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This paper aims to investigate how the relation between stock returns of US firms and West Texas Intermediate (WTI) oil prices is affected by leverage from 1990 to 2020.

This paper examines how the relationship between stock returns of US firms and WTI oil prices is affected by leverage from 1990 to 2020 using a fixed-effect model estimation framework.

Results from the fixed-effect regression models suggest that leverage effects on stock returns are pervasive both in aggregate and cross-industry levels, while the mining industry is more sensitive. In addition to the positive oil price effects attenuated by leverage at the aggregate level, the authors observe stronger marginal effects of leverage only for the mining sector. Being more exposed to commodity prices, the positive effects of oil prices on stock returns in the mining sector are offset by large debt ratios. Asymmetries, effects of debt maturity structure and implications are also discussed.

This study is grounded on the contemporary cash flow claim of leverage NOT on the long-run effect of leverage considering cash flow constraints. The oil price increase is assumed to represent an advancement of the overall economy. This study does not capture the oil prices response to some other economic forces and vice-versa.

Mining companies should therefore reduce the stock of debt with respect to their assets to make possible the “pass-through” from oil prices to the stock market.

Previously undocumented and the authors show that leverage reduces the total effect of oil prices on stock returns, consistent with the hypothesis. Asymmetric and debt maturity structures effects are also discussed.

The purpose of this is paper is to pay a closer look at the 2008-2009 financial crisis (and its aftermath) and analyzes stock returns of nine major US oil companies as well as the oil and gas sector under daily data from January 1992 to April 2012.

The authors adopt the arbitrage pricing theory model to examine the relationship between stock returns and their influences including oil price return, yield spreads, and US dollar index return. The authors also provide a test for structural changes in each regression model of return series to capture for multiple breaks. To examine the asymmetric effect of oil price returns on stock returns, the authors separate oil price returns series into two series: positive changes in oil price and negative changes in oil price.

The authors find stock returns of oil companies as well as the oil and gas sector are positively affected by oil prices and have stronger effects in the downward direction. Interestingly, The authors find the effects of oil price movements on stock returns increase over time. The authors examine the possibility that investors wishing to hedge against a weakening USD invest in US oil companies and find that more than half of these companies benefit from a weaker USD against the JPY, while all strongly benefit from a weaker USD against major currencies.

The authors employ daily data for two-decade period including the last global financial crisis. Due to the long-term period covered in this study, sequential Bai-Perron tests are used to detect structural breaks of stock return series. In addition, the data-dependent procedures result in good specifications throughout with white-noise processes in almost all cases.

The purpose of this paper is to examine what happens to the variance of individual stocks forming the Dow Jones Industrial Average (DJIA) allowing for aggregate uncertainty measured by VIX, the “fear gauge index” of US options contracts. In examining each individual stock belonging to DJIA in 2011, the authors reconsider aggregate market uncertainty (VIX) as the mixing variable. In contrast to studies on the effects of VIX on the aggregate equity market, the data set used in this paper allow a further look at the proposition that market aggregate uncertainty should have varying impact on individual stock variance.

GARCH-M models estimate individual stock returns belonging to the DJIA in 2011 on its lags and on the ARCH-M term in the mean equation linking stock returns to the variance equation. The longest time span has 5,738 observations for most stocks under daily frequency from January 3, 1990 to December 30, 2011. The authors use one lag for the VIX2 term to address simultaneity problems in the variance equation. In order to allow for interactions between volatility and business cycles, the authors include a dummy variable for the three recessions identified by the NBER over the period.

Adding the “fear gauge” VIX index and a dummy variable for recessions to the variance equation in GARCH-M models, the VIX coefficient always increases variance and the recession dummy has mixed effects. Overall, VIX acts as expected as mixing variable. Supporting the mixture of distribution hypothesis, the impact of VIX is always positive (1.039 on market variance) and GARCH effects vanish completely for the index and almost as much for 24 stocks.

In theory, the effects of VIX on stock variance should be positive and statistically significant, together with reductions of GARCH persistence. The authors find this to be the case for the aggregate stock market and for 24 out of its 29 DJIA stocks. The authors leave for further work extensions to estimating the variance equation for companies very exposed to idiosyncratic changes, such as oil price fluctuations or stock buybacks. The implication of this research for the academic or financial community relies on the estimation of VIX effects on individual stock variance, controlling for business cycles.

Due to its benchmark in equities, stocks in the Dow Jones Industrials make it a very interesting case study. This paper reconsiders the aggregate uncertainty hypothesis for two main reasons. First, the financial press and traders keep a very close track on the daily evolution of VIX. Second, recent research emphasizes the formal predictive power of VIX in US stock markets. For the variance equation, existing works report positive values for the VIX-coefficient on the S&P 500 index but they have not examined individual stocks as the authors do in this paper.

This study aims to expand the existing body of knowledge on crowdfunding (CF) motivational patterns with special reference to intangible factors, which most scholars assume to be the most important ones, especially in non-investment-based CF. The purpose is to understand how the presence of an established brand in a CF campaign can affect backers’ funding choices and the reasons behind them. To this end, the authors combine principles from identification, brand relationship and self-determination theories.

The authors considered the (altruistic in nature) domain of CF for social causes as the most widespread type of branded CF and chose the relevant empirical setting of “research CF” run by universities which seem to be more and more interested in connecting branding and fundraising efforts through the active involvement of their “relational circles”. Accordingly, the authors surveyed an extensive sample of students as a primary stakeholder group of potentially engaged backers from one of the first Italian universities to launch a CF program and used structural equation modelling to test the research hypotheses.

The authors found that, despite the CF domain considered, the choices made by backers (counterintuitively, women, in particular) manifest themselves as mostly self-oriented. This is partly explained by brand identification, which fully mediates the effect of brand pride and partially mediates the effect of brand respect (BR) on funding intention. Moreover, BR also directly drives CF choices.

This study portrays a remarkably different CF playground compared with conventional campaigns for both project proponents and backers with several theoretical and managerial implications.

With the increasing use of crowdfunding platforms in raising funds, it has become an important and oft-researched topic to analyze the critical factors associated with successful or failed crowdfunding. However, as a major subject of crowdfunding, medical crowdfunding has received much less scholarly attention. The purpose of this paper is to explore how contingency factors combine and casually connect in determining the success or failure of medical crowdfunding projects based on signal theory.

The paper adopts the crisp-set qualitative comparative analysis to analyze the causal configurations of 200 projects posted on a leading medical crowdfunding platform in China “Tencent Donation.” Five anecdotal conditions that could have an impact on the outcome of medical crowdfunding campions were identified. Three relate to the project (funding duration, number of images and number of updates) and two relate to the funding participants (type of suffer and type of fund-raiser).

The results show that diversified configurations of the aforementioned conditions are found (six configurations for successful medical crowdfunding projects and four configurations for failed ones).

Despite the fact that there are a considerably large number of medical crowdfunding projects, relatively few researches have been conducted to investigate configurational paths to medical crowdfunding success and failure. It is found that there are certain combinations of conditions that are clearly superior to other configurations in explaining the observed outcomes.

Information opacity in donation crowdfunding activities has constrained the healthy development of China’s public welfare activities. Addressing the trust crisis and enhancing public engagement warrants further investigation. This study aims to uncover the moderating effect of activity transparency by utilizing data from 1,029 donation crowdfunding projects on the Sina Weibo Public Welfare Social Platform. In this way, we seek to elucidate the impact of donation crowdfunding events on fundraising ability.

This study selects text complexity, number of supporters, creator experience, and social capital as explanatory variables; innovatively selects the number of updates of online crowdfunding activities and total reading volume as moderating variables; selects the number of shares of crowdfunding activities as a mediating variable; and constructs a moderated mediation multiple regression model for fundraising ability.

Our findings indicate that independent variables, such as text complexity, number of supporters, and social capital, can significantly affect the dependent variable, fundraising ability. However, creator experience does not influence fundraising ability. Furthermore, social interaction has a mediating effect, whereas activity transparency has a reverse moderating effect. These results indicate that social interaction can enhance the fundraising ability of donation crowdfunding events. However, with an increase in information transparency, the fundraising ability of social media decreases.

The originality of this research is in clarifying the internal factors affecting fundraising ability through induction, making bold assumptions, and focusing on how social media’s effective interaction and activity transparency will affect public welfare crowdfunding fundraising ability.

The paper aims to examine the unique nature of crowdfunding and its association with supporters' well-being, measured by Seligman's (2011) well-being theory and its five elements of PERMA: positive emotions, engagement, relationships, meaning and accomplishment.

22 structured interviews were conducted with supporters of crowdfunding projects. The interviews were analyzed using deduction, generating themes and assigning them to the relevant PERMA elements.

Almost all interviews included five or four PERMA elements, supporting the hypothesis about crowdfunding as a form of economic behavior that is triggered by the desire for fulfillment in life. The authors found that the tendency to become a serial crowdfunder is triggered by PERMA and a sense of trust.

This is the first study that presents a well-being theory of non-investment crowdfunding contributions. Based on the interviews, we suggest a theory linking the motivation for backing current and future projects with PERMA elements, sense of trust and the nature of adaption to activities with intrinsic attributes.

This conceptual paper focuses on a common observation in the implementation stage of reward-based crowdfunding (RBC) – entrepreneurs' failures and delays in delivery of rewards to investors, which, in turn, may be perceived as violations of reward delivery obligations.

Drawing on entrepreneurial personality theory and psychological contract theory, this paper develops propositions and identifies factors related to both entrepreneurs (overconfidence and narcissism) and factors related to investors (types of motivators and psychological contracts) that may explain the perceived violations of reward delivery obligations. Implications for theory and practice are also discussed.

The theoretical analysis, by wielding two independently developed literatures, has demonstrated that it is important to investigate factors that are related to both investors and entrepreneurs in understanding issues and challenges at different stages of the RBC model. The authors believe that the current analysis provides an integrated understanding and a solid foundation for researchers to further examine these issues by empirically testing these propositions.

The authors examined two previously understudied psychological factors in the context of RBC – entrepreneurial traits, mainly overconfidence and narcissism, and the type of psychological contracts formed between investors and entrepreneurs, both of which, according to McKenny et al. (2017), need greater attention from researchers studying crowdfunding.

The purpose of this paper is to propose a decision support model to prioritize equity crowdfunding (ECF) evaluation criteria under an uncertain environment.

The proposed decision support model first identifies a holistic list of evaluation criteria and subcriteria. These criteria are then analyzed using the analytic hierarchy process (AHP) method in an interval-valued intuitionistic fuzzy (IVIF) environment to identify the relative importance attached by crowdfunding investors to five sets of evaluation criteria (fundraiser, platform, project, campaign and investment characteristics) and their associated subcriteria. The proposed decision support model and ECF evaluation criteria were empirically examined using a real-life case study from January to February 2023.

The case study illustrated that the decision support model enhanced fairness and transparency in the prioritization of ECF evaluation criteria. Project characteristics were the most important criterion, followed by fundraiser characteristics and investment characteristics. These results can serve as a benchmark to help crowd investors choose ventures more wisely and make better investment decisions.

The tasks of modeling and prioritizing ECF evaluation criteria are relatively rarely addressed in the literature, especially under uncertainty. This study is one of the first attempts to use the AHP to explore ECF evaluation criteria in an IVIF environment; in particular, it sheds light on the importance that crowd investors attach to criteria related to fundraiser, platform, project, campaign and investment characteristics.