Published papers

*Urminsky, O., *Dietvorst, B. J., (forthcoming). Taking the Full Measure: Integrating Replication Into Research Practice to Assess Generalizability. Journal of Consumer Research.

Fei, L., Dietvorst, B. J., (2024). Prediction by Replication: People Prefer Prediction Algorithms That Replicate the Event Being Predicted. Journal of the Association for Consumer Research, 9(3).

Valenzuela, A., Puntoni, S., Hoffman, D., Noah, C., Julian, D. F., Dietvorst, B. J., Hildebrand, C., Huh, Y. E., Meyer, R., Sweeney, M. E., Talaifar, S., Tomaino, G., Wertenbroch, K., (2024). How artificial intelligence constrains the human experience. Journal of the Association for Consumer Research, 9(3).

*Desiraju, S., *Dietvorst, B. J., (2023). Reason Defaults: Presenting defaults with reasons for choosing each option helps decision makers with minority interests. Psychological Science, 34(12), 1363-1376.

Dietvorst, B. J., Bartels, D. M. (2021). Consumers object to algorithms making morally relevant tradeoffs because of algorithms’ consequentialist decision strategiesJournal of Consumer Psychology, 32(3):406-424. MM CBR

Dietvorst, B. J., Bharti, S. (2020). People Reject Algorithms in Uncertain Decision Domains Because They Have Diminishing Sensitivity to Forecasting ErrorPsychological Science, 31(10):1302-1314. CBR APS MM

     • Winner of 2023 SJDM Best Paper Award from the Society for Judgment and Decision Making

Mislavsky, R., Dietvorst, B. J., Simonsohn, U. (2019). The Minimum Mean Paradox: An Explanation for Apparent Experiment Aversion, Proceedings of the National Academy of Sciences, 116(48),23883-23884. DC

Mislavsky, R., Dietvorst, B. J., Simonsohn, U. (2019). Critical Condition: People Don’t Dislike A Corporate Experiment More than They Dislike Its Worst Condition, Marketing Science, 39(6):1092-1104.

Dietvorst, B. J., Simonsohn, U. (2019). Intentionally "Biased": People Purposely Use To-Be-Ignored Information, But Can Be Persuaded Not To, Journal of Experimental Psychology: General, 148(7):1228-1238. DC CBR

     • Winner of 2020 Early Career Award from the Society for Experimental Psychology and Cognitive Science (Division 3 of the American Psychological Association)

Dai, H., Dietvorst, B. J., Tuckfield, B., Milkman, K. L., Schweitzer, M. E. (2018). Quitting When the Going Gets Tough: A Downside of High Performance Expectations, Academy of Management Journal, 61(5):1667-1691. CBR K@W UAR

     • Winner of 2019 SPSP Cialdini Prize from the Society for Personality and Social Psychology

Dietvorst, B. J., Simmons, J. P., & Massey, C. (2016). Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them, Management Science, 64(3):1155-1170. BG HBR MIT NYT SCI QSB 538

     • Finalist for 2020 Decision Analysis Society Publication Award from INFORMS

Dietvorst, B. J., Simmons, J. P., & Massey, C. (2015). Algorithm Aversion: People Erroneously Avoid Algorithms After Seeing Them Err, Journal of Experimental Psychology: General, 144(1):114-126. NPR HBR BG HBR FT K@W NYT WEF CBR QSB 538

     • Data, Code, Study Materials, & Supplementary Materials (also hosted by the Journal of Experimental Psychology: GeneralSupplemental Material)

Papers in review process

Hu, B., Gaertig, C., Dietvorst, B. J., “How Should Time Estimates Be Structured to Increase Customer Satisfaction?” (revision submitted to Management Science)

Dietvorst, B. J., Fei, L., “People Take More Risk When Their Prospects are Tied to Future States of the World” (preparing for resubmission) 

Dietvorst, B. J., “Aligning Algorithms with People’s Prediction Preferences” (preparing for initial submission)

Bharti, S., Dietvorst, B. J., “Consumers opt for more attribute upgrades when selecting among preconfigured products as opposed to configuring the product themselves” (preparing for initial submission)

(*Denotes equal authorship)