Yi-Jen (Ian) Ho

Color portrait of Yi-Jen (Ian) Ho

Assustant Professor of Information Systems

Department Supply Chain & Information Systems
Office Address 465 Business Building
Phone Number 814-865-0678
Email Address ian.ho@psu.edu

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Yi-Jen (Ian) Ho is an assistant professor of Supply Chain and Information Systems at the Smeal College of Business, Pennsylvania State University. He received his Ph.D. in Information Systems at Merage School of Business at the University of California, Irvine. He is mainly interested in understanding the impacts of information technologies on consumer choice. His current research focuses on the areas of social media, location-based services, and mobile technologies in digital markets. To obtain the insights and identify casualty, he applies various methods ranging from game theory-based modeling, econometrics, randomized experimentations, and machine learning applications.

Expertise

Social media, location-based services, mobile analytics, digital marketing

Education

Ph D, Information Systems, University of California, Irvine, 2016

MS, Management Information Systems, University of Arizona, 2008

BS, Management Information Systems, National Central University, 2003

Courses Taught

BA 841 – Bus Intelligence (3)
Business intelligence encompasses the IT tools for exploring, analyzing, integrating, and reporting business data for fact-based, intelligent decision making. This course primarily investigates methods and tools for exploring and analyzing large amounts of business data, also called "Big Data". Learning methods emphasize active learning in the application of methods and tools to real data and the presentation of the results. Students will be exposed to a variety of methods for analyzing both structured and unstructured data and they will work with business data sets to understand the value that can be extracted from large data sets. They will also learn how to classify and associate data to discover business rules that can be used to support decision making. The course will also cover methods to analyze social media information and tools that can facilitate such analysis and discovery. Students will work with data from real social networks to gain an appreciation of how value can be obtained from such networks. Finally, they will learn about techniques for visualizing, presenting, and communicating information in a useful way, e.g. through dashboards and with other technologies on various platforms. Upon successful completion of this course, students will have: ¿ acquired the tools and techniques of data cleaning and preparation, data mining, and data visualization ¿ become competent in analyzing both structured and unstructured data ¿ developed an understanding of, and an appreciation for, the complexities of mining unstructured data such as text data including documents, web pages, emails, etc. ¿ developed an understanding of social networks as well as mobile and location-based analytics

MIS 441 – Bus Intelligence (3)
Application of Information Technology based methods and tools to analyze business data and support decision making. MIS 441 Business Intelligence for Decision Making (3) Business intelligence encompasses the IT tools for exploring, analyzing, integrating, and reporting business data for fact-based, intelligent decision making. This course primarily investigates methods and tools for exploring and analyzing large amounts of business data also called "Big Data." Learning methods emphasize active learning in the application of methods and tools to real data and the presentation of the results. Students will be exposed to a variety of methods for analyzing both structured and unstructured data and they will work with business data sets to understand the value that can be extracted from large data sets. They will also learn how to classify and associate data to discover business rules that can be used to support decision making. The course will also cover methods to analyze social media information and about tools that can facilitate such analysis and discovery. Again they will get a chance to work with data from real social networks to gain an appreciation of how value can be obtained from such networks. Finally, they will learn about techniques for visualizing, presenting and communicating information in a useful way, e.g. through dashboards and with other technologies on various platforms.

Selected Publications

Ho Y., Ho Y., Tan Y., "Online Cash-back Shopping: Implications for Consumers and e-Businesses." Information Systems Research, vol. 28, no. 2, 2017, pp. 250–264, pubsonline.informs.org/doi/abs/10.1287/isre.2017.0693
Dewan S., Ho Y., Ramasprasad J., "Popularity or Proximity: Characterizing the Nature of Social Influence in an Online Music Community." Information Systems Research, vol. 28, no. 1, 2017, pp. 117-136, pubsonline.informs.org/doi/abs/10.1287/isre.2016.0654
Chen H., Li X., Chou M., Ho Y., Tseng C., "Using Open Web APIs in Teaching Web Mining." IEEE Transactions on Education, vol. 52, no. 4, 2009, pp. 482-490, ieeexplore.ieee.org/document/5152946