Consumers’ perceptions and decisions toward artificial intelligence

Abstract

The advent of computer technology and Artificial intelligence (AI) has transformed the way businesses operate, and taken over various tasks that are traditionally performed by humans. Despite the widespread prevalence of technology and the evident benefits it brings, consumer acceptance of AI as a replacement for human tasks remains relatively limited. This dissertation focuses on understanding consumers’ pre- and post-consumption perceptions and decision-making when encountering AI in various technological contexts, including customer service, automated negotiations, and algorithmic pricing. Essay 1 demonstrated that consumers attribute less responsibility toward a robot than a human for service failure because people perceive robots to have less controllability over the task. Instead, they attributed more responsibility toward a service firm when a robot delivered a failed service than when a human delivered the same failed service. In Essay 2, I showed that consumers in an ultimatum game give smaller offers to an AI (vs. human) counterpart, indicating different treatment toward AI in negotiations. The research further distinguishes this behavior toward AI as a lower need for fairness toward AI, rather than strategic behavior, through the dictator game. In Essay 3, I demonstrated that consumers believe an AI dealer to provides a narrower price dispersion than a human dealer. Consumers perceive greater similarity and smaller variation in price quotations and a narrower range between the highest and lowest trade-in prices by an AI dealer in comparison to a human one. This perception generalizes across various products, including both utilitarian and hedonic products. This belief can be leveraged to target consumers with low negotiator self-efficacy, who anticipate better deals in a narrower price dispersion that is potentially provided by an AI (versus human) dealer. Together, these three essays offer empirical contribution to marketing researchers and practitioners in understanding how AI implementation influences consumers’ perceptions and decisions.