XIAN GU. Specialization in Quantitative Marketing; Minor in Economics Robert H. Smith School of Business, University of Maryland, College Park, MD

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1 XIAN GU Suite 3330 Van Munching Hall College Park, MD EDUCATION Ph.D. in Marketing 2019 (expected) Specialization in Quantitative Marketing; Minor in Economics,, College Park, MD M.A. Economics 2014 Doctoral Coursework in Economics and Doctoral Comprehensive Exams Passed Stony Brook University, Stony Brook, NY Bachelor of Economics 2012 Peking University, Beijing, China RESEARCH INTERESTS Substantive: Mobile Marketing Omnichannel Marketing Multi-devices Marketing Methodological: Treatment Effect Estimation Field Experiment Structural Model Machine Learning DISSERTATION Title: Committee: Marketing in Mobile, Omni-channel and Multi-Format Contexts P. K. Kannan (chair), Liye Ma (co-chair), Michel Wedel, David Godes, Guido Kuersteiner MANUSCRIPTS UNDER REVIEW Gu, Xian and P. K. Kannan, The Dark Side of Mobile App Adoption: Examining the Impact on Customers Multichannel Purchase, Under preparation for 2 nd round review at Journal of Marketing Research Gu, Xian, P. K. Kannan and Liye Ma, Selling the Premium in Freemium, Under 2 nd round review at Journal of Marketing

2 SELECTED RESEARCH IN PROGRESS A Structural Model of Mobile App Adoption and Multichannel Choice of Purchase, with Liye Ma and P. K. Kannan Marketing Applications of Generalized Transfer Entropy Metrics, with P. K. Kannan and Vithala R. Rao Optimal Pricing Strategy with Mobile-Assisted Shopping, with David Godes and Yogesh Joshi Identifying the Competitors in the Market: A Spatial Approach, with P. K. Kannan HONORS & AWARDS AMA Sheth Doctoral Consortium Fellow (2018) Haring Symposium Fellow (2018) Winner, Shankar-Spiegel Best Dissertation Proposal Award (2017) Robert Mittelstaedt Doctoral Symposium Fellow (2017) INFORMS Marketing Science Doctoral Consortium Fellow (2016) CONFERENCE PRESENTATIONS A Structural Model of Mobile App Adoption and Multichannel Choice of Purchase INFORMS Marketing Science Conference, Philadelphia, PA (June 2018) The Dark Side of Customer Mobile App Adoption: Examining the Impact on Their Multichannel Purchase Robert Mittelstaedt Doctoral Symposium, Lincoln, NE (March 2017) AMA Winter Academic Conference, Orlando, FL (February 2017) INFORMS Marketing Science Conference, Shanghai, China (June 2016) Selling the Premium in Freemium: The Impact of Product Line Extensions Haring Symposium, Bloomington, IN (April 2018) INFORMS Marketing Science Conference, Los Angeles, CA (June 2017) Marketing Applications of Generalized Transfer Entropy Metrics Marketing Dynamics Conference, Hong Kong, China (August 2017) Advanced Research Techniques (ART) Forum, San Diego, CA (June 2015)

3 TEACHING EXPERIENCE Instructor, Marketing Research Methods (Undergraduate Core),,, Spring 2017 (Overall Rating: 3.1 out of 4.0) COMPUTER SKILLS R, MATLAB, STATA, C, EViews, SPSS, LaTeX DOCTORAL COURSEWORK Marketing Marketing Models Marketing Models with MCMC Structural Models Analytical Models Marketing Strategy Consumer Behavior P. K. Kannan Michel Wedel Tao Chen David Godes Roland Rust Amna Kirmani Economics Computational Economics Econometrics II Econometrics IV Theories of Industrial Organization Empirical Studies in Industrial Organization Empirical Microeconomics Microeconomics I Microeconomics II Macroeconomics I Macroeconomics II Econometrics Applied Econometrics Industrial Organization I Industrial Organization II Game Theory I Game Theory II Mathematical Statistics Andrew Sweeting Guido Kuersteiner, Ingmar Prucha Guido Kuersteiner, Ingmar Prucha Daniel Vincent Ginger Jin Raymond Guiteras Sandro Brusco Pradeep Dubey Alexis Anagnostopoulos Eva Carceles-Poveda Mark R. Montgomery Mark R. Montgomery Sandro Brusco Yiyi Zhou Yair Tauman Pradeep Dubey Jiaqiao Hu

4 REFERENCES P. K. Kannan (chair) Liye Ma (co-chair) Dean s Chair in Marketing Science Associate Professor 3445 Van Munching Hall 3323 Van Munching Hall College Park, MD College Park, MD pkannan@rhsmith.umd.edu liyema@rhsmith.umd.edu Phone: (301) Phone: (301) Michel Wedel David Godes Distinguished University Professor and Professor and Department Chair PepsiCo Chair in Consumer Science 3321 Van Munching Hall 3303 Van Munching Hall College Park, MD College Park, MD dgodes@rhsmith.umd.edu mwedel@rhsmith.umd.edu Phone: (301) Phone: (301)

5 RESEARCH ABSTRACTS Selling the Premium in Freemium with P. K. Kannan and Liye Ma (won the 2017 Shankar-Spiegel Best Dissertation Proposal Award) We investigate how to increase the effectiveness of the freemium model by extending the product line as a means to spur demand for the existing premium version. We discuss the conceptual nuances that the presence of the free version introduces in analyzing the impact of product line extensions in this context. We conduct a randomized field experiment with an online content provider, the National Academies Press, which offers book titles in a PDF format for free and sells the paperback format for a premium. Overall, we show that paperback titles accompanied by an additional premium format, either an ebook or a hardcover format, have higher sales than those in the control condition. The positive impact on paperback sales is stronger for titles that are more popular and/or lower in price, and the effect of introducing the ebook format is higher when the ebook price is closer to the paperback price. By analyzing customer choices at the individual level, we confirm the existence of the compromise effect and the attraction effect in the extended product line setting, a significant contribution not only in the freemium context but also to the product line literature. We provide specific managerial recommendations to increase the sales of premium products in the freemium model. The Dark Side of Mobile App Adoption: Examining the Impact on Customers Multichannel Purchase with P. K. Kannan Increasingly firms are using mobile applications to engage with customers, provide services, and encourage customer spending. Conventional wisdom indicates that apps have a positive impact on customer spending. We critically examine this premise by estimating the impact of app adoption on customers' omni-channel spending in the context of a hotel chain and identifying the factors contributing to such impact. Exploiting the variation in customers' timing of app adoption and difference-in-differences approach, we find that app adoption has a significant negative impact on total customer spending. This negative effect is robust to controlling for customer self-selection bias, measuring effects across alternative time frames, customer spending patterns and app usage behaviors, using different measures of purchase and alternative model specifications, and using different random samples. A survey of app adopters reveals that customers who adopt the focal app are also most likely to adopt competitors' apps, and therefore are likely to search more and

6 shop around, leading to decreased share of wallet with the firm. Our analysis also reveals that the negative impact on spending is lower for those customers who use the apps for mobile check-in than those who use the apps for just searching. By encouraging customers to engage with the full functionality of the app, firms can possibly mitigate the negative impact. A Structural Model of Mobile App Adoption and Multichannel Choice of Purchase with Liye Ma and P. K. Kannan Consumers' multi-channel shopping is a widely observed phenomenon. From a firm's perspective, understanding consumers' channel choice and purchase decision is critical for their revenue. Furthermore, mobile applications (apps) have become a popular shopping channel for firms to engage with customers, provide services, and impact customer spending and loyalty. Therefore, another key question to answer is how the introduction of this new channel (i.e., mobile apps) impact consumer cross-channel shopping behavior. Using data from a leading hospitality firm covering a four-year period, we develop an integrated dynamic structural model to investigate consumers' decision to adopt mobile applications, and its subsequent impacts on their decisions to purchase using alternative shopping channels. With counterfactuals we examine the impact of firm's decision not to introduce an app and availability of app services on customer spending. Marketing Applications of Generalized Transfer Entropy Metrics with P. K. Kannan and Vithala R. Rao This research introduces the generalized transfer entropy (GTE) methodology to provide a fast and useful solution for analyzing big data in marketing. More specifically, the proposed methodology can process large volume of multi-channel marketing data at the individual level in a long-time horizon, without making strict assumptions on the underlying nature of the relationship. The results from this work can assess the incremental contribution from each marketing channel in leading to conversions. We applied GTE to two real click-stream data sets: multichannel attribution and customer paths across multiple firms in travel industry. In the first application, we focused on how best to design effective media-mix and channel-mix strategies by properly attributing conversions/sales occurring in different online and offline channels. In the second application, we used GTE measures to investigate customer path across different hotel brands and travel websites, and thus shed some light on whether travel websites take away or bring in customers of a hotel brand. While many methodologies have been proposed in recent times in marketing literature for analyzing path data (Abhishek, Fader, and Hosanagar 2012; Berman

7 2014; Kireyev, Pauwels, and Gupta 2016; Li and Kannan 2014; Xu, Duan, and Whinston 2014), most of them follow a parametric framework and make assumptions about the underlying relationship with different model structures. In addition, these parametric approaches also require significant time on model estimation with limited sample size. In contrast, the GTE methodology is fast and can provide useful, satisfying solutions using all available data in near real time.