題 目：Information Provision and Halo Effect of Food Labels: What Can Response Time Tell?
報(bào)告人：Xiaoli Fan (University of Alberta)
時(shí) 間：2025年11月27日 星期四 14:00-15:30
報(bào)告地點(diǎn)：北京大學(xué)王克楨樓508會(huì)議室
報(bào)告人簡介：
Xiaoli Fan is an Associate Professor at the Department of Resource Economics and Environmental Sociology at the University of Alberta. Xiaoli received her Ph.D. (2017) degree from the Dyson School of Applied Economics and Management, Cornell University. Xiaoli’s research focuses on understanding consumer and producer behaviour to inform better agricultural policies and decision-making. Her specific research interests include consumer preference for emerging food issues, agrifood sustainability, agrifood value chain coordination, antibiotic use in livestock, bioeconomic modelling, and agent-based modelling. Her current research interests center on how information and behavioral frictions shape consumer decision-making and on exploring novel data sources, such as response time, video-based behavioral observations, and social media data for analyzing choice processes. She is associate editor of Agribusiness: An International Journal, serves on the editorial board of Canadian Journal of Agricultural Economics (CJAE), and has served as the councillor of Canadian Agricultural Economics Society (CAES). Her work has been published on American Journal of Agricultural Economics, Food Policy and Nature Human Behavior.
報(bào)告內(nèi)容：
The halo effect of food labels occurs when labels lead consumers to infer superior health or quality attributes, especially for credence claims that cannot be directly verified, such as organic, grass fed, or animal welfare approved. Evidence on whether information provision mitigates this bias remains mixed. Using a nationally representative Canadian survey with an embedded discrete choice experiment, we examine whether information about beef label requirements reduces the halo effect and whether incorporating response time affects model estimates. Half of the participants were randomly assigned to receive detailed label information, and response times were recorded for all choice tasks. We estimate a hybrid choice model that integrates discrete choice models with latent variable models, in which response time is incorporated as the observable indicator of the latent construct for survey engagement. Our model allows taste and scale heterogeneity to be separated while avoiding endogeneity concerns present in models that directly use response time as an explanatory variable. Our results show that information provision reduces the halo effect, and that longer response times, which indicate greater cognitive effort, are associated with lower willingness to pay for credence labels. These findings suggest that more deliberate processing helps mitigate the halo effect of food labels.