Journal Publications
Gai, Phyliss J., Mirjam A. Tuk, and Steven Sweldens (in press), “Light or Regular, Now or Later: The Impact of Advance Ordering and Restrained Eating on Choices and Consumption of Light and Regular Vice Food," Journal of the Association for Consumer Research.
When choosing between regular and light vice food, restrained eaters prefer the light and consume lower calories. The timing of choice (immediate or in advance) does not impact choices or consumption.
Gai, Phyliss J. and Amit Bhattacharjee (2022), “Willpower as Moral Ability," Journal of Experimental Psychology: General. [Link]
People infer moral goodness from the success in non-moral self-control, but not moral badness from the failure, because willpower indicates the ability to be good.
*See a easier-to-digest summary here.
*See a easier-to-digest summary here.
Gai, Phyliss J. and Stefano Puntoni (2021) “Language and Consumer Dishonesty: A Self-Diagnosticity Theory," Journal of Consumer Research, 48, 333-351. [Open Access]
A theory of when using a foreign language would increase, decrease, and not change lying behavior, compared to using one's native language.
* Created an original paradigm on cheating, summarized here and adapted for neural studies.
* Early findings incorporated in a meta-analysis by Köbis et al. (2019).
* A short summary in layperson language on JCR website
Gai, Phyliss J. and Anne-Kathrin Klesse (2019), “Making Recommendations More Effective through Framings: Impacts of User- versus Item-based Framings on Recommendation Click-throughs," Journal of Marketing, 83 (6), 61-75. [Open Access]
Framing the same recommendation as "People who like this also like" versus "Similar items" improves the click-through rate of recommendations, under certain conditions.
* Coverage on Forbes, RSM Discovery, and AMA site
* Video of me summarizing it
* Coverage on Forbes, RSM Discovery, and AMA site
* Video of me summarizing it
Working papers
Gai, Phyliss Jia, Eugina Leung, and Anne Klesse, "Diversity signaling to algorithmic versus human recommenders"
Algorithmic (versus human) recommenders are perceived as lacking the purpose as well as the ability to recommend diverse products. In turn, consumers are less likely to indicate their diverse preferences.
Gai, Phyliss Jia and Gita Johar, "Using mobile devices leads to more discriminative sharing of information"
Analyses of Twitter data and experiments reveal that people are more discriminative in sharing information of high (versus low) quality on mobile devices as opposed to non-mobile devices.
Yiqi Yu, Yu Feng, Phyliss Jia Gai, "Lucky Machine: Task Delegation to AI versus Human with Uncertainty"
Book
Gai, Phyliss Jia (2020), Contextualized Consumers: Theories and Evidence on Consumer Ethics, Product Recommendations, and Self-Control. ERIM PhD Series Research in Management, Erasmus University Rotterdam. [Link]