Master of ScienceConsumer Behavior and Decision Sciences
This 36-semester hour Consumer Behavior and Decision Sciences Master of Science degree program is an applied behavioral research degree driven by industry and public sector demand for actionable insights into human behavior.
The degree prepares students to pursue marketable careers in applied behavioral research (e.g., Consumer Insights Manager, Market Research Analyst, Marketing Manager, Sensory Scientist and Behavioral Scientist).
HU’s Consumer Behavior and Decision Sciences is an innovative multidisciplinary STEM degree, with a curriculum well suited for students with a background in the social and/or quantitative sciences. It merges the experimental methodologies of behavioral scientists, the decision theories of economists, marketers, and psychologists, and the quantitative skills of analysts, with the applied focus of business and industry. Students learn to synthesize theory in order to perform cutting edge consumer, market, and applied behavioral research, evaluate data to uncover actionable insights, and leverage those insights to shape behavior.
The program focuses on emergent and advanced experimental methods and analytic techniques, ensuring graduates can adapt and innovate in their chosen field(s). Through an applied research project in partnership with industry, the public sector, or community organizations, students produce direct evidence of their ability to conduct transformative research, setting them apart from their peers as they enter the job market. Graduates will be able to assess consumer (broadly defined) preferences (insights) using a variety of traditional and emergent research methodologies and turn those insights into actionable strategies using quantitative/qualitative decision making.
Students have the opportunity for further practical research experiences through a connection with HU’s Consumer Insights Research Lab. This collaboration is designed to fuel students’ passions for applied behavioral research, while highlighting their aptitude to potential employers. Through participation in the Consumer Insights Research Lab students work on a variety of research projects commissioned by our industry and public sector partners, providing them a unique opportunity to foster relationships with research and industry leaders.
This program is not eligible for CPT (Curricular Practical Training).
Graduates of the Master of Science in the Consumer Behavior and Decision Sciences Technologies program will be able to:
- Determine the best research methodologies to employ in order to gain robust consumer insights;
- Turn consumer insights into actionable recommendations through the application of appropriate analytic techniques;
- Effectively communicate consumer research to diverse audiences; and,
- Innovate consumer research.
Consumer Behavior and Decision Sciences Advisory Board
The Consumer Behavior and Decision Sciences program is guided by a diverse and talented local and global membership, ensuring the program produces graduates capable of stepping into a variety of roles. We thank the members of the board for their insight and continued guidance:
Joanna Crishock, Director of Strategy and Innovation, Giant
Chad Firestone, Client Relationship Executive, Deloitte
Darby Hughes, Director of Brand Strategy, Pavone
Corey Meyer, Director Strategic Acceleration, Penn Medicine Lancaster General Health
Jennifer Neidigh, Senior Customer Experience Strategist, Capital Blue Cross
Adam Pardes, COO, NeuroFlow, Inc.
Alicia Titus, Vice President for Mission Advancement, Messiah Lifeways
Craig Troop, Deputy Director of Research, Pennsylvania Lottery
Chris Clegg, President, Portland Marketing Analytics
Jacqueline Bichsel, Ph.D., Director of Research, CUPA-HR
Roxanne van Giesen, Senior Researcher, CentERdata NL
Kathi Kaiser, Partner, Centralis
Sharon Livingston, President, The Livingston Group for Marketing
Cara Lousararian, Research Director, Chadwick Martin Bailey
Evan Zeller, Founder and Chief Strategy Officer, Furtive Collective
The following courses comprise the Master of Science in Consumer Behavior and Decision Sciences – 36 semester hours. The semester hour value of each course appears in parentheses ( ). Complete all of the following:
This course takes an applied perspective and provides the statistical tools and analytic thinking techniques needed to: formulate a clear hypothesis, determine the most efficient method to obtain required data, determine and apply the proper statistical techniques to the resulting data, and effectively convey the results to both experts and laypersons. The course begins with a review of the descriptive analytics concepts (i.e., sampling, and statistical inferences) introduced in ANLY 500 as well as general conventions regarding experimentation and research. It then progresses to predictive and prescriptive analytics techniques such as regression and forecasting that can be used to predict future events. Later sessions focus on issues related to lack of experimental control (e.g., quasi-experimental design and analysis). The course culminates with a research project in which the student applies the concepts learned to their own research interests.
The visualization and communication of data is a core competency of analytics. This course takes advantage of the rapidly evolving tools and methods used to visualize and communicate data. Key design principles are used to reinforce skills in visual and graphical representation.
Human Behavior is the result of complex interactions between physiological and psychological processes. This is an accelerated course designed to give the student a firm understanding of these processes, as well as insight into how this knowledge can be used to garner unique insights which can be leveraged to influence behavior. Foundational topics such as perception, learning and memory, emotion, and cognitive biases and attempt to exploit them via nudging are covered through lectures, discussion or current applied research, and a team project developing an applied behavioral research plan.
The easiest way to find out about people is to ask them questions. As a result, a large amount of the data used to generate insights comes from simple survey questions. This course is designed to teach the student how to develop efficient questions and to deploy surveys in person, telephonically, or online (mobile). Statistical methods for determining question and construct reliability are covered. Course material is presented via lectures, texts (textbook and supplementary readings), and several projects.
Innovative ideas often come from spontaneous conversation and interactions. Focus groups (panels) and observational research methods facilitate the discovery of these unique consumer insights. This course provides an overview of the proper use of focus groups, panels, and observational designs in consumer research. Central topics include question design, planning, implementation, moderation/observation techniques, virtual panels, data processing, and qualitative and quantitative analysis strategies. Course materials are presented via lectures, guest lectures, and as well as individual and team projects.
To generate actionable insights and implement them effectively we need to know how consumers are distributed across the population, what segments will want a product or service, and how we can sample from relevant segments so that our data is representative of relevant populations. This is an advanced course designed to provide an overview of these topics from an applied analytic perspective. The first half of the course focuses on sampling methods for data collection such as: Stratification, cluster sampling, systematics selection, multistage sampling, and probability proportional to size sampling. The second half of the course focuses on analytic methods for the four main types of market segmentation: Demographic, behavioral, psychographic, and geographic. Material is presented via lectures, discussions, immersive labs, and an applied team project.
Bespoke marketing tools and methods of approach underly much of today’s marketing research. This course is separated into three sections related to appealing to your customer base: The first covers conjoint analysis tools used to determine the value of product/services features as viewed by the customer and to assess (attractive) market prices. The second provides an overview of market mix modeling allowing for an efficient marketing plan to be deployed. The final section covers customer relationship management (CRM). An overview of what CRM is, what CRM has and has not yet delivered, popular CRM technologies, and how analytic techniques can be employed to determine customer equity, customer lifetime value, and predict customer loyalty and churn is provided. Material is presented via lectures (guest lectures), discussions of current research and theory, case studies, labs, and applied projects.
Theories of human behavior and behavioral research methods are constantly evolving. This seminar is designed to provide an overview of the state-of-the-art in applied behavioral research. Each session will consist of a discussion of recent advances in consumer research and/or a relevant story pulled from the headlines. Guest lectures from academia, industry, and the public sector will also present their work and their views on the future of applied behavioral research.
As technology advances so do applied behavioral research methodologies. This frequently updated course provides the knowledge and skills needed to conduct innovative applied behavioral research using emergent methodologies. Research applications covered include: Decision time analysis, mouse tracking, eye tracking, affect measurement, and practical neural measurement techniques (e.g., NIRS and ECG/EEG). Material is presented via lectures (guest lectures), discussions of transformative research, labs, and an immersive research project.
This seminar is designed to assist the student as they produce the final deliverable of their studies – an applied behavioral research project. In the first weeks the student will deliver an overview of their project and what stage they are currently in. During the following weeks the student will deliver status updates allowing them to seek out feedback and advice for how to approach issues encountered (e.g., implementation and analysis problems), while also benefitting from their classmates’ experiences. In the final weeks the student will give a presentation which will be in the format of a “mini-defense”.
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