. It also examines how institutional support structures, collaborative efforts, and professional development programs contribute to the creation of a lifelong learning and competency-enhancement culture in higher education. This chapter presents best practices and practical ideas to handle the changing needs and complexity of public administration management in academia via case studies and empirical data.
Pawan Pant
IGI Global
To guarantee the legitimacy and integrity of higher education institutions, ethical norms are essential. With an emphasis on governance, openness, and integrity norms, this chapter delves into the complex aspects of ethical standards in higher education administration. This chapter begins with an overview of the role that ethical standards play in preserving public confidence and institutional reputation. It next explores how governance institutions, such as boards of trustees and governing bodies, contribute to accountability by respecting ethical principles. It looks at ways to promote open communication, financial disclosure, and regulatory compliance as means of promoting transparency in administrative procedures. The chapter also emphasizes administrators' ethical obligations to uphold honesty, abstain from conflicts of interest, and advance justice and fairness in decision-making procedures.
Pawan Pant, Kaushal Kishore Kishore, Swati Priya, Sunil Kant Mishra, and Kavita Dahiya
IGI Global
The incorporation of robo-advisors into wealth management signifies a revolutionary change in the provision of financial services. An outline of the difficulties involved in this integration is given in this abstract. Issues ranging from client trust and the changing role of human advisors to regulatory obstacles and data security concerns are brought to light by the growing prevalence of robo-advisory platforms. This abstract examines the various obstacles that fintech companies and financial institutions must overcome to integrate robo-advisors into wealth management procedures smoothly. It explores the complexities of managing legal frameworks, protecting personal information, and creating an atmosphere that encourages cooperation between technology and human knowledge. The abstract also emphasizes how crucial it is to handle ethical issues and uphold client trust in this ever-changing environment. Industry participants hoping to fully utilize robo-advisors while providing dependable and moral wealth management solutions must comprehend and overcome these obstacles.
Kaushal Kishore Mishra and Pawan Pant
IGI Global
The global shift toward sustainability changes the behaviour of consumers, thus altering investment decisions. Conscious factors involve financial performance and risk management in finance, thereby changing consumers' preferences toward green investments; the subconscious ones have even more motivating effects. This chapter surveys the underlying psychological mechanisms that may explain this: cognitive dissonance, social norms, emotional resonance, and the application of cognitive bias-including the availability heuristic and the halo effect. Unconscious drivers- such as the desire for moral identity, loss aversion, and reciprocity- do not bias green finance appetite among consumers. Furthermore, this literature reveals that cognitive priming effects, green branding and narrative framing would subtly inform decision-making in such cases. Awareness of these factors brings a deeper understanding of why people are so keen on and attracted to green investments.
Pawan Pant and Kaushal Kishore Mishra
IGI Global
This shift in financial decision-making, influenced by behavioural economics and sustainable investment, is a significant and crucial development. Understanding how cognitive biases, social preferences, and psychological factors impact investor behaviour in the context of ESG and impact investments is of utmost importance. This understanding can explain why investments often deviate from sustainability. We can gain insights into these deviations by analyzing present bias, loss aversion, and herd behaviour. The chapter delves into the types of nudges, such as framing effects and default options, that can guide financial decisions towards sustainability. The chapter uses global and local case studies, such as India's emergence in green bonds and ethical funds, to illustrate that behavioural economics not only explains but also drives the trend towards responsible investing. It concludes by offering insights into how policymakers, financial institutions, and corporations can leverage behavioural insights to promote long-term sustainable investments.
Uttam Barua, Pawan Pant, and Md Helal Miah
IEEE
This research purposes to explore and develop advanced metaheuristic methods to optimize machine learning unambiguously in ‘‘Macro-Economic Factors’’ (MEFs) price prediction. The principal goal is to increase the precision and efficacy of machine learning models employed in forecasting MEFs prices. This attempt involves discovering, designing, and implementing advanced metaheuristic algorithms proficient of successfully optimizing machine learning model constraints. The study emphases on enhancing ‘‘Stock Market’’ (SM) forecast precision through five innovative methods: an upgraded metaheuristic algorithm, metaheuristic algorithm-optimized ‘‘Extreme Learning Machine’’ (ELM), ‘‘Intrinsic Time-scale Decomposition’’ (ITD) based optimized ELM, ‘‘Fuzzy Inference System based ELM’’ (ELMFIS), and the addition of MEFs. Anticipated techniques such as ‘‘Sine Cosine Algorithm optimized Fuzzy Symbiotic Organism Search’’ (SCAOFSOS) and ‘‘Particle Swarm Optimization-based Group-oriented Crow Search Algorithm’’ (PGCSA) are showcased as effective tools, with reasonable analysis supporting PGCSA for its preeminence. These metaheuristic practices are further applied to assembly ELM, thereby attractive forecast accurateness. The amalgamation of ITD with ‘‘Cluster-based Modified Crow Search Algorithm’’ (CMCSA) optimized ELM validates superior predictive abilities. The study’s result highlights the substantial impact of MEFs, such as money exchange rates and crude oil prices. As a result, SM dynamics, with SM price forecast notably enhanced by integrating real and forecast MEFs along with conventional stock-index parameters.
Uttam Barua, Pawan Pant, and Md Motahar Hossain
CRC Press
Uttam Barua, Pawan Pant, and Md. Motahar Hossain
IEEE
Economists and policymakers dispute how much monetary policy affects economic growth. India is a fascinating case study due to its complex socio-economic milieu. The study examined how India's monetary policies have affected GDP, inflation, and balance of payments. The study analyzed 2000–2020 data using Ordinary Least Squares. Changes in the money supply caused by monetary policy lower inflation while improving GDP and the balance of payments. The analysis found that monetary policy control of interest rates, currency exchange rates, and liquidity improves investment conditions. The money market also has to meet the increased expertise of market participants by providing a more significant assortment of financial products. The topic is money policy, economic development, transmission, and money flow.
Pushpak Sharma, K. K. Mishra, Swati Priya, and Pawan Pant
IEEE
The present study explores the impact of artificial intelligence (AI) on employment in the context of Keynesian theory of employment. The Keynesian theory suggests that employment is directly related to aggregate demand in the economy and that government intervention can help stabilize employment levels. The emergence of Artificial Intelligence (AI) has the potential to create disruption in the employment patterns that are traditional as the machines are rapidly becoming able to perform the tasks that are done by humans. This paper studies the potential impact of AI on both skilled and unskilled labor markets. The current study argues that while artificial intelligence can enhance the productivity and output, it may also expand the income inequality and lead to job displacement for certain segments of the workforce. The paper also discusses the role of government intervention in response to the potential effects of AI on employment. The paper argues that government policies, such as education and retraining programmes, are necessary to ascertain that the workforce is able to adapt to the changing dynamics of labour market. Therefore, the impact of artificial intelligence (AI) on employment generation is both multi-dimensional and tangled and Keynesian theory provides a useful framework for understanding the impact of AI on employment as well as the role of government intervention in response.