Discovery, Mystery Solving, and Mystery Creation in Marketing Research: PLS and QCA: An Abstract

Abstract

This paper analyzes how marketing phenomena can be framed using such discovery-mystery solving-mystery creation approach. This paper tests a UTAUT (unified theory of acceptance and use of technology; Venkatesh et al. 2003) using PLS (partial least squares) technique (discovery stage) to test the model and then utilizes fsQCA (fuzzy-set qualitative comparative analysis) technique to confirm (mystery solving) and reject (mystery creation) PLS findings. This paper follows a methodological approach highlighting the interaction between theory and data (Alvesson and Kärreman 2007), an approach still nascent in marketing (Wagemann 2015). UTAUT uses performance-expectancy theory, facilitating conditions, and social influence to explain usage and behavioral intentions and use behavior of technology. Activity tracker is a suitable product to test the model since continuous use of these wearables drops to 70% after 6 months and about 55% after 1 year of use (Endeavour Partners 2014). A purposive sample of 176 complete questionnaires was collected from a gender-balanced sample of employees with undergraduate and graduate education and relatively mid-high income. Measurement model was acceptable. Performance expectancy had the higher (β = 0.418; p < 0.001) influence on behavioral continuance intentions followed by effort expectancy (β = 0.272; p < 0.05). Paths’ social influence to continuance intentions and facilitating conditions to continuance intentions were found nonsignificant. Continuance intentions had higher influence (β = 0.585; p < 0.001) on use than facilitating conditions (β = 0.182; p < 0.05) on use.