New Channels for Old Businesses: Examining the Drivers and Obstacles of Mobile Commerce Adoption for Complex Products

Although revenues in mobile retail are continuously growing, mobile commerce for complex products such as insurance lags far behind. A basic reason is consumers’ perceived misfit of product and channel characteristics. However, scholars and practitioners have only vague ideas of the causes for this misfit. This prevents the development of adequate means to overcome consumer resistance. The present thesis confronts this shortcoming by systematically investigating the psychological mechanisms which produce reluctance, as well as the appropriate countermeasures to facilitate its adoption. In order to do this, four studies with mixed method approaches have been carried out; two studies cover the sources of m-commerce resistance, and two cover the means through which such resistance can be overcome. Study 1 examines and identifies key antecedents of channel choice based on field data. A synthesis of three fundamental theories was undertaken to pinpoint associated cognitive processes. Product complexity and expertise were found to be key determinants in this context. A quadratic moderating role of product expertise is shown to regulate the extent to which complexity enters the purchase decision. Subsequently, Study 2 examines the cognitive processes underlying resistance in m-commerce. Therefore, consumers’ cognitions were mapped and structured by using the laddering interview technique. This revealed hierarchical value linkages. Poor service and system components were the main reasons of customer resistance. In a field evaluation, Study 3 elaborates the understanding of resistance emergence and explores effective countermeasures by applying a set of four statistical analyses. A structural investigation of the concept of risk indicated that psychological risk concentrates the impact of other risk dimensions and acts as mediator towards purchase intention. The induction of service quality moderated the negative effect of risk on purchase intention in a quadratic fashion (inverted-U), leading to minimal risk influence for low and high service quality, but high influence for modest service quality. A laboratory experiment in Study 4 finally presents ways of how to configure service in m-commerce to efficiently support its adoption. Based on task-technology fit considerations, the findings propose a hybrid service approach which combines human-technology mediated and mere technology generated service to leverage the synergies of both. The theoretical and practical implications of all four studies are discussed