Syllabus. 1 Title Experimental Research in Marketing & Management

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1 1 Title Experimental Research in Marketing & Management 2 Faculty Xueming Luo Charles Gilliland Chair Professor of Marketing, Strategic Management, and Information Systems Founder/Director of Global Center on Big Data and Mobile Analytics Fox School of Business, Temple University, Philadelphia, PA, USA luoxm@temple.edu Sascha Raithel Junior Professor of Financial Performance-based Marketing and Management Institute for Market-based Management Munich School of Management, Ludwig-Maximilians-University in Munich, Germany raithel@bwl.lmu.de 3 Outline This is a 4-day PhD course about randomized and quasi/natural laboratory/field experiments in marketing & management research and provides an introduction to relevant methods and quantitative models. It is designed with the goal of providing exposure to cutting-edge topics in various disciplines and its applications in marketing & management research. The course is divided into two parts: 1. On the first two days, students get exposure to relevant experimental methods and quantitative techniques during computer lab sessions. Students learn to know Difference between correlation and causality Classes of experiments (laboratory vs. field, randomized vs. quasi/natural experiments) Difference between internal and external validity in experiments Remedies against threats to validity Characteristics of various experimental designs Basics in Analysis of Variance (ANOVA) Basics in linear regression and selected problems (e.g., correct selection of relevant exogenous variables, heteroscedasticity, autocorrelation, multicollinearity) Basics in mediation and moderation Basics in logit/probit regression 1

2 Tips and tricks for optimizing analyses/results for submission/revision covering topics like presentation and communication of results, missing data detection and treatment, outlier detection and treatment, robustness checks 2. On the last two days, students present selected papers (see list below) and one of their own dissertation projects (including proposals). Topics for dissertation projects include (not exhaustive): Marketing strategy Mobile marketing Brand management Marketing-information systems interface Customer relationship management Digital social media strategy Corporate social responsibility and sustainability Paper presentations: Each day, students will be assigned to present the papers; focusing on Hypotheses, Model, Data, Contributions; 5 min, PPT based. Presentation of project proposals from PhD students: Hypotheses, Model, Data, Contributions; 30 min; PPT based. Particularly, the learning objectives of the course include: 1) Understand and apply basic empirical methodologies in quantitative research 2) Read and critique the literature on the applications of the above topics in A+ journals. 3) Identify interesting and important research questions in those fields 4) Understand the various models and experimental designs to match different research questions 5) Draft and prepare to submit research projects to top A+ journals in marketing (JM/JMR/MKSC/MGSC), management (SMJ/AMJ), and information systems (ISR/MISQ/MGSC). 4 Administration 4.1 Tentative schedule Day 1: March 9th, 2015 [Sascha Raithel] Location: tbd 13:30 15:00 Introduction to course & Correlation vs. causality 15:15 16:45 Experimental designs 17:00 18:30 ANOVA 2

3 Day 2: March 10th, 2015 [Sascha Raithel] Location: tbd 09:00 10:30 Linear regression and selected problems (I) 10:45 12:15 Linear regression and selected problems (II) 12:15 13:30 Lunch 13:30 15:00 Mediation & moderation 15:15 16:45 Logistic/probit regression 17:00 18:30 Optimizing analyses/results for submission/revision Day 3: March 11th, 2015 [Xueming Luo] Location: tbd 09:00 10:30 Paper presentations 10:45 12:15 Paper presentations 12:15 13:30 Lunch 13:30 15:00 Paper presentations 15:15 16:45 Paper presentations 17:00 18:30 Project intensive training (Projects to be assigned) Day 4: March 12th, 2015 [Xueming Luo] Location: tbd 09:00 10:30 Paper presentations 10:45 12:15 Project intensive training (Projects to be assigned) 12:15 13:15 Lunch 13:15 15:00 Project intensive training (Projects to be assigned) 3

4 15:15 16:45 Project intensive training (Projects to be assigned) Professor Xueming Luo intends to select some students and invite them to work with him on his ongoing projects! 4.2 Location Ludwig-Maximilians-University, Munich, Germany 4.3 Max. number of participants The number of participant is limited to 10 because of the extensive efforts for the towardpublication submissions to top journals. 4.4 Cost The course fee amounts to EUR Prerequisites Prior exposure to basics in statistics is recommended. 6 Course Material Will be provided prior to and during the workshop. # Papers Michelle Andrews, Xueming Luo, Z. Fang, and J Aspara (2014), Cause Marketing 01 Effectiveness Journal of Marketing, November, Forthcoming. Luo, Xueming, M. Andrews, Z. Fang, and Z. Phang (2014), Mobile Targeting, 02 Management Science, 60(7), M. Andrews, Xueming Luo, Z. Fang, and A Ghose, Mobile Crowdsensing, at Marketing 03 Science working 04 D. Phang, Z. Fang, X Luo, Geo-Social Mobile Targeting at Management Science working Nathan Fong, Zheng Fang, and Xueming Luo, Geo-conquesting Mobile Promotions 05 Journal of Marketing Research. working Luo, Xueming, M. Andrews, Y. Song, and J. Aspara (2014), Group-Buying Deal 06 Popularity, Journal of Marketing, 78(2), Chan, K, Y. Li, J. Zhu, and Xueming Luo, Crowdsourcing with Customers Journal of 07 Marketing Research. working Luo, Xueming, CX Li, Y. Song, and C. Phang, Eco-Friendly Car Policy Effects American 08 Economics Review, working paper 4

5 09 10 Raithel, S.; Taylor R. C.; Stewart, D. W. (2014): Do Super Bowl Ads Build Brands?, working. Hock, S.; Raithel, S. (2014): Negative Celebrity Publicity and Firm Value: How Critical Are Immediate Firm Reactions?, Marketing Science, working. 7 To Prepare To use own laptops during lab sessions, a Stata license is recommended (but PCs with Stata installed will be provided). 8 Assessment The grade will be based on three things: 1. Attendance, class Q&A (25% of the grade) 2. Literature oral presentation and PPTs (25% of the grade) 3. Project oral presentation and PPTs before the intensive training and project implementation during/after the project intensive training (50% of the grade) 9 Credits The course is eligible for 6 ECTS. 5