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This chapter explores the role of artificial intelligence (AI), particularly its subfield of machine learning (ML) methods, as a core technology of the fintech revolution in the financial services industry. It simplifies some of the complex concepts related to AI by introducing the main ML paradigms and related techno-methodic aspects. This chapter uses real-world examples to illustrate how next-generation AI powered by ML is transforming the financial services industry. Next, in illustrating the risks associated with AI adoption, this chapter discusses the need for regulation to address the essential facets of AI governance, including transparency, accountability, ethics, and responsible use. Lastly, it looks at emerging regulatory approaches across leading global jurisdictions. The primary goal is to give readers an initial understanding of AI's profound impact on the financial sector.

This research introduces an innovation strategy aimed at bolstering the reliability of a renewable energy resource, which is hybrid energy systems, through the application of a metaheuristic algorithm. The growing need for sustainable energy solutions underscores the importance of integrating various energy sources effectively. Concentrating on the intermittent characteristics of renewable sources, this study seeks to create a highly reliable hybrid energy system by combining photovoltaic (PV) and wind power.

To obtain efficient renewable energy resources, system designers aim to enhance the system’s reliability. Generally, for this purpose, the reliability redundancy allocation problem (RRAP) method is utilized. The authors have also introduced a new methodology, named Reliability Redundancy Allocation Problem with Component Mixing (RRAP-CM), for optimizing systems’ reliability. This method incorporates heterogeneous components to create a nonlinear mixed-integer mathematical model, classified as NP-hard problems. We employ specially crafted metaheuristic algorithms as optimization strategies to address these challenges and boost the overall system performance.

The study introduces six newly designed metaheuristic algorithms. Solve the optimization problem. When comparing results between the traditional RRAP method and the innovative RRAP-CM method, enhanced reliability is achieved through the blending of diverse components. The use of metaheuristic algorithms proves advantageous in identifying optimal configurations, ensuring resource efficiency and maximizing energy output in a hybrid energy system.

The study’s findings have significant social implications because they contribute to the renewable energy field. The proposed methodologies offer a flexible and reliable mechanism for enhancing the efficiency of hybrid energy systems. By addressing the intermittent nature of renewable sources, this research promotes the design of highly reliable sustainable energy solutions, potentially influencing global efforts towards a more environmentally friendly and reliable energy landscape.

The research provides practical insights by delivering a comprehensive analysis of a hybrid energy system incorporating both PV and wind components. Also, the use of metaheuristic algorithms aids in identifying optimal configurations, promoting resource efficiency and maximizing reliability. These practical insights contribute to advancing sustainable energy solutions and designing efficient, reliable hybrid energy systems.

This work is original as it combines the RRAP-CM methodology with six new robust metaheuristics, involving the integration of diverse components to enhance system reliability. The formulation of a nonlinear mixed-integer mathematical model adds complexity, categorizing it as an NP-hard problem. We have developed six new metaheuristic algorithms. Designed specifically for optimization in hybrid energy systems, this further highlights the uniqueness of this approach to research.

The purpose of this study is to investigate the benefits and challenges of implementing circular economy (CE), as well as shed light on the influence of procurement strategy in CE implementation in construction projects.

A qualitative research approach with abductive reasoning was adopted. The empirical data were collected from the construction industry in the United Arab Emirates (UAE).

The results reveal that clients, consultants and contractors have limited awareness, knowledge and motivation to implement CE in construction projects. The absence of incentives to design projects following CE principles, lack of involvement of contractors and suppliers, non-use of materials that use CE principles and current procurement strategies are the main challenges for the implementation of CE in the UAE.

Previous research offers limited knowledge on CE and its implementation in construction projects particularly from a procurement strategy perspective. The findings of the study provide new knowledge of the benefits, challenges and role of procurement strategy for implementing CE. It is suggested that collaborative and partnering-based procurement methods are needed to facilitate the effective implementation of CE.

The purpose of this paper is to examine the impact of affiliate marketing strategies as a tool for increasing customers' engagement and vulnerability over financial services. This is attempted by examining the connection between affiliate marketing factors and customers' brand engagement and vulnerability metrics.

The authors developed a three-staged methodological context, based on the 7 most known centralized payment network (CPN) firms' website analytical data, which begins with linear regression analysis, followed by hybrid modeling (agent-based and dynamic models), so as to simulate brand engagement and vulnerability factors' variation in a 180-day period. The deployed context ends by applying the cognitive modeling method of producing heatmaps and facial analysis of CPN websites to the selected 47 vulnerable website customers, for gathering more insights into their brand engagement.

Throughout the simulation results of the study, it becomes clear that a higher number of backlinks and referral domains tend to increase CPN firms' brand-engaged and vulnerable customers.

From the simulation modeling process, the implication for backlinks and referral domains as factors that enhance website customers' brand engagement and vulnerability has been highlighted. A higher number of brand-engaged website customers could mean that vulnerable categories of customers would be impacted by CPNs' affiliate marketing. Improving those customers' knowledge of the financial services utility is of utmost importance.

The outcomes of the research indicate that online banking service providers can increase their customers' engagement with their brands by adopting affiliate marketing techniques. To avoid the increase in customers' vulnerability, marketers should aim to apply affiliate marketing strategies to domains relevant to the provided financial services.

The paper's outcomes provide a new approach to the literature, where the website customer's brand engagement comes out as a valuable metric for estimating online banking sector customers' vulnerability.

In this paper we ask: “What are the opportunities and challenges that creative methods pose in terms of conducting research processes with indigenous peoples impacted by emergencies and disasters?” To do that, we critically examine the creative and collaborative methodological approaches applied in the research project, Moving with Risk: Forced Displacement and Vulnerability in Colombia. This project sought to understand the trajectories of risk of families who were forcibly displaced as a result of the armed conflict in Colombia and resettled in areas at risk of disaster.

This article is intentionally written from the perspective of the researchers’ positionality. In doing so, we embrace writing that is situated and embodied in the researcher’s experiences and positionalities. This reflexive writing allows us to question the methodological experience of the research project we are analysing and, at the same time, ourselves, “the researchers” be questioned by it.

In this paper, we show how creative methods and participatory research can foster awareness and become the basis for inclusive and reciprocal research processes with indigenous communities in disaster studies. Specifically, we show that the use of creative methods helped us recognise that agency needs to be framed in collective spaces with the indigenous women we were working with and in relation to their livelihoods needs. We argue that finding spaces to conduct collaborative research and recognize agency is inextricably related to how the researchers reflect on their positionality.

This article contributes to critical perspectives in Disaster Studies and to an overall understanding of the role that creative methodologies play in research processes with people affected by disasters. It provides a novel perspective on the opportunities and challenges of applying arts-based methods in disaster risk studies with indigenous communities in Latin America.

This study aims to investigate the relationship between personality traits and innovative behaviour, using a mixed-methods approach to provide deeper insights into these dynamics.

The authors used a mixed-methods approach, integrating fuzzy set qualitative comparative analysis (fsQCA) with traditional multiple linear regression analysis. This study was conducted among 76 university graduates, using the Big Five personality model and the Innovator DNA model to assess innovative behaviour.

The findings reveal significant positive correlations between conscientiousness, extraversion and innovative behaviour. The inclusion of fsQCA allowed for a more nuanced understanding of the complex interactions between personality traits and innovative behaviour, highlighting configurations of traits that traditional methods may overlook.

This study's sample size and focus on university graduates may limit the generalisability of the findings. Future research should explore these relationships in more diverse populations and settings to enhance generalisability.

The insights gained from this study can inform the development of more effective talent management strategies, helping organisations to better align personality traits with roles that demand high innovation. This approach can optimise team composition and improve innovative output.

Understanding the configurations of personality traits that lead to innovative behaviour can help educational institutions and organisations foster environments that support diverse and innovative thinking, ultimately contributing to societal progress.

This research contributes to the literature by demonstrating the efficacy of fsQCA in capturing the complexities of human behaviour, particularly in the context of personality traits influencing innovation. By combining qualitative and quantitative analyses, this study provides a comprehensive perspective that enhances both methodological rigour and the depth of understanding in psychological and innovation studies.

This study aims to introduce a novel machine learning feature vector (MLFV) method to bring machine learning to overcome the time-consuming computational fluid dynamics (CFD) simulations for rapidly predicting turbulent flow characteristics with acceptable accuracy.

In this method, CFD snapshots are encoded in a tensor as the input training data. Then, the MLFV learns the relationship between data with a rod filter, which is named feature vector, to learn features by defining functions on it. To demonstrate the accuracy of the MLFV, this method is used to predict the velocity, temperature and turbulent kinetic energy fields of turbulent flow passing over an innovative nature-inspired Dolphin turbulator based on only ten CFD data.

The results indicate that MLFV and CFD contours alongside scatter plots have a good agreement between predicted and solved data with R² ≃ 1. Also, the error percentage contours and histograms reveal the high precisions of predictions with MAPE = 7.90E-02, 1.45E-02, 7.32E-02 and NRMSE = 1.30E-04, 1.61E-03, 4.54E-05 for prediction velocity, temperature, turbulent kinetic energy fields at Re = 20,000, respectively.

The method can have state-of-the-art applications in a wide range of CFD simulations with the ability to train based on small data, which is practical and logical regarding the number of required tests.

The paper introduces a novel, innovative and super-fast method named MLFV to address the time-consuming challenges associated with the traditional CFD approach to predict the physics of turbulent heat and fluid flow in real time with the superiority of training based on small data with acceptable accuracy.

The purpose of this paper is to examine the effect of the financial structure on innovation.

We utilize the matched firm-level data from two sources: the World Bank Enterprise Survey and the Innovation Follow-Up Survey. A total of 3,664 firms from 11 African countries are included.

The authors find a financially constrained and low technology-intensive firm that uses internal finance more than its peers is less likely to innovate. Our results also show that a firm that uses new equity and debt finance more than its peers is more likely to innovate. The results particularly suggest the significant effect of bank and trade credit finance on firms’ innovation. The extent and, in some cases, the direction of the effect of dependence on internal finance, new equity finance and debt finance on innovation vary due to the heterogeneity in firm size, age and ownership status. Corporate innovation is also associated with firm size, R&D, cooperation, staff training, public support, exportation and group membership.

The management of companies, particularly financially constrained firms, should reduce their dependence on internal finance, which negatively affects their innovation. As a remedy, they could improve their reliance on new equity finance and debt finance, especially bank finance and trade credit finance, which positively affect their innovativeness.

A pending policy task for African business leaders is to design and evaluate reforms that help create strong financial sectors willing to provide capital to a broad range of firms, particularly small and young firms.

This study adds new evidence to the recent surge of debate on the trade-off between going public, using debt or heavily using internal sources to finance innovative projects, and which of these is more important in promoting firm-level innovation.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

In response to water scarcity in Sri Lanka, the government is implementing strategies such as rainwater harvesting, efficient irrigation, wastewater treatment and desalination. Initial efforts include the establishment of a desalination plant in Jaffna, with additional plans for the dry zones (DZ). The study aims to comprehensively identify the barriers to establishing desalination plants in the DZ and provide recommendations to mitigate these barriers. Additionally, this research provides valuable insights aimed at minimizing barriers to the construction of future desalination plants within Sri Lanka.

The study used qualitative methods, using an expert survey to identify current and future barriers, along with strategies for overcoming them. The collected data were analysed using the template analysis technique.

Regarding desalination plant establishment, various barriers such as high capital costs, high energy expenses, brine discharge, pollution, emissions, technical challenges, health concerns and waste disposal have been identified. However, specific strategies exist to address and mitigate each of these obstacles.

The study offers recommendations to environmental experts and government on expediting the approval procedures for desalination plants in Sri Lanka’s DZ. Adapted to Sri Lanka’s specific challenges, it highlights strategies and barriers essential for upcoming desalination projects. Furthermore, it emphasizes the financial advantages such as increased production and job creation resulting from establishing desalination facilities.

Through this study, promoting sustainable practices and fostering community involvement, it aims to enhance livelihoods, accelerate economic development and improve overall well-being through reliable access to water. Additionally, the study aims to enhance understanding of the importance of desalination in alleviating water scarcity, promoting community engagement and ultimately facilitating improved living conditions, health outcomes and economic opportunities in Sri Lanka’s DZs.

This study provides crucial direction for decision-makers by highlighting the main barriers to the establishment of desalination plants in Sri Lanka and outlining practical solutions. Implementing these strategies helps meet the region’s increasing water demands, advance sustainable water management, improve the standard of living for nearby communities and promote the socioeconomic development of desalination plants in Sri Lanka’s DZ.