COVID-19 and Finance: Market Developments So Far and Potential Impacts on the Financial Sector and Centres

FinTech and financial instability. Is this time different?

We study the development of FinTech, defined as a set of innovations and an economic sector that apply recently developed digital technologies to financial services, with particular focus on payment and lending platforms, and digital asset management and online trading apps. We use mixed methods, including a theoretical exercise on the main balance sheet interactions involved in FinTech banking, and empirical insights from fieldwork in Latin America and the United States. Our analysis corroborates previous literature identifying several systemic risks in FinTech payment and lending platforms. These include the enhanced risk of a bank run, the increase in liquidity risk for incumbent banks, the fueling of precarious lending, and the potential compromise in the efficacy of monetary policy. Our discussion of online asset management and trading apps also highlights the risk of enhanced volatility in financial markets due to the increase in the participation of low-income and inexperienced investors. We observe that while the FinTech sector is still small in size, it already contains seeds of financial instability which should be all-too-familiar from recent history.

Economic geography II: The economic geographies of the COVID-19 pandemic

This is the second of three reports on economic geography. It focuses on research that addresses issues deemed to be both urgent and generative of crisis. This report focuses on the crisis created by the emergence of COVID-19. While the virus may have been novel, many of its implications were not, as several important processes of uneven development and inequality accelerated. The paper first determines the extent to which the emergence of a pandemic virus constituted a 'crisis', before examining some of the most salient economic geographical impacts of the COVID-19 pandemic. These include the rise of friction within the global economy resulting in significant disruption to global supply chains; the acceleration of the digital platform as an ever more dominant form of economic organisation; and how the pandemic deepened social inequalities and uneven development. The report concludes with observations about the emergence of what has been described as a post-pandemic polycrisis.

Evaluation of the Construction of a Data Center-Driven Financial Shared Service Platform From the Remote Multimedia Network Perspective

The financial shared service (FSS) platform under the remote multimedia network perspective is a newly proposed accounting and reporting business management mode in recent years that plays a good role in the operation of enterprises. The multimedia technology in the health cloud biological authentication and data management system can be applied to the construction of the data center-driven FSS platform. This study used multimedia in the data management system to build a data center-driven FSS platform to maintain the normal operation of the enterprise. Moreover, the study analyzed from the perspective of employee satisfaction, work efficiency, enterprise cost, and work continuity and drew a conclusion. The survey of employee satisfaction showed that the satisfaction of employees after modeling had been greatly improved compared with that before modeling. Moreover, according to the survey of work efficiency, the work efficiency of employees in the five enterprises after modeling has been greatly improved compared with that before modeling. Furthermore, in the survey of enterprise cost, the cost reduction effect of postal enterprises is best after using multimedia technology to model the data center-driven FSS platform. Then, according to the survey on work continuity, the work continuity of the five enterprises has been improved to varying degrees after the establishment of the FSS platform. Among them, the work continuity of Enterprise 2 has been improved by 11%, with the best effect. The multimedia modeling in the health cloud biological authentication and data management system plays a role in promoting the development of enterprises.

Systematic review of MCDM approach applied to the medical case studies of COVID-19: trends, bibliographic analysis, challenges, motivations, recommendations, and future directions

When COVID-19 spread in China in December 2019, thousands of studies have focused on this pandemic. Each presents a unique perspective that reflects the pandemic's main scientific disciplines. For example, social scientists are concerned with reducing the psychological impact on the human mental state especially during lockdown periods. Computer scientists focus on establishing fast and accurate computerized tools to assist in diagnosing, preventing, and recovering from the disease. Medical scientists and doctors, or the frontliners, are the main heroes who received, treated, and worked with the millions of cases at the expense of their own health. Some of them have continued to work even at the expense of their lives. All these studies enforce the multidisciplinary work where scientists from different academic disciplines (social, environmental, technological, etc.) join forces to produce research for beneficial outcomes during the crisis. One of the many branches is computer science along with its various technologies, including artificial intelligence, Internet of Things, big data, decision support systems (DSS), and many more. Among the most notable DSS utilization is those related to multicriterion decision making (MCDM), which is applied in various applications and across many contexts, including business, social, technological and medical. Owing to its importance in developing proper decision regimens and prevention strategies with precise judgment, it is deemed a noteworthy topic of extensive exploration, especially in the context of COVID-19-related medical applications. The present study is a comprehensive review of COVID-19-related medical case studies with MCDM using a systematic review protocol. PRISMA methodology is utilized to obtain a final set of (n = 35) articles from four major scientific databases (ScienceDirect, IEEE Xplore, Scopus, and Web of Science). The final set of articles is categorized into taxonomy comprising five groups: (1) diagnosis (n = 6), (2) safety (n = 11), (3) hospital (n = 8), (4) treatment (n = 4), and (5) review (n = 3). A bibliographic analysis is also presented on the basis of annual scientific production, country scientific production, co-occurrence, and co-authorship. A comprehensive discussion is also presented to discuss the main challenges, motivations, and recommendations in using MCDM research in COVID-19-related medial case studies. Lastly, we identify critical research gaps with their corresponding solutions and detailed methodologies to serve as a guide for future directions. In conclusion, MCDM can be utilized in the medical field effectively to optimize the resources and make the best choices particularly during pandemics and natural disasters.

Financial information, physical proximity and COVID: The experience of Asian sell-side equity research analysts

The need for physical proximity and face-to-face communication in financial information flows is contested. But the movement restrictions imposed across Asia during the COVID-19 pandemic, together with the elevated information needs as financial markets became stressed, provided the unique circumstances for a natural experiment to test the extent to which physical interaction is important in the origination and distribution of financial information. Drawing upon 70 interviews undertaken across Asia during 2021, primarily with sell-side analysts who act as information intermediaries in the financial ecosystem, this article provides evidence that physical proximity and face-to-face communication remains highly valued, particularly when accessing information embedded in informal local networks and originated through reciprocal client relationships. Analysts physically restricted from contacts at corporates and within their associated operating environments, reported a degradation of knowledge, especially versus more proximate competitors. The enforced physical separation also weakened previously strong social and reciprocal relationships with clients, even those co-located in the same city. Although these trends may be gradual and incremental rather than dramatic, they are persistent and self-reinforcing, and demonstrate the continued benefits of proximity and face-to-face interaction, with longer-term implications for financial geographies.

Challenges for ATM management in times of market variability caused by the COVID-19 pandemic crisi

One of the most important issues related to the management of an Automatic Teller Machine (ATM) network is the correct forecasting of the demand for cash. Typically, this demand, expressed as the value or number of ATM withdrawals, has some regularities that can be used to evaluate future values for these variables. However, forecasting becomes a challenge when a crisis occurs that could affect the behavior of ATM users. In this context, it is important to identify how the development of the crisis and the various information concerning it may affect people's attitudes to cash. This study aims to examine the impact of the COVID-19 pandemic on the behavior of ATM customers. On the basis of daily data from 81 ATMs, we analyze the changes in the value and number of withdrawals just before and during the COVID-19 pandemic in Poland. An event study analysis allows us to determine precisely the moments in which changes in user behavior took place. This means that it is also possible to examine the reaction of ATM users to the announcement and implementation of the pandemic restrictions, and to determine the factors that had an impact on the change in people's attitude to cash. Such a study is also important from a sociological point of view, as it enables one to understand people's reactions to the emerging crisis. Hence, its results may be useful not only for managers of ATM networks, but also for various authorities and policy makers.

Public attention, oil and gold markets during the COVID-19: Evidence from time-frequency analysis

This paper uses time-frequency analysis, including wavelet analysis and time-frequency domain causality, to evaluate the relationship between public attention to the COVID-19 pandemic, crude oil, and gold markets in the G7 countries over time and frequency. Empirical findings show that WTI oil lead gold returns during the COVID-19 outbreak, and vice versa when Omicron spread. The relationship between public attention to the COVID-19 and WTI oil/gold markets appears to be heterogeneous for G7 countries. European public attention caused by the COVID-19 outbreak has a strong impact on gold returns at the 32-64 day frequency, while public attention generated by Omicron has a significant effect on WTI oil returns at 4-128 day frequency. The public in the US and Canada is more concerned about the global stock and WTI oil markets slump than the COVID-19 pandemic. The Italian public seems to be the most sensitive to the EU's economic support plan. The heterogeneity of the public attention-oil/gold nexus in the G7 implies that portfolio diversification across markets and investment horizons may be extremely beneficial.

The relationship between global stock and precious metals under Covid-19 and happiness perspectives

In this paper, we examine the relationship between global stock markets, as respectively represented by the FTSE All-World Series and the MSCI Emerging Markets indexes, and the S&P GSCI Precious Metals index from 01 September 1999 to 03 May 2021. We employ the conditional correlation multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) to investigate this stock-precious metals nexus in terms of return and volatility spillovers. The study assesses impacts of the Covid-19 pandemic on the stock-precious metals nexus and further examine this relationship by supplementing the Twitter's Daily Happiness Sentiment index to the methodological framework for the period from 01 January 2020 to 03 May 2021. We find that precious metals positively influence stock markets before the Covid-19 outbreak and firmly play a valuable role due to their hedge and safe haven characteristics. In contrast, the bivariate GARCH framework does not provide statistically significant evidence on the stock-precious metals nexus during the Covid-19 pandemic. Meanwhile, the tri-variate GARCH approach with stock markets, precious metals, and happiness sentiment indexes reveals sufficiently complicated interactions between these return series. Prominently, past change in the happiness index negatively affects the stock returns but positively drives the performance of precious metals. These findings indirectly demonstrate the stock-precious metals nexus under impacts of the Covid-19 pandemic and reflect the demand of precious metals during crisis periods. Accordingly, we suggest a reasonable method of adjusting the proxies when no interaction effect is significantly found during unprecedented outbreaks.

Expert model of risk assessment for the selected components of smart city concept: From safe time to pandemics as COVID-19

The purpose of the paper is to create an information, fuzzy risk assessment model to support the decision-making of Municipality management for the establishment and management of measures in the safe mode (regular) of City, emergency and disaster situations, in the selected components of Smart City concept. Research on this topic was motivated by the need for support, especially in emergency situations, such as the COVID-19 pandemic. It is proposed that the evaluation be carried out at local level within the framework of the Smart City concept and selected components integrated into the entity, including the Smart Security, Smart Healthcare, and Smart Environment components supported by the Smart WebGIS subsystem. The model also assesses proposed solutions for self-government financing to ensure the acceptable risk, and economic impact of decisions on the city budget within the Smart Budget aspects of selected components. Decision-making is based on intellectual analysis, processing of fuzzy data and use of fuzzy inference. The output of the model is the assessment of the risk of the municipality subsystems, taking into account the threshold for the functioning of the municipality subsystems, the linguistic interpretation of the level of risk and the acceptability of the tolerable risk resource. The model algorithm was used to create a web application to support the Municipal management for the above-mentioned agenda, from safe time to pandemics.

Global Economic Impact in Stock and Commodity Markets during Covid-19 pandemic

The outbreak of the novel coronavirus led everyone globally to face various setbacks. Such a sector that oversaw several shocks worldwide was the financial sector, namely the stock and the commodity markets. Both the markets had different and unprecedented reactions in the different corners of the world. This was due to several reasons like government intervention, welfare policies, investor behaviour etc. This paper discusses that topic in further detail, with examples and studies from all around the planet. The main objective is to expand the pre-existing knowledge on how different regions had different reactions to the pandemic and the policies that it brought along. The stock market, in general, faced an adverse shock that led to low investments and careful foreign investment. The commodity market saw the prices of all commodities on an upward trend except for gold which observed a downward trend. Moreover, this paper also discusses the future scope and the challenges that might be faced by the markets further down the line.

Enhancing Employee Creativity in the Banking Sector: A Transformational Leadership Framework

Despite the growing academic interest in transformational leadership and employee creativity, the banking sector has not yet received enough consideration. Mostly, the banking sector was assumed to be an inappropriate setting for employee creativity as it is a tightly supervised and controlled segment of an economy. Nevertheless, some research studies in advanced nations emphasized the significance of employee creativity in a banking context. However, the case of developing countries (e.g., Pakistan) has remained an understudied area. Against this background, the objective of this study was to examine the relationships between transformational leadership (TL), perceived organizational support (POS), and employee creativity (EC) through work engagement (WE). Some private banks were selected, situated in a large metropolitan city, with data collected for the present research by a self-administered questionnaire. The structural equation modeling (SEM) technique was employed to analyze data. It was observed that TL and POS induce EC, whereas WE mediated these relationships. These findings may help policymakers of the banking industry to improve employee creativity through WE.

The Effects of Health Crisis on Economic Growth, Health and Movement of Population

The COVID-19 pandemic crisis, which was triggered in 2019 with oscillating evolution in 2020 and 2021, was a factor that has had dramatic effects on the economic growth of countries worldwide. In the context of the pandemic crisis, population health has deteriorated; education and economic activity in all the countries around the world have been affected. The main purpose of this paper is to highlight the special situations that humanity is experiencing as a result of the unprecedented effects that the COVID-19 crisis is having on the socioeconomic evolution. Specific statistical econometric methods (such as analysis of linear correlations, multiple linear regression, analysis based on dynamics indicators, and spectral analysis, comparability based on indices) were applied to highlight the evolution and future prospects of the COVID-19 virus worldwide. The COVID-19 crisis has generated another major issue for mankind, along with global warming and the energy transition, namely, population health. For this reason, in this study, we focused on the impact of the COVID-19 crisis on population health in a broader context; the sustained growth of populations in developing countries and aging populations in developed economies.

Examining factors that boost intention and loyalty to use Fintech post-COVID-19 lockdown as a new normal behavior

This study predicts factors affecting the tendency to use financial technology (Fintech) services post-COVID-19 lockdown as a new normal behavior. Fintech services have boosted the number of users during the COVID-19 lockdown. However, to maintain the loyal behavior of consumers after usage, firms need to predict key reasons to enhance their intention to use the service and maintain current consumers in the long term. This study offers a model to assess the components of the perceived usefulness toward Fintech. Data were collected via Mechanical Turk (MTurk), and structural equation modeling was used to predict the factors that influence the intention and loyalty to use Fintech post-COVID-19 lockdown. The findings reveal that the COVID-19 lockdown, trust, data security and privacy, and especially staff services are factors that enhance the intention to use through perceived usefulness. In return, it builds consumers' loyalty toward Fintech services and is considered a new normal behavior. This research sheds light on how Fintech firms develop their capabilities and increase their competitive advantages. Both theoretical and practical implications are also discussed.

Sustainable Construction Investment, Real Estate Development, and COVID-19: A Review of Literature in the Field

Aspects of sustainable construction investment and real estate development (CIRED) and their interrelations during the period pre-, intra-, and post-COVID-19, are presented in the research. Applications of the topic model, environmental psychology theory, building life cycle method, and certain elements of bibliometrics, webometrics, article level metrics, altmetrics, and scientometrics make it possible to perform a quantitative analysis on CIRED. The CIRED topic model was developed in seven steps. This paper aims to present a literature review on CIRED throughout the pandemic and to look at the responses from the real estate and construction sector. This sector is a field that appears to be rapidly expanding, judging from the volume of current research papers. This review focuses on last year’s leading peer-reviewed journals. A combination of various keywords was applied for the review and the criteria for paper selections included construction investment, real estate development, civil engineering, COVID-19, and sustainability, as well as residential, industrial, commercial, land, and special purpose real estate, along with their risks, strategies, and trends. The articles reviewed for this paper, which analyzes three hypotheses, look at pre-, intra-, and post-pandemic CIRED. The three hypotheses were validated by analyzing scientific publications from around the world. Two innovative elements make this study stand out among the most advanced research on pre-, intra-, and post-pandemic CIRED. The first of the two innovations is the integrated analysis of the COVID-19 pandemic, COVID-19-related national policies, and business investment strategies relevant to CIRED and the interests of investors as well as on the impact a CIRED policy and investors make on the spread of COVID-19. In addition, this research demonstrates a marked increase in the effectiveness of a CIRED analysis, when the life cycle of a CIRED, the involved stakeholders with their own individual interests, the COVID-19 situation, and the external micro-, meso-, and macro-environments are covered comprehensively as a single entity.

Model of Evaluation and Selection of Expert Group Members for Smart Cities, Green Transportation and Mobility: From Safe Times to Pandemic Times

This paper presents the development of technologies to support the decision-making of local government executives and smart city concept managers in selecting and evaluating the competencies of new members for advisory groups for solving problems that are implemented in safe times in individual areas or in crises, such as pandemics. The reason for developing effective urban transformation strategies and for the transparent selection of independent experts (non-politicians) for policymaking, decision-making, and implementation teams is not only the heterogeneity of smart city dimensions together with the necessary complexity and systems approach, but also the nature of the capacities and tools needed for smart city concepts. The innovative hybrid competency assessment model is based on fuzzy logic and a network for neuro-fuzzy assessment. It is a technological model for evaluating the competencies of specialists, taking into account the influence of human factors on the processes of personnel selection and system management. An innovative web platform named “Smart City Concept Personnel Selection” has been designed, which can be adapted to various users of municipalities or regional institutions for the transparent selection of qualified personnel for effective decision-making and the use of public funds during safe times or emergencies, such as the COVID-19 pandemic.

COVID-19 pandemic and stability of stock market-A sectoral approach

The COVID-19 pandemic seems to be the most important phenomenon observed from March 2020 in virtually all countries of the world. The necessity to prevent the spread of COVID-19 and keep health care systems efficient resulted in the forced, drastic limitation of economic activity. Many service sectors were hit particularly hard with this but industry and agriculture were also affected. In particular, the pandemic substantially influenced financial markets and we can observe that some markets or instruments vary in stability since they have been affected in the different degree. In the paper, we present the problem of stability of stock markets during the COVID-19 pandemic. Due to the low number of works related to CEE countries during the pandemic, we analyze the Warsaw Stock Exchange, which is one of the most important markets in the CEE. Our main goal was to find how various industries represented by stock market indices have reacted to the COVID-19 shock and consequently which sectors turned out to keep stability and remained resistant to the pandemic. In our investigation, we use two clustering methods: the K-means and the Ward techniques with the criterion of maximizing the silhouette coefficient and six indicators describing stability in terms of profitability, volume, overbought/oversold conditions and volatility. The results of the research present that during the pandemic it was possible to identify 5 clusters of sector indices in the short term and 4 in the medium term. We found that the composition of the clusters is quite stable over time and that none of the obtained clusters can be univocally considered the most or the least stable taking into account all the analyzed indicators. However, we showed that the obtained clusters have different stability origins, i.e. they vary from each other in terms of the investigated indicators of stability.

The Development and Adoption of Online Learning in Pre- and Post-COVID-19: Combination of Technological System Evolution Theory and Unified Theory of Acceptance and Use of Technology

After the outbreak of COVID-19, schools heavily depend on e-learning technologies and tools to shift from in-person class to online. This review article analyzes the changes of technology evolution and technology adoption of e-learning in pre- and post-COVID-19 based on the Technology System Evaluation Theory (TSET) and technology adoption of e-learning based on the Unified Theory of Acceptance and Use of Technology (UTAUT). We intend to explore the interaction of technology evolution and technology adoption in the different focus of e-learning technology in the two stages and the particularity and heterogeneity of the UTAUT model. The results indicate that (1) The moderating results of technology evolution are proposed and evaluated under the UTAUT model before the COVID-19 outbreak. Studies after the COVID-19 pandemic paid more attention to technology efficiency rather than effectiveness; (2) Research on e-learning focuses on the infrastructure to reach more users after the outbreak of COVID-19 because e-learning is the only way to continue education; (3) COVID-19 fear moderates the relationship between the external factors and the behavior intention of e-learning users. The lack of financial support on technology evolution will directly weaken the implementation of new technology. Social Isolation offers more opportunities for students to engage in e-learning. Meanwhile, it slows down the implementation of e-learning because of out-to-date hardware and software. This article offers an enhanced understanding of the interaction of technology evolution and technology adoption under unexpected environments and provides practical insights into how to promote new technology in a way that users will accept and use easily. This study can be tested and extended by empirical research in the future.