A Model to Explain Charitable Donation - Health Care Consumer Behavior

ABSTRACT - This paper deals with the choice process of individuals for making charitable donations to non-profit organizations. Specifically, a Donating Behavior Model (DBM) is proposed, to assess the criteria with which consumers base their decisions concerning giving to one non-profit organization as opposed to another. The focus of the paper is on validating the antecedent and consequent variables proposed in the model of charitable donations in the case of limited donation budgets. The results indicate that severity, involvement, predominance and alleviation are good predictors of importance, and that importance in turn is a good predictor of donating behavior.


Jerry A. Rosenblatt, Alain J. Cusson, and Lee McGown (1986) ,"A Model to Explain Charitable Donation - Health Care Consumer Behavior", in NA - Advances in Consumer Research Volume 13, eds. Richard J. Lutz, Provo, UT : Association for Consumer Research, Pages: 235-239.

Advances in Consumer Research Volume 13, 1986      Pages 235-239


Jerry A. Rosenblatt, Concordia University

Alain J. Cusson, University of Sherbrooke

Lee McGown, Concordia University


This paper deals with the choice process of individuals for making charitable donations to non-profit organizations. Specifically, a Donating Behavior Model (DBM) is proposed, to assess the criteria with which consumers base their decisions concerning giving to one non-profit organization as opposed to another. The focus of the paper is on validating the antecedent and consequent variables proposed in the model of charitable donations in the case of limited donation budgets. The results indicate that severity, involvement, predominance and alleviation are good predictors of importance, and that importance in turn is a good predictor of donating behavior.


Charitable donations are an important issue in our society. The increasing number of non-profit organizations which conduct annual or periodic fund raising campaigns have made it difficult for the consumer to allocate his donations. As consumers do not have unlimited budgets, they must use decision strategies not unlike those required in a product choice situation. Dichter (1972) concluded that a major motivating factor for blood donors is the belief that they are probably helping themselves. It can be considered that the act of giving to any non-profit organization partly constitutes an act wherein the donor is either purchasing 'personal insurance', is attempting to alleviate personal guilt or is obtaining some other such personal benefit. Kotler (1975) posited that consumers expect an exchange process in a social marketing context similar to the exchange process implied in the classical definition of marketing (AMA 1960). The act of donating viewed in this light can clearly be viewed as an exchange process.

The present research considers that the act of contributing to any non-profit organization, and in particular to a fund raising campaign, corresponds to the act of buying. The altruistic feeling of helping others, or the feeling of security, hoping that one day the individual will benefit from the contribution, are considered potential motivators (eg. the belief that contributions to cancer research could help in the finding of a cure that could one day save that individual's life). The act of donating funds is then considered as a purchase, in that a consumer is investing in some security. It is argued that the perceived risk toward the cause defended by the non-profit organization would be very important in triggering the behavior. Perceived risk would not inhibit the buying situation, but would instead initiate the process by which the consumer would eventually make his/her decision. The contribution could then have the effect of lowering the perceived risk for that Particular cause.

This paper proposes a Donating Behavior Model (DBM) partly based on the Health Belief Model (HBM - Becker 1974; Rosenstock 1966 ) and the Behavior Intentions Model (BIM - Fishbein 1967) . The present model is similar to HBM in that even if the service is not performed immediately, the act of giving for a social cause implies the act of buying a service more preventative than compulsory. The HBM is thus adapted to render it more suitable to any type of non-profit organization's fund raising. It is suggested that the model could be generalized to all cases where charitable donations (i.e. financial contributions or volunteer aid) are made to non-profit organizations.

Health Belief Model (HBM)

Rosenstock (1966) first proposed the Health Belief Model. It was derived from a value-expectancy framework in the attempt to predict the probability of an individual engaging in a preventative health care action. It was argued that three factors contributed to this decision: 1) a benefits-barriers analysis of the advantages and disadvantages of the health prevention activity; 2) the perceived threat associated with the condition or illness; and 3) various cues-to-action which include both mass media and interpersonal communications. The complete model is depicted in Figure 1.



Oliver and Berger (1979) have noted that while this model is widely accepted among medical sociologists there are a number of problems that have not been resolved, including: a) the HBM is more a collection of variables than a formal theory or model; and b) there are serious measurement problems - it is not uncommon to find identical constructs operationalized totally differently from study to study with the same disease under consideration.

Behavioral Intentions Model

Fishbein (1967) proposed the behavioral intentions model which stated that behavior is a function of the intention to perform that behavior. Intentions are then posited to be best predicted by two components: the attitude toward the act, and a subjective norm. The complete Fishbein Behavioral Intentions Model is depicted in Figure 2.



Oliver and Berger (1979) note that the Fishbein model has been used sparingly in the field of health care, although it has been argued that it is a good alternative to the HBM (Jaccard 1975). Results using the BIM in the field of health care have been demonstrated its usefulness. Jaccard and Davidson (1975) reported that the BIM was a valid predictive framework and more parsimonious than others. Schlegel, Crawford and Sanborn (1977) found that the addition of 33 variables exogenous to the BIM resulted in only a seven percent increase in explained variance.

The Proposed Donating Behavior Model (DBM)

Referring to the HBM and BIM, Oliver and Berger (1979) argued that,

...both models explained a statistically significant portion of the variance in behavioral intention... Consequently, practitioners can, with some degree of confidence, apply concepts in the models to the decision-making process used by their organization... In addition, researchers concerned with the most complete determination of health care decisions (eg. when an epidemic is imminent) may wish to combine further improve prediction (p.120).

This paper reports a first attempt to build a better health care/donating behavior model using variables from both the HBM and BIM as well as additional variables. The variables included from the previous models are behavioral intention, perceived severity and perceived threat. It is suggested that examining other variables including involvement, perceived possibility of alleviating the condition, perceived predominance (visibility) of the condition, and the importance for the individual of giving to a particular non-profit organization, is essential for the understanding of donating behavior. Specifically, the variables of the proposed model are:

Involvement: Valence (1981 ) has argued that perceived risk can be synonymous with involvement. Valence points out 6 similarity criteria with respect to involvement and perceived risk. The DBM considers an individual perceiving a certain risk associated with a particular situation to be more highly involved than an individual who perceives no risk of being affected by the situation.

Alleviation: This refers to the perceived possibility of alleviating the condition or situation with the health care action. Incorporating Dichter's (1972) belief concerning the reasons why individuals donate blood, and Kotler's notion of an exchange process, it is herein accepted that individuals attempt to maximize the utility of their health care actions (eg. donations, volunteer work). Thus, an individual would like to believe that his contribution of money or effort will in some way alleviate the actual situation as he perceives it. This construct is similar to the perceived benefits proposed by Zaltman and Vertinsky (1971).

Perceived Severity: Zaltman and Vertinsky (1971) and Becker and Maimon (1975) proposed a measure of perceived seriousness or severity of the cause. The construct is herein used in a broader sense, measuring how an individual perceives the serious of any social cause.

Perceived Predominance: Similar to the cues-to action in the HBM, predominance is a way of measuring the visibility of the situation defended by the non-profit organization. It is suggested that more visible situations act as a reminder of the cause. For example, not all consumers perceive diseases or starvation as equally visible. Among diseases, some are more visible than others. The recent example of African famine is an excellent example. It appears that with the tremendously increased activities concerning the famine in Africa, individuals are starting to act.

Importance of Giving: As in the BIM, it is important to measure the extent to which consumers want to contribute. In the HBM, only the probability of contributing is measured. The inclusion of the measure of importance makes it possible to know whether or not the consumer would contribute if they were not given easy access. In the case of charitable donations, consumers must be given the opportunity to contribute, as in regular buying situations. There is probably an inverse relationship between the importance of giving and the required level of easy access.

The entire model is depicted in Figure 3. As shown, it is believed that importance is an intermediate variable between the donation (or any health care act) and the other four predictor variables. Importance of giving is hypothesized to be determined by the severity of the situation, the predominance of the condition, the possibility of alleviating the situation and consumer involvement (as measured by perceived risk). Importance of giving, in turn, is hypothesized to be the best predictor of the health care act, in this particular situation, the amount of the charitable donation.



The importance construct is defined as the perceived necessity for a specific consumer to contribute to a non-profit organization. A consumer may consider it to be very important to contribute to cancer research, and may also consider it important (but less important) to contribute to his church. It is suggested that more of his budget would be spent on cancer research. Thus, it is proposed that consumers facing a donation choice, would rank the organization according to their perceived importance, and their donations would reflect this ranking.

It is suggested that this model is not only applicable to actual financial donations but could be generalized to giving behavior of all types and for M l kinds of non-profit organizations.

Relationships Among the Variables

The relationships between.the variables indicate that a consumer considers the perceived severity of a situation (eg. the severity of an illness or disease, the size of the local orchestra's deficit); the degree to which the disease or issue affects his personal life (involvement - dying from heart disease, losing the opportunity to attend live music concerts); the predominance of the situation, or the extent to which the problem is highly visible (wheel chairs, muscular problems as opposed to high blood pressure, also media visibility); and the potential to alleviate the problem with his donation (eg. feeding one child for a year in Africa with a $25 contribution).

Given these variables, a consumer rates all possible alternatives in terms of the necessity for him to contribute. This rating then serves as the basis for the donor to divide his available budget for charitable donations.

The following section reports the results of a pilot study to test the model using financial donations to charitable organizations as the dependent measure.

Objectives of the Research

The objectives of this pilot study were three-fold:

1) to validate the proposed DBM;

2) to demonstrate that importance of giving is a good predictor of behavioral intention; and

3) to generalize a model that could be applied to any type of non-profit organization's fund raising campaign.

Research Method

The study was conducted in the months of February and March, 1985 in the Province of Quebec. A questionnaire was distributed to 100 individuals who were asked to complete the questionnaire in the presence of the researcher. of the 100 questionnaires handed out, 86 were considered usable. The sample consisted of 43 males and 43 females. with an average age of 35 years, family income of over 20,000 per annum. Most were married with an average of one child.

The Questionnaire

The questionnaire was structured and contained three parts. The first section contained questions concerning previous donations. In addition, the respondent was placed in a situation wherein he/she was "given" $100 and asked to distribute the funds among 10 charitable organizations. The respondent was told to allocate the funds in any way, and that it was not necessary to contribute to all organizations. The list of organizations is as follows:

* Research on cancer ..........................................$        

* Local hospital foundation ..................................$        

* Research on lung disease ..................................$        

* Research on child disease .................................$        

* Local Church charity ........................................$        

* United Way .....................................................$        

* Research on cardio-vascular disease ................$        

* Help for alcoholics ...........................................$        

* Help for Third-World Countries .......................$        

* Half-Way houses for women young offenders ...$        

The second part of the questionnaire contained a number of questions measuring the five independent variables in the DBM. In all cases, 7-point semantic differential scales were utilized (eg. It is "very important "very unimportant" for me to support research into cardio-vascular disease, etc.). Other variables not related to the present study were also measured. The third part of the questionnaire contained the demographic variables previous reported.

Data Analysis

The dependent variables in the study are the amounts given to each of the non-profit organizations. Every respondent indicated the amount he/she would contribute to each of the ten charities. In addition each individual responded to the five independent measures (i.e. severity, involvement, alleviation, predominance and importance).

In order to validate the model a multiple linear regression was first used with all five independent measures and the level of donation as the dependent measure. Next, a multiple linear regression was utilized using the four independent measures that were hypothesized to predict importance, and a simple regression using importance as the independent measure and donations as the dependent measure. Finally, a partial correlation was computed for donation with respect to the four independent measures (i.e. severity, alleviation, predominance and involvement) controlling for importance. A significant fall in the correlation coefficients would then indicate that importance would depend on the four independent variables, and that it in turn, is related to the amount of the charitable donation.

Path Analysis Procedure

A path analysis procedure is used to evaluate the model. Importance is regressed on the four proposed antecedents using ordinary least squares regression (Duncan, 1975; Wright, 1934) to determine if the independent variables account for the variance in importance. Evans (1978) and Oliver and Berger (1979) applied path analysis to BIM and HBM respectively. This technique appears to be an ideal procedure for testing the proposed model. In functional form, the investigated relationships appear in Table 1.




The results of the multiple regressions and the path coefficients obtained with the variables suggested by DBM are presented in Table 2.

The results indicate that the level of donation can in part be explained by these variables. All regression equations are significant at p < .05 with the exception of cancer research and heart research. The percentage of explained variance (for the significant equations) varied from .10 to 20.

The path coefficients clearly indicate that the importance of a specific cause is the single best predictor of donating behavior. Further, the results suggest that it is much easier to predict importance than behavior.

The results indicate that the four independent variables explain a significant amount of the variance of the importance variable. All eleven regression equations are significant at p <.01, with R-SQUARE ranging from .16 to .50. These results are highly significant and support the intermediary positioning of the importance variable in the model.





The results indicate that importance explains a significant amount of the variance of the level or donation for 8 of the 10 charitable organizations (again, the results for cancer research and heart research do not support the model). All other regression equations are significant at p <.10, with R-SQUARE ranging from .03 to .16.

The final step in the initial testing of the model is to determine whether or not importance can be considered an intermediate variable. The method is to use partial correlations between the five independent variables and the level of donations to control for importance. A fall in the correlation between the zero-order correlations and the first-order partial correlations would indicate that importance is an intermediate variable between the four prior independent variables and the level of donation.

Tables 4 and 5 present the correlations between the independent and dependent variables. Table 4 presents the zero-order correlations and Table 5 presents the first-order partial correlations.

The results of the correlation analysis reveal that almost all zero-order correlations fall significantly when the first-order partials are applied, indicating support for the hypothesized relationships in the proposed model.






The model and pilot study reported in this paper are an initial attempt to develop a better understanding of the way individuals behave in a non-profit marketing context. Specifically, this paper has suggested a new model for understanding and predicting charitable donation/health care consumer behavior. It is believed that the model is not specific to certain types of non-profit organizations, but rather, can be generalized to all or most non-profit situations.

Past research (eg. Oliver and Berger 1979) has indicated that some variables in the HBM and BIM models have more immediate effects on one's intention and behavior decisions. Thus, research similar to that proposed herein is useful when one is interested in prediction,  resulting in a more parsimonious model consisting of antecedent and consequent variables. From a practical standpoint, given that our model suggests that importance is consequent to severity, involvement, predominance and alleviation, it may be more meaningful for the non-profit organization to deal with these four specific variables before attempting to "sell" an individual on how important the cause is.

There are a number of limitations in the current research. Firstly, the sample is quite small and relatively unique and may not be representative of any relevant donating universe. Secondly, the research reported herein describes and utilizes a very limited number of variables, and thus the external validity of the model and research must be investigated further.

Future research should attempt to validate the proposed model in a more formal and extensive research setting, correcting some of the above-mentioned limitations. In addition, other factors such as perceptions or the method of collecting donations, the differences in individuals propensities to give, concentrated versus dispersed giving, the differences between the various charitable organizations, peer pressure, etc. should be thoroughly investigated.


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Jerry A. Rosenblatt, Concordia University
Alain J. Cusson, University of Sherbrooke
Lee McGown, Concordia University


NA - Advances in Consumer Research Volume 13 | 1986

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