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The purpose of the study was to classify donors who make large donations and those who make small donations to athletics programmes. In particular, the study investigated the degree to which involvement with the athletics programme, income and donor type discriminate individuals who make large donations from those who make small donations in an effort to predict donation level of prospect donors. The hypothesis that the three variables (involvement with the athletics programme, income and donor type) would classify athletics donors of small donations from athletics donors of larger donations was confirmed. The findings of the study provide theoretical and practical implications in predicting donation size, determining donor cultivation strategies and increasing fundraising effectiveness.

Corporate donation behavior sends two financial-related signals, i.e. sufficient cash flow and self-confidence in future earnings. This paper aims to investigate whether these financial-related signals released by corporate donation drive investors to make more optimistic forecasts about the firm’s future earnings per share (EPS) and whether this effect varies across different historical earnings trends.

This study is based on a controlled online experiment with 553 MBA students.

The results demonstrate that a financial signaling mechanism works, but it is moderated by historical earnings trends. When the earnings trend is always increasing, the more the number of financial signals received, the higher the investors’ EPS forecast; when the earnings trend is fluctuating (down then up or up then down), investors’ EPS forecast is higher when they receive financial signal(s) than when they do not, but no additive effect occurs from receiving one signal to two signals; when the earnings trend is always decreasing, investors’ EPS forecast is irrelevant to the number of financial signals received.

To the best of the authors’ knowledge, this study is the first to experimentally investigate a possible mechanism to explain investors’ positive response to corporate social responsibility (CSR) (specifically, corporate donation) disclosures – the financial signaling mechanism. This study also extends the research on the impact of financial information on investors’ use of nonfinancial information by investigating the moderating role of historical earnings trends on the financial signaling mechanism of the CSR effect.

A key goal of this research is to examine empirically whether politically connected board members are likely to impact corporate philanthropy. A further goal of this study is to contribute to the existing literature by examining the moderating role of political connections on the relationship between family ownership and corporate donations.

Based on the content analysis approach, the authors determined the level of cash and in-kind donations made by a group of 94 non-financial Jordanian companies listed on the Amman Stock Exchange. This study examined 658 annual reports spanning over seven years from 2010 to 2016. Ordinary least squares regression (OLS) is used to test the study hypotheses. In addition, this study used the probit regression to validate those results reported by the OLS regression.

Compared to unconnected companies, politically connected companies in Jordan are more likely to donate to philanthropic causes. Moreover, the results revealed that the presence of significant family ownership shareholding in a firm can weaken the firm tendency to donate. Despite this, the regression analysis results indicate that family-controlled firms with political connections are more likely to engage in charitable giving activities compared to those without political nexuses.

The study contributes to the conversation surrounding corporate giving and sheds light on the role political connections and ownership structure (particularly family-owned firms) play in affecting donations by firms.

Managers of Jordanian firms listed on the stock exchange can use the study's findings to make better decisions about their donations and other philanthropic activities.

This study is the first to examine the relationship between firm donations and political connections in Jordan, and how political nexuses can moderate the relationship between family ownership and corporate donations. Hence, it extends prior research significantly.

Extant research shows mixed results on the impact of expressed negative emotions on donations in online charitable crowdfunding. This study solves the puzzle by examining how different types of negative emotions (i.e. sadness, anxiety and fear) expressed in crowdfunding project descriptions affect donations.

Data on 15,653 projects across four categories (medical assistance, education assistance, disaster assistance and poverty assistance) from September 2013 to May 2019 come from a leading online crowdfunding platform in China. Text analysis and regression models serve to test the hypotheses.

In the medical assistance category, the expression of sadness has an inverted U-shaped effect on donations, while the expression of anxiety has a negative effect. An appropriate number of sadness words is helpful but should not exceed five times. In the education assistance and disaster assistance categories, the expression of sadness has a positive effect on donations, but disclosure of anxiety and fear has no influence on donations. Expressions of sadness, anxiety and fear have no impact on donations in the poverty assistance category.

This work has important implications for fundraisers on how to regulate the fundraisers' expressions of negative emotions in a project's description to attract donations. These insights are also relevant for online crowdfunding platforms.

Online crowdfunding research often studies negative emotions as a whole and does not differentiate project types. The current work contributes by empirically testing the impact of three types of negative emotions on donations across four major online crowdfunding categories.

Governments often encourage charitable giving through the tax system, by a deduction or tax credit. In 1988, Canada moved from a deduction system to a tax credit system. The tax credit for donations above $250 was calculated at the highest tax rate, even if the taxpayer was at the lowest tax rate. This gives what can be called a “superdeduction.” At the same time, the top rate of tax was reduced. Thus, the cost of giving was reduced for the lower taxpayers and increased for the higher-income taxpayers.

The article reports whether taxpayer behavior changed from 1986 (pre reform) to 1988 and 1992 (post reform). The analysis also investigates the influence of inflation on the charitable donations. The percentage of taxpayers giving over $250 was analysed for both all the taxpayers and those consistently in the low and high tax brackets. The lower-income taxpayers were found to reduce their giving, contrary to expectations. The middle-income taxpayers, in general, increased their giving, which was expected and so took advantage of the superdeduction. The results of the moderate high-income taxpayers were mixed. Taxpayers who had very high incomes decreased their giving, as was expected.

This chapter provides a comprehensive review of several social-cognitive models that have been lately applied in public health and donation contexts. The current review included the elaboration likelihood model (ELM), the prototype willingness model (PWM), and the organ donation model (ODM). This review also details and discusses the main strengths and limitations of these models. Importantly, this review helps to identify the gap of the current social marketing and health-care literature. In particular, this chapter provides a solid theoretical foundation and has initiated further pathways for future researchers who are interested in the fields of public health and social change literature, organ donation context, as well as social-cognitive decision-making models. The significance of this review is defined by advancing public health practitioners, social marketing communicators, and educationalists, evidencing how conceptual models can inform and guide the research.