Discounting of Algorithms? Consumers’ Valuation of Human- vs. Algorithm-Created Digital Products
Speaker: Dr. Benedikt Berger
Abstract: The ‘handmade’ label, which indicates that a product has been manufactured by a human instead of machine, traditionally serves as a quality signal for physical products. Owing to advances in generative artificial intelligence (AI), machines can now also create digital products like software applications or media content, evoking calls to label such products as ‘AI made’. It is uncertain, however, how consumers of digital products would react to such a label. In this study, we leverage a choice-based conjoint analysis with 421 respondents to reveal that consumers apply an ‘algorithm discount’ in the valuation of digital products created by algorithms instead of humans. We refer to these changes in consumers’ responses as the source effect. Besides revealing the source effect, we identify product-related and consumer-related antecedents to this effect. These findings highlight the potential negative effects of delegating primary value activities to algorithms due to the prevalence of algorithm aversion.
Short Bio: Benedikt Berger is an assistant professor of Digital Transformation and Society at the Department of Information Systems at the University of Münster, Germany. His current research focuses on digital products and services as well as on AI-based information systems. His work has appeared in Journal of Management Information Systems, Electronic Markets, Business and Information Systems Engineering, Information Systems Frontiers, The Data Base for Advances in Information Systems, and in various international conference proceedings.