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Purpose: The goal of this study is to delve into the causes behind the Fintech sector’s rise in various areas and its prospects. Fintech is rapidly expanding because of government legislation, multiple schemes, consumer expectations, a cashless economy, digitisation, globalisation, innovation, and other drivers.

Need for the Study: Fintech firms are forming alliances with traditional financial organisations to stay afloat and compete. India is becoming a superpower regarding e-startups, especially unicorns. Many startups are undergoing initial public offerings (IPOs). Fintech is an emerging space in India, spreading its wings rapidly in every sector.

Methodology: This work is based on a literature review. It utilises secondary data from numerous research publications, magazines, newspapers, published reports, relevant websites, Forbes magazine articles, stories from The Economic Times, the RBI Portal, and information from StartupIndia, Assocham, and Pwc, among others, to develop a conceptual framework showing the growth drivers of Fintech.

Findings: The whole world has been affected severely due to COVID-19. Crisis always comes with some opportunity, and it is up to us how to turn the calamities into opportunities that further turn into innovation that has the power to lead the world. Fintech is that fruit that had been born normally but grew abnormally (tremendous growth) during the pandemic. Also, the roots are so deeper that they will flourish more and more. It has been found that the emergence of a cashless economy, ease of internet connectivity, etc., are the major factors that paved the way for growth for Fintech in India.

Practical Implications: This study contains the conceptual framework which can guide the stakeholders, policymakers, management teams, field experts, etc., in knowing about their area expertise and looking for improvement, if any.

Originality: There are many papers on the relationship between Fintech and financial inclusion, but this is the first study that builds the conceptual framework for the growth drivers of Fintech.

This chapter provides an overview of the marketing strategy development process in the commercialization of breakthrough technologies. Important concepts and elements that are considered critical when developing market applications are presented with emphasis on three key decisions: target market selection, segmentation, and positioning. These strategic decisions will guide the more tactical considerations relating to the specific elements, or marketing mix, of the product’s marketing strategy. Marketing strategy development is a dynamic process that is impacted by many factors. This chapter highlights the dynamic nature of this process as well as providing insight as to the fundamental considerations in strategy formulation.

This chapter provides an overview of the marketing strategy development process in the commercialization of breakthrough technologies. Important concepts and elements that are considered critical when developing market applications are presented with emphasis on three key decisions: target market selection, segmentation, and positioning. These strategic decisions will guide the more tactical considerations relating to the specific elements, or marketing mix, of the product's marketing strategy. Marketing strategy development is a dynamic process impacted by many factors. This chapter highlights the dynamic nature of this process as well as provides insight into the fundamental considerations in strategy formulation.

This chapter presents an investigation into the theory of labour market segmentation and income inequality in the Ghanaian mining sector. Mining activity especially gold mining has been a significant component of exports as well as employment and income earning in the three major mining regions of Ghana. While income growth is an economic benefit, the high incomes associated with the mining sector may lead to greater income inequality. This chapter provides an analysis of mining activity and income inequality in the Western, Eastern, and Ashanti regions of Ghana. The application of labour market segmentation and the Gini coefficient (a measure of inequality) for personal income are found to be significantly associated with the type and levels of mining employment. However, this observation is not linear as income inequality initially increases with mining activity before decreasing at medium to high levels of mining employment, thus following a Kuznets curve pattern. Segregating datasets for indigenous and expatriate staff reveals very different patterns of income inequality. It poignantly increases with indigenous and/or local community personnel relative to expatriate technical personnel at high levels of mining employment; income inequality is lower among the local community residents relative to nationals from other regions and/or from neighbouring countries. This means segmented labour markets (SLM) within the mining industry are likely to be a problem as they result in increased income inequality among locales relative to foreign expatriates.

The chapter briefly reviews the eight volumes in my Legend series – organizational buying behavior, consumer behavior, product and new product management, marketing strategy, market segmentation, global marketing, marketing research and modeling, and the future of marketing. In addition, the chapter highlights the three driving forces of much of my research: (a) the real world challenges facing corporations and organizations, (b) the search for new methodological developments, and (c) the continuous challenge of the prevailing marketing concepts and approaches. The chapter concludes with some reflections on the evolution of marketing in the past five decades and my wish list for the discipline and my future activities.

One of the most neglected sources of energy loss is streetlights that generate too much light in areas where it is not required. Energy waste has enormous economic and environmental effects. In addition, due to the conventional manual nature of operation, streetlights are frequently seen being turned ‘ON’ during the day and ‘OFF’ in the evening, which is regrettable even in the twenty-first century. These issues require automated streetlight control in order to be resolved. This study aims to develop a novel streetlight controlling method by combining a smart transport monitoring system powered by computer vision technology with a closed circuit television (CCTV) camera that allows the light-emitting diode (LED) streetlight to automatically light up with the appropriate brightness by detecting the presence of pedestrians or vehicles and dimming the streetlight in their absence using semantic image segmentation from the CCTV video streaming. Consequently, our model distinguishes daylight and nighttime, which made it feasible to automate the process of turning the streetlight ‘ON’ and ‘OFF’ to save energy consumption costs. According to the aforementioned approach, geo-location sensor data could be utilised to make more informed streetlight management decisions. To complete the tasks, we consider training the U-net model with ResNet-34 as its backbone. Validity of the models is guaranteed with the use of assessment matrices. The suggested concept is straightforward, economical, energy-efficient, long-lasting and more resilient than conventional alternatives.