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«Zhuping Liu June 2016 McCombs School of Business Mobile: (860) 336-8705 University of Texas at Austin Fax: (512) 471-1034 2110 Speedway Stop B6700 ...»

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Zhuping Liu

June 2016

McCombs School of Business Mobile: (860) 336-8705

University of Texas at Austin Fax: (512) 471-1034

2110 Speedway Stop B6700 Zhuping.Liu@mccombs.utexas.edu

Austin, Texas 78712-1275 sites.utexas.edu/zhuping-liu/

Education

Ph.D., Marketing, 2017 (expected)

McCombs School of Business, University of Texas at Austin Dissertation proposal defended in April 2016 Advisors: Vijay Mahajan and Frenkel ter Hofstede M.S., Statistics, 2012 Ph.D. student in Operations and Information Management, 2010-2012 University of Connecticut M.S., Management Science and Engineering, 2010 Beijing University of Aeronautics and Astronautics, China B.S., Management Information Systems, 2007 Qingdao University, China Research Interests Topics: Mobile Marketing, Location-Based Targeting, Pricing Methodologies: Bayesian Econometrics, Parallel Computing, Field Experiments, Spatial Models, Point Processes, Dynamic Linear Models, Applied Game Theory, Machine Learning Teaching Interests Digital Marketing, Marketing Analytics, Marketing Research, Pricing Journal Publications Jianqiang Zhang, Zhuping Liu and Weijun Zhong (2016). “Attack and Defend: The Role of Targeting in a Distribution Channel.” Marketing Letters, 27(2), 375-386.

Zhuping Liu (Page 2) Manuscripts Completed Zhuping Liu, Jason. A. Duan and Frenkel ter Hofstede. “Marketing Spillovers of Location- Based Mobile Services.” Being revised for resubmission to Marketing Science.

Zhuping Liu, Frenkel ter Hofstede, Jason. A. Duan and Vijay Mahajan. “Dynamics and Peer Effects of Brand Revenue in College Sports.” To be submitted to Quantitative Marketing and Economics.

Jianqiang Zhang, Zhuping Liu and Raghunath Singh Rao. “Flirting with the Enemy: Online Competitor Referral and Entry-Deterrence.” Under review at Management Science.

Raghunath Singh Rao, Julie Irwin and Zhuping Liu. “Flying with a Net, and without:

Preventive Devices and Self-Control.” Under review at Quantitative Marketing and Economics.

Zhuping Liu, Frenkel ter Hofstede and Vijay Mahajan. “Engaging and Targeting Consumers on Mobile: Connecting Mobile Promotions to Foot Traffic.” Job Market Paper.

Selected Work in Progress Zhuping Liu, Frenkel ter Hofstede and Vijay Mahajan. “Personalizing Mobile Ads for Geofence Targeting.” Field Experiments in progress.

Zhuping Liu, Frenkel ter Hofstede and Vijay Mahajan. “Mobile Promotions, Targeting and Consumer Retention.” Model estimation in progress.

Zhuping Liu, Frenkel ter Hofstede, Rongwei Chu and Vijay Mahajan. “Marketing to Rural Consumers through Fairs in Developing Countries: Exploration or Exploitation?” Model estimation in progress.

Other Publications Zhuping Liu, Qiuhong Zhao, Shouyang Wang and Jianming Shi (2013). “Modeling the Impact of Partial Information Sharing in a Three-echelon Supply Chain.” Asia-Pacific Journal of Operational Research, 30(5).

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Conference Presentations 2016 INFORMS Marketing Science Conference, Shanghai, China

- Engaging and Targeting Consumers on Mobile: Connecting Mobile Promotions to Foot Traffic 2015 Marketing Dynamic Conference, Beijing, China

- Dynamics and Peer Effects of Brand Revenue in College Sports 2015 INFORMS Marketing Science Conference, Baltimore

- Dynamics and Peer Effects of Brand Revenue in College Sports 2014 INFORMS Marketing Science Conference, Atlanta

- Marketing Spillovers of Location-Based Mobile Services Teaching Experience

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Selected Coursework Quantitative Marketing Marketing Models I (Frenkel Ter Hofstede, UT Austin) Marketing Models II (Jason Duan, UT Austin) Marketing Research Methods (Raghunath S. Rao, UT Austin) 2015 Quantitative Marketing and Structural Econometrics Workshop (Northwestern) Economics and Econometrics Microeconomics I (Svetlana Boyarchenko, UT Austin) Introduction to Game Theory (Maxwell B. Stinchcombe, UT Austin) Experimental Methods in Economics (Dale O Stahl, UT Austin) Empirical Industrial Organization (Eugenio J. Miravete, UT Austin) Econometrics II (Jason Abrevaya, UT Austin) Advanced Econometric Theory (Brendan Kline, UT Austin)

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Dissertation Overview Title: Push and Pull: Targeting and Couponing in Mobile Marketing Advisors: Vijay Mahajan and Frenkel ter Hofstede Committee members: Raghu S. Rao, Jason Duan, James Scott and Cotter Cunningham The prevalence of mobile marketing practices has profoundly changed the way consumers shop. Consumers are increasingly shifting to mobile coupons to enhance their shopping experiences. It is estimated that the number of mobile coupon users will pass 1 billion by 2019 worldwide (Juniper Research, 2014). This shift to mobile coupons has created unique opportunities for marketers to engage and target consumers who both actively pull coupons from the mobile app and passively receive targeted push messages about coupons. Consumers may be targeted either based on their past behavior (“behavior-based push”) or their current locations (“location-based push”).

The purpose of my dissertation is to advance our understanding of the role of mobile promotions in consumers’ shopping journeys and to propose effective targeting strategies in mobile marketing. Through cutting-edge location-awareness mobile technology, I will see whether a consumer visits a shopping mall after receiving targeted mobile promotions. With state-of-the-art mobile personalization technology, I will manipulate the timing, location and content of mobile pushes to test different mobile personalization strategies.





I focus on connecting mobile promotions to offline foot traffic, examining the interactions between marketer-initiated mobile push and shopper-initiated coupon pull, and personalizing mobile pushes in timing, location and content. The introduction to my dissertation reviews what we already know about mobile marketing and identifies the significant research gaps, in particular the importance of understanding the interactions between mobile push and pull, connecting mobile promotions to foot traffic and personalization in mobile targeting. To address these research gaps, Essay 1 studies the effects of mobile push and pull on shopping activities by developing a new empirical model and estimating it through large-scale parallel computing, and shows how malls and retailers can leverage mobile pushes to increase foot traffic and to help contend with their competition. In Essay 2, l look into the strategy of integrating behavior-based push into location-based push to reveal unique insights into mobile targeting personalization by designing and implementing a large-scale field experiment.

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Essay 1: “Engaging and Targeting Consumers on Mobile: Connecting Mobile Promotions to Foot Traffic.” Job Market Paper.

This study examines the effect of mobile promotions on foot traffic to shopping malls by capturing the dynamic interactions among shopper-initiated and publisher-initiated activities.

Shoppers may actively pull coupons from the mobile app or visit a shopping mall. They may also be passively targeted based on their individual historical behavior (“behavior-based push”) or based on their current locations (“location-based push”). These shopping activities often occur at vastly different frequencies. We develop a novel multinomial multivariate point process model, “zooming into” days that include shopping activities and “zooming out of” days without them. We model coupon pull and mall visit activities as “shopper-initiated events,” which may interact both within the same type of event and between two different types of events.

Behavior-based push and location-based push, assigned to shoppers according to the publisher’s targeting strategy, are modeled as “publisher-initiated events,” which directly influence coupon pull events and indirectly influence mall visits. We estimate our model through large-scale parallel computing. Our estimation results reveal interesting insights into mobile marketing. First, high consumer engagement with the mobile app drives more traffic to shopping malls and more app use in the future. In addition, both effects are non-monotonic over time. Second, visiting a shopping mall significantly increases the propensity of using the mobile app while decreasing the propensity to visit a shopping mall. Third, behavior-based promotions pushed to a shopper’s mobile phone directly boost her engagement with the mobile app and indirectly accelerate the next shopping trip. In contrast, a location-based push decreases mobile engagement and decelerates the next shopping trip. Fourth, the effects of home locations are stronger than work locations for both regional malls and strip malls. Home (work) locations are more important on weekends (weekdays) than on weekdays (weekends).

Essay 2: “Personalizing Mobile Ads for Geofence Targeting.” Work in progress.

Targeting and personalization has become the top priority for digital marketing (eMarketer, 2015). Geofence targeting delivers mobile push messages to consumers based on their locations, which ignores the heterogeneity of consumer behavior. In this study, I integrate each shopper’s past behavior into geofence targeting and empirically test how much marketers should target shoppers, and when geofence targeting personalization can help with mobile engagement, shopping duration and a visit to a nearby mall. In a large-scale field experiment, I randomize the push sending time from a shopper entering a geofence and the affinity score that determines whether a push will be sent, and I manipulate the push message content (e.g., general message, specific offer, etc.). Using data from the field experiment, I fit an empirical model to understand the effects of personalization in geofence targeting. This study contributes to the marketing literature by introducing personalization into geofence targeting and by empirically testing when personalization is effective.

Zhuping Liu (Page 7) Abstracts of Selected Research Zhuping Liu, Jason. A. Duan and Frenkel ter Hofstede. “Marketing Spillovers of LocationBased Mobile Services.” Being revised for resubmission to Marketing Science.

This paper studies the increasingly prevalent check-in phenomenon on location-based service platforms. We examine the range of spatial correlation among check-ins of restaurants and bars on Foursquare, a location-based mobile service, and empirically test the promotion effect on venues’ check-ins. Our model, built on an inhomogeneous Poisson process, employs an instrumental variable approach to correct for the potential bias induced by a dummy endogenous promotion variable. The model can be used to study a broad array of problems based on spatio-temporal count data from social media. We find significant spatial correlations

among neighboring venues’ check-ins. Our estimation results indicate strong spillover effects:

venues’ promotions not only significantly increase their own check-ins but also benefit their neighboring venues. More interestingly, the spillover effects between restaurants and bars are asymmetric: Bars’ promotions benefit neighboring restaurants while restaurants’ promotions do not benefit neighboring bars. These results have implications for marketers who are using or considering using location-based service platforms like Foursquare, Facebook, and Yelp.

Zhuping Liu, Frenkel ter Hofstede, Jason. A. Duan and Vijay Mahajan. “Dynamics and Peer Effects of Brand Revenue in College Sports.” To be submitted to Quantitative Marketing and Economics.

Team branding plays a key role in attracting corporate sponsorship for the multi-billion dollar business of college sports. In this paper, we study peer effects in the dynamic brand revenue evolution of major college sports teams that play in the same National Collegiate Athletic Association conferences. To examine the peer effects in each conference, we propose a novel dynamic model that can identify conference-specific peer effects while capturing the dynamic evolution of brand revenue. Our model estimation results reveal significant positive peer effects in four major conferences—Big 12, Big Ten, Southeast Conference, and Pacific-12— indicating that teams benefit from playing in a conference with strong teams. Our approach also sheds light on the effect of conference switches on a team’s brand revenue. By constructing the counterfactual brand revenue trajectory of not switching conferences for a switched team, we show the difference between the counterfactual trajectory and the actual brand revenue evolution after switch, which scientifically quantifies the effect of a conference switch. We also study the case where a team had considered but did not make a conference switch.

Zhuping Liu (Page 8) Jianqiang Zhang, Zhuping Liu and Raghunath Singh Rao. “Flirting with the Enemy: Online Competitor Referral and Entry-Deterrence.” Under review at Management Science.



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