Date of Conferral
2023
Degree
Ph.D.
School
Management
Advisor
Daphne Halkias
Abstract
Finance and information technology scholars wrote that there is a literature gap on what factors drive investors in Western financial markets to use a Robo-advisor to manage their investments. The purpose of this qualitative, single case study with embedded units is to understand the adoption intentions of retail investors in U.S. markets to use a Robo-advisor instead of a human advisor. A single case study design addressed the literature gap, and qualitative data from seven semi=structured interviews, reflective field notes, and archival data were triangulated to answer the research question. This study was grounded in a theoretical framework that includes the theory of planned behavior, the technology acceptance model, the unified theory of acceptance, and the use of technology. Thematic analysis revealed nine themes of the study: a) awareness of Robo-advisory systems, (b) perceptions of risk connected to customer’s financial literacy, (c) data security risk lowers acceptance of Robo-advisor technology, (d) Robo-advisor is filtering out emotional customer biases, (e) customer ambivalence on Robo-advisor capabilities, (f) perceived ease of use, (g) trust in the Robo-advisor, (h) customer ambivalence on adoption intention, and (i) low adoption intention for customers with low financial literacy. This study’s results indicated that financial institutions must still earn customers’ trust by protecting their data through secure platforms and processes and customizing Robo advisor services, products, and offers, to their needs. By further understanding retail investors’ adoption intentions in using a Robo-advisor, this study’s results may drive positive social change by offering pathways to very low-cost, automated financial management advice to a broader segment of new and intermediate investors.
Recommended Citation
Wall, Deborah, "Understanding U.S. Customers' Intention to Adopt Robo-Advisor Technology" (2023). Walden Dissertations and Doctoral Studies. 11875.
https://scholarworks.waldenu.edu/dissertations/11875