Fuzzy QCA applicability for a refined selection of drivers affecting IS adoption: The case for Ecuador

Abstract

A nightmarish list of empirically proposed drivers affecting Information System (IS) adoption, and the limitation of measurements focusing their applicability in Latin America (LAT) economies is an issue. This causes uncertainty in the decision making process of which model and proposed drivers should be used to measure Successful Information System Adoption (SISA) in local public organizations, particularly in Public Ecuadorian Organizations (PEOs) as the focus case of the current study. Fuzzy QCA (fs/QCA), considered as a mechanism to evaluate empirical analysis based on qualitative approaches, was applied to reveal patterns of association across the set of 50 formed themes (as possible drivers), providing support for the existence of causal relations between these themes obtained from prevailing empirical literature and local primary and secondary sources. The Fuzzy logic of QCA applied in this study offers an easy way to systematically quantify various uncertainties in the selection of relevant themes as candidate drivers of SISA in local contexts and provides more realistic support to justify the decision.