A consumer demands-resources model of engagement: Theoretical and managerial contributions from a cross-validated predictive ability test procedure

Abstract

Despite the widespread economic and social interest in consumer engagement (CE) in do-it-yourself (DIY) or “making” activities, the construct remains underexplored in the literature. Integrating the theoretical frameworks of CE, the service-dominant logic, and conservation of resources theory, this study uses a mixed-methods approach to identify the resources that best predict CE in making activities. We conduct an exploratory qualitative study through 26 semi-structured interviews with consumers and professionals to refine our hypotheses. We then use a quantitative approach (N = 210) based on the latest advances in partial least squares structural equation modeling (PLS-SEM) to determine predictive validity. It thus offers an empirical application of the latest guidelines in this field. In particular, the study applies the new cross-validated predictive ability test (CVPAT) to test and compare several models. Combined with an importance-performance map analysis (IPMA), the CVPAT approach helps identify operational levers for decision-makers in the maker ecosystem.