Financial Technology: Review of Trends, Approaches and Management

A social network analysis of college students' online learning during the epidemic era: A triadic reciprocal determinism perspective

The way in which college students learn online has dramatically altered due to the COVID-19 pandemic. Using the triadic reciprocal determinism (TRD) theory, this study aimed to identify the key factors influencing college students' online learning experience through sentiment analysis, text mining, and social network analysis (SNA). Macro- and micro-level parsing was conducted on the SNA model, which was divided into core, mantle, and shell layers to determine the most influential factors in the core layer. This study found that learners' personal factors, learning behaviors, and related elements in the online learning environment significantly influenced the learning outcomes of college students enrolled in online courses. Additionally, this study explored the distribution of SNA model elements in the mantle and peripheral shell layers, which also impact the online learning experience of college students. Overall, this study provides a comprehensive overview of the various factors affecting college students' online learning experience, and highlights the importance of considering these factors when designing online learning environments for college students.

Architecting an enterprise financial management model: leveraging multi-head attention mechanism-transformer for user information transformation

Financial management assumes a pivotal role as a fundamental information system contributing to enterprise development. Nonetheless, prevalent methodologies frequently encounter challenges in proficiently overseeing diverse information streams inherent to financial management. This study introduces an innovative paradigm for enterprise financial management centered on the transformation of user information signals. In its initial phases, the methodology augments the Transformer network and self-attention mechanism to extract features pertaining to both users and financial data, fostering a more cohesive integration of financial and user information. Subsequently, a reinforcement learning-based alignment method is implemented to reconcile disparities between financial and user information, thereby enhancing semantic alignment. Ultimately, a signal conversion technique employing generative adversarial networks is deployed to harness user information, elevating financial management efficacy and, consequently, optimizing overall financial operations. The empirical validation of this approach, achieving an impressive mAP score of 81.9%, not only outperforms existing methodologies but also underscores the tangible impact and enhanced execution prowess that this paradigm brings to financial management systems. As such, this work not only contributes to the state of the art but also holds promise for revolutionizing the landscape of enterprise financial management.

Is green FinTech reshaping the finance sphere? Unravelling through a systematic literature review

The revolutionary and transformative potential of FinTech has led to the Green Digital Finance Alliance, noting the dawn of a new era of FinTech-"the green FinTech", yet, surprisingly, the scholarly exploration surrounding climate finance in general and green FinTech and climate FinTech remains restrained. In our attempt to decode the intricate interlinkage between green finance and FinTech, the study wrestles with the theoretical complexity of the "green FinTech" concept through a systematic review of relevant studies and conceptual mapping. We develop a comprehensive grasp of the concept, how to leverage it to combat the pressing climate crisis, and its implications for the FinTech segment-the first of its kind in the scanty green FinTech literature. Based on the PRISMA analysis, we find that green FinTech promotes a green economy through its manifold impact on all aspects of the finance sphere, thereby channelling climate finance and promoting sustainability. It has the power to heighten inclusivity, disclosure, trust, and democratisation, thus reducing information asymmetry and greenwashing. Hence, FinTech integration can be game-changing in eliminating the hurdles before conventional green finance. However, the literature remains fragmented, along with a young, growing green FinTech market. Therefore, this study proposes a framework for future researchers by providing a holistic research agenda to fully integrate "green FinTech" into practical real-world applications.

Model for Sustainable Financial Planning and Investment Financing Using Monte Carlo Method

The article deals with current issues of finance and investment planning with a selective focus on financial decision-making processes using sophisticated software tools. The article has a special significance in this period when it is necessary to re-evaluate and consider ways of appropriate and effective investment and financial policy in view of the restrictions in enterprises in Slovakia, which brings with it the global pandemic COVID-19 or another crisis in enterprises. The aim of the article is to propose a methodology as a tool for streamlining the investment activities of companies. The proposed methodology combines the usability of traditional and modern economic methods, making it an important tool for the sustainability and competitiveness of enterprises. Three variants of investment decisions in the enterprise were simulated using simulation in terms of two approaches. The first approach focuses on mathematical–economic calculations of deterministic modeling through traditional software tools. The second stochastic modeling uses the simulation of financial risks using a modern software tool using the Monte Carlo method. The output is the creation of a graphical management model in the form of an algorithm.

Construction of Development Momentum Index of Financial Technology by Principal Component Analysis in the Era of Digital Economy

The purpose is to study applying mathematical analysis in financial technology (FinTech) development in the era of digital economy. An Evaluation Index System (EIS) for the current situation of Chinese FinTech enterprises is established by considering the impact of the era of the digital economy on the development of FinTech. Specifically, the Principal Component Analysis (PCA) is introduced to construct the principal component prediction model based on functional data. Then, six Chinese State-owned Enterprises (SOEs) are selected. Their stock prices are predicted using the proposed model through an empirical study. The results show that selecting three principal components to evaluate the financial situations of six SOEs is reasonable. The accumulated variance values of the first three principal components of the stock's closing price and opening price are all greater than 85%. Thus, the selected three principal components can obtain the potential information of the original data. The gap between the actual value and the proposed model-predicted value of the stocks of the six SOEs is relatively small. The Root Mean Square Error (RMSE) of China National Petroleum Corporation (CNPC) is 0.105, more than 10%. The predicted values of Huadian Energy and China Shenhua are 9.4% and 8.5%, respectively, second only to CNPC. Therefore, the proposed principal component prediction model based on functional data can predict the closing price of stocks well. The accuracy is relatively high and matches well with financial data analysis. This research has important implications for the development of FinTech.

A non-cooperative behavior management method for multi-attribute large group decision-making

In multi-attribute large group decision-making (MALGDM), the ideal state indicates a high degree of consensus among a set of decision-makers (DMs). It is complex to reach consensus because the number of decision attributes and DMs increases. Thus, we developed a novel consensus model to manage the decision-making in large group based on the non-cooperative behavior. The improved clustering method takes account of the similarities among different DMs. Similar DMs will be grouped into the same group. The consensus threshold is determined from an objective and subjective aspect to judge whether the consensus reaching process continues. With the introduction of three non-cooperative behaviors, we investigated a non-cooperative behavior detection method under the change of consensus level. Base on the number of DMs who are willing to change their preliminary views and the change value of consensus level, the non-cooperative degree of subgroup can be computed. According to the non-cooperative degree, the subgroups’ weight can be modified to raise the consensus level. Meanwhile, the subgroup is allowed to change. Based on the adjustment amount of DMs’ opinions, whether decision maker (DM) belongs to this subgroup is recalculated. Finally, an emergency decision-making problem in flood disaster is applied to manifest the feasibility and distinctive features of the proposed method.

A Novel Noncooperative Behavior Management Method for Multiattribute Large Group Decision-Making

In multiattribute large-group decision-making (MALGDM), the ideal state indicates a high degree of consensus for decision-makers. However, it is difficult to reach a consensus because the conflict between various decision attributes and decision-makers increases. To deal with the problem, a novel consensus model was developed to manage the decision-making in large groups based on noncooperative behavior. The improved clustering method was used to take account of the similarities among different decision-makers, while similar decision-makers will be grouped into the same group. Moreover, the consensus threshold was determined from an objective and subjective aspect to judge whether the consensus reaching process continues. The noncooperative behavior and adjustment amount of decision-makers' opinions were investigated based on the proposed consensus model, and an emergency decision-making problem in flood disaster is applied to manifest the feasibility and distinctive features of the proposed method. The results show the proposed novel consensus model demonstrated strong applicability and reliability to the noncooperative subgroup problem and can be explored to manage multiattribute interactions in LGDM.

Feasibility Assessment for E-Commerce: A Data Collection from Developing Country (Ethiopia)

This methodology work has been made to investigate the factors which affect the feasibility and readiness of e-commerce in developing nations. An online and offline survey has been carried out to collect feedback from the banks, government bodies, consumers, and e-retailers all over Ethiopia and their responses have been analyzed through descriptive statistics by using Statistical Package for the Social Sciences software program. The results and finding give a clear understanding of the feasibility and readiness of e-commerce and reveals that the technological and organizational aspects, lack of Information and Communications Technology infrastructure, cross-country legal and regulatory differences, lack of digital literacy among consumers and businesses in terms of computer literacy, language barriers, lack of distribution system, lack of trust on e­commerce are the factors which affect the feasibility of e-commerce in Ethiopia. The feasibility can be improved by providing suitable information and communications technology infrastructure, improving cross-country regulatory differences, promoting ICTs in education targeting all levels of the educational system, facilitating foreign direct investment drive in ICTs, making a website attractive and user-friendly. The results of statistical analyses indicate that Ethiopia has significant potential for the feasibility of e-commerce.•

E-Commerce offers potential in the form of enhanced participation in the international value chain and public relations.

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The feasibility can be improved by providing suitable ICT infrastructure, improving cross-country regulatory differences.

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This research study reveals interesting facts about the potential and opportunity of e-commerce in Ethiopia.

Research on Art Teaching Practice Supported by Virtual Reality (VR) Technology in the Primary Schools

Nowadays, teaching and learning methods are constantly changing with the development and popularization of information technology. Many teaching activities are exploring the integration of virtual technology. However, the specific effects of VR are challenging to verify. In this paper, “teaching in VR environment” and “traditional teaching” were designed to carry out a series of teaching comparison practices between two groups of a primary school. By analyzing the experimental data of the experimental group and the control group, the research found that it is easier to enter mental flow in virtual reality, and the introduction of virtual reality technology is positively correlated with learning engagement. What is more, compared with traditional teaching and learning methods, virtual reality technology and related software can help individuals give full play to their creativity.

Evaluation of the product quality of the online shopping platform using t-spherical fuzzy preference relations

As a generalization of Pythagorean fuzzy sets and picture fuzzy sets, spherical fuzzy sets provide decision makers more flexible space in expressing their opinions. Preference relations have received widespread acceptance as an efficient tool in representing decision makers’ preference over alternatives in the decision-making process. In this paper, some new preference relations are investigated based on the spherical fuzzy sets. Firstly, the deficiency of the existing operating laws is elaborated in detail and three cases are described to identify the accuracy of the proposed operating laws in the context of t-spherical fuzzy environment. Also, a novel score function is proposed to obtain the consistent value in ranking of the alternatives. The backbone of this research, t-spherical fuzzy preference relation, consistent t-spherical fuzzy preference relations, incomplete t-spherical fuzzy preference relations, consistent incomplete t-spherical fuzzy preference relations, and acceptable incomplete t-spherical fuzzy preference relations are established. Additionally, some ranking and selection algorithms are established using the proposed novel score function and preference relations to tackle the uncertainty in real-life decision-making problems. Finally, evaluation of the product quality of the online shopping platform problem is demonstrated to show the applicability and reliability of proposed technique.

Examining the Research on Business Information-Entropy Correlation in the Accounting Process of Organizations

Open business organizations, where information flows, is shared, and exchanged, are more prepared to adapt and survive chaos, uncertainty, and entropy, so they will be more predisposed to change management. The aim of this study is to analyze research trends at the international level on business information-entropy correlation in the accounting process of organizations. Mathematical and statistical techniques were applied to 980 articles during the period 1974-2020, obtaining results on the scientific productivity of the driving agents of this topic: authors, research institutions, countries/territories, and journals. Five lines of research were identified during the period analyzed, which mainly study information theory, maximum entropy, information entropy, decision-making, and enthalpy. Future research should focus on analyzing the evolution of this topic, which forms new thematic axes related to bitcoin market efficiency, business hierarchy information, business model evaluation systems, catastrophic economic collapse, corporate diversification, CSR reports affecting accounting conservatism, economic income accounting, and information loss. Currently, the research presents an upward trend, which allows a growing interest in the subject to be deduced in the academic and scientific community worldwide.

Blockchain Technology for Secure Accounting Management: Research Trends Analysis

The scope of blockchain technology, initially associated with the cryptocurrency Bitcoin, is greater due to the multiple applications in various disciplines. Its use in accounting lies mainly in the fact that it reduces risks and the eventuality of fraud, eliminates human error, promotes efficiency, and increases transparency and reliability. This means that different economic sectors assume it as a recording and management instrument. The aim is to examine current and emerging research lines at a global level on blockchain technology for secure accounting management. The evolution of the publication of the number of articles between 2016 and 2020 was analyzed. Statistical and mathematical techniques were applied to a sample of 1130 records from the Scopus database. The data uncovered a polynomial trend in this period. The seven main lines of work were identified: blockchain, network security, information management, digital storage, edge computing, commerce, and the Internet of Things. The ten most outstanding emerging research lines are detected. This study provides the past and future thematic axes on this incipient field of knowledge, which is a tool for decision-making by academics, researchers, and directors of research investment programs.

Exploring the Role of Islamic Fintech in Combating the Aftershocks of COVID-19: The Open Social Innovation of the Islamic Financial System

The purpose of the current study is to investigate the role of the Islamic financial system in recovery post-COVID-19 and the way Fintech can be utilized to combat the economic reverberations created by COVID-19. The global financial crisis of 2008 has established the credentials of the Islamic financial system as a sustainable financial system which can save the long run interests of the average citizens around the world while adding value to the real economy. The basic ethical tenets available in the Islamic financial system make it more suited and readymade to fight the economic aftershocks of a pandemic like COVID-19. The basic principles of ethical Islamic finance have solid connections to financial stability and corporate social responsibility within the wide-reaching business context. With the emergence of Financial technology (Fintech) it has provided a missing impetus to the Islamic financial system to compete on equal ground with its conventional counterpart and prove its mettle. The study uses discourse analysis along with the content analysis to extract content and draw a conclusion. The findings of the study indicate that COVID-19 pandemic has provided the opportunity for the social and open innovation to grow and finance world have turned to open innovation to provide a speedy, timely, reliable, and sustainable solution to the world. The findings of the study provide significant implications for governments and policy makers in efficient application of Fintech and innovative Islamic financial services to fight the economic consequences of the COVID-19 pandemic.

Customer Experience in Fintech

The purpose of this paper is to analyse customer experience (CX) in the fintech sector. Fintech is a dynamic and innovative field that fully benefits from advances in information and communication technology. The concept of customer experience is multidimensional, analysed from various perspectives, and with distinct valences in different industries. Based on the stimulus-organism-response (S-O-R) approach, we proposed a model in which customer experience in fintech is the result of customer’s evaluation of the stimuli proposed by fintech companies. Using partial least squares equation modelling (PLS-SEM), we tested a series of hypotheses and validated the proposed model. The results showed that perceived value, customer support, assurance, speed and perceived firm innovativeness are positively related to customer experience in fintech. In turn, customer experience is positively associated with loyalty intentions of the customer. Our paper contributes in identifying the dimensions, the determinants and the outcomes of customer experience in fintech, while from a managerial perspective, we demonstrate how fintech companies must integrate customer experience in their business models.

Management Accounting for Healthy Nutrition Education: Meta-Analysis

Unequal economic growth shapes food systems. Nutrition problems incorporate inappropriate practices, so nutrition education is key to empowering consumers to choose healthy foods. However, increasing the accessibility of healthy diets is related to reducing the cost of nutritious foods. The accounting management of healthy nutrition should allow for optimal global decision-making. The evolution of scientific production and global research trends on this topic between 1968 and 2019 have been studied. Statistical and mathematical methods have been applied to 1738 documents from the Scopus database. The results provided data on the agents that participate in the development of the theme. Data reveal an exponential trend, especially in the previous decade, with more than 50% of scientific production. Future lines of research have been identified: investment in health systems; green label education; early impact of food insecurity; WIC (Women, Infants, and Children) nutrition education; food waste audit; and ecological footprint of food. The central contribution of the study has been to detect the main future directions of research, providing critical points that will allow us to identify the themes of future publications, in addition to providing an instrument for decision-making carried out by the research funding sponsors.

Research Analysis on Emerging Technologies in Corporate Accounting

The technological transformation has directly affected the functional areas of companies. This circumstance has been a challenge for corporate accounting, since the emerging technology allows handling a large volume of data, and providing valuable information for operational management, managerial control, and strategic planning. The aim of this study is to analyze current and future lines of research globally, during the period 1961–2019, on emerging technologies in corporate accounting. For this, bibliometric techniques were applied to 1126 articles on this subject to obtain findings on scientific production and the main subject areas. Scientific production has increased annually, so that in the last decade de 60.66% of all articles have been published. The main subject areas in which more articles were linked were business, management and accounting, social sciences, and economics, econometrics, and finance. Six lines of research have been identified that generate contributions on this topic. Furthermore, the analysis of the relevance of the keywords has detected the main future directions of research. The increasing worldwide trend of scientific production shows interest in developing aspects of this field of study. This study contributes to the academic, scientific, and professional discussion to improve decision-making based on the available information.

Implications of Virtual Reality in Arts Education: Research Analysis in the Context of Higher Education

Technological advances have posed a challenge in university learning ecosystems in terms of the application of immersive technologies that offer an educational and innovative framework to the student. The evolution of global research on this topic during the period 1980 to 2019 was studied. For this purpose, a bibliometric analysis of 1296 articles was applied, obtaining results of the scientific productivity of the journals, authors, institutions, and countries that contribute to this research. The evidence shows a growing interest, especially in the last three years, in the study of the application of virtual reality in higher education. The main subject area is Social Science. The most productive research institution is the Complutense University of Madrid. The United States is the country with the most publications and citations. In addition, The United States, Spain and the United Kingdom are the countries with the most international collaborations in their publications. The study detected five new directions for future research. The growing worldwide trend of scientific production demonstrates the interest in developing aspects of the use of virtual reality in arts education in the context of higher education. This study contributes to the academic, scientific and institutional discussion around the improvement of decision making based on the available information.

IoT Technology Applications-Based Smart Cities: Research Analysis

The development of technologies enables the application of the Internet of Things (IoT) in urban environments, creating smart cities. Hence, the optimal management of data generated in the interconnection of electronic sensors in real time improves the quality of life. The objective of this study is to analyze global research on smart cities based on IoT technology applications. For this, bibliometric techniques were applied to 1232 documents on this topic, corresponding to the period 2011–2019, to obtain findings on scientific activity and the main thematic areas. Scientific production has increased annually, so that the last triennium has accumulated 83.23% of the publications. The most outstanding thematic areas were Computer Science and Engineering. Seven lines have been identified in the development of research on smart cities based on IoT applications. In addition, the study has detected seven new future research directions. The growing trend at the global level of scientific production shows the interest in developing aspects of smart cities based on IoT applications. This study contributes to the academic, scientific, and institutional discussion to improve decision making based on the available information.