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Abstract
This study examines U.S. consumer preferences for automation in fast-food services using data from a national online survey of 1,273 adults. The instrument collected demographic and behavioral information, followed by a discrete choice experiment varying price, speed, accuracy, and task-specific automation. Respondents also rated perceived benefits, risks, and trust in food automation. Conditional logit models and latent class segmentation were estimated. Results show strong preferences for high accuracy and faster service, with mixed acceptance of automation across tasks. Segmentation reveals three consumer types shaped by technology use and education, offering insights into targeted strategies for foodservice automation adoption.