Michael He JIA
Prof. Michael He JIA
Marketing
Deputy Area Head of Marketing
Associate Professor
Associate Director, Institute of Behavioural and Decision Science

3917 8309

KK 707

Academic & Professional Qualification
  • Ph.D., Marshall School of Business, University of Southern California
  • M.A., School of Business, Nanjing University
  • B.A., School of Business, Nanjing University
Biography

He (Michael) Jia received his Ph.D. in marketing from the University of Southern California. His research focuses on visual processing and aesthetics on digital platforms, numerical processing and promotion decisions, and marketing for the greater good. His research has been published in Journal of Consumer Research, Journal of Marketing, Journal of Marketing Research, and Journal of Consumer Psychology. He has won the AMA Retail and Pricing SIG Emerging Scholar Award (2023), the AMS-Mary Kay Dissertation Proposal Competition (2016), and the ACR-Sheth Foundation Dissertation Award (2015).

Selected Publications
  • Gao, Huachao, He (Michael) Jia, and Bingxuan Guo (2023), “Resources Available for Me versus Us: Implications for Mitigating Consumer Food Waste,” Journal of Marketing Research, forthcoming.
  • Jia, He (Michael), Yunhui Huang, Qiang Zhang, Zhengyu Shi, and Ke Zhang (2024), “Final Price Neglect in Multi-Product Promotions: How Non-Integrated Price Reductions Promote Higher-Priced Products,” Journal of Consumer Research, 50 (6), 1097-116.
  • Jia, He (Michael), Echo Wen Wan, and Wanyi Zheng (2023), “Stars versus Bars: How the Aesthetics of Product Ratings ‘Shape’ Product Preference,” Journal of Consumer Research, 50 (1), 142–66. (Equal Authorship)
  • Jia, He (Michael), B. Kyu Kim, and Lin Ge (2020), “Speed Up, Size Down: How Animated Movement Speed in Product Videos Influences Size Assessment and Product Evaluation,” Journal of Marketing, 84 (5), 100–16.
  • Jia, He (Michael), Sha Yang, Xianghua Lu, and C. Whan Park (2018), “Do Consumers Always Spend More When Coupon Face Value is Larger? The Inverted U-Shaped Effect of Coupon Face Value on Consumer Spending Level,” Journal of Marketing, 82 (4), 70–85.
  • Eisingerich, Andreas B., Hae Eun Chun, Yeyi Liu, He (Michael) Jia, and Simon J. Bell (2015), “Why Recommend a Brand Face-to-Face but not on Facebook? How Word-of-Mouth on Online Social Sites Differs from Traditional Word-of-Mouth,” Journal of Consumer Psychology, 25 (1), 120–28. (Equal Authorship)
Honours and Awards
  • AMA Retail and Pricing SIG Emerging Scholar Award, Co-Winner, 2023
  • HKU Business School Research Postgraduate Supervision Award, 2023
  • HKU Business School Research Output Prize, 2019
  • HKU Business School Outstanding Teacher Award (Undergraduate), 2019
  • AMS-Mary Kay Doctoral Dissertation Proposal Competition, Winner, 2016
  • ACR-Sheth Foundation Dissertation Award, Co-Winner, 2015
  • USC Graduate School Dissertation Completion Fellowship, 2015
  • AMA-Sheth Foundation Doctoral Student Consortium Fellow, 2015
  • Inaugural AMS Doctoral Consortium Fellow, 2015
  • PDMA-UIC Innovation Doctoral Consortium Fellow and Research Award of Excellence, 2014
External Grants
  • General Research Fund, The Research Grants Council of Hong Kong, PI, 2023
  • General Research Fund, The Research Grants Council of Hong Kong, PI, 2021
  • General Research Fund, The Research Grants Council of Hong Kong, PI, 2020
  • Early Career Scheme, The Research Grants Council of Hong Kong, PI, 2017
Recent Publications
Final Price Neglect in Multi-Product Promotions: How Non-Integrated Price Reductions Promote Higher-Priced Products

Price reductions take either an integrated form (e.g., a discount shown directly on the price tag) or a non-integrated form (e.g., a discount contained in a coupon sent to consumers and thus separate from the price tag). This research examines how non-integrated versus integrated promotions influence choices among vertically differentiated products. Under an integrated promotion (e.g., $10 off) applicable to multiple products (e.g., original list prices: $50 vs. $30), consumers directly compare these products’ post-promotion final prices displayed on their price tags (after a reduction of $10: $40 vs. $20). In contrast, under a non-integrated promotion of the same monetary value, consumers simply compare these products’ original list prices ($50 vs. $30) and neglect their post-promotion final prices, which require calculations. The list prices ($50 vs. $30; relative to the final prices: $40 vs. $20) as a basis for price comparison reduce the perceived price difference between these products. Consequently, a non-integrated promotion (compared to an integrated promotion) increases consumers’ choice of higher-priced products. A series of experiments (N = 5,187) demonstrate this effect and support the final price neglect mechanism. Furthermore, although attenuated, this effect still emerges for price reductions of a smaller magnitude or in a percent-off format.

Stars versus Bars: How the Aesthetics of Product Ratings “Shape” Product Preference

Websites commonly use visual formats to display numerical product ratings. Highlighting the overlooked notion of the “aesthetics” of product ratings, the current research examines how the shape of basic visual rating units (rectangular vs. non-rectangular) influences product preference. Seven experiments (and 23 supplementary experiments; N = 17,994) demonstrate a visual rounding effect. Specifically, compared to the rectangular rating format (e.g., bar ratings), the non-rectangular rating format (e.g., star ratings) increases product preference when product ratings (e.g., 3.7, 3.8, 3.9) are below the nearest integer. In contrast, the non-rectangular rating format decreases product preference when product ratings (e.g., 4.1, 4.2, 4.3) are above the nearest integer. Occurring for both the overall rating and by-attribute ratings of a product, the visual rounding effect results from a visual completeness restoration process, wherein consumers perceive non-rectangular rating units to be incomplete after vertical cutting. This research contributes to the product rating and visual marketing literatures and provides actionable implications by demonstrating what visual rating format should be adopted based on rating distribution, how the visual rounding effect can be prevented if needed, and who are even more susceptible to the visual rounding effect.