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Cost-Effective Acquisition of First-Party Data for Business Analytics

Release time: 2024-06-20      clicks:

Time: July 9, 2024  09:30 a.m.-11:30 a.m.

Venue: Meeting Room 925, Engineering Management & Intelligent Manufacturing Research Center

Speaker: Professor Li Xiaobai, University of Massachusetts

Organizer: School of Management, Hefei University of Technology

Abstract:

Data mining and sharing enable organizations to extract valuable knowledge from data, thereby gaining a competitive edge by better understanding and serving their customers. Customer data acquisition is an important task in data-driven business analytics. Recently, there has been a growing interest in the effective use of an organization’s internal customer data, also known as first-party data. This report will explore the acquisition of new data resources based on first-party data, discussing issues related to acquisition costs and data quality. The proposed models maximize the quality of the acquired data while satisfying budget constraints. By analyzing, deriving and discussing solutions to optimize models, management insights can also be provided from the solutions.

Biography:

Dr. Xiaobai Li is a Professor of Information Systems in the Department of Operations and Information Systems at the University of Massachusetts Lowell, USA. He received his Ph.D. in managementscience from the University of South Carolina. Dr. Li’s research focuses on machine learning, data science, data privacy, and business analytics. He has received funding for his research from National Institutes of Health (NIH) and National Science Foundation (NSF), USA. His work has appeared inManagement Science, Information Systems Research, MIS Quarterly, Operations Research, INFORMS Journal on Computing,Journal of the Association for Information Systems,IEEE Transactions(TKDE, TSMC, TAC),Decision Sciences,Decision Support Systems, Communications of the ACM,andEuropean Journal of Operational Research, among others. He currently serves as an associate editor forInformation Systems Research, Decision Support Systems,and other journals.