Search results

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.

Economic costs and benefits are at the core while taking decision to adopt digitalization in the supply chain. The present chapter provides an in-depth exploration of the economic dimensions of digital supply chain management (DSCM) adoption in a firm. Drawing from a diverse source of literature, this chapter discusses the effect of economic outlook on DSCM adoption, the economic benefits of DSCM adoption and costs associated with it, and economic analysis and evaluation methodologies. The chapter also shares the case studies illustrating the real-world implications of economic considerations within DSCM initiatives. The chapter highlights how changing international socioeconomic and political dynamics can influence businesses across the globe. By analyzing the impacts of evolving market trends, changing consumer preferences, and geopolitical tensions, organizations can considerably forecast the possible impacts of these macroeconomic forces adeptly. The chapter also undertakes discussion on the economic cost and benefits associated with DSCM adoption. The economic analysis helps understand that the expected benefits outweigh economic costs, substantiating the economic viability of DSCM projects. The chapter concludes by discussing the examples of some real-world companies, highlighting how organizations have successfully applied economic analyses to their DSCM initiatives. This also highlights as to how showcasing how detailed economic assessments can justify substantial investments, deliver operational efficiencies, and reshape industries.

Like several of its neighbouring countries, the Kingdom of Saudi Arabia (KSA) has seen a move away from an oil-based economy towards a knowledge-based economy in recent decades. Research productivity in the Kingdom is increasing quickly along with international collaborations. Nonetheless, postgraduate research at universities in KSA is a relatively young domain, which certainly is a core factor in the evolving research management structures in the country.

Going forward, increased openness in research, along with continuing significant investment into higher education and research both by the government and the strong private sector points to a need for refined research governance and policy frameworks with designated expert research management staff developing and facilitating the underlying processes to enable Saudi institutions to engage at the forefront of academic research.

The emergence of Research Management and Administration (RMA) is a result of the pressure on academics to secure research funding from external sources, the increasing competition for these funds, as well as the rising requirements of research funders in terms of reporting and compliance with regulations. This is relevant in the case of the current Horizon Europe Framework Programme for Research and Innovation (HEU) funded by the European Union (EU) which requires important level of professionalisation of the research support staff on behalf of the applicant institutions. Data management, open science, research ethics and integrity, achieving impact beyond academia and the valorisation of project results can be regarded as non-research specific criteria which have to be met by applicant organisations to secure the highly competitive funding. Meeting these non-specific criteria is not always possible in countries whose performance is lagging behind compared to the Western European competitors in EU-funded programmes, such as Hungary.

Our findings reveal two things. First, research support in Hungary is in its early stage of maturity, similary to many countries in Central and Eastern Europe. In several cases, Research Managers and Administrators (RMAs) do not possess the knowledge necessary to meet the non-research specific criteria even if the knowledge is present at the institution or with other colleagues. Second, due to the continuously increasing participation in EU-funded framework programmes (FPs), the state of research support in Hungary is constantly evolving. There is also willingness to learn and improve capacities, which needs strategic planning, studying others’ examples and their adaptability. Such processes can support the capacity building and professionalisation of research offices not only in Hungary, but in countries of the Central and Eastern European region with a similar maturity level of RMA.