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This chapter proposes a model for discovering suspicious financial operations such as money laundering. To achieve this, the authors reviewed research papers on money laundering and financial institutions’ cases and problems, especially those related to financial transfers. They also collected primary data through face-to-face semi-structured interviews with financial companies’ owners and experts in financial transfers to identify hypotheses that help discover suspicious transfers. The chapter discusses the six big data analysis cycle phases from problem discovery to model deployment to identify suspicious transfers. The chapter uses hypothetical data and models to discuss the results and focuses on exchange companies willing to analyze financial operations. The chapter proposes tools that exchange companies can use to monitor and prevent suspicious transfers including data visualization and machine learning algorithms.

This chapter focuses on a case study of Kareem Exchange Company and its use of big data analysis to detect and prevent fraud and suspicious financial transactions. The chapter describes the various phases of the big data analysis cycle, including discovery, data preparation, model planning, model building, operationalization, and communicating results, and how the Kareem Exchange Company team implemented each phase. This chapter emphasizes the importance of identifying the business problem, understanding the resources and stakeholders involved, and developing an initial hypothesis to guide the analysis. The case study results demonstrate the potential of big data analysis to improve fraud detection capabilities in financial institutions, leading to informed decision making and action.

The incidence of the COVID-19 pandemic has come as a big blow to every dimension of any economy. It disrupts the usual constructs and functioning of economies across the globe. Different macroeconomic variables such as income, employment, etc. have been in shambles because of the unprecedented pandemic. Such a situation needs an alternative thought to turn around everything, and circular economic approach indeed is a potent tool to weather this tumultuous situation. Circular economic framework facilitates recycling and reusing of wastes discarded. Because of various activities, wastes are generated, and if products could be generated out of wastes through a system, it would be beneficial to economies as this ensures the judicious utilisation of resources. Recycling, refurbishing and reducing are three important pillars of the circular economic framework, where product lifecycle gets extended and prudent use of existing resources can be possible. The usage of resources even out of wastes stands out to be a game changer in terms of sustainability of environment. The alternative usage of resources in this way creates alternative employment opportunities. The extension of product lifecycle through recycling and reusing creates alternative rooms for employment, giving ample opportunities for sustainable development. It leads to market creation for waste products. Such a circular economy approach, paving the way for alternative employment generation, leads to sustainable development. The present work tries to re-examine the efficacy of the circular economic framework and its resilience in the context of the unprecedented pandemic in terms of providing alternative employment opportunities. It attempts to underscore how circular economic construct positively impacts prudent use of resources through alternative employment generation in pandemic.

It is essential for developed nations to have adequate and functional infrastructure to sustain economic growth and well-being. Despite efforts to reduce the chances of infrastructure problems, several scholars have expressed concern about infrastructure standards deteriorating at an alarming rate and the need to ensure their sustainability. To achieve sustainable infrastructure development (SID), Sahely et al. (2005) proposed an uncomplicated strategy based on fundamental cooperation between infrastructure and ecological, economic, and social frameworks. Sustainable infrastructure is defined as the development and dependable management of a safe built environment based on efficient resource utilization and environmental standards. SID aims to mitigate or eliminate ecological problems and challenges while maximizing the potential social and economic benefits. United Nations Economic and Social Commission for Asia and the Pacific (UN-ESCAP, 2007) defines SID as infrastructure compatible with continued financial and environmental sustainability. Sustainable road development infrastructure (SRID) is a procedure for constructing infrastructure that incorporates all the essential sustainable development (SD) parameters and is complicated by the interdependence of multiple factors. Stakeholders are essential for the successful execution of infrastructure projects, and a comprehensive evaluation of stakeholder interests and requirements is necessary to achieve SRID goals while meeting the needs of all parties involved. To achieve SRID, it is necessary to understand the relationship between road infrastructure development (RID) processes and SD standards and to implement criteria and indicators that accurately depict the long-term viability of a development process. Al Sanad (2015) identified several factors that may impede the implementation of SD in the infrastructure sector. Shafii et al. (2006) identified insufficient knowledge of SID, lack of SID training, a perception of SID as expensive, acquisition concerns, administrative issues, expert capacities, and motivational factors for manufacturing local materials as potential obstacles. Serpell (2013) identified four categories of SID challenges, including knowledge, economic and financial, organizational, and go. Darko and Chan (2016) identified the most prevalent barriers as a lack of data, training, research, information, and expertise, high cost, government interest, premium and demand, and the absence of SID standards of practice. Azis et al. (2012) identified improved project efficiency, waste reduction in the construction industry, and energy efficiency as advantages of SID. Ametepey and Aigbavboa (2014) identified energy savings, environmental protection, contribution to a higher standard of living and a healthy work environment, resource preservation for future generations, reduction in lifecycle costs, promotion of sustainable economic development, and stakeholder satisfaction as the top benefits of sustainable construction (SC). Du Plessis (2007) identified technological factors, Al Sanad (2015) identified educational programmes, Serpell et al. (2013) identified transformation, economic, and stakeholder engagement as drivers of SC, and Hankinson and Breytenbach (2012) identified enhanced SC awareness. This chapter reviewed the literature on international infrastructure and sustainability development, discussing factors, and benefits promoting SID.

The main problem addressed by this research is the current debate between the negative and positive effects of industrial clusters. This debate is a result of gaps between theoretical implications and empirical evidence in both the classical agglomeration theory and the agglomeration lifecycle theory. The purpose of this study is to propose a framework for developing an index measuring both organizational cluster involvement and organizational supply chain including the three pillars (economic, social, and environmental). Furthermore, the index acts as a quantitative predictor of the stages of the life cycle of industrial clusters. Adopting a case study methodology, the applicability of the index development framework is demonstrated. First, cross-sectional exploratory interviews are performed to locate items measuring the three pillars of organizational sustainability within Egyptian communication industry. Second, an explanatory, cross-sectional approach is applied gathering data from eight professionals related to involvement and supply chain sustainability of their organizations. Analytical hierarchical process is used for weighting and aggregating individual item metrics into two indicators (Saaty, 1980). Measuring, managing, and controlling capabilities of organization's supply chains outweighs the need to manage risks. The proposed framework aids firms within a cluster in making timely decisions about what needs addressing to improve supply chain sustainability performance. Hence, all environmental, social, and economic capabilities can be effectively monitored and controlled.

This chapter proposes a new architecture to address challenges to security and the privacy in e-healthcare under Industry 5.0. With the growing needs for high-quality medical treatment and the continuously growing costs of treating global medical problems, systems and web-based medical care are regarded as innovative solutions. In particular, the new progress in Internet of Things (IoT) has led to the development of Internet of Medical Things (IoMT). The patient history data is handled and processed remotely in real-time rather than visiting any clinic and then having that data transferred for subsequent use to third parties, such as data that gets saved in the cloud. This patient data faced security threats and it is observed as major limitations of using such systems in Industry 5.0. This chapter analyzes the security and secrecy challenges, together with the necessities, the danger involved and proposed secured blockchain-based framework which is capable of future research scope in Industry 5.0. The study has described an Eye Hospital case study that stores the eye donors’ details. With such critical scenario, this study addresses healthcare scenario with poverty-led agenda and social developmental features.

This chapter tests theoretically and empirically the existence of a stable relationship between energy consumption and CO2 emissions. Based on microeconomics and physics, a model has been specified and applied to annual data for twenty countries, which representing 61 percent of the world’s population in 2018, over the period 1995–2015. The data are from the International Energy Agency (2019) and econometric techniques including panel data and causality tests have been used. The results indicate that there is a causal relationship between energy consumption and CO2 emissions. In general, consumers cannot directly change emissions caused by production processes, but they can act on emissions caused by their own domestic energy consumption. Approximately three quarters of domestic energy consumption is due to heating and domestic hot water consumption. Taking into account the lower emissions and the lower economic cost of the initial investment, four potential energy systems have been selected for use in heating and domestic hot water. Their social returns have been assessed across nine of the twenty countries in the sample over a lifecycle of 25 years from 2018: France, Portugal, Ireland, Spain, Iceland, Germany, United Kingdom, Morocco and the United States. Cost-benefit analysis techniques have been used for this purpose and the results indicate that the use of thermal water, where applicable, is the most socially profitable system among the proposed systems, followed by natural gas. The least socially profitable systems are those using electricity.

A paradigm shift was observed a couple of decades back when the relationship marketing took over the transactional marketing. Concepts such as customer lifetime value came into existence. Customer lifetime value is nothing but the aggregate income which an organisation can expect from a customer as long as the customer remains a client. Customer Relationship Management (CRM) took the centre stage as the organisations are transformed into customer-centric organisations. The implementation of CRM earmarked the collection of customer data that enabled the personalisation of products. Business use cases emerged with differential pricing models and loyalty programs contributing to the profitability of the organisations. The different types of CRM, i.e. Strategic CRM, Operational CRM, Analytical CRM and Collaborative CRM, contributed further to the organisation to generate value for the customers as well as for the organisation. Innovations in the digital technologies supported the business use cases with the help of real-time data. The usage of real-time analytics delivered unmatched customer experience resulting in a higher degree of customer satisfaction and customer retention. Customer retention as we know is directly related to the longevity of an organisation, while customer acquisition is expensive. Researchers in this chapter have attempted to unleash the importance of CRM simultaneously presenting the impact of digital technologies on CRM. Readers could be greatly benefitted from this research as practical use cases are discussed, while academicians can cascade this information further.