Degree Name

Doctor of Philosophy


School of Management & Marketing - Faculty of Commerce


The present research project grew out of a practical problem being experienced by a local environmental volunteering organisation – how to attract and retain volunteers. The purpose of the study was to gain insight into the volunteering market by investigating whether understanding of systematic heterogeneity among volunteers can be harvested to attract more volunteers from non-traditional groups within the community. This involved investigating a number of different segmentation criteria hypothesised to be relevant to the behaviour of volunteering, to identify the most managerially useful approach to the development of targeted recruitment campaigns. Four separate investigations were conducted. Study 1 qualitatively investigated the role of ethnic identification in volunteering behaviour, using the Theory of Planned Behaviour as the theoretical framework for the enquiry. Results indicated that while differences were found between ethnic groups, heterogeneity within ethnic groups was so high that treating them as separate distinct market segments was not a feasible marketing strategy. Findings from Study 1 did, however, point to other potentially valuable segmentation criteria, especially bicultural identity, family life stage and image beliefs towards the organisation. Studies 2 and 3 investigated additional segmentation criteria which emerged both from Study 1 and prior literature. Family life stage, bicultural identity and images beliefs towards volunteering organisations were explored using quantitative data from an Australian sample of 1,415 participants. Segmenting the volunteer market based on (1) family life stage and (2) bicultural identity (Study 2) produced distinct groups of volunteers which could be used for market targeting. Yet, these segment profiles appeared to be strongly influenced by image beliefs towards volunteering organisations. Consequently, Study 3 focused on using image beliefs towards the organisation as the key segmentation variable. This analysis led to a number of valuable insights into the structure of the volunteering market. Firstly, different generic image positions were found to exist in the volunteering market, indicating that a limited number of particular combinations of image beliefs can be used to characterise volunteering organisations. Secondly, certain volunteering organisations are more strongly associated with particular generic image positions than others, indicating that they do actually possess distinct brand images. Thirdly, preference levels for individual volunteering organisations differ at different generic image positions. This information enables volunteering organisations to understand which generic image positions are seen most favourably for them by the market. Heterogeneity based on image beliefs towards organisations thus emerged as the most managerially useful source of heterogeneity to form the basis of a volunteering segmentation. Finally, in Study 4 the results derived from Studies 2 and 3 using exploratory methodology were tested, using the Theory of Planned Behaviour. If harvesting systematic heterogeneity among volunteers is a superior strategy to mass marketing to attract volunteers, the predictive power of regression models accounting for this heterogeneity should be higher than that of models that assume that all volunteers are driven by the same degree of attitude, social norm and perceived behavioural control. Results indicate that the predictive power of the theory was greater when applied at the segment level, particularly for segments based on image beliefs towards organisations. This supports the conclusion that segmenting the market based on image beliefs towards organisations results in the greatest insight for managers, and is the criterion most able to harvest heterogeneity to attract more volunteers from the general community. The results of this study contribute to theory in three ways. Firstly, novel sources of heterogeneity are investigated to assess their effectiveness in identifying subgroups within the volunteering market which are homogeneous in their volunteering behaviour. Secondly, the assumption that general volunteering behaviour is indicative of volunteering behaviour for specific organisations is challenged, therefore questioning the validity of much of the current research on volunteering which typically uses volunteering behaviour in general as a proxy to predict and explain heterogeneity in volunteering behaviour for specific causes. Thirdly, the Theory of Planned Behaviour is expanded to account for heterogeneity, and an additional construct – image beliefs towards organisations – is added to improve the predictive ability of the model. Results are important for volunteering managers because they provide insight into ways of segmenting the volunteer market to identify groups which are homogeneous in their attitudes and volunteering behaviour. This subsequently allows managers to (1) identify the generic image position which is most preferred for their organisation and provide direction as to the type of brand and image attributes that they should be promoting; (2) understand which people are most likely to volunteer for their organisation; and (3) understand how to reach these people and the messages which would be most meaningful and motivating for them. Ultimately, this information enables more efficient spend of the limited marketing dollars available, and maximises the number of volunteers recruited and retained by volunteering organisations.

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