Decision Sciences and MIS

Research

The Decision Sciences Department has three major research disciplines: statistics, operations research and operations management. Statistics research topics include datamining, quality control, correlation/covariance and skewness models; in Operations Research, nonlinear optimization, which encompasses a range of mathematical methods to model and optimize the performance of complex systems in business, engineering, and medicine; and in Operations Management, the modeling and analysis of strategic and operational decisions in supply chain management and healthcare systems.

Recent Works

Van Bergen, Matthijs, Steeman, Michiel, Reindorp, Matthew, and Gelsomino, Luca, Supply Chain Finance Schemes in the Procurement of Agricultural Products. Journal of Purchasing and Supply Management (Forthcoming)

Dimitrov, Stanko, and Ceryan, Oben, Optimal Inventory Decisions when Offering Layaway. International Journal of Production Research (Forthcoming)

Li, Xiaolin, Wu, Chaojiang, and Mai, Feng, The Effect of Online Reviews on Product Sales: A Joint Sentiment-Topic Analysis. Information and Management (Forthcoming)

Du, Bowen, Zhou, Wenjun, Liu, Chuanren, Cui, Yifeng, and Xiong, Hui, Transit Pattern Detection Using Tensor Factorization. Informs Journal on Computing (Forthcoming)

McCullough, B D., Using Student Evaluations of Teaching to Support Faculty: Use Proportions Instead of Means to Analyze SETs. Journal of Higher Education Theory and Practice (Forthcoming)

Reindorp, Matthew, Tanrisever, F., and Lange, A., Purchase Order Financing: Credit, Commitment, and Supply Chain Consequences. Operations Research (Forthcoming)

McWilliams, Thomas P., Davis, Darwin, Saniga, Erwin, Lucas, James, and Faraz, Alireza, Characteristics of Economically Designed CUSUM and X-Bar Charts. Frontiers in Statistical Quality Control (Forthcoming)

Warkentin, Merrill, Sharma, Shwadhin, Gefen, David, Rose, Greg, and P.A, Pavlou, Social identity and trust in internet-based voting adoption. Government Information Quarterly 35 (Spring 2018): 195-209.

Gupta, Sachin, and Schneider, Matthew, Protecting Customers’ Privacy Requires More than Anonymizing Their Data. Harvard Business Review (Digital Article) (Jun 2018):

Gefen, David, Miller, Jacob, Armstrong, Johnathon, Cornelius, Fran, Robertson, Noreen, Smith-McLallen, Aaron, and Taylor, Jennifer, Identifying Patterns in Medical Records with Latent Semantic Analysis. Communication of the ACM 61 (Jun 2018): 72-77.

Prekopa, Andras, and Lee, Jinwook, Risk Tomography. European Journal of Operational Research 265 (Feb 2018): 149-168.

Schneider, Matthew, Jagpal, Sharan, Gupta, Sachin, Li, Shaobo, and Yu, Yan, A Flexible Method for Protecting Marketing Data: An Application to Point-of-Sale Data. Marketing Science (Year 2018):

Zhou, X., Xu, Z., Tu, Y., Lev, Benjamin, and Pedrycz, W., A Novel Data Envelopment Analysis Model for Evaluating Industrial Production and Environmental Management System. Journal of Cleaner Production 170 (Jan 2018): 773-788.

Yan, Erjia, Wu, Chaojiang, and Song, Min, The Funding Factor: A Cross-disciplinary Examination of the Association Between Research Funding and Citation Impact. Scientometrics 115 (Year 2018): 369-384.

McCullough, B D., Sun, H.-J., and Fukuda, Kaoru, Inaccurate Regression Coefficients in Microsoft Excel 2003: An Investigation of Volpi’s Zero Bug. Computational Statistics 32 (Dec 2017): 1411-1421.