Although self-service data preparation and analytics tools (SSPATs) have become increasingly popular and can provide major benefits to users, barriers associated with the technology and its usage may prevent adoption. Based on prior work on technology acceptance and related theories, this study develops a net effects model and a configurational effects model to further the understanding of SSPAT acceptance. Using a configurational lens, this study shows how a fresh methodological approach from a different epistemological stance applied to a well-established theoretical basis can offer novel insights into effects and patterns that may complement exisiting findings. The results of our empirical study based on a sample of 339 firms confirm insights from previous studies and advance them by providing vision for compound antecedents of SSPAT acceptance and complementarity effects among antecedent conditions.
Zaki, Mohamed; Fischer, Svenja; Woodall, Philip; and Leischnig, Alexander, "FACTORS INFLUENCING THE ACCEPTANCE OF SELF-SERVICE BIG DATA PREPARATION AND ANALYTICS TOOLS" (2023). ECIS 2023 Research Papers. 348.