Consumer reactions to technology in retail: choice uncertainty and reduced perceived control in decisions assisted by recommendation agents

• Published in: Electronic commerce research Vol. 24; no. 2; pp. 901 - 923
• Main Authors: Rohden, Simoni F., Espartel, Lélis Balestrin
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-06-2024; Springer Nature B.V
• Subjects: Agents (artificial intelligence); Artificial intelligence; Boundary conditions; Business and Management; Computer Communication Networks; Consumer behavior; Customer satisfaction; Data Structures and Information Theory; Decisions; e-Commerce/e-business; Electronic commerce; IT in Business; Operations Research/Decision Theory; Purchase intention; Recommender systems; Risk aversion; Risk management; Risk perception; Uncertainty; Choice overload; Maximization tendencies; Risk perception; Smart retailing; Artificial intelligence
• ISSN: 1389-5753; 1572-9362
• DOI: 10.1007/s10660-024-09808-7

The emergence of artificial intelligence technologies, such as recommendation agents, presents new challenges and opportunities for marketing. Recommendation agents assist consumers in their online grocery shopping decisions by analyzing data on preferences and behaviors. This research highlights that while recommendation agents can reduce choice overload and make purchase decisions easier for consumers, they are also associated with higher uncertainty in decision-making. Three experimental studies confirmed that purchases aided by recommendation agents are perceived as more uncertain and reduced perceptions of control over the choices explain this outcome. Furthermore, lower choice satisfaction and purchase intentions are confirmed as consequences of perceived uncertainty. Personal characteristics such as risk aversion and maximization tendencies are considered boundary conditions for these effects.