Unit 3 Introduction To Marketing Coursework Stanford

Units: 3

Quarter Offered: Not offered this year

Applied introduction to good empirical research and causal inference for social scientists and others analyzing social data. Designed to provide an introduction to some of the most commonly used quantitative techniques for causal inference in social data including: survey design and inference, regression and propensity score matching, instrumental variables, differences-in-differences, regression discontinuity designs, standard errors, and the analysis of big data. Applications: organizations, entrepreneurship, public policy, innovation, economics, online education, visual representations, communication, critique and design of figures, graphs. Does not explicitly cover social network structure or machine learning as these topics are well-covered elsewhere. Students work in groups and individually to design and carry out a small research project based on the use of analytics, large data sets, or other digital innovations related to business or other organizations. Students become acquainted with a variety of approaches to research design, and are helped to develop their own research projects. Course prioritizes a thorough substantively grounded understanding of assumptions over mathematical proofs and derivations. Aimed at PhD students, but open by permission to Master's students and to students in other Stanford programs with relevant coursework or experience in analytics and statistics.

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MKTG 337:Applied Behavioral Economics

The field of behavioral economics couples scientific research on the psychology of decision making with economic theory to better understand what motivates economic agents, including consumers, managers, public policymakers, investors, and employees. In this course, we will examine topics such as the "irrational" patterns of how people think about products, money and investments, designing strategies and offerings to change behavior, and the drivers of happiness and the role of emotions in decision-making. This highly interdisciplinary course will be particularly relevant to students with interests in general management, entrepreneurship, Marketing, Strategy, Behavioral Finance, public policy, and nonprofit. Topics covered will include: Rationality and choice, choice complexity, intertemporal choice, emotional influences on choice, the role of behavioral economics in marketing, spending and savings behavior, social welfare, choice architecture, and defaults. The goals of this course ar more »

The field of behavioral economics couples scientific research on the psychology of decision making with economic theory to better understand what motivates economic agents, including consumers, managers, public policymakers, investors, and employees. In this course, we will examine topics such as the "irrational" patterns of how people think about products, money and investments, designing strategies and offerings to change behavior, and the drivers of happiness and the role of emotions in decision-making. This highly interdisciplinary course will be particularly relevant to students with interests in general management, entrepreneurship, Marketing, Strategy, Behavioral Finance, public policy, and nonprofit. Topics covered will include: Rationality and choice, choice complexity, intertemporal choice, emotional influences on choice, the role of behavioral economics in marketing, spending and savings behavior, social welfare, choice architecture, and defaults. The goals of this course are threefold: a) to study the basic principles of behavioral economics, b) To learn the application of the principles to various aspects of business and policy, and c) to think about a framework for developing products, programs, and tactics that are behaviorally informed. The course is composed of a mixture of lectures, exercises, academic paper reviews, and in-class case discussions. The purpose of the lectures is to present and discuss theories, concepts, analytical techniques and empirical findings. In-class exercise will be used to apply the concepts and techniques covered in the class. We will discuss a few business cases. In addition, students working in teams will prepare an analysis and recommended behavioral strategy for a company/startup of their choice.

Units: 3 | Grading: GSB Letter Graded

Instructors: Simonson, I. (PI)

2017-2018 Spring

  • MKTG 337 | 3 units | Class # 32041 | Section 01 | Grading: GSB Letter Graded | CAS | Students enrolled: 29 / 50
    04/05/2018 - 06/05/2018 Tue 8:30 AM - 11:20 AM at GSB Patterson 102 with Simonson, I. (PI)
    Instructors: Simonson, I. (PI)
    Notes: No Exam. Case and Problem Discussion. P/F Not Allowed. Non-GSB students: See gsb.stanford.edu/NonGSBReg. Capacity limited to 50 students. Open to MBA and MSx students. Participation 40% Proj/Papers 40% Assignments 20%. Mandatory attendance. Absences impact grade.
  • MKTG 337 | 3 units | Class # 32042 | Section 02 | Grading: GSB Letter Graded | CAS | Students enrolled: 34 / 50
    04/05/2018 - 06/05/2018 Tue 3:00 PM - 5:50 PM at GSB Patterson 102 with Simonson, I. (PI)
    Instructors: Simonson, I. (PI)
    Notes: No Exam. Case and Problem Discussion. P/F Not Allowed. Non-GSB students: See gsb.stanford.edu/NonGSBReg. Capacity limited to 50 students. Open to MBA and MSx students. Participation 40% Proj/Papers 40% Assignments 20%. Mandatory attendance. Absences impact grade.

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