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Abstract This study presents a detailed literature review on financing for renewable and sustainable energy through bibliometric analysis and scientific mapping, utilizing the Scopus database from 2000 to 2023. Using network analysis techniques, it identifies eight main clusters, each focusing on different aspects of financing renewable energy and their geographic and technical contexts. The study highlights the most frequently cited articles, notable authors, key institutions, affiliations, and journals in sustainable energy finance. A random effects model meta-analysis was also conducted to assess the overall effect size of each research stream. Findings indicate that the literature on renewable energy finance has expanded since 2000 and exhibits considerable diversity. The study pinpoints five major themes suitable for discussion and exploration of new research questions: (i) the role of Fintech in renewable energy finance, (ii) the regulatory framework governing renewable energy finance, (iii) the economic feasibility of renewable energy in emerging markets, (iv) the influence of private and public finance on renewable energy development, and (v) the relationship between renewable energy finance and sustainable development goals. The insights from this study aim to inspire and equip readers as they embark on their inquiries into the connections between energy investment, policy, finance, and behavioral sciences. Following identifying research gaps, this paper outlines potential future research directions. It serves as a thorough resource on current trends in sustainable energy investments and recommends viable research topics, thus benefiting researchers, professionals, and policymakers alike.

The article extends the empirical literature on overconfidence bias in G7 stock markets during pre- and post-COVID-19 and provides additional evidence. Using vector autoregression and impulse response functions (IRFs), we analyze the overconfidence bias for the daily data from January 2015 to December 2021. Because the pertinent coefficients are positive and highly significant for only a few lags, there is a strong contemporaneity between market volume and market return in the pre-COVID-19 period of the Canadian and Italian stock markets. The study shows compelling evidence of overconfident behavior in the Italian market during the COVID-19 crisis. Along with trading volume, market liquidity influences overconfidence bias, which tracks market return but not vice versa. For investors, decision-makers, and market regulators, the study has significant ramifications in the current market turbulence caused by the COVID-19 pandemic. Furthermore, overconfidence contributes to the reported extra unpredictability due to the high level of sensitive data.

This study investigates how the Global Financial Crisis has affected the weak-form Efficient Market Hypothesis (EMH) on the stock prices of sixteen nations throughout the globe based on a suite of Fourier unit root tests. Considering the smooth structural breaks, we employed the Fourier-based unit root tests to assess the weak-form efficient market hypothesis. We used multiple frequency datasets of global financial stock market indexes that span over 20 years to have comprehensive analysis and robustness in the results. The study is performed from distinct sub-sample periods of the global financial crisis, including the pre-crisis period (2000–2007), the crisis and post-crisis period (2008–2020), and the overall sample period (2000–2020). We observed seven stock markets in the total sample period and twelve in the pre-crisis period, which were weak-form efficient across different frequency data sets. During the crisis and post-crisis period, just four out of sixteen stock market indexes were found to be weak in efficiency based on Fourier unit root tests. Given the superior properties of the Fourier unit root tests, this study reiterates that investors may receive a stream of arbitrage benefits in all markets due to the inefficiency of these countries. We offer investment implications that enable forecasting future stock price changes based on past performance and creating trading methods that produce anomalous profits.

Unified Payments Interface (UPI) has grown rapidly in recent times. It has increased its user base, volume, and transaction value through a variety of mobile applications. Various models have been used to study the reasons for UPI adoption. Earlier studies neither measured ‘Use Behavior’ (UB) as the outcome variable nor examined the influence of attitude on UPI adoption behavior. This study fills the gap by integrating UB into the model and using the extended meta-UTAUT model to explore the UPI adoption behavior of Indian urban users. The model included four exogenous and three endogenous variables. The data were collected from 894 UPI urban users using the purposive sampling method. Covariance-Based Structural Equation Modeling (CB-SEM) was applied for hypotheses testing. The study explained 82.7 % and 84.1 % of the variance for attitude and use behavior, respectively. The results of this study found that performance expectancy significantly impacts use behavior; attitude significantly affects behavioral intention; and trust affects the attitude. The results of the study will be useful in improving the features of UPI so as to increase customer base. The findings will help in smoothly introducing Central Bank Digital Currency (CBDC) among urban masses in India. The results provide future research scope for moderation and mediation. A future study can also be carried out on Indian rural users.

The study investigates the dynamic interconnections and opportunities for hedging among cryptocurrency, commodity, and Islamic stock markets using DCC-GARCH and Spillover connectedness models. Using daily data covering the Russia-Ukraine war and COVID-19 outbreak from December 1, 2019 to April 15, 2022, we document weak and frequently negative correlation between Bitcoin and Islamic stock markets. Thus, Bitcoin could be viewed as a haven from Islamic stock market losses. The results also indicate that Bitcoin's diversification benefits are normally steady and increase considerably during turbulence. Furthermore, the net return spillovers from the Bitcoin market remain above zero during most of the study period. We also find that utilizing Bitcoin as a hedge during the COVID-19 pandemic phase leads to higher expenses. The outcomes of this investigation are expected to carry substantial ramifications for Indonesian investors and portfolio managers who adhere to Shariah law since they will enable them to comprehend the advantages of diversifying portfolios across various periods of stock holding or investment horizons.

The study investigates the tail-risk spillover between the markets for sukuk and conventional bonds across fifteen countries between 2016 and 2023. First, we estimate a time varying parameter-value at risk (TVP-VAR)-based frequency connectedness model to measure the total, short-, and long-term frequency connectedness, which address the varying investment horizons of different investors. The connectedness in the sukuk market is smaller at all frequencies than in the bond market, which might offer investors better opportunities for diversification. Dynamic total connectedness fluctuates over time, which proves that connectedness is time varying and event dependent. The Covid-19 crisis and the Russia-Ukraine war are the main periods when connectedness intensified with high uncertainty. The results of this study offer insights for investors who seek diversification opportunities and policy makers especially during uncertain economic conditions.

This study investigates the pivotal roles of trust, perceived ease of use, and religiosity on individuals' intentions to adopt Islamic peer-to-peer (P2P) lending platforms within the digital economy context. The novelty of this study lies in its focus on an area that has received limited attention in prior studies (Islamic P2P lending) and the inclusion of individual factors, particularly religiosity, in the analysis. Additionally, a five-point Likert scale survey and purposive sampling technique were employed, targeting young Muslim potential borrowers aged 18-24 (Generation Z) who are presently engaged in microbusiness activities and have knowledge of financial technology. However, they had not yet utilized any P2P lending platforms. Data from three hundred twenty-three respondents was analyzed to investigate the relationships between variables. The results of this study suggest that all examined variables, including trust, perceived ease of use, and religiosity, have a significant and positive impact on individuals' willingness to use Islamic P2P lending. This implies that the more trust individuals have in Islamic P2P lending platforms, the easier they perceive them to use, and the stronger their religious beliefs, the more likely they are to accept and utilize these new Islamic financial services.

This study delves into the intricate impact of board social networks and local economic development on abnormal earnings within the financial statements of listed companies in Vietnam. The unique focus lies in internal board linkages, differentiating it from external engagements with other firms. Employing quantile regression, from a dataset encompassing 4449 observations from 241 listed companies in Vietnam, our findings reveal that firms with educational-professional linked managers tend to have low earnings quality at quantiles 0.05 and 0.10 but exhibit better earnings quality at quantiles 0.90 and 0.95. Executives sharing professional ties contribute to more accurate profit reporting at quantiles 0.05 and 0.10, whereas lower quality is observed at quantiles 0.25, 0.50, and 0.75. Executives sharing educational ties contribute to more accurate profit reporting at quantile 0.05 only, whereas lower quality is evident at quantiles 0.75, 0.90, and 0.95. Furthermore, the development of local GDP can enhance corporate financial reporting accuracy at quantiles 0.05, 0.20, and 0.25 but diminishes the quality of financial statements at quantile 0.10. These findings offer valuable insights into the complex interplay between board networks, economic development, and financial reporting quality in the Vietnamese corporate landscape.

AbstractThe study uses wavelet power spectrum and wavelet coherence transformation methodologies to examine how geopolitical risk affected the returns on stocks, oil, and gold during the GFC, COVID-19, and Russia-Ukraine war-three disruptive events that affected the world’s financial markets. For better diversification benefits during the turbulent times, we further investigate the degree of co-movement in frequency and time domains. We observe that GPR has high variations during Russia-Ukraine war period compared to COVID-19 period and is shown to have least variation during the GFC period. WTI crude oil and DJGI indexes are observed to have high variations during GFC, and COVID-19 periods followed by Russia-Ukraine war. We further observe that GOLD offers better diversification opportunity as well as leading movement against WTI and DJGI during disruptive events in financial markets. The results provide new understanding of how geopolitical risk affects financial assets for international investors, fund managers, and regulators, which would further aid to find risky and safer haven possibilities during the turmoil periods.

The current study aims to investigate how index returns of conventional and shariah indices of the USA, Europe, and Asia are affected by changes in oil prices, gold prices, VIX, gold-VIX, and oil-VIX. In our investigation, we used the S&P 500, S&P Europe 350, S&P Pan Asia, and their relevant shariah counterparts for the USA, Europe, and Asia. To examine how the explanatory factors affect the overall distribution of the explained variables, we used OLS and quantile regression. For the time frame prior to Covid-19, we discover that all volatility indices—OVX, GVZ, and VIX—influence returns of all indices simultaneously, and that all variables—aside from the spot price of oil—have a greater impact during the bear phase according to QR findings. Further, Volatility indices have a greater impact on volatility of index returns during the Covid-19 period. This is largely because the Covid-19 outbreak had a rapid impact on economies all around the world, and the only thing that affected financial markets consistently was high volatility. This is further supported by the findings of BEKK, which demonstrate that volatility extends across all markets and originates from commodities like gold, oil, gold-VIX, and VIX. Evidence for this can be seen in the fact that during the COVID-19 period, stock prices reacted more favorably to oil price volatility than to oil spot prices, which even went negative on April 20, 2020. Because of this, market stability can be promoted by reducing volatility through the prompt dissemination of crucial information, even while governments have little direct control over the prices of significant commodities like gold and crude oil.

The study examines the intraday volatility spillover between the exchange rate, gold, and crude oil using the Dynamic Generalized Conditional Correlation GARCH model (DCC GARCH) and the BEKK GARCH model. We investigate the spillover effects using the Diebold and Yilmaz, 2012 model to gain a better understanding of the spillover effects between asset classes. We find that gold is the most effective transmitter of return spillover to the exchange rate and crude oil, whereas crude oil is the most effective receiver of spillover from other variables in the system. The study comes to the conclusion that volatility is a crucial component of the market for commodities derivatives and can influence transaction profitability, hedging efficiency, and overall market risk. Market participants need to keep an eye on volatility and modify their plans accordingly. The research is expected to play an important role in assisting investors, portfolio managers, and financial institutions in constructing an optimal portfolio and hedging strategy based on crude oil, gold, and foreign exchange.

In this study, we investigate the dynamic volatility connectedness of FinTech, innovative technology communication, and cryptocurrency indices for the period from June 2018 to June 2022. We investigate the connectivity and risk spillovers before and after the COVID-19 period to understand the volatility fluctuations by employing the dynamic connectedness measures based on TVP-VAR methodology. We find that volatility connectedness is strong among the FinTech, and cryptocurrency indices and it increase further during uncertainty caused due to COVID-19 pandemic & also during escalations of Russian-Ukraine war period compared to the pre-pandemic levels. We identify the net transmitters and net recipients of volatility among the FinTech, innovative technology communication, and cryptocurrency indices. We observe that spillovers among the variables under study are dynamic in nature and shift from net recipients to net transmitters of volatility and viceversa during different time periods Our study has beneficial implications for policymakers, regulators, investors, and financial market constituents to redevelop their existing strategies and understand the fourth industrial revolution and new economies' indices to avoid financial losses during the financial markets’ turmoil.

This article presents a comprehensive overview of the relationship between economic growth, financial development, and carbon emissions by utilizing bibliometric analysis and scientific mapping. The research utilized the Scopus database, covering the period from 1989 to 2023. Through network analysis, the study identified five primary clusters, distinguished by the geographical and technological extent of the topic. The main objective of this review is to provide a comprehensive understanding of the future research avenues in the nexus between economic growth and carbon emissions. The article discusses the authors, journals, regions, and organizations that have had a significant impact on the growth-emission nexus, along with a summary of the most frequently cited works in this field. Furthermore, a meta-analysis was conducted to determine the aggregate impact of each research initiative. Based on the analysis and identified gaps, the study proposes future research paths.

The study examines the vital connection between stock returns and oil price changes for oil exporting/importing countries separately. We present evidence employing granger causality, impulse response and error variance decomposition based on panel vector autoregression. The results of panel granger causality suggested that after oil price crash owing to covid-19 pandemic, the interdependence between oil and stock price changes increased. Similar results were revealed by impulse response graphs and forecast error variance decomposition. Specifically, in the period marked by the rapid outbreak of the covid-19 pandemic, causality from oil to stocks increased. Although we found that both oil exporting and oil importing countries were affected in a similar way, oil price changes had a larger impact on oil exporting countries. The findings of the present study have implications for investors and fund managers. By incorporating crude oil price in the prediction models, the accuracy of stock returns forecast can be improved.

This study examines the influence of Oil Price Volatility on Banks efficiency within the BRICS countries (Brazil, Russia, India, China, and South Africa) noting the importance of the banking sector efficiency as a tool to ensure financial stability in the region. Being able to measure efficiency levels in banks determines how successful a bank is in managing its operations and achieving its goals. A sample data of 112 banks was selected using the Bank Scope database over the time interval 2003 to 2018 to inspect banking sector relative efficiency following a non-parametric methodology known as Data Envelopment Analysis (DEA). The paper applies a two-stage model to process the empirical results consisting in using the Data Envelopment Analysis (DEA) to identify the scores of banks efficiency at a first stage (Stage 1) and determining how volatility in Oil price has impact on these scores of efficiencies on a second stage (Stage 2). Findings of the study indicate that the Chinese banking system shows the highest efficiency (90%), followed by the South Africa (87%), followed by the Brazilian and Indian banking system with efficiency level of (77%), the Russian bank industry revealed the lowest efficient banking system with level of efficiency (50%).

This study reviews Islamic FinTech research development from 2017 to 2022. The study adopts a hybrid approach combining bibliometric and content analysis to reveal the current research trend of Islamic FinTech research. Using the Scopus database, we retrieve 85 documents and analyze them using RStudio and VOSviewer. The content analysis categorizes the research output in Islamic FinTech into four distinct streams. The study finds potential for cointegrating FinTech into Islamic finance to benefit the unbanked and small-medium-size businesses, the adoption of FinTech in Islamic finance will also help the government improve financial inclusion, conquer financial crises, such as COVID-19, and achieve SDGs for a sustainable nation. However, the lack of legal regulation and the lower financial literacy becomes the primary obstacle to the development of FinTech in Islamic finance.

The emergence of disruptive cryptocurrency platforms and decentralized finance (DEFI) has revolutionized the financial landscape over the last couple of years. Against this backdrop, and in view of the limited opportunities for diversification in the conventional assets, it becomes evident for the investors to look for better opportunities by searching for rather non-conventional assets like cryptocurrencies as a means of portfolio diversification. This study analyses the major cryptocurrencies based on their market capitalization and the major markets from MENA regions to evaluate the potential of cryptocurrencies in portfolio diversification. The study employs the mean-variance approach and then compares the results with the higher-order moments. We found that cryptocurrencies offer considerable potential for diversification for the MENA markets, but these exposures must be conservatively given the explosive price evolution and extreme volatility of the cryptocurrencies. The results also suggest that cryptocurrencies do not considerably contribute to the portfolio diversification in the uncertain market movements and crises, such as that witnessed during Fed's regime shift, accentuated by the Ukraine crisis.

This paper analyses the socio-economic impact of the noble Corona virus (COVID-19) on ‘Middle East and North Africa’ (MENA) region as well as the role and opportunities of Islamic finance post COVID-19. The findings show that pandemic has affected the MENA region massively like any other region in the world. Since around 69% of the word’s crude oil supply is from this region alone, this causes it to suffer from dual shocks of COVID-19 pandemic as well as the declining crude prices that is caused by shocks from both ends, negative supply shock and a negative demand shock. The 19 countries in MENA region include from some of the richest countries of the world such as, Qatar, Kuwait, and Saudi Arabia, to some of the most vulnerable, poor and war ridden countries like Yemen, Syria, and Morocco. To mitigate the adverse effects of the pandemic, we suggest some immediate actions that can be taken such as a public fund to support health system, financial support to individuals and SME’s, financial support to corporations in order to prevent job loss and layoff and assurance of liquidity in domestic markets to prevent liquidity crunch. Finally, the paper analyses the role of Islamic finance in the region in recovery post COVID-19 and show that Islamic finance can be utilized as an alternative financial system in providing the relief to the COVID-19 affected people and entrepreneurs.

The emerging-market banking sector plays a significant role in modern-day banking sector stability. In this study, we have used the dynamic conditional correlation (DCC) version of the Generalised autoregressive conditional heteroscedasticity (GARCH) model to estimate the correlation among Emerging Markets (BANKSEK), Latin America (BANKSLA), Brazil, Russia, India, and China (BRIC) (BANKSBC), Portugal, Ireland, Italy, Greece, and Spain (PIIGS) (BANKSPI) and Far East (BANKSFE). The study covers more than 100, 200 and 300 trading days of the GFC (starting July 8, 2008) and the COVID-19 pandemic (starting January 1, 2020). We have found that generally, in the short-term excluding PIIGS, all banks show similar pairwise correlation, and the pattern holds in the medium and long term. The far east banking sector displays a reduced correlation than their counterparts, even following the same pattern.

This study brings novelty to the tourism literature by re-examining the role of exchange rate in the tourism-growth nexus. It differs from previous tourism-led growth narrative to probe whether tourism exerts a positive effect on economic growth when the exchange rate is accounted for. Using a moderation modelling framework, instrumental variables general method of moments (IV-GMM) and quantile regression techniques in addition to real per capita GDP, tourism receipts and exchange rate, the study engages data on 44 Asian countries from 2010 to 2019. Results from the IV-GMM show that: (1) tourism exerts a positive effect on growth; (2) exchange rate depreciation hampers growth; (3) the interaction effect is positive but statistically not significant; and (4) results from EAP and SA samples are mixed. For the most part, constructive evidence from the quantile regression techniques reveals that the impact of tourism and exchange is significant at lower quantiles of 0.25 and 0.50 while the interaction effect is negative and statistically significant only for the SA sample. These are new contributions to the literature and policy recommendations are discussed.

This study aims to determine the impact of banking efficiency on the profitability of the Indian banking division. The ratios (key variables) used in the study are mentioned by the Reserve Bank of India—RBI (Central bank of India). Through a quantitative approach, pooled panel regression, univariate analysis, correlation, and descriptive statistics models are used by taking annual data of the Indian banking division from 2001 to 2020 available on the Thomson Reuters (Refinitiv) Database. Unbalanced cross-sectional data (panel data) comprising 527 bank-year observations for 33 Indian banks were studied. It was decided to evaluate the impact of efficiency (cost to income ratio and staff expenses to total expenses ratio) on the profitability (return on assets and net interest margin ratio) of the banks from the Indian banking division. The results revealed that the cost to income ratio has a significant negative impact on the bank return on assets and net interest margin ratio. The staff expenses to total expenses ratio has a significant positive impact on the bank return on assets and a positive nonsignificant impact on the bank net interest margin ratio.

Debt finance, when considered a source of finance, always leads to financial risk; however, it is also considered a source of increased profitability in the normal business scenario. It has always been challenging to find the correct debt equity combination. In the discussed sample of the telecom industry in the USA, an abnormally high total liability-to-total assets ratio was observed. Thus, it is inclined to investigate the capital structure (CapSt) effect on firms’ profitability. By taking annual data of the telecom industry from 2012 to 2020 in the USA, unbalanced cross-sectional data (panel data) comprising 421 firm-year observations for 72 firms were studied using pooled panel regression, univariate analysis, correlation, and descriptive statistics models. We decided to test the impact of CapSt (Total Liabilities to Total Assets (TLsTAs) and Total Equity to Total Assets (TETAs)) on the profitability (Return on Assets (ROA) and Return on Equity (ROE)) of firms in the telecommunication industry in the USA. The results reveal that the ratio of TLsTAs has a significant impact on ROA, and TETAs has a significant impact on ROA. However, TLsTAs and TETAs have no impact on ROE.

This study examines the antecedents/determinants of behavioral intentions toward the utilization of Islamic financial technology for Middle Eastern customers. The study applied structural equation modeling (PLS-SEM). After robust research efforts were invested in the identification of factors, they and were converted into measures, and the results were analyzed. The results demonstrate that the independent variables shown in the UTAUT model have a significant impact on the behavior to adopt Islamic financial technology, which implies that the people are ready to use Islamic financial technology while making online transactions. The work in this study adds to the knowledge regarding the factors affecting behavioral intention to use Islamic fintech, as there is scarcity of studies in this domain, especially in the context of Middle Eastern online customers. Moreover, this study also considers the major categories of online payments.

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.

The banking sector plays a crucial role in the economic growth of a nation. The purpose of this study is to examine the long-term association between banks’ performance and the economic growth of a developing economy: India. The study used a panel of data of 20 public sector banks for the period 2009 to 2019. It applied the Pedroni and Kao test of co-integration, panel vector error correction model (VECM) dynamic, panel fully-modified ordinary least squires OLS (FMOLS), and dynamic OLS (DOLS) to estimate the relationship of interest margin return on assets, bank investment, and lending capacity of the bank with gross domestic product (GDP) of the country. The identification and incorporation of these bank-related variables are the innovations of this study. The results indicate that the bank-related variables are co-integrated with economic growth. Further analysis indicates a significant relationship between interest margin and return on assets with economic growth. In addition, lending capacity and investment activities are not significantly associated with economic growth, leading to the policy recommendation to improve upon these two factors in order to achieve higher growth rates.

Novel Coronavirus, also known as COVID-19, is a health emergency that is having an ever-growing impact on the global economy. COVID-19 has caused economic disruption at an unprecedented speed and scale. The economic costs it will bring to society can only be measured in times to come. Millions of people across the globe have already become unemployed, and similarly, millions of businesses have either shut down or are on the verge of collapse. It is a great challenge for policymakers to minimize the economic impact of COVID-19 and put the economy on a growth trajectory once again. Unfortunately, there is so far no country in the world that can be viewed as a role model for its economic response to the COVID-19 pandemic. The present study proposes Islamic finance as a potential tool to help affected economies safely pass through the economic crisis resulting from the pandemic. This study identifies a four-stage COVID-19 model and proposes ten innovative Islamic financial services for each stage of the pandemic. In addition, it analyzes how these services can be effectively utilized at different stages to overcome the economic damage caused by the pandemic.

One of the latest innovations in business and technology is the use of big data, as daily data are generated by billions of events. The big data issue is now considered in the accountants and finance professionals’ field as one of the most important sources for the analysis of financial products and services. This study is very innovative, with our research aiming to identify the opportunities, challenges, and implications of big data in the finance area. It is our purpose to find competitive advantages in terms of the extent to which big data brings visible benefits, also pointing out the challenges that a company may face in this field, such as cases of customers’ data security or customer satisfaction processes. The identification of this kind of dynamics allows us to draw conclusions on the advantages of big data based on these analyses and big data’s deep impact on finance. In particular, big data is now commonly used by financial institutions and banks for analytical purposes in financial market contexts. We conducted an exploratory survey of the existing literature to highlight such connections. In the last part of our study, we also propose directions for future research.