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EMAC 2024 Annual


From ChatGPT to the Metaverse – New Insights into Behavioral Drivers and Consequences of AI-Based Technologies
(A2024-119824)

Published: May 28, 2024

AUTHORS

Meike Zehnle, University of St.Gallen, Institute of Behavioral Science and Technology; Begum Celiktutan, Erasmus University; Mirjam Tuk, RSM Erasmus University; Anne-Kathrin Klesse, Erasmus University, Rotterdam School of Management; Edmond Kozah, ESADE Business School, Barcelona; Ana Valenzuela, Baruch College, CUNY; Christian Hildebrand, University of St. Gallen; Mandeep Dhami, Midlesex University London; Ying Zhu, The University of British Columbia

ABSTRACT

From ChatGPT to the metaverse, AI-based technologies have become integral to consumers’ lives and offer a whole new dimension of consumer experiences and decision-making contexts. Previous research has primarily focused on consumers’ reactions to AI compared to human recommendations (e.g., Dietvorst et al., 2015, Longoni and Cian 2022), but little is known about the behavioral consequences post-AI adoption and the psychological drivers behind it (De Freitas et al. 2023, Puntoni et al. 2021). This special session presents four papers that explore these less-studied areas, including biases in AI usage evaluation, lay beliefs about AI functioning, and AI’s impact on consumer expression. Moving beyond the investigation of mere recommendation acceptance, it provides conceptual guidance for future research on consumer responses in an increasingly AI-enabled (and sometimes fully virtual) decision environment. The first paper examines whether it is acceptable to use ChatGPT to complete tasks. In “Acceptability Lies in the Eye of the Beholder: Self-Other Biases in ChatGPT Collaborations”, Begum Celiktutan, Mirjam Tuk, and Anne-Kathrin Klesse presents eight studies demonstrating that the answer to this question depends on the evaluation target (the self vs. others). People evaluate their own contribution to an output co-produced with ChatGPT as higher compared to that of others. This, in turn, makes ChatGPT usage more acceptable for the self than for others. The second paper shifts the focus from the acceptability of AI co-creation to the acceptability of AI data processing. In “Theory of Machine: Lay Beliefs About Algorithmic Data Processing – Drivers of Recommendation Acceptance”, Edmond Alcheikh Kozah and Ana Valenzuela investigate consumers’ lay understanding of how AI systems utilize various typologies of data to generate recommendations, and the subsequent likelihood of accepting those recommendations. Four studies show the influence of two identified lay beliefs: the “individuality threat” posed by different data types and the “acceptability of data type processing.” The third paper expands the data collection perspective by exploring conversational AI’s impact on consumers’ written expression. In “When “Chatting” Backfires: Conversational Interfaces Reduce Consumers’ Written Expression”, Meike Zehnle, Gizem Yalcin Williams, and Christian Hildebrand demonstrate an unintended consequence of AI usage across six studies in three different market research contexts: conversational AI, compared to more traditional methods of data collection (e.g., forms) results in shorter writing and reviews of inferior quality, depth, and breadth. The fourth paper, “Judgment and Decision Making in the Metaverse” by Mandeep K. Dhami and Ying Zhu, broadens the perspective to the metaverse. It compares judgment and decision-making in the metaverse and physical world and discusses the effects of metaverse technologies on cognitive functions like perception, attention, memory, and reasoning, and their influence on consumer judgment and decision-making. Moreover, the paper presents the metaverse’s potential for researching judgment and decision-making. Collectively, the four papers combine actual consumer-AI interactions, consequential choice experiments, automated text analyses with large language models, and a novel conceptual framework, thus offering a fresh perspective on consumer issues in an increasingly complex AI-driven consumption environment.