Technological Risks Research Articles

An Assessment of the Critical Success Factors of Microfinance Institutions (MFIs) in Lusaka, Zambia

This research focuses on the critical success and failure factors of microfinance institutions (MFIs) in Lusaka, Zambia, addressing a vital aspect of the financial landscape that impacts small businesses and low-income individuals. Despite the positive role of MFIs in providing financial assistance to entrepreneurs, recent closures of six institutions in Zambia underscore the need to understand the factors influencing their success or failure. The problem statement highlights the potential consequences of MFI closures, such as negative impacts on women, increased poverty levels, income inequality, child labor, and barriers to sustainable local economic development. Notably, the study aims to fill a research gap by assessing factors affecting MFIs' operations in Zambia, particularly those leading to closures, which the Bank of Zambia has not yet addressed or documented. The research objectives are clear and specific, intending to assess both critical failure factors from MFIs that have closed in Lusaka and critical success factors for the functioning of MFIs in the region. Additionally, the study aims to suggest measures to enhance the application of these critical success factors. Moving into the research methodology, an exploratory research design is chosen, providing a foundation for assessing the critical success factors of MFIs in Zambia. The mixed-method approach, incorporating qualitative and quantitative strategies, enhances the comprehensiveness of the study. The target population comprises 29 registered MFIs in Lusaka, and a one-stage cluster sampling technique is applied to select 10 MFIs with 60 key informants. The use of questionnaires for data collection, both open and closed-ended, facilitates the gathering of both qualitative and quantitative information. Ethical considerations are diligently addressed, ensuring informed consent, confidentiality, justice, anonymity, and protection from harm. In the discussion of findings, a demographic analysis reveals important characteristics of the respondent base, emphasizing the predominantly male representation and the prevalence of tertiary education among participants. Objective one focuses on assessing critical failure factors, with limited access to funding, operational efficiency, and limited financial literacy emerging as primary challenges. Objective two delves into critical success factors, highlighting financial stability, marketing strategies, technology adoption, and outreach to the underserved population as significant considerations. Objective three provides insights into measures employed by MFIs, such as technology integration, capacity building, customer-centric approaches, and risk management systems. The recommendations emphasize diversification of funding sources, tailored financial literacy initiatives, operational efficiency optimization, and enhanced community engagement to address identified challenges. In summary, this study contributes valuable insights into the dynamics of MFIs in Lusaka, offering practical recommendations for their sustained success and impact on local communities.

OPTIMAL CENTRAL BANK DIGITAL CURRENCY DESIGN FOR EMERGING ECONOMIES

The growth of digitalisation presents the possibility for Central Bank Digital Currency (CBDC) to emerge as a secure and efficient payment method. However, despite the benefits, CBDC implementation needs to be adapted to the capabilities and needs of each country. This study uses meta-strength, weakness, opportunity, and threat (meta-SWOT) analysis to assess the internal strengths and weaknesses, as well as the external opportunities and threats, to determine the most optimal CBDC design for emerging economies. In analysing internal aspects, CBDC allows for an efficient payment system, followed by a more effective monetary policy. Furthermore, the technology creates the possibility to boost financial inclusion and trace many illicit activities. However, to achieve that, high investment costs and privacy issues must be accommodated, followed by technological risks such as the digital divide and electrical outages. Turning to external aspects, growing technology, the network effect, enthusiasm for CBDC, and the impracticality of cash usage have become catalysts for CBDC development. Despite these opportunities, central banks should be wary of the threat of cyberattacks, quickening bank disintermediation, legal issues within their respective countries, and competition with private crypto companies. Altogether, the most optimal CBDC design in emerging economies is retail and wholesale coverage, interest-bearing (wholesale) and noninterest-bearing (retail) remuneration, account-based and token-based paymentsystems, a traceable degree of anonymity, hybrid architecture, a Decentralised Ledger Technology (DLT) ledger system, and domestic and cross-border scope. These results are supported by rigorous examination of global CBDC research and development.

Risk Management Strategy on Financial Performance of Micro Finance Institutions in Uganda: A Case of Rushere Savings and Credit Cooperative Organization in Kiruhura District

Microfinance institutions (MFIs) play a crucial role in promoting international and local development goals, especially in the context of poverty reduction, economic empowerment, and financial inclusion. MFIs provide financial services, such as microloans and savings accounts, to low-income individuals and small businesses. These services are intended to help people lift themselves out of poverty by providing access to capital for income generating activities. Many of the United Nations' Sustainable Development Goals, such as no poverty, zero hunger, and gender equality, can be furthered through the work of MFIs. However, it's essential to note that the impact of MFIs varies depending on the specific institution, its approach, and the regulatory environment in which it operates. While microfinance has the potential to be a powerful tool for development, it is not a panacea and must be implemented effectively to achieve the desired outcomes. Consequently, MFIs face various risks in their operations, which impact their financial stability and ability to achieve their social and economic development goals. To manage these risks effectively, MFIs need to implement robust risk management strategies. The specific objective of carrying out this study was to examine the extent to which risk management influences the financial performance of Rushere Savings and Credit Cooperative Organization in Kiruhura Uganda. The research questions focused on risk assessment, diversification of portfolio, credit risk management, member education, technology risk management, and insurance risk coverage. This study was based on a quantitative research approach. The study was underpinned by the modern portfolio theory. A descriptive research design was used to obtain the responses that were later statistically described in quantified formats. The study considered a target population of 160 people from which a sample size of 127 respondents was selected for this study. Both Stratified proportionate sampling and simple random sampling techniques were used to select individual respondents in their strata. Structured self-administered questionnaires were used for primary data collection. Data was analyzed by the use of inferential statistics with the aid of Statistical Package for Social Scientists (SPSS) version 24.0. The study established a significant positive relationship between risk management and financial performance (β1=-124, p=0.000<0.05). The study concluded that there is a strong positive relationship between risk management and financial performance. The study recommended the implementation of risk management strategies to enhance the performance of SACCOs. Keywords: Risk Management, Performance, Strategy, SACCOs

The effect of proximity on risk perception: A systematic literature review

The use of geospatial analytical tools has recently advanced risk perception research, with growing interest in spatial dimension. Available reviews of risk perception studies usually focus on specific types of risk or look at various socio-psychological, cognitive and cultural factors, and there are no systematic reviews of empirical research analysing the effect of proximity on risk perception. This article synthesizes the evidence from 81 empirical studies that investigate the significance of proximity on subjective risk perception. The systematic review focused on summaries of research methods, samples, geographic coverage, measurements and direction of influence of proximity variables on risk perception and types and sources of risk. The majority of the studies analysed implemented quantitative research. The most popular data collection methods were face-to-face interviews and postal surveys, but only half had representative samples. Studies looking into the effect of proximity on risk perception most often analysed environmental and technological risks. Two-thirds of the empirical studies found a significant impact of proximity on risk perception; the majority of these showed a positive correlation, with respondents living closer to hazards having higher risk perceptions. Negative correlations of risk perception with proximity are more characteristic of nuclear risks. Co-occurrence analysis of sources-of-risk and objects-at-risk has identified three most frequent clusters: impact of floods on economic properties; impact of other natural hazards on economic properties and impact of industrial facilities on health and lives.

THE OPPORTUNITIES, LIMITATIONS, AND CHALLENGES IN USING MACHINE LEARNING TECHNOLOGIES FOR HUMANITARIAN WORK AND DEVELOPMENT

Novel digital data sources and tools like machine learning (ML) and artificial intelligence (AI) have the potential to revolutionize data about development and can contribute to monitoring and mitigating humanitarian problems. The potential of applying novel technologies to solving some of humanity’s most pressing issues has garnered interest outside the traditional disciplines studying and working on international development. Today, scientific communities in fields like Computational Social Science, Network Science, Complex Systems, Human Computer Interaction, Machine Learning, and the broader AI field are increasingly starting to pay attention to these pressing issues. However, are sophisticated data driven tools ready to be used for solving real-world problems with imperfect data and of staggering complexity? We outline the current state-of-the-art and identify barriers, which need to be surmounted in order for data-driven technologies to become useful in humanitarian and development contexts. We argue that, without organized and purposeful efforts, these new technologies risk at best falling short of promised goals, at worst they can increase inequality, amplify discrimination, and infringe upon human rights.

Contesting efficacy: Tensions between risk and inclusion in computer vision technology

Contesting efficacy: Tensions between risk and inclusion in computer vision technology

Hybrid quantitative–qualitative method for technology portfolio selection: a case study of Iran’s space industry

The space industry is known as an economic driver for many world economies. In Iran, the acquisition of satellite technology knowledge is one of the achievements of the country’s scientific and technological indicators in recent years, but the position and importance of optimal investment in this industry in Iran have been ignored. The optimal technology portfolio is one of the tools that can cover this gap and lead to better decision-making by policymakers. In this paper, the optimum technology portfolio determination regarding its goals, attributes and challenges is addressed for Iran’s space industry with a hybrid quantitative–qualitative method in two short and medium-term periods. We formulate a technology portfolio selection model with these multi-objective functions: maximization of benefits in using different technologies comprising of both short and medium-term portfolios, maximizing the total summation of all Technology Readiness Levels (TRLs) of technologies, maximizing the acquisition speed for the technologies, and minimizing the acquisition risk of technologies in each portfolio. In the proposed model, the usability, acquisition cost, and complexity of each technology are considered meticulously. Also, the goal programming method is used to integrate the objective functions. Another novelty of this paper is the formulation of two portfolios with two different periods in which their corresponding inputs and outputs affect the other. This research can significantly help in directing the country’s investment in the space industry, spatial ecosystem orientation, facilitating the creation of space-based businesses, improving economic growth, and also providing guidelines to improve the related policies in this area. In addition, this research can be an inspiration for other developing countries in the space industry.

Towards algorithm auditing: managing legal, ethical and technological risks of AI, ML and associated algorithms.

-Business reliance on algorithms is becoming ubiquitous, and companies are increasingly concerned about their algorithms causing major financial or reputational damage. High-profile cases include Google's AI algorithm for photo classification mistakenly labelling a black couple as gorillas in 2015 (Gebru 2020 In The Oxford handbook of ethics of AI, pp. 251-269), Microsoft's AI chatbot Tay that spread racist, sexist and antisemitic speech on Twitter (now X) (Wolf et al. 2017 ACM Sigcas Comput. Soc. 47, 54-64 (doi:10.1145/3144592.3144598)), and Amazon's AI recruiting tool being scrapped after showing bias against women. In response, governments are legislating and imposing bans, regulators fining companies and the judiciary discussing potentially making algorithms artificial 'persons' in law. As with financial audits, governments, business and society will require algorithm audits; formal assurance that algorithms are legal, ethical and safe. A new industry is envisaged: Auditing and Assurance of Algorithms (cf. data privacy), with the remit to professionalize and industrialize AI, ML and associated algorithms. The stakeholders range from those working on policy/regulation to industry practitioners and developers. We also anticipate the nature and scope of the auditing levels and framework presented will inform those interested in systems of governance and compliance with regulation/standards. Our goal in this article is to survey the key areas necessary to perform auditing and assurance and instigate the debate in this novel area of research and practice.

中国面部识别技术发展考察

Recently, the rapid development of facial recognition technology, which is an important field of artificial intelligence, has attracted more and more attention worldwide due to the integration of big data and artificial intelligence technology. This technology has been widely applied in various fields and continues to develop with many advantages and convenience. However, the concerns and potential risks associated with the widespread use of facial recognition technology are also significant. Therefore, this study aims to comprehensively and critically review the development and risks of this technology, focusing on the current situation in China. It is intended to offer guidance and support for the ethical advancement of contemporary facial recognition technology as well as to promote responsible oversight and regulation. In this paper, first, the development process of facial recognition technology such as the technological origin and core technological innovation in the world and China is reviewed. Next, it also examines the application and convergence of big data and artificial intelligence algorithms in facial recognition technology. Furthermore, it analyzes the latest development of facial recognition technology in China, including the driving role of the government and companies and trends in major application fields. Simultaneously, this discourse delves into the extensive risks and challenges associated with facial recognition technology, such as privacy, data security, potential misuse, ethics, and legal regulations. To put it another way, the practical risks of facial recognition technology are focused on its specific applications in the fields of public safety, commerce, and social management, highlighting the resulting technical vulnerabilities, privacy threats, and abuse of social monitoring. Finally, this study summarizes the development status of facial recognition technology, points out the major problems and risks facing it once again, and presents appropriate countermeasures and policy recommendations.

A taxonomy for cybersecurity standards

Cybersecurity standards on a global scale are exhaustive, appealing to several types, such as glossaries, guidelines, methods, and objectives (e.g., Information Technology evaluation, requirement identification, risk management, and technical specifications). This chaotic range of standards towards the rapid pace of technological and threat evolution hinders stakeholders (e.g., security architects/developers, policymakers, testers, and auditors) from discovering which standards best meet their security needs. The paper analyzes this challenge and contributes to harmonizing standards by identifying relationships between the EU regulation and prominent cybersecurity standards. The current work develops a taxonomy that classifies cybersecurity standards according to their objective, usage, and sector, aiming to help stakeholders understand their purpose and decide which they should adopt to cover their organizational needs. The taxonomy is represented in a semantic ontology, following the Web Ontology Language Edition 2 knowledge engineering approach. A realistic scenario is described to illustrate the applicability of the taxonomy.

Supply and demand behaviors in the Chinese emission allowances pledge credit market under different value type: An evolutionary game analysis

Chinese Emission Allowances (CEAs) pledge credit provides a new way for banks to reduce green credit risks and for low-carbon enterprises to improve the credit availability. However, insufficient supply and demand is the main dilemma of CEAs pledge credit in China. One of the reasons for this dilemma may be the neglect of the forward value of CEAs in value assessment. This research explores the decision-making behavior of the supply and demand subjects in the CEAs pledge credit market under different value types of CEAs. First, the improved B–S options pricing model with consideration of transaction costs is used in the construction of the payoff matrix to measure the option value of CEAs. The new matrix aims to place both the option value (corresponding to forward value) and the market value (corresponding to spot value) in the CEAs pledge value evaluation framework. Then, based on the new matrix, an evolutionary game model between key emission enterprises (KEEs) and commercial banks (CBs) is built to dynamically analyze the equilibrium state of supply and demand as well as the strategic interaction of participants in CEAs pledge credit market. Finally, numerical simulations demonstrate the driving factors of supply and demand for CEAs pledge credit. The research results show that compared to market value, the option value of CEAs is more conducive to stimulating the supply and demand of CEA pledge credit; and the shorter the remaining valid period of CEAs, the higher the participation enthusiasm of supply and demand parties. Furthermore, reducing low-carbon technology risks and increasing the carbon emissions trading prices at the end of pledge period can significantly improve the supply and demand of CEAs pledge credit, but the loan and deposit interest rates of CEAs pledge credit are ineffective.

MART 23: A Tool to Audit Information Technology Risk Management Maturity

MART 23: A Tool to Audit Information Technology Risk Management Maturity

Barriers to Older Adults Adapting Smart Homes: Perceived Risk Scale Development

The 21st century has marked the dawn of an aging population. China’s aging process ranks first worldwide. The country has recognized the gravity of this demographic shift and implemented strategies to address it at the national level. A vast majority of elderly Chinese individuals (approximately 90%) aspire to age in their own homes. Smart homes, endowed with cutting-edge digital technologies, such as AI, the Internet of Things, and big data, hold vast potential for enabling this vision. However, acceptance of smart home products and services among elderly individuals in China remains low. The main reason is that the related products and services fail to effectively alleviate the perceived risk of this population in the R&D process of related products and services, and there is a lack of effective measurement methods. To holistically assess the potential obstacles faced by elderly individuals using smart home products and services, this study targeted individuals aged 45–60 years in China. This study aimed to develop a comprehensive perceived risk scale specific to smart homes for this demographic. Initially, this study identified key risk dimensions and corresponding measurement items through a rigorous literature review, user interviews, and expert consultations. Subsequently, it ensured the reliability and validity of each dimension and its corresponding observation variables through preliminary research, exploratory factor analysis, and confirmatory factor analysis. This approach allowed for a comprehensive understanding of the challenges faced by future elderly individuals when utilizing smart home products and services, thus enabling the development of more effective solutions. The scale encompassed ten factors and seventy measurement items, including Privacy and Security Risk (seven items), Physical Risk (seven items), Technological Risk (nine items), Performance Risk (seven items), Service Risk (nine items), Financial Risk (five items), Psychological Risk (seven items), Industry and Market Risk (six items), Social Support Risk (six items), and Policy and Legal risk (seven items). The measurement scale developed in this study represents a groundbreaking first attempt to create a systematic scale for assessing the perceived risks associated with smart homes for the elderly in China. It not only enables professionals, businesses, and manufacturers to avoid or reduce barriers in the R&D process of related products and services, facilitating smart home industry growth and enhancing user adoption, but also serves as a universal reference for the potential obstacles that digital technology may encounter in addressing aging-related issues, which has significant theoretical value and practical importance.

A decision-making framework for the funding of shipping decarbonization initiatives in non-EU countries: insights from Türkiye

The decarbonization of the shipping industry is a critical imperative in the global fight against climate change. Non-EU countries, being significant contributors to shipping emissions, play a crucial role in shaping the industry's sustainable future. However, securing funding for shipping decarbonization initiatives in these countries presents challenges, such as limited access to capital, lack of financial initiatives, political and regulatory uncertainties, technological risks, lack of local expertise, and the effects of global economic volatility. Addressing these challenges demands innovative strategies. The paper explores ways of effectively allocating funds for decarbonization projects in the shipping industry of non-EU countries, Türkiye in particular, using a structured decision-making framework tailored to their specific needs and challenges. We adopt the Moment Integrated Solution Method (THEMIS) to identify the “best” option from the range of alternative strategies identified in the framework. Our findings show that the use of incentive mechanisms is the most prioritized funding alternative, followed by the implementation of a sound Cap-and-Trade system and the promotion of strict local regulations to combat emissions. These imply that the prioritization of funding mechanisms, market-driven approaches, and more stringent regulation are key drivers in maritime decarbonization efforts. The Türkiye case study on strategies to achieve a greener maritime industry in developing countries also shows that securing funding for decarbonization requires a concerted effort by governments, private entities, and international organizations.

Research on risk identification of manufacturing enterprises' Internet strategic transformation.

The Communist Party of China's 19th National Congress underlined the necessity of speeding the development of a manufacturing powerhouse and advanced manufacturing sector by supporting the deep integration of the Internet, big data, artificial intelligence, and the real economy. This study employed principal component analysis to extract the prominent risk factors from questionnaire data in order to manage the risks connected with the Internet strategic transformation of manufacturing firms. To confirm the major risk factors, a structural equation modeling was created using Amos-24 software. The findings revealed that risk factors of Internet strategic transformation in manufacturing businesses are mostly expressed in equipment flexibility risks, organizational versatility risks, smart technology risks, Internet technology risks, flexible management risks, and financing management risks. The paper offers useful theoretical and practical insights into the risks of China's manufacturing businesses' Internet strategic transformation. The findings can assist manufacturing firms in better identifying and managing these risks, supporting their smooth transition to the Internet economy.

Ten principles for responsible quantum innovation

This paper proposes a set of guiding principles for responsible quantum innovation. The principles are organized into three functional categories: safeguarding, engaging, and advancing (SEA), and are linked to central values in responsible research and innovation (RRI). Utilizing a global equity normative framework and literature-based methodology, we connect the quantum-SEA categories to promise and perils specific to quantum technology (QT). The paper operationalizes the responsible QT framework by proposing ten actionable principles to help address the risks, challenges, and opportunities associated with the entire suite of second-generation QTs, which includes the quantum computing, sensing, simulation, and networking domains. Each quantum domain has different technology readiness levels, risks, and affordances, with sensing and simulation arguably being closest to market entrance. Our proposal aims to catalyze a much-needed interdisciplinary effort within the quantum community to establish a foundation of quantum-specific and quantum-tailored principles for responsible quantum innovation. The overarching objective of this interdisciplinary effort is to steer the development and use of QT in a direction not only consistent with a values-based society but also a direction that contributes to addressing some of society’s most pressing needs and goals.

Evaluation Method for Technology Readiness Assessment in High-purity Metal Target

Technology readiness level is an assessment tool for technology risk control, widely used in large-scale complex engineering such as military and aerospace industries. High purity metal targets are one of the key materials required for production in fields such as semiconductors, flat panel displays, and solar cells. The technology and process are very complex, which determines the level of technological maturity and will have a significant impact on downstream applications. This article combines the needs of downstream users and establishes a technology maturity evaluation model for high-purity metal targets with "parameters-indicators-data" as the core. It develops a technology maturity evaluation method suitable for high-purity metal targets and uses high-purity cobalt targets as an example for evaluation and application practice. It diagnoses the problems existing in the industrialization process, proposes improvement suggestions, and helps target production enterprises continuously improve and enhance.

Commentary] Healthspan Horizon — Pioneering Preventive Care as the New Standard of Healthcare

The contemporary healthcare landscape is experiencing a profound transformation, transitioning from a reactive to a proactive model focused on ongoing health maintenance, prediction, and disease prevention. This shift is driven by several factors, including the demographic shift towards an ageing population, increasing prevalence of chronic diseases, and economic challenges posed by the current hospital-centric care model. Proactive prevention, emphasizing early intervention and health promotion, emerges as imperative to mitigate the burden of chronic diseases and improve patient well-being. Innovative approaches leveraging technology, personalized medicine, and comprehensive risk management are at the forefront of this paradigm shift. This evolution requires significant investment and collaboration among stakeholders, however. Startups and investors will play a crucial role in driving meaningful innovation and navigating the regulatory landscape to realize the full potential of preventive medicine. Sustainability and efficiency in healthcare systems are paramount, necessitating smarter distribution of resources and prioritization of preventive care to ensure healthier populations and manageable expenditures. While implementation challenges exist, promising trends in personalized and digital health technologies offer new opportunities to address health proactively. Ultimately, the goal has to be to create a global healthcare ecosystem that prioritizes preventive measures and fosters interdisciplinary collaboration, ensuring access to quality healthcare for all. With this editorial, we want to initiate the discussion and subsequently provide more specific information through subsequent selected chapters on different clinical topics and future-oriented technological approaches.

How do digital financial inclusion, ICT diffusion, and education affect energy security risk in top energy-consuming countries?

Energy security has become a crucial issue as the world economy depends more and more on energy supplies. In the context of the top energy-consuming nations, this research examines the connection between digital financial inclusion, information and communication technology (ICT), education, and energy security risk from 2011 to 2022. To that end, the study applies the two-stage least squares and system generalized method of moments estimation techniques. According to our study's findings, digital financial inclusion and associated factors, including automatic teller machines, bank branches, debit cards, and electronic payments, mitigate energy security risks. The energy security risks are also reduced due to ICT, education, gross domestic product, and renewable energy production. However, carbon emissions increase energy security risks. These findings suggest that policymakers in top energy-consuming economies should focus on the digital inclusiveness of the financial sector, ICT diffusion, and human capital to increase the opportunities for investment in the energy sector to mitigate energy security risks.

The role of bank governance in managing the risks associated with banking institutions

This study explores the crucial role of bank governance in maintaining financial system stability by managing risks within banks. It differentiates from prior research by not solely focusing on the 2008 financial crisis. Data from a survey of 220 bank employees were analyzed using structural equation modeling. Key findings include the necessity of well-informed boards and robust governance structures that adhere to regulations for effective risk management. Open communication with stakeholders and stringent control over technological risks are also vital due to the banking sector's increased technology reliance. These insights underscore the complexities of risk management in banking governance, stressing the need for a comprehensive, adaptable strategy. This research contributes new evidence to the importance of strong governance in risk management, with significant implications for bank and corporate governance fields. The study's model demonstrates high predictive accuracy and explanatory power.