To share or not to share: A quantitative analysis on the effect of personality dimensions and the self-determination theory on the willingness to disclose private data

In recent years, digitalization has become an artificer of data that is being generated by society at an extraordinary pace. As technological shifts are determining the course of businesses in today’s digital age, it is becoming increasingly important to understand the notions of big data. Ultimately, businesses that adapt to utilizing this data are the ones to hold a competitive edge. Therefore, it is becoming more vital to not only understand how this data can be used, but also how it is obtained. Personalized marketing, an approach powered by private data, has repeatedly shown its effectiveness. Recent evolvements in marketing have discovered a more niche marketing strategy, namely personality marketing, in which psychometrics are used to accurately target niche groups of people. This empirical study aims to gain insight into the complex notion of sharing private data by studying the influence of one’s personality traits and motivators from the self-determination theory on behavioral intent, and contributes to an academic discussion that offers insight into the theoretical and practical implications of this new concept. A quantitative online experiment with 253 Dutch participants was conducted to explore the behavioral intent of sharing private data in the market of health insurance. Three experimental conditions investigated whether different motivators, specifically extrinsic or intrinsic, would moderate the relationship of someone’s personality traits to behavioral intent. Contrary to prior research, findings demonstrate that personality traits are not a significant predictor of the willingness to disclose private data, nor when different motivators derived from the self-determination theory moderated this relationship. However, a significant multiple regression model showed significant results when predicting the willingness to disclose private data. Further results aligned with earlier literature when age was found to be an accurate predictor for the willingness to disclose private data, and when participants presented with an intrinsic trigger were more willing to disclose their data compared to participants who were not presented with any reward. While this study reiterates the power of personalized marketing, it simultaneously highlights the fact that future research should be conducted to gain a deeper understanding of using psychometrics that will likely have a big impact on the world of marketing.