Michael Brusco

Haywood & Betty Taylor Eminent Scholar in Business Administration
Michael Brusco
359 RBB
Academic Specialty
Business Analytics

Ph.D., Florida State University, 1990
MBA, Florida State University, 1986
BBA, Florida Atlantic University, 1985
A.A., Broward Community College, 1982

Areas of Expertise

Linear ordering

Dr. Michael Brusco is the Haywood & Betty Taylor Eminent Scholar in Business Administration and a professor in the Department of Business Analytics, Information Systems and Supply Chain at Florida State University’s College of Business. His academic specialty is operations management, and he teaches courses in the MBA and Master of Science in Business Analytics (MS-BA) programs. From 1988 to 2000 his research focused primarily on mathematical models and methods for workforce staffing and scheduling problems and was published in journals in the fields of operations research and management science (Management Science, Naval Research Logistics, Operations Research). Since 2000 his research has focused mostly on clustering, sequencing, and variable selection problems in business and the social sciences and has been published in journals in the fields of marketing (Journal of Marketing, Journal of Marketing Research, Marketing Science), industrial engineering (IIE Transactions, Optimization Letters), computational statistics (Computational Statistics and Data Analysis, Statistical Analysis and Data Mining, Technometrics), network analysis (Network Science, Social Networks), general science (Science, Nature Reviews Methods Primers, PLoS ONE), and quantitative psychology (Journal of Mathematical Psychology, Multivariate Behavioral Research, Psychological Methods, Psychometrika). Recently, he has also focused on the development of Excel spreadsheets for business analytics and operations management courses and this work has appeared in several pedagogical journals (Decision Sciences Journal of Innovative Education, INFORMS Transactions on Education, Spreadsheets in Education). He serves on the editorial review board of Psychological Methods and as an associate editor for the British Journal of Mathematical and Statistical Psychology.

He earned his bachelor’s degree in marketing from Florida Atlantic University. His MBA and Ph.D. in information and management sciences are both from Florida State University.

Selected Published Research

Brusco, M. J., Steinley, D., & Watts, A. L. (in press). A maximal-clique-based set-covering approach to overlapping community detection. Optimization Letters.

Brusco, M. J., Steinley, D., & Watts, A. L. (in press). Improving the walktrap algorithm using K-means clustering. Multivariate Behavioral Research.

Brusco, M. J., Steinley, D., & Watts, A. L. (in press). On the maximization of the modularity index in network psychometrics. Behavior Research Methods.

Brusco, M. J., Steinley, D., & Watts, A. L. (in press). A comparison of logistic regression methods for Ising model estimation. Behavior Research Methods.

Brusco, M. J., Steinley, D., & Watts, A. L. (in press). A comparison of spectral clustering and the walktrap algorithm for community detection in network psychometrics. Psychological Methods.

Brusco, M. J., Watts, A. L., & Steinley, D. (in press). A modified approach to fitting relative importance networks. Psychological Methods.

Brusco, M. J. (2022). Spreadsheet-based analysis of multisource continuous facility location problems. Decision Sciences Journal of Innovative Education, 20 (2), 102-111.

Brusco, M. J. (2022). Solving classic discrete facility location problems using Excel spreadsheets. INFORMS Transactions on Education, 22 (3), 160-171.

Brusco, M. J. (2022). Logistic regression via Excel spreadsheets: Mechanics, model selection, and relative predictor importance. INFORMS Transactions on Education, 23 (1), 1-11.

Brusco, M. J., & Steinley, D. (2022). A variable neighborhood search heuristic for nonnegative matrix factorization with application to microarray data. Optimization Letters, 16 (1), 153-174.

Brusco, M. J., Steinley, D., & Watts, A. L. (2022). Disentangling relationships in symptom networks using matrix permutation methods. Psychometrika, 87 (1), 133-155.

Neal, Z., Forbes, M., Neal, J., Brusco, M., Krueger, R., Markon, K., Steinley, D., Wasserman, S., & Wright, A. (2022). Critiques of network analysis of multivariate data in psychological science. Nature Reviews Methods Primers, 2, Article 90.

Brusco, M. J., Cradit, J. D., & Steinley, D. (2021). A comparison of 71 binary similarity coefficients: the effect of base rates. PLoS ONE, 16 (4): e0247751.

Brusco, M. J., Davis-Stober, C. P., & Steinley, D. (2021). Ising formulations of some graph-theoretic problems in psychological research: models and methods. Journal of Mathematical Psychology, 102 (June), Article 102536.

Brusco, M., Doreian, P., & Steinley, D. (2021). Deterministic blockmodeling of signed and two-mode networks: a tutorial with psychological examples. British Journal of Mathematical and Statistical Psychology, 74 (1), 34-63.

Huse, C., & Brusco, M. J. (2021). A tale of two linear programming formulations for crashing project networks. INFORMS Transactions on Education, 21 (2), 82-95.

Loeffelman, J., Steinley, D., Boness, C. L., Trull, T. J., Wood, P. K., Brusco, M. J., & Sher, K. J. (2021). Combinatorial optimization of classification decisions: An approach to refine psychiatric diagnoses. Multivariate Behavioral Research, 56 (1), 57-69.

Steinley, D., & Brusco, M. J. (2021). On fixed marginal distributions and psychometric network models. Multivariate Behavioral Research, 56 (2), 329-335.

Stolze, H. J., Brusco, M. J., & Smith, J. S. (2021). Exploring the social mechanisms for variation reduction for direct store delivery (DSD) and vendor managed inventory performance: An integrated network governance and coordination theory perspective. International Journal of Production Economics, 234, Article 108025, pp. 1-10.