Sean Hansen Headshot

Sean Hansen

Department Chair

Department of MIS, Marketing, and Analytics
Saunders College of Business
shansen@saunders.rit.edu
585-475-3974
Office Location
LOW-3331

Sean Hansen

Department Chair

Department of MIS, Marketing, and Analytics
Saunders College of Business

Education

BA, Harvard University; MBA, Ph.D., Case Western Reserve University

Bio

Sean Hansen is the Department Chair of MIS, Marketing, & Analytics and a Professor of Management Information Systems (MIS) in RIT's Saunders College of Business. He received his PhD from the Weatherhead School of Management at Case Western Reserve University. His research interests are in software design and development, health IT, IT strategy, and the application of contemporary cognitive theory to information systems development. Prior to embarking on a career in research and teaching, Sean provided management and technology consulting services to companies across the industrial spectrum. His research has been published in leading journals in the MIS field, including MIS Quarterly, Information Systems Research, Communications of the ACM, Information Systems Journal, Information and Organization, The Information Society, and Decision Sciences, as well as multiple edited volumes. He regularly presents his research at leading academic conferences.

shansen@saunders.rit.edu
585-475-3974
Areas of Expertise
Ethics in business
Ethics in society
Facilitation and group process
Information management and systems
Qualitative and quantitative methods
Strategic planning
Systems analysis and design
Technology management
Computing
Healthcare Technology
Information Science

Currently Teaching

BANA-785
Business Analytics Experience
3 Credits
Students apply their mathematical, data analytic, and integrative business analytics skills in a complex project involving real or simulated data. Under the supervision of an advisor, students work in teams to perform a stipulated task/project and write a comprehensive report at the end of the experience. Subject to approval by the program director, an individual student internship/coop followed by an in-depth report may obtain equivalent credit.
DECS-864
Systems Support for Operations
2 Credits
This course focuses on the application of information technology to gain greater efficiency and effectiveness from operational and managerial processes and systems. The conceptual foundations of operations, supply chain management and information technology are surveyed and contemporary approaches analyzed from a managerial perspective.
MGIS-720
Information Systems Design
3 Credits
This course provides students with fundamental knowledge and skills required for successful analysis of problems and opportunities related to the flow of information within organizations and the design and implementation of information systems to address identified factors. Students are provided with knowledge and experience that will be useful in determining systems requirements and developing a logical design.
MGIS-735
Design and Information Systems
3 Credits
Students who complete this course will understand the principles and practices employed to analyze information needs and design appropriate IT-based solutions to address business challenges and opportunities. They will learn how to conduct requirements analysis, approach the design or redesign of business processes, communicate designs decisions to various levels of management, and work in a project-based environment.
MGIS-815
Research Design
3 Credits
The doctoral seminar course introduces students to the most prominent theoretical streams within the scholarly discipline of Management Information Systems. Students read, analyze, and discuss seminal research manuscripts within the field. Through these analyses, they discern underlying assumptions, philosophical/ ontological stances, and central arguments of the various works. In addition, students complete a focused exploration of the research corpus of one or more significant researchers within the discipline.
MKTG-830
Structural Equation Modeling
3 Credits
This course provides a detailed look at structural equation modeling (SEM) for doctoral students. SEM is a technique for modeling the relationships among multiple latent variables. It includes models that have multiple indicators of constructs (latent variables; confirmatory factor analysis) that have directional relationships among constructs (path analysis; structural equations). The course will cover both conceptual and practical aspects of SEM, with the goal of preparing the student to use SEM in original research and to critically evaluate its use in scholarly work. Further, it introduces the student to partial least squares modeling and to Bayesian approaches in structural equations modeling.