- 2001-2006 Ph.D. in Business Administration (Marketing), University of Chicago
- 2001-2006 MBA, University of Chicago
- 1991-1996 Ph.D. in Law (Demography), Peking University
- 1987-1991 BA in Economics, Peking University
Junhong Chu is a professor of marketing at the University of Hong Kong (HKU). Before joining HKU, she worked at the NUS Business School as a dean’s chair and a tenured associate professor of marketing and earlier at Peking University as an associate professor of economics. Professor Chu has also visited Harvard University as a research fellow and the University of Michigan as an associate professor.
Professor Chu is an empirical modeler, works on big data, and does quantitative research in marketing and industrial organization. Her research interests include platform markets and the sharing economy, e-commerce, social media, P2P markets, and distribution channels. She applies both the classical and Bayesian approach to study firm competition and consumer behavior.
Professor Chu’s research has been published in leading academic journals such as Marketing Science, Journal of Marketing Research, Management Science, Journal of Marketing, Proceedings of the National Academy of Sciences (PNAS), Nature Human Behaviour, Population and Development Review, and Demography. She was an MSI (Marketing Science Institute) 2011 Young Scholar and has also won several research awards.
Professor Chu earned a BA in economics and a PhD in Law (Demography) from Peking University, and an MBA and PhD in Business Administration (Marketing) from the University of Chicago.
- Platform Business Models and the Sharing Economy
- Customer Relationship Management
- Marketing Research
- Marketing Models
- Marketing Strategy (in Chinese)
I am an empirical modeler and work on big data, doing empirical industrial organization and structural modeling research. I am interested in platforms and the sharing economy, e-Commerce, and social media. I employ both the classical approach and Bayesian approach to study consumer and firm behavior and interactions between agents in these businesses.
- Yao, Dai, Chuang Tang, and Junhong Chu. 2023. “A Dynamic Model of Owner Acceptance in Peer-to-Peer Sharing Markets,” Marketing Science, 42(1): 166-188.
- Yi, Junjian, Junhong Chu, and I.P.L. Png. 2022. “Early-life exposure to hardship increased risk tolerance and entrepreneurship in adulthood with gender differences,” Proceedings of the National Academy of Sciences (PNAS), 119(15).
- Duong, Hai Long, Junhong Chu, and Dai Yao. 2023. “Taxi Drivers’ Response to Cancellations and No-shows: New Evidence for Reference-dependent Preferences,” Management Science, 69(1): 179–199.
- Xu Zhang, Puneet Manchanda, and Junhong Chu. 2021. “‘Meet Me Halfway’: The Costs and Benefitsof Bargaining,” Marketing Science, 40(6): 1081-1105.
- Junhong Chu, Yige Duan, Xianling Yang, and Li Wang. 2021. “The Last Mile Matters: Impact of Dockless Bike Sharing on Subway Housing Price Premium,” Management Science, 67(1): 297-316.
- Junhong Chu, Haoming Liu, and Alberto Salvo. 2021. “Air Pollution as a Determinant of Food Delivery and Related Plastic Waste,” Nature Human Behaviour, 5(2): 212-220.
- Chintagunta, Pradeep K. and Junhong Chu. 2021. “Geography as Branding: Descriptive Evidence from Taobao,” Quantitative Marketing and Economics, 19(1): 53-92.
- Cao, Zike, Junhong Chu, Kai-Lung Hui, and Hong Xu. 2021. “The Relationship between Online Referral Marketing and Price Promotion: Evidence from a Large E-Commerce Platform,” Journal of Management Information Systems, 38(3): 855-888.
- Chu, Yanlai, Junhong Chu, and Hongju Liu. 2021. “The Impact of Mergers and Acquisitions on Brand Equity: A Structural Analysis,” International Journal of Research in Marketing, 38(3): 615-638.
- Junhong Chu, Haoming Liu, and Ivan Png. 2018. “Marriage and Non-labor Income: Evidence from China’s Heating Policy,” Demography, 55(6): 2345-2370.
- Yan, Wei, Yu Xiong, Junhong Chu, Gendao Li and Zhongkai Xiong. 2018. “Clicks and Bricks: Optimal Marketing Channels for a Durable Goods Firm,” European Journal of Operational Research, 265(3): 909-918.
- Junhong Chu and Puneet Manchanda. 2016. “Quantifying Cross and Direct Network Effects in Online Consumer-to-Consumer Platforms,” Marketing Science, 35(6): 870-893.
- Sun, Li, Surendra Rajiv, and Junhong Chu. 2016. “Beyond the More the Merrier: The Variety Effect and Consumer Heterogeneity in System Markets,” International Journal of Research in Marketing, 33(2): 261-275.
- Goh Khim-Yong, Junhong Chu, and Jing Wu. 2015. “Mobile Advertising: An Empirical Study of Temporal and Spatial Differences in Search Behavior and Advertising Response,” Journal of Interactive Marketing, 30: 34-45.
- Sriram, S., Puneet Manchanda, Mercedes Esteban Bravo, Junhong Chu, Liye Ma, Minjae Song, Scott Shriver, and Upender Subramanian. 2015. “Platforms: A Multiplicity of Research Opportunities,” Marketing Letters, 26(2): 141-152.
- Junhong Chu. 2013. “Quantifying Nation Equity with Sales Data: A Structural Approach,” International Journal of Research in Marketing, 30(1): 19-35, runner up, MSI and IJRM Award for Best Paper in IJRM Special Issue on Marketing in Emerging Markets.
- Chintagunta, Pradeep K., Junhong Chu, and Javier Cebollada. 2012. “Quantifying Transaction Costs in Online / Offline Grocery Channel Choice,” Marketing Science, 31(1): 96-114 (received the Spanish Marketing Academy and ASEDAS Best Paper Award, 2013).
- Junhong Chu and Pradeep K. Chintagunta. 2011. “An Empirical Test of Warranty Theories in the U.S. Server and Automobile Markets,” Journal of Marketing, March 75(2): 75-92.
- Junhong Chu, Marta Arce-Urriza, Javier Cebollada, and Pradeep K. Chintagunta. 2010. “An Empirical Analysis of Shopping Behavior across Online and Offline Channels for Grocery Products: The Moderating Effects of Household and Product Characteristics,” Journal of Interactive Marketing, 24: 251-268 (runner-up for best paper award 2011).
- Junhong Chu and Pradeep K. Chintagunta. 2009. “Quantifying the Economic Value of Warranties in the U.S. Server Market,” Marketing Science, 28(1): 99-121
- Junhong Chu, Pradeep K. Chintagunta, and Javier Cebollada. 2008. “A Comparison of Within-household Price Sensitivity across Online and Offline Channels,” Marketing Science, 27(2): 283-299.
- Junhong Chu, Pradeep K. Chintagunta, and Naufel J. Vilcassim. 2007. “Assessing the Economic Value of Distribution Channels – An Application to the Personal Computer Industry,” Journal of Marketing Research, 44(1): 29-41.
- Junhong Chu. 2001. “Prenatal Sex Determination and Sex-selective Abortion in Rural Central China,” Population and Development Review, 27(2): 259-281.
- MSI (Marketing Science Institute) Young Scholar, 2011
- Editorial Review Board, Marketing Science, from January 2019
- Editorial Review Board, Journal of Interactive Marketing, from April 2016
Peer-to-peer (P2P) sharing marketplaces enable sharing of idle resources. When a renter requests an owner’s resource, the owner needs to decide whether to accept the request: accepting it helps the owner fill up the idle periods of the resource and generate a payoff but reduces the flexibility to serve a future request for a longer duration. This paper develops a framework to uncover the tradeoffs faced by owners on these platforms when making acceptance decisions, which can be used by owners to optimize their decisions and by platforms to improve their operations. The model explicitly accommodates two types of owners: some are attentive to the availability states of their cars and forward-looking, whereas others myopically make the acceptance decisions. Applying the model to unique data from a leading peer-to-peer car sharing platform in China, we obtain similar sizes of both types of owners and find that female, experienced, and younger owners are more likely to be strategic. The results also reveal the differentiated preferences of the two types of owners toward their renters. Building on model estimates, we calibrate the option value of each day in the future (i.e., the value of having the day available) for strategic owners and find it to first increase, then decrease. Two counterfactual analyses are conducted. The first analysis shows that if the platform imposes a minimum rental duration, strategic owners may become more reluctant to accept requests, even if the current availability state entails a higher expected payoff. The second analysis shows that with better understanding of its owners, the platform can greatly improve the matching efficiency by optimal (re)allocation of rental requests, a move that benefits almost all participants in the business.