Segmenting Australian online panellists based on volunteering motivations

The purpose of this paper is to seek to assess whether online commercial panel volunteering can be segmented based on their motivations, using the volunteer functions inventor. The authors also investigate whether segments exist which differ in demographic characteristics.

The authors survey 484 Australian online panel volunteers using a adapted version of the 30 item of the volunteer function inventory (VFI) scale developed by Clary et al. (1998). Data were analysed using confirmatory factor analysis (CFA) and cluster analysis, as well as ANOVA and χ2 test comparisons of demographics between clusters.

CFA verifies that the VFI scale is suitable instrument to gauge online participants’ motivations. Cluster analysis produced a five-cluster solution, where respondents with low motivations overall comprised the largest grouping. Segments are interpreted by assessing the difference between the total sample average and the segment profile. The examination also identifies that the only demographic factor that varies across the five clusters is “respondents” employment status”.

Future research could explore if differences in segments result in differences in online participation. The high number or respondents with low motivations may explain the relatively high levels of churn that take place within online panels and as a result panel operators would need to continually attract new members. Further research could also investigate whether the levels of motivation change over time and if so what effect such variation would produce on respondents’ retention.

Research on online panel respondents’ motivation is still limited and investigating online panellists’ motivation as volunteers is very important as it unveils, as in the study herein reported, that alternative types of respondents may be driven by different factors when joining an online panel (or completing a given survey). Recruitment strategies could, therefore, be shaped to suit the motivation of the different segments. By refining the matching between volunteers’ profiles and their motivation, managers could improve how volunteers are recruited, managed and retained.