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The great recession of 2008–2009 busted the market bubble and highlighted the loopholes in the banking sector related to excessive leverage and inadequate capital. It has led to the increased rigidity of financial regulations, forcing banks to focus more on compliance rather than moving towards innovation. All these factors together led to the emergence of new players in the financial market in the name of financial technology (Fintech) companies. With the help of Fintech, banking operations are now being revolutionised and transformed into techno-friendly systems. They, hence, can promise to act as a game changer for the banking sector as a whole.

This chapter aims to understand different perspectives of Fintech and how it helps the banking sector to improve its operations. This chapter will also offer insight into various types of Fintech instruments used by the banking sector, collaboration between banks and Fintech, and the benefits of its application to the banking sector.

This chapter attempts to lay out a literature review on Fintech. It examines the implications of applying Fintech in the banking sector to revolutionise its traditional banking operations and achieve its pre-established targets. Different techniques banks use to match up with Fintech and adapt it easily in its organisational structure.

This chapter presents a list of challenges linked to the application of financial technology in the banking industry. The chapter will also address the difficulties of using Fintech and ways to deal with them.

“First principles” of international business (IB) thinking should be applied systematically when assessing the functioning of internationally operating firms. The most important first principle is that entrepreneurially oriented firms seek to create, deliver and capture economic value through cross-border linkages. Such linkages invariably require complementary resources from a variety of parties with idiosyncratic vulnerabilities to be meshed. Starting from first principles allows bringing to light evidence-based insight. For instance, most companies are not global and even the world’s largest firms rarely change the location of key strategic functions. International new ventures (INVs), emerging economy multinational enterprises (MNEs) and family firms face unique vulnerabilities but also command resources that can be used to create value across borders. The quest for “optimal” international diversification appears to be a futile academic exercise, and in emerging economies with institutional voids, relational networks – and more broadly, informal institutions – are unlikely to function as scalable substitutes for formal institutions. In global value chains (GVCs), many lead firms and their partners have been able to craft governance mechanisms that reduce bounded rationality and bounded reliability challenges, and it is also critical for them to use governance as a tool to create entrepreneurial space. Finally, many of the world’s largest companies have been on successful trajectories toward reducing their climate change footprint for a few decades. But these firm-specific trajectories are fraught with challenges and cannot just be imposed via unilateral, macro-level targets decided upon by individuals and institutions lacking a clear understanding of innovation and capital expenditure processes in business.

This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.

This chapter provides an in-depth look at how digital supply chain management (DSCM) can revolutionize supply chains in the post-COVID world. The COVID-19 pandemic exposed the vulnerabilities of traditional supply chains, highlighting the need for resilience and adaptability. The chapter begins by examining these COVID-induced disruptions, setting the foundation for the discussion on DSCM. DSCM, leveraging advanced technologies and data insights, offers a solution to these challenges, promoting agility, transparency, and sustainability in supply chain operations. This represents a significant shift from traditional practices, equipping organizations to cope with the dynamic postpandemic environment. Key capabilities of DSCM, such as resilience, integration, agility, and risk management, are discussed, supported by real-world examples from leading companies. These examples showcase the successful implementation of DSCM and its benefits in navigating the complexities of modern supply chains. However, the adoption of DSCM is not without challenges, including cybersecurity risks and integration difficulties. The chapter suggests strategies to overcome these challenges, emphasizing the importance of technology, collaboration, sustainability, and data-driven decision-making. By embracing these strategies, organizations can effectively manage their supply chains in the evolving global market, leveraging DSCM to withstand future uncertainties.

The supply chain is undergoing a significant digital transformation to adapt to the increasingly digitalized and globalized business environment. To remain competitive in this evolving market, businesses must seamlessly integrate digital technologies throughout the supply chain, spanning all stages from procurement to distribution. This chapter delves into models and methodologies critical to digital supply chain (DSC) transformation, with a focus on advanced techniques such as the Internet of Things (IoT), artificial intelligence (AI), blockchain, and data analytics to boost the resilience and agility of supply chain operations. By leveraging practical examples and case studies, the chapter highlights the myriad enhancements digital transformation can introduce across diverse supply chain stages, including sourcing and after-sales service. Additionally, the chapter examines the complexities of cybersecurity, data integrity, and change management within the digital transformation framework, proposing strategies to address these challenges. The insights offered in this chapter will serve as a thorough guide for both practitioners and scholars in the supply chain field, equipping them to adeptly navigate the multifaceted arena of digital transformation.

This final chapter delves into the future of digital supply chain management (DSCM) amid today's dynamic business environment, shaped by technological advancements and factors like automation, artificial intelligence (AI), sustainability, and resilience. It emphasizes the crucial role of digital technologies (DTs) such as AI, the Internet of Things (IoT), Industrial IoT, and the Internet of Everything (IoET), along with blockchain, in revolutionizing supply chain operations. These technologies enable agility, flexibility, efficiency, and responsiveness, crucial for supply chains to proactively adapt to market changes. The chapter explores the trends in DSCs, focusing on real-time data analytics, end-to-end visibility, sustainability, and resilience. It highlights the growing importance of transparency in supply chains, driven by consumer demand for sustainable practices and product origins. DSCM is identified as pivotal for prioritizing sustainability, leading organizations toward green practices. Despite the opportunities in DSCM, challenges like cybersecurity, data management complexities, geopolitical uncertainties, and talent shortages are acknowledged. To overcome these, the chapter stresses strategic foresight in DSCM and the importance of robust process management, risk management, and talent development. The future-readiness of supply chain professionals is discussed, highlighting the need for change management, development of social and deep work skills, collaboration, and ethical practices. The chapter concludes by underscoring the transformative potential of DTs in the digital era, urging organizations to embrace innovation, transparency, and sustainability in their supply chains, recognizing that the future of DSC is an imminent reality.

Purpose: This research discusses the importance of corporate social responsibility (CSR) and its link to a financial performance metric called net interest margin (NIM) in the context of non-banking financial companies (NBFCs). CSR initiatives can lead to long-term sustainability and improved financial performance, attracting investors seeking to align their investments with their values.

Need for the Study: The research composes portfolios based on financial companies’ CSR performance and NIM ratios to help investors understand the difference between CSR and financial performance, making investment decisions based on their portfolio goals and values. Striking a balance between sustainability and the financial performance of financial companies, will help investors find a suitable balance between portfolios for investment purposes.

Methodology: The authors used data from 55 financial companies for daily returns from 2014–2015 to 2021–2022 and used descriptive statistics to measure the performance of portfolios.

Findings: The findings suggest that financial companies in India have improved their CSR scores over time, indicating an increased focus on integrating socially responsible practices into their operations. The data also show that NBFCs are catching up with banks regarding CSR scores, and some NBFC portfolios even outperform banks regarding returns. However, the study also highlights the need for some companies to focus more on CSR and business operations.

Practical Implications: The results serve as a benchmark for financial companies to assess their relative CSR performance, highlighting the need for companies to focus on integrating socially responsible practices into their operations and guiding areas where companies can improve.

A quick search of the headlines of major newspapers reveals a treasure trove of technology procurement gone wrong. While the private sector seems to adopt and implement new technology seamlessly and quickly to deliver for customers, the government struggles to accomplish technology purchases and integrations with the same ease. As governments in the United States are looking to retain their current workforce and attract the next generation of workers, the technological capabilities and ethos of governments will be paramount. With nearly every industry being transformed by technology and Generation T being the first generation to have an ingrained “technology first” mindset, the ability of governments to attract these workers depends, in large part, on the ability to transform their government technology culture, policies, and practices.

In this chapter, the authors examine the administrative branch and observe two key components at the root of most technology failures: poor organizational structure in the bureaucracy and the lack of an empowered Chief Information/Technology Officer. Building upon case studies from Massachusetts and California, this chapter looks at the factors related to failure or success to understand the technology procurement culture. The chapter concludes by presenting four key “best practice” principles of public policy and administration that can be implemented by almost any governmental entity to improve their acquisition and implementation of technology.