My new financial companion! non-linear understanding of Robo-advisory service acceptance

Robo-advisory services are gaining traction and could usher in the next cycle of disruptive change in the financial services industry. Yet, many are reticent to embrace this service innovation for their wealth management. This study probes this phenomenon by examining the interplay among technology characteristics (i.e. performance expectancy, effort expectancy, and perceived security), human-like characteristics (i.e. perceived autonomy, perceived intelligence, and perceived anthropomorphism), and consumer characteristics (i.e. financial literacy and affinity for technology interaction) to explain the acceptance of robo-advisory services. For this purpose, a fuzzy set qualitative comparative analysis and an artificial neural network analysis were performed to uncover the interdependency and complexity of the proposed variables, based on 375 responses collected through a large consumer panel survey in China. The findings revealed the presence of six configurations conducive for high acceptance of robo-advisory services, with perceived anthropomorphism and a combination of perceived effort expectancy and perceived security identified as core conditions. Moreover, according to the artificial neural network analysis, perceived intelligence is the most important determinant of robo-advisory service acceptance. This study challenges the conventional linear and symmetric perspective adopted in prior research.