J. Risk Financial Manag., Volume 16, Issue 1 (January 2023) – 55 articles

The paper builds a Variance-Gamma (VG) model with five parameters: location ($\mu$), symmetry ($\delta$), volatility ($\sigma$), shape ($\alpha$), and scale ($\theta$); and studies its application to the pricing of European options. The results of our analysis show that the five-parameter VG model is a stochastic volatility model with a $\mathsf{\Gamma }(\alpha ,\theta )$ Ornstein–Uhlenbeck type process; the associated Lévy density of the VG model is a KoBoL family of order $\nu =0$, intensity $\alpha$, and steepness parameters $\frac{\delta }{{\sigma }^2}-\sqrt{\frac{{\delta }^2}{{\sigma }^4}+\frac{2}{\theta {\sigma }^2}}$ and $\frac{\delta }{{\sigma }^2}+\sqrt{\frac{{\delta }^2}{{\sigma }^4}+\frac{2}{\theta {\sigma }^2}}$; and the VG process converges asymptotically in distribution to a Lévy process driven by a normal distribution with mean $(\mu +\alpha \theta \delta )$ and variance $\alpha ({\theta }^2{\delta }^2+{\sigma }^2\theta )$. The data used for empirical analysis were obtained by fitting the five-parameter Variance-Gamma (VG) model to the underlying distribution of the daily SPY ETF data. Regarding the application of the five-parameter VG model, the twelve-point rule Composite Newton–Cotes Quadrature and Fractional Fast Fourier (FRFT) algorithms were implemented to compute the European option price. Compared to the Black–Scholes (BS) model, empirical evidence shows that the VG option price is underpriced for out-of-the-money (OTM) options and overpriced for in-the-money (ITM) options. Both models produce almost the same option pricing results for deep out-of-the-money (OTM) and deep-in-the-money (ITM) options. Full article

This paper empirically investigates the influence of intellectual capital on changes in total factor productivity of 36 BSE-listed banks in India from 2005 to 2019. This study employs a two-stage analysis that begins by investigating changes in total factor productivity using the Malmquist Productivity Index estimated through Data Envelopment Analysis, and then computes intellectual capital and its sub-components within the Value Added Intellectual Coefficients model framework. Then, using the System Generalised Method of Moments, we investigate the impact of intellectual capital on changes in total factor productivity. According to our findings, productivity growth is primarily driven by efficiency changes rather than technological changes. Furthermore, regression results show that the intellectual capital index and its two sub-components, human capital and capital employed, have a strong positive impact on bank productivity. This research could help bank senior executives measure their productivity and intellectual capital, identify relevant intellectual capital elements that contribute to productivity and develop future policies to encourage and improve their intellectual potential. Furthermore, this is one of the few studies in the Indian context that examines the nexus between intellectual capital and productivity using the Malmquist Productivity Index. Full article

We study the impact of financial literacy on financial risk preference. When financial literacy is measured jointly by actual and self-assessed scores, we find compelling evidence of a valley-shaped relationship between actual financial literacy and risk preference. At a given level of self-assessment, as actual financial literacy increases, the willingness to take risks initially decreases and then rises. Actual financial literacy is modeled to impact risk preference through self-assessed financial literacy, the mediator; this mediation effect is significant. Furthermore, increasing actual financial literacy has a positive (negative) effect in underconfident (overconfident) individuals on several financial behaviors. Full article

This study aims to test financial literacy and credit conditions in determining formal credit access to determine the performance of MSMEs. This research includes the type of associative research that is accompanied by hypothesis testing. This research was conducted on MSMEs of as many as 324 creative industry players in four cities in East Java (Mojokerto, Pasuruan, Gresik, and Sidoarjo) with a sample size of 100 actors who had accessed formal credit using the stratified random sampling method for data collection. The results of Smart PLS analysis show that financial literacy and credit terms directly and significantly affect access to formal credit and MSME performance; formal credit access directly and significantly affects MSME performance. Likewise, financial literacy and credit terms indirectly affect the performance of MSMEs. These results mean that financial literacy and credit terms have a strategic role in explaining why access to formal credit is growing and is attracting MSMEs to strengthen capital to improve performance. Full article

The research purpose of this paper is to obtain an algorithm model with high prediction accuracy for the price of Bitcoin on the next day through random forest regression and LSTM, and to explain which variables have influence on the price of Bitcoin. There is much prior literature on Bitcoin price prediction research, and the research methods mainly revolve around the ARMA model of time series and the LSTM algorithm of deep learning. Although it cannot be proved by the Diebold–Mariano test that the prediction accuracy of random forest regression is significantly better than that of LSTM, the prediction errors RMSE and MAPE of random forest regression are better than those of LSTM. The changes in the variables that determine the price of Bitcoin in each period are also obtained through random forest regression. From 2015 to 2018, three US stock market indexes, NASDAQ, DJI, and S&P500 and oil price, and ETH price have impact on Bitcoin prices. Since 2018, the important variables have become ETH price and Japanese stock market index JP225. The relationship between accuracy and the number of periods of explanatory variables brought into the model shows that for predicting the price of Bitcoin for the next day, the model with only one lag of the explanatory variables has the best prediction accuracy. Full article

Across the globe, COVID-19 has disrupted the financial markets, making them more volatile. Thus, this paper examines the market volatility and asymmetric behavior of Bitcoin, EUR, S&P 500 index, Gold, Crude Oil, and Sugar during the COVID-19 pandemic. We applied the GARCH (1, 1), GJR-GARCH (1, 1), and EGARCH (1, 1) econometric models on the daily time series returns data ranging from 27 November 2018 to 15 June 2021. The empirical findings show a high level of volatility persistence in all the financial markets during the COVID-19 pandemic. Moreover, the Crude Oil and S&P 500 index shows significant positive asymmetric behavior during the pandemic. Apart from this, the results also reveal that EGARCH is the most appropriate model to capture the volatilities of the financial markets before the COVID-19 pandemic, whereas during the COVID-19 period and for the whole period, each GARCH family evenly models the volatile behavior of the six financial markets. This study provides financial investors and policymakers with useful insight into adopting effective strategies for constructing portfolios during crises in the future. Full article

Understanding how employees act at work to save energy and the meaning for sustainability and environmental protection is essential. This research aimed to analyze the influences of Subjective Norms (SN), Descriptive Norms (DN), and Environmental Knowledge (EK) on employees’ intention to save energy (ISE) in the Philippines (PH) and the Dominican Republic (DR). The effects of SN, DN, and EK on ISE were evaluated by comparing two developing countries and the mediation effect of EK on the relationship between DN, SN, and ISE. Confirmatory factor analysis (CFA), followed by structural equation modeling and path analysis based on samples collected from employees from DR (340) and PH (339), was performed. Also, construct convergent and discriminant validity were assessed using composite reliability, maximal reliability, average variance extracted, and maximum shared variance. The findings of this study indicate that SN influences ISE positively among employees in PH (β = 0.15, p < 0.05) but not among employees in DR. Descriptive Norms positively influence ISE among employees in PH (β = 0.47, p < 0.01) and DR (β = 0.27, p < 0.01), while EK has a positive and significant influence on the ISE among employees in PH (β = 0.22, p < 0.01) and not in DR. There is a partial mediation effect between SN and EK on ISE when EK is the mediator in PH, and no mediation effects for RD. The intention to save energy is significant in economic terms because reducing energy consumption can help decrease energy costs and improve business profitability and competitiveness; in social terms, it can reduce energy consumption worldwide and improve social health, reducing gas emissions and pollution. Full article

Entrepreneurial risk is an important factor that individuals must consider when starting their own business. The COVID-19 continues to rage, bringing great challenges to China’s economy and entrepreneurial activities. In this study, college students encounter greater entrepreneurial risks. There are two opposing views on the role of entrepreneurial risk in shaping individual entrepreneurial motivation: one view that risk is a threat, and the other view that entrepreneurial risk contains opportunity. Existing studies have discussed the issues from individual factors and environment factors, respectively, ignoring the combined effects of individual and environment factors. Person–situation transactions theory points out that individuals usually make their final behavior choices based on their comprehensive evaluation of environmental factors and themselves. Therefore, individual and environment factors should be integrated to investigate the effect of entrepreneurial risk on entrepreneurial motivation. Based on the person–situation transactions theory, this study establishes a theoretical model that entrepreneurial risk perception influences necessity and opportunity entrepreneurial motivation through entrepreneurial self-efficacy and discusses the moderating effect of entrepreneurship policy. A questionnaire survey was conducted on 595 fresh graduates from eight universities in China to obtain relevant data and the Structural Equation modelling was established to test the hypothesis. The results confirm that without the influence of external factors, college students regard entrepreneurial risk as a great threat, which not only weakens their entrepreneurial self-efficacy, but also reduces their necessity and opportunity entrepreneurial motivation. However, with the support of good entrepreneurial policies, entrepreneurial risk can be transformed into an opportunity to improve the entrepreneurs motivation driven by necessity of college students, but the impact on the opportunity motivation is not significant. This study deeply analyzes the dual characteristics of entrepreneurial risk perception in the process of shaping individual entrepreneurial motivation, expands the related research on entrepreneurial risk perception and entrepreneurial motivation, and has important implications for the government and universities to formulate entrepreneurial policies for college students. Full article

Extraordinary economic conditions during the COVID-19 pandemic caused many IFRS 9 impairment models to produce unreliable results. Severe market reactions, resulting from unprecedented events, prompted swift action from the regulatory authorities to maintain the financial system’s stability. Banks managed the uncertainty and volatility in the models with expert overlays, increasing the risk of biased outcomes. This study examines new ways of enhancing the governance and transparency of the IFRS 9 economic scenarios within banks and suggests additional financial disclosures. Benchmarking is proposed as a useful tool to evaluate the IFRS 9 economic scenarios and ensure effective challenge as part of a model risk governance framework. Archimedean copulas are used to generate objective economic benchmarks. Ideas around benchmarking are illustrated for a set of South African economic variables, and the outcomes are compared to the IFRS 9 scenarios published by the six biggest South African banks in their annual financial statements during the pandemic. Full article

Real estate markets are frequently affected by growth and contraction cycles. Given the social and economic impacts of changes on real estate prices, the understanding of these cycles is crucial from a socio-economic perspective, but also, and more importantly, from a public policy view. The literature has provided several contributions focusing on the deconstruction of the main determinants of housing prices. This research focuses on the analysis of housing prices variation with a particular emphasis on the analysis of the impacts of the 2008 financial crisis. Within the existing body of knowledge, few studies have focused on this particular issue, and even fewer have focused on countries where the financial crisis led to an external bailout, as was the case in Portugal. The analysis confirmed that the 2008 financial crisis had a negative impact on real estate prices, and the ex-post growth in GDP and low interest rates had a positive impact. The paper also provides a long-term analysis of housing price trends over the last decades. Full article

This paper reviews the case of nuclear energy. Currently, the worldworld is facing one of the greatest energy crises due to the Russo-Ukrainian war. This conflict has lead to limited sources of gas, causing a dramatic decrease in energy supply, leading to emerging energy crisis risks. This is one on the main purposes of reviewing nuclear energy as a possible energy alternative in the future. Apart from presenting the basis of nuclear energy and nuclear reactors, we attempt to compare this source of electricity with other renewable energy forms, such as solar, wind and hydroelectric power. Furthermore, we illustrate the benefits and drawbacks that have been observed regarding nuclear power as well as its contribution to economic growth and the impact it has had on the environment. It has been said that, with the use of nuclear power, air pollution will be reduced because of the elimination of greenhouse gases. However, nuclear power, apart from the final product, generates waste that in this case is radioactive, meaning that the management and disposal techniques are of the utmost importance. Of course, unfortunate events that involved nuclear power do exist and are unfortunately engraved in our memories. Both the nuclear accidents, such as Three Mile Island, Chernobyl and Fukushima, and nuclear weapons usage by military forces, the well-known atomic bombing of Hiroshima and Nagasaki, bring great controversy regarding the adaptation of nuclear power. As is presented in the paper, since the beginning of the new millennium the scheme of energy production and electricity production appears to have changed drastically. By using available data reported by BR, we illustrated that the production of energy and electricity has increased over the last 22 years (2000–2021) due to excessive demand; however, what is more important to mention is the share of both electricity and energy derived from renewable forms such as solar, wind and hydroelectric power. It is shown that more and more countries adopt those sources of energy than did in previous decades. It is crucial to note that it is not the science that causes catastrophic events, but rather the errors of humans. Full article

This study is based on the idea that Saudi Arabia’s Vision 2030 considered the achievement of economic diversification is very crucial for the economy. In turn, this target requires a sustained increase in the contribution of the manufacturing sector in Gross Domestic Product (GDP). At the same time, the transition towards industrialization might trigger high rates of CO₂ emissions, due to the escalated manufacturing demand for primary energy consumption (specifically fossil fuel). Ultimately, the high rates of CO₂ emissions would have severe environmental consequences, such as environmental degradation. These environmental consequences might be more dangerous in a country extensively dependent on oil, such as Saudi Arabia. The study aims to investigate the manufacturing and environment nexus in an attempt to explore the validity of the inverted U-shaped curve, the so-called Kuznets hypothesis, during 1971–2021. Applying the econometric model autoregressive distributed lag (ARDL), the findings of the study do not show evidence supporting the validity of an inverted U-shaped Kuznets function in Saudi Arabia during the period of the study. Furthermore, the short-term results do not confirm the impact of increasing manufacturing on CO₂ emissions. However, there are indications of positive effects, although limited, in the long-term. Full article

This paper introduces an alternate measure of idiosyncratic risk leveraged from the decomposition method to further eliminate the residual systematic risk inherent in the factor asset pricing model. Combining both complementary techniques contributes to a more comprehensive firm-level idiosyncratic risk that is crucial in both portfolio diversification and alpha investing. We focus our result on the idiosyncratic risk estimations and their behaviour on 36 emerging markets covering 39 industries. We show that the new measure exhibits a declining trend across time, consistent with the fact that emerging markets are becoming more integrated with the increased level of common effect across time. Full article

After the events in March 2020, it became clear to U.S. policymakers that the 2014 reform of the money market funds (MMFs) industry had not successfully addressed the stability concerns associated with surges in withdrawals. In December 2021, the SEC proposed a new set of rules governing how money market funds can operate. A fundamental problem behind the instability of money market funds is the expectation that backstop liquidity support will be provided by the government in the event of financial distress, along with the government’s inability to credibly commit to not provide such support. This expectation dampens funds’ incentives to take steps ahead of time to mitigate the risk of sudden withdrawals. The newly proposed reforms are aimed at constraining withdrawals or penalizing them with “swing pricing”. We argue that if the commitment problem is the fundamental issue, it would be more useful to reduce expectations of ex-post support by requiring MMFs to have contractual commitments in place, ex-ante, for liquidity support from private parties. Full article

This article examines the asymmetric volatility spillover effects between Bitcoin and alternative coin markets at the disaggregate level. We apply a frequency connectedness approach to the daily data of 11 major cryptocurrencies for the period from 1 September 2017 to 2 March 2022. We try to uncover the existence of the “fear of missing out” psychological effect and “pump-and-dump schemes” in the crypto markets. To do that, we estimate the volatility spillovers from Bitcoin to altcoin and the cryptos’ own risk spillovers during bull and bear markets. The spillover results from Bitcoin to altcoin provide mixed results regarding the presence of this theory for major cryptocurrencies. However, the empirical findings carried out by the cryptos’ own spillover effects fully confirm the existence of a fear-of-missing-out effect and pump-and-dump schemes in all cryptocurrencies except for USDT. Full article

This study focused on increasing firm value through CSR- and profitability-moderated investment decisions in emerging markets. A panel data analysis method was used for this study with a total of 215 observations of non-financial sector companies on the Indonesian Stock Exchange from 2018 to 2020. The results of the Chow test and the Hausman test showed that the fixed effect model with GLS was the most feasible. The model showed that there was a negative effect of investment decisions on firm value and the role of CSR and profitability strengthened this effect. Based on the results of the robustness check, the research model remained consistent with the results of previous studies. Investment decisions have a negative effect on firm value, and CSR and profitability moderate this effect, either when using other control variables or when using a different estimation model, which in this case was quantile regression. Our findings provide an understanding of the fact that investment decisions are important financial decisions for companies and that they can be controlled through good fund management and risk management. Full article

Cross-border acquisitions (CBA) are a form of foreign direct investments and have been dramatically increasing over the last three decades. India has been one of the top CBA destinations among emerging economies, making it interesting to explore the determinants. Even though the CBA research is voluminous, the role of economic freedom is understudied. In this background, by extending the knowledge of distance measures impacting cross-border acquisition (CBA) activities, we examine the impact of economic freedom distance on India’s inbound CBA volume and the moderating role of economic distance. We used a sample of 979 observations by collecting the CBA data from Thomson’s EIKON Mergers and Acquisitions database for our study period covering 1990 to 2020. We show that economic freedom distance negatively impacts India’s inbound CBA volume. Moreover, economic distance significantly moderated their effect. These results indicate that India should strengthen its economic freedom and grow steadily to attract more CBA volume inflow. These findings have important theoretical and practical implications for multinational firms and policymakers in making emerging economies like India an attractive destination for CBA activities. Full article

In economics, some transactions are conducted by the bid rate, and some are conducted by the ask rate. The spread between these two rates creates an essential cost and inefficiency for the economy. Taking these problems into account, the purpose of this study was to analyze the effects of macroeconomic and financial variables on the USD/TL exchange rate bid–ask spread for Türkiye using daily data spanning the period between 2 January 1990 and 2 August 2022. The quantile autoregressive distributed lag (QARDL) model was drawn upon to capture possible asymmetry in parameters and distinguish the results between different locations. The results obtained in this study may differ from the linear model and may change by the location, implying that the spread is reduced by the volume while it is increased by volatility and interest rates in the long run for some quantiles. Stock prices stir it in the long run, yet they decline it in the short run, indicating an asymmetry. Following the examples from the literature that analyzed the relationship via linear models, this paper employed a QARDL model for exploring location and sign asymmetry in the results for some quantiles. As the results indicate, efficiency in the bid–ask exchange rate spread can be controlled; therefore, it is our suggestion for policymakers to consider the extreme levels and asymmetry of the bid–ask exchange rate spread while evaluating its penetrating macro-financial variates. Full article

Recent literature shows that adopting an accounting information system (AIS) can lead to better decision-making, planning, efficiency and on-time management control, and organisational functionality. However, the impact of AIS implementation on role creation in the organisation is unclear. With the digital transformation of AIS and daily advances in machine learning and other innovative technologies, it is also unclear how these changes interact with human roles in organisations and which AIS components are considered essential. This paper addresses the above issues by applying the actor-network theory to examine the impact of deep machine learning modules in predicting the human actor roles in accounting information systems in organisations. We targeted 120 human actors and examined the influence of deep machine learning modules in predicting 11 personnel and professional features of human actors, based on multivariate statistical analysis. Our findings show that two human factors (familiarity with accounting information and time spent on becoming familiar with it) are the most influential elements that can predict the human actor roles in accounting information systems in organisations. So, human and non-human actors are both essential parts of an integrated AIS that must be considered. The current literature has focused on the AIS structure with less on the interaction between human and non-human actors. One of the main contributions of this study is providing evidence that AIS heavily relies on its human and non-human actors to form a coherent and united AIS network to promote AIS management strategies. The practical implication of the results is that investing in either technology or human resources alone is not enough to achieve the best productivity and performance in organisations. Instead, there must be a balance between human and non-human actors. Full article

The coronavirus disease 2019 (COVID-19) has significantly reshaped consumer behaviors in Saudi Arabia, as in most other countries worldwide, and it has played a critical role in rising commercial online activities. The purpose of this study is to test the factors affecting online shopping amid COVID-19 in Saudi Arabia. The five main factors identified from the literature review towards online shopping namely, product variety, convenience, payment method, trust, and psychological factors were analyzed and examined in the Saudi context. The research collected data online through a pre-tested instrument, which was directed to online Saudi consumers via different electronic tools, e.g., email and social media platforms. The results of a statistical analysis showed that only three factors have a direct significant impact on online shopping amid the COVID-19 pandemic. These factors were product variety, payment method, and psychological factors. Convenient and trust factors failed to have a significant impact on consumers’ decisions to shop online amid COVID-19. Both factors were less important for consumers, since shopping online amid COVID-19 has become most common among people. The result will assist e-commerce businesses to better meet consumer demands by adjusting their marketing strategies, especially in times of crisis. Full article

This paper examines the literature on paradoxes and tensions in interorganizational relationships (IORs) and identifies how such tensions are managed in interorganizational settings. In a systematic literature review, we analyzed 95 papers published between 1997 and 2021 on the subject of paradoxes in IORs. The sample showed a variety of paradoxes occurring in different interorganizational contexts, such as knowledge sharing and protection, short- and long-term orientation, and exploration and exploitation. The diversity of such paradoxes has led to crescent interest in cooperation. Our main results show that contextual factors and management practices influence the balance between paradoxes. Although the particular context of each IOR may be unique in terms of balancing paradoxical elements, we identified a set of “pre-tension practices” and “post-tension practices” which may help avoid the emergence of tensions or reduce their adverse effects. The findings of our systematic literature review have also enabled us to propose future research avenues concerning managing tensions in IORs, for instance, the link between paradoxes and IOR performance. Full article

The paper focuses on the relationship between firms’ characteristics and cross-section returns. The author reviews and critically assesses the most recent contributions in the literature. After comparing the abnormal returns (Alpha) and t statistics of the original works with those of replication works, the author concludes that 94 characteristics are robust. The limitation of the paper is that measurement errors in the COMPUSTAT could affect the predictability of cross-section returns. The practical implication of the paper is that the author validates the practice of fundamental analysis. Investors could benefit from those discovered characteristics. The author validates the policy consequence and connects the theoretical frameworks with empirical results. The author evaluates the empirical methodology and proposes several methods to improve future research. Full article

The article is aimed at increasing the probability of successful IT project completion by identifying the sources of 105 universal risks as well as establishing cause-and-effect relationships between these risks. The article presents the results of an analysis of 105 risks relevant to IT projects; five of them are commercial risks, 45 are compliance risks and 55 are project risks. Risk analysis was carried out using the 5Why, SWIFT and Harrington coefficients. Based on the results of the analysis, the root causes initiating the onset of risks were identified, such as the user, customer, project manager, project team, subcontractor and competitor. Moreover, it was found that the share of the users in the total number of risk sources is 2%, 15% for the customer, 43% for the project manager, 36% for the project team, 2% for the subcontractor and 2% for the competitor. The article also shows models of cause-and-effect relationships of compliance and project risks, presents the results of assessing the risks occurrence probability and their possible impact in cases of materialization, and establishes the most likely and dangerous scenarios in IT projects. The results obtained allowed the development of a criterion to assess the management maturity of a contractor (executor, supplier) planning to develop an computer program as part of an IT project. Full article

This paper studies the impact of a change in promoter shareholding on small-cap-value stocks. NIFTY Small Cap 250 index stocks within the top 20th percentile of the book-to-market (B/M) ratio of the same universe have been considered for this study. The paper uses regression analysis for understanding the impact of independent variables on returns. The universe is further narrowed down to stocks with a positive change in promoter shareholding, which is found to be negatively related to stock returns. In addition, although the book-to-market ratio does not play any role in the prediction of returns while within this narrowed-down universe, the size effect is present. The results are discussed with reference to some relevant past research literature, and the scope for further research is also discussed. Full article

AI (Artificial intelligence) has the potential to improve strategies to talent management by implementing advanced automated systems for workforce management. AI can make this improvement a reality. The objective of this study is to discover the new requirements for generating a new AI-oriented artefact so that the issues pertaining to talent management are effectively addressed. The design artefact is an intelligent Human Resource Management (HRM) automation solution for talent career management primarily based on a talent intelligent module. Improving connections between professional assessment and planning features is the key goal of this initiative. Utilising a design science methodology we investigate the use of organised machine learning approaches. This technique is the key component of a complete AI solution framework that would be further informed through a suggested moderation of technology-organisation-environment (TOE) theory with the theory of diffusion of innovation (DOI). This framework was devised in order solve AI-related problems. Aside from the automated components available in talent management solutions, this study will make recommendations for practical approaches researchers may follow to fulfil a company’s specific requirements for talent growth. Full article

This paper aims to analyse the ways in which risk management has been embedded in management control systems in Italian municipalities. Through a qualitative method, this study presents multiple case studies from six municipalities with two levels of analysis: content analysis on the information published on the institutional website, and interviews through a questionnaire with open and closed questions addressed to the public managers of the Italian municipalities selected. Moreover, the municipality respondents were classified into medium (two municipalities with over 50,000 inhabitants), medium-high (two municipalities with between 100,000 and 500,000 inhabitants), and high (one municipality with over 500,000 inhabitants). The multiple case studies reported show how there is not a strong level of integration between risk management and the management control system in use. This research is useful to sustain the debate about risk management in the public sector. It should help practitioners and scholars to cover their municipalities’ needs. Full article

We report on the results obtained from ten annual surveys of global business executives on their perceptions of the most significant risks facing their organizations in the ensuing calendar year. These surveys of C-suite executives, directors and other risk professionals elicit their concerns about risks that may affect their organization’s success over the near-term horizon (i.e., the next calendar year). After a decade, we believe these results provide an opportunity to examine how the global risk landscape has evolved. In addition, two additional survey questions allow us to examine how these executives view the overall risk context and how enterprise risk management (ERM) is deployed and augmented in the face of an escalating risk environment. On average, we find that executives view the risk landscape they face as persistently risky over the ten-year period, even during the relatively robust economic environments for much of that time frame. Two industries report much more volatility in their risk environments, with respondents from the Healthcare sector and in Technology, Media and Telecommunications acknowledging the largest volatility. We also observe an increase in entities’ decisions to devote more time and resources to risk management over the ten-year period, suggesting that ERM has become an essential mechanism for organizational success. Our goal is to highlight the realities of constantly changing risk conditions and how context (e.g., industry and time) is an important distinguishing factor that affects an organization’s given risk profile, which is relevant to both executives and academics. Collectively, our findings emphasize the importance of understanding the ever-changing context of an organization’s environment, that risk identification must be an ongoing process, and that there is no “one-size-fits-all” approach to risk governance. We believe all this signals the importance of future research to help organizations respond with robust risk governance. Full article

This study mainly aims to test the impact of gender diversity on a firm’s performance. Namely, the non-linear and the quantile impact on the listed companies in Palestine Exchange during the period 2010 to 2020. The study also aims to determine the impact of a firm’s internal characteristics on gender diversity. The study uses instrument analysis, traditional panel models, and quantile regression to fulfil the aims. The results demonstrate the existence of a critical mass for the impact of gender diversity on firms’ performance and that mass is about 30% for the ROA and 41% for the EPS. Full article

This study aims to examine the effect of entrepreneurship education and artificial intelligence (AI) development on entrepreneurial intentions while investigating the mediating role of perceived behavioral control. The proposed model also accounts for individual and contextual socioeconomic factors. This study tries to fill the gap in the entrepreneurship literature, which is still lacking with respect to the impact of new technologies on entrepreneurship intentions and shows conflicting results regarding the influence of entrepreneurship education. Our study surveyed 223 business students in Lebanon. The context of this study is of high importance, particularly since the country is currently facing a deep, multifaced political, economic, and financial crisis, and entrepreneurship might be considered an important channel for generating basic sources of income, steering the recovery process, and increasing Lebanese resilience against this highly unstable economy. The structural equation modeling technique (SEM) was conducted to validate the hypotheses. The results show that perceived behavioral control fully mediates the relations between performance expectancy of AI solutions, entrepreneurship education, and entrepreneurial intention. Risk aversion and social support exert a direct impact on entrepreneurial intentions. The findings highlight the need to account for entrepreneurship education and AI development when analyzing entrepreneurial intentions. Full article

We investigate how state-owned corporate venture capital differs from privately owned corporate venture capital in fostering innovation among startups. Based on the data of Chinese A-share listed companies and the startups in their portfolios that they invested in between 2009 and 2018, we find that startups backed by state-owned corporate venture capital are less innovative than startups backed by privately owned corporate venture capital. Using a two-stage least-squares analysis yields the same results. Further, we find evidence consistent with two potential mechanisms: Investors of state-owned corporate venture capital provide weaker technical support and are less tolerant of failure. These results have important implications for stakeholders, management, and policy makers who care about incentivizing young and rapidly growing companies to innovate more effectively. Full article