Search results

This paper aims to investigate technological innovations within the crypto space that have engendered novel financial crime risks and their potential utilization amidst geopolitical conflicts.

The theoretical paper uses an analysis of recent geopolitical events, with a key focus on using cryptocurrencies to undertake illicit activities.

The study found that cryptocurrencies and the innovations made within the crypto domain are used for both legitimate and illicit purposes, including money laundering, terrorism financing and sanction evasion.

This research contributes to understanding the critical role cryptocurrencies play amidst geopolitical conflicts and emphasizes the need for regulatory considerations to prevent their misuse. To the best of the authors’ knowledge, this paper is the first scholarly contribution that considers the evolving mechanisms afforded by cryptocurrencies amidst geopolitical conflicts in undertaking illicit activities.

In July 2021, the European Commission has proposed a set of conjunct initiatives to reform the antimoney laundering/countering the financing of terrorism (AML/CFT) regulatory regime in Europe with the main aims to (i) harmonize the AML/CFT regulation and (ii) centralize the authority to a higher degree at European Union (EU) level. This paper aims to assess the reform in light of the EU subsidiarity principle.

The paper uses a benchmark approach to compare the proposed EU money laundering reform against Article 5(3) of the Treaty on the Functioning of the European Union.

The paper confirms that more centralized decision-making at EU level in this policy area is justified, mainly because (i) the policy area is not an area where the EU has exclusive competence, (ii) EU centralized action is necessary and (iii) it also adds value, for instance, for level playing field and efficiency considerations as long as local information advantage will not be lost. As such, the subsidiarity principle can be applied and is an adequate tool to legitimize EU centralized action in the field of money laundering combat.

As the EU AML regulatory reform has not yet been sufficiently discussed in light of the subsidiarity principle, the article is of innovative nature.

Integrating artificial intelligence (AI) into various industries, including the financial sector, has transformed them. This paper aims to examine the influence of integrating AI, including machine learning, process automation, predictive analytics and chatbots, on financial institutions and explores its various aspects and areas. The study aims to determine the impact of AI integration on financial services, products and customer experience.

The research study uses quantitative and qualitative methods, as well as secondary data analysis. It investigates four AI subfields: machine learning, process automation, predictive analytics and chatbots.

The research findings indicate that integrating AI, particularly in machine learning and chatbot subfields, holds promise and high strategic potential for financial institutions. These subfields can contribute significantly to enhancing financial services and customer experience. However, the significance of predictive analytics integration and process automation is relatively lower. Although these subfields retain their usefulness, they might necessitate alternative workflows and tools that incorporate human involvement. Overall, AI integration minimizes human interactions and errors in financial institutions.

The research study contributes original insights by exploring the specific subfields of AI within the financial industry and assessing their strategic significance. It provides recommendations for financial institutions to adopt AI integration partially in multiple phases, measure and evaluate the impact of the transformation and structure internal units and expertise to strategize adoption and change.

Business intelligence (BI) systems and tools are deemed to be a transformative source with the potential to contribute to reshaping the way different healthcare organizations’ (HCOs) services are offered and managed. However, this emerging field of research still appears underdeveloped and fragmented. Hence, this paper aims to reconciling, analyzing and synthesizing different strands of managerial-oriented literature on BI in HCOs and to enhance both theoretical and applied future contributions.

A literature-based framework was developed to establish and guide a three-stage state-of-the-art systematic literature review (SLR). The SLR was undertaken adopting a hybrid methodology that combines a bibliometric and a content analysis.

In total, 34 peer-review articles were included. Results revealed significant heterogeneity in theoretical basis and methodological strategies. Nonetheless, the knowledge structure of this research’s stream seems to be primarily composed of five clusters of interconnected topics: (1) decision-making, relevant capabilities and value creation; (2) user satisfaction and quality; (3) process management, organizational change and financial effectiveness; (4) decision-support information, dashboard and key performance indicators; and (5) performance management and organizational effectiveness.

To the authors’ knowledge, this is the first SLR providing a business and management-related state-of-the-art on the topic. Besides, the paper offers an original framework disentangling future research directions from each emerged cluster into issues pertaining to BI implementation, utilization and impact in HCOs. The paper also discusses the need of future contributions to explore possible integrations of BI with emerging data-driven technologies (e.g. artificial intelligence) in HCOs, as the role of BI in addressing sustainability challenges.

With the rapid growth of the domestic lending industry, assessing whether the borrower of each loan is at risk of default is a pressing issue for financial institutions. Although there are some models that can handle such problems well, there are still some shortcomings in some aspects. The purpose of this paper is to improve the accuracy of credit assessment models.

In this paper, three different stages are used to improve the classification performance of LSTM, so that financial institutions can more accurately identify borrowers at risk of default. The first approach is to use the K-Means-SMOTE algorithm to eliminate the imbalance within the class. In the second step, ResNet is used for feature extraction, and then two-layer LSTM is used for learning to strengthen the ability of neural networks to mine and utilize deep information. Finally, the model performance is improved by using the IDWPSO algorithm for optimization when debugging the neural network.

On two unbalanced datasets (category ratios of 700:1 and 3:1 respectively), the multi-stage improved model was compared with ten other models using accuracy, precision, specificity, recall, G-measure, F-measure and the nonparametric Wilcoxon test. It was demonstrated that the multi-stage improved model showed a more significant advantage in evaluating the imbalanced credit dataset.

In this paper, the parameters of the ResNet-LSTM hybrid neural network, which can fully mine and utilize the deep information, are tuned by an innovative intelligent optimization algorithm to strengthen the classification performance of the model.

The main purpose of this paper is to establish the mediating effect of credit counselling in the relationship between access to microcredit and survival of micro small and medium-sized enterprises (MSMEs) in developing countries in sub-Saharan Africa post COVID-19 pandemic with data collected from rural Uganda.

Structural equation modelling (SEM) through SmartPLS 4.0 was used to generate the standardized parameters to test whether credit counselling mediates the relationship between access to microcredit and survival of MSMEs in developing countries in sub-Saharan Africa post COVID-19 pandemic with data collected from rural Uganda.

The SEM bootstrap results revealed that credit counselling enhances access to microcredit by 27% to promote survival of MSMEs in developing countries in sub-Saharan Africa post COVID-19 pandemic with data collected from rural Uganda.

The current study focused only on women MSMEs. Future studies may possibly collect data from all the MSMEs to draw better generalization of the findings within the sector.

The findings can help public finance policy to ensure provision of credit counselling to microentrepreneurs who borrow from different financial institutions to reduce the problem of loan defaults and delinquency rampant in lending. This could be done through conducting routine business education and counselling sessions for microentrepreneurs who often need credit to grow their businesses.

This study is amongst the first few studies to establish the mediating effect of credit counselling in the relationship between access to microcredit and survival of MSMEs in developing countries in sub-Saharan Africa in the aftermath of COVID-19 pandemic with data collected from rural Uganda. There is a dearth in literature and theory on the rehabilitative and preventive role of credit counselling in reducing repayment defaults amongst borrowers within the credit market to spur survival of MSMEs seen as the main enabler of economic growth, especially in developing countries. In fact, credit counselling acts as a safety net by substituting financial literacy and education to solve the rampant problem of overindebtedness amongst borrowers who are debt illiterate within the credit market.

This study aims to investigate the connections between the adoption of technology, user experience (UX), financial transparency and accountability, specifically focusing on the moderating influence of cultural sensitivity in the Jordanian context.

This study gathered data from 272 participants who are working in the operational Islamic banks in Jordan. Partial least squares structural equation modeling (PLS-SEM) is used for the hypotheses testing.

The results indicate that cultural sensitivity plays a significant role in shaping the UX, consequently influencing perceptions of financial transparency and accountability in e-Islamic finance within the metaverse. This study underscores the intricate interplay between technological advancements, adherence to Sharia principles and diverse cultural expectations, forming the crux of the research.

This research brings a novel perspective by examining the complex connections among technology adoption, UX, financial transparency and accountability, specifically within the distinctive context of Jordan. This research study innovates by checking out how social sensitivity moderates these partnerships, specifically in the context of e-Islamic finance in the metaverse. It adds value to the academic area by shedding light on the intricate interaction between technological development, adherence to Sharia concepts and differing cultural expectations. Ultimately, this adds to a much deeper understanding of the multifaceted nature of this domain.

Recognizing women’s potential and directing their talents to realize these potentials can be of great benefit. Accordingly, this paper aims to identify the characteristics of entrepreneurial intelligence in female entrepreneurs, drawing on a national-level study and the international literature on this topic.

The present paper conducted two studies. First, 15 female entrepreneurs in the Guilan province of Iran, who were selected using purposive sampling, were interviewed to identify the characteristics of entrepreneurial intelligence nationally. The data gathered by interviews were analyzed using inductive content analysis. Then, their validity was tested using qualitative validation and analyzed using Shannon entropy. In the second study, the characteristics of female entrepreneurial intelligence were identified through a qualitative metasynthesis. The results of the two studies were compared together.

This categorized entrepreneurial intelligence into six categories, namely, entrepreneurial insights, cognitive intelligence, social intelligence, intuitive intelligence, presumptuous intelligence and provocative intelligence. Ultimately the characteristics of women’s entrepreneurial intelligence in each category were compared according to the national-level study and the international literature.

This study has the potential to discover credible and robust approaches for further examining the contextualization of women’s entrepreneurial intelligence at both national and international levels, thereby advancing new insights. By conceptualizing various dimensions of entrepreneurial intelligence for the first time and exploring how contextual factors differ across nations and internationally for women’s entrepreneurship, this paper challenges the assumption that the characteristics of women’s entrepreneurial intelligence are uniform across the world.

The purpose of this study is to define and investigate the governance requirements of supply chain finance (SCF).

A qualitative analysis of 849 news articles published in UK newspapers (2000–2022) using the Gioia method.

SCF governance relies on developing capacities for reflexive scrutiny at two stages: (1) prior to entering into an SCF relationship and (2) during its operation. Based on the notion of SCF as a complex adaptive system, we theorise SCF governance requirements as a dual-layered semipermeable boundary. The semipermeability of the two layers allows for a dynamic exchange between the SCF system and its environment. The first layer is the capacity to selectively enable or control the entry and access of certain actors and practices into the SCF system. The second layer is a capacity for ongoing scrutiny of the SCF operation and its development. Further, we identify five aspects of governance to be enabled, i.e. enhancing adaptability, building confidence, improving efficiency, advancing technology and promoting transparency; and four aspects to be controlled, i.e. preventing abuse of power, curbing fraud risk, constraining operational risk and restricting risky extensions to SCF practices.

Our dynamic framework can guide supply chain (SC) members in making decisions about whether to participate, or continue to operate, in an SCF relationship. Moreover, the findings have implications for policymakers and authorities who oversee entry/access and the involvement of SCF providers, particularly, fintech firms.

The study contributes to both the SC and governance literature by providing a systematic analysis of what SCF governance has to accomplish. Our novel contribution lies in its analysis of SCF governance based on a complex adaptive system approach, which expands the existing literature where SCF is described in rather static terms. More specifically, it suggests a need for a dynamic duality of SCF governance through the semipermeable boundary that selectively enables and controls certain SCF actors and practices.

This paper reviews recent research on the expected economic effects of developing artificial intelligence (AI) through a survey of the latest publications, in particular papers and reports issued by academics, consulting companies and think tanks.

Our paper represents a point of view on AI and its impact on the global economy. It represents a descriptive analysis of the AI phenomenon.

AI represents a driver of productivity and economic growth. It can increase efficiency and significantly improve the decision-making process by analyzing large amounts of data, yet at the same time it creates equally serious risks of job market polarization, rising inequality, structural unemployment and the emergence of new undesirable industrial structures.

This paper presents itself as a building block for further research by introducing the two main factors in the production function (Cobb-Douglas): labor and capital. Indeed, Zeira (1998) and Aghion, Jones and Jones (2017) suggested that AI can stimulate growth by replacing labor, which is a limited resource, with capital, an unlimited resource, both for the production of goods, services and ideas.

Our study contributes to the previous literature and presents a descriptive analysis of the impact of AI on technological development, economic growth and employment.