Mobile Marketing and Quantitative Models

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1 Mobile Marketing and Quantitative Models Author: JEAN-PIERRE DUBE - jdube@chicagobooth.edu University: UNIVERSITY OF CHICAGO Track: SPECIAL INTEREST GROUP Access to this paper is restricted to registered delegates of the EMAC 2015 Conference.

edu University: UNIVERSITY OF CHICAGO Track: SPECIAL INTEREST

2 Special session Mobile Marketing and Quantitative Models (Papers, authors, affiliations): Chair: Xueming Luo (Temple University), JP Dube (University of Chicago) Self-Signaling and Pro-Social Behavior: Mobile Field Experiments - JP Dube* (U. Chicago), Xueming Luo (Temple U.), Zheng Fang (Sichuan U.) Mobile Media and Customer Engagement - Vijay Viswanathan* (Northwestern U.), Linda Hollebeek (Northwestern U.), Ed Malthouse (Northwestern U.), Su Jung Kim (Northwestern U.), Wei Xie (Northwestern U.) Mobile App Analytics: A Multiple Discrete-Continuous Choice Framework - Sang Pil Han* (Arizona State U.), Sungho Park (Arizona State U.), Wonseok Oh (Korea Advanced Institute of Science and Tech.) Geo-social Mobile Targeting - Xueming Luo* (Temple U.), Andy Reinaker (Temple U.), Chee Wei Phang (Fudan U.), Zheng Fang (Sichuan U.) * Presenting author; Each presenter has agreed to serve if the proposal is accepted, and none of the papers have previously been presented at EMAC, or have already been published in any journal.

), Linda Hollebeek (Northwestern U.), Ed Malthouse (Northwestern U.), Su Jung Kim (Northwestern U.), Wei Xie (Northwestern U.

3 Mobile Marketing and Quantitative Models 125-Word Abstract Mobile marketing and advertising offer innovative ways to test psychology theories and economics models. Dube et al. show that price discount crowds out the consumer s warm-glow feeling from the charitable donation, supporting a self-signaling theory. This evidence converges via randomized controlled field experiments and structural model of demand. Viswanathan et al. investigate the effects of customers (dis)engagement with a brand s mobile app on purchase and redemption behaviors over time with time-series econometric VAR models. Han et al. develop a utility theory-based structural choice model of mobile app demand and satiation, using a unique panel data set detailing individual user-level mobile app time consumption. Luo et al. point out the importance of a comprehensive model via geo-location, social influence messages, and regulatory focus for mobile marketing effectiveness.

This evidence converges via randomized controlled field experiments and structural model of demand. Viswanathan et al.

4 Mobile Marketing and Quantitative Models Paper Abstracts Self-Signaling and Pro-Social Behavior: Mobile Field Experiments - JP Dube* (U. Chicago), Xueming Luo (Temple U.), Zheng Fang (Sichuan U.) We test a self-signaling theory using two large-scale, randomized controlled field experiments. Mobile phone users are randomly sampled to receive promotional offers for movie tickets via SMS technology. Test groups are exposed to different pre-determined levels of price discounts and charitable donations tied to the ticket purchase. The main effects of price discounts and charitable donations increase ticket demand. However, the combination of both discounts and donations can decrease ticket demand. In a post-purchase survey, the same subjects self-report lower ratings of feeling good about themselves as the motivation for buying a ticket when discounts and donations are both large. These findings are consistent with a self-signaling theory, whereby the discount crowds out the consumer s warm-glow feeling from the charitable donation. Alternative behavioral explanations are ruled out. A structural model of demand with self-signaling is fit to the data using a constrained optimization algorithm to handle the potential multiplicity of equilibria. The estimated preferences reveal that consumers do not derive consumption utility from donations bundled with the ticket. However, they derive significant diagnostic utility: the warm-glow feeling of the self-perception of valuing charitable donations. Mobile Media and Customer Engagement - Vijay Viswanathan* (Northwestern U.), Linda Hollebeek (Northwestern U.), Ed Malthouse (Northwestern U.), Su Jung Kim (Northwestern U.), Wei Xie (Northwestern U.) Firms are still figuring out the best way to engage with their customers and measure the effects of engagement. Many attempts at engagement fail to create value for consumers and instead disengage them. In this study, we analyze data provided to us by a large loyalty program. The data captures customers (dis)engagement with a brand s mobile application (app hereafter) as well as their purchase and redemption behaviors over time. We model engagement as a dynamic, iterative process using a vector autoregressive (VAR) model. The results from the model enable us to understand how increases in engagement as well as decreases in engagement (i.e., disengagement) affect purchase behaviors. Mobile App Analytics: A Multiple Discrete-Continuous Choice Framework - Sang Pil Han* (Arizona State U.), Sungho Park (Arizona State U.), Wonseok Oh (Korea Advanced Institute of Science and Tech.) The number of mobile apps is exponentially growing to over 2 million, but little is known about how users choose and consume apps in numerous categories. This study develops a utility theory-based structural model for mobile app analytics. Specifically, based on the theoretical notions of utility and satiation along with the factor analytic approach, we model users multiple discrete app choice and continuous consumption decisions simultaneously in order to uncover the complex relationships among choice, consumption, and utility maximization for numerous mobile apps. Using a unique panel data set detailing individual user-level mobile app time consumption, we quantify the baseline utility and satiation levels of diverse mobile apps and delineate how users app preferences and consumption patterns vary across demographic factors. The findings suggest that users baseline utility diverges substantially across app categories and their demographic characteristics explain a substantial amount of heterogeneity in baseline utility and satiation. Furthermore, both positive and negative correlations exist in the baseline utility and satiation levels of mobile web and app categories. Our modeling approaches and computational methods could open new perspectives and opportunities for handling large-scale, micro-level data, while serving as important resources for big data analytics and mobile app analytics in particular.

Mobile phone users are randomly sampled to receive promotional offers for movie tickets via SMS technology.

5 Geo-social Mobile Targeting - Xueming Luo* (Temple U.), Andy Reinaker (Temple U.), Chee Wei Phang (Fudan U.), Zheng Fang (Sichuan U.) Mobiles ads, despite their appealing potential, face the challenge of overall ineffectiveness. The authors conduct two randomized field experiments to test the notion of consumer-conscious mobile ads, i.e., effective mobile ads must coordinate the ad message content with the consumer geographic location context and mindset focus. Findings show that messages are effective when the mobile ad message content fits the consumer mindset in each of two location contexts (home and work). In addition to being driven by message congruence with the current location, mobile ad messages are more persuasive when framed with the correct regulatory focus (promotion and prevention-focus) given the reference to primary or secondary social goal reminders. The findings have important implications for managers who are conscious of receiving a return on their use of mobile ads and provide key insights into how to capitalize on the work/life balance for higher mobile ad effectiveness.

The authors conduct two randomized field experiments to test the notion of consumer-conscious mobile ads, i.e., effective mobile ads must coordinate the ad message content with the consumer geographic location context and mindset focus.

6 Contact Author Information JP Dube, Professor of Marketing, Department of Marketing, University of Chicago Zheng Fang, Associate Professor of Marketing, Sichuan University, China Sang Pil Han, Assistant Professor, Informations Systems Department, City University of Hong Kong Linda Hollebeek, Professor of Marketing, Northwestern University Koert Van Ittersum, Professor of Marketing, University of Groningen Su Jung Kim, Professor of Marketing, Northwestern University Xueming Luo, Charles Gilliland Distinguished Professor of Marketing, Department of Marketing, Temple University Ed Malthouse, Professor of Marketing, Northwestern University Wonseok Oh, Professor of Graduate School of Information and Media Management, Korea Advanced Institute of Science and Technology Sungho Park, Assistant Professor, Department of Marketing, Arizona State University Chee Wei Phang, Professor of Marketing, Fudan University Andrew Reinaker, Ph.D. Student, Department of Marketing, Temple University Vijay Viswanathan, Professor of Marketing, Northwestern University Wei Xie, Professor of Marketing, Northwestern University

com Sang Pil Han, Assistant Professor, Informations Systems Department, City University of Hong Kong sangphan@cityu.edu.

Mobile Targeting and Marketing Analytics. Xueming.Luo@temple.edu GBM Center Director/Founder, Charles Gilliland Distinguished Professor

Mobile Targeting and Marketing Analytics Xueming.Luo@temple.edu GBM Center Director/Founder, Charles Gilliland Distinguished Professor Mobiles change how people live and work (big data) With when, where,