Willingness to Disclose Personal Information: How to Measure it?

Abstract

The study investigates a possibility of multidimensionality of a construct of willingness to disclose personal information (WTD). Willingness or unwillingness to disclose personal information has been a widely studied phenomenon as personal data is becoming increasingly important for many industries including marketing. Most of these studies treat the willingness to disclose personal information as a homogenous construct. In many cases it is measured by providing a number of personal information items and asking about the willingness to share them. Although recently there have been studies that find possible multidimensionality of the construct, most of them do not further elaborate this possibility. Therefore, we have adopted a scale used in many previous studies and made an attempt to test the hypotheses that would base the argument regarding the multidimensionality of this construct or even the possibility to consider several separate variables and constructs aimed at measuring the willingness to disclose personal data. This was achieved by using three antecedents of the willingness to disclose personal data – the perceived regulatory effectiveness, privacy awareness and disposition to value privacy – and comparing how they interact with different types of the willingness. This allowed to assess different relationship patterns between the antecedents and possible dimensions of the willingness to disclose personal information. We have employed Exploratory and Confirmatory Factor Analysis to check the homogeneity of the willingness to disclose personal information and Structural Equation Modelling to test the patterns of the relations. We have found that there is more than one separate dimension of WTD which means it could not be treated as a homogenous construct. Factorial analysis distinguishes three types of the willingness linked with three types of data: the willingness to disclose personal data that includes individual facts (profile data), social networking data and online browsing/purchasing data. The conclusion of multidimensionality is also supported by the differences in relationship patterns observed between the antecedents and the willingness to disclose personal information.