Assistant Professor | Supply Chain Management | Rutgers Business School
Assistant Professor | Supply Chain Management | Rutgers Business SchoolAssistant Professor | Supply Chain Management | Rutgers Business SchoolAssistant Professor | Supply Chain Management | Rutgers Business SchoolAssistant Professor | Supply Chain Management | Rutgers Business School
Research THEMES
Analytics for Societal Good
Analytics for Societal Good
Analytics for Societal Good
Projects in this theme leverage operations research and managerial strategies to address challenges that have a significant societal impact.
A. Park, M. Rodgers, S. Cho, Toward Sustainable Freight Services: Ensuring Equitable Job Distribution for Independent Truckers, American Business Review, 27(1), 1-15, May 2024.
D. Singham, M. Rodgers, A Battery Depletion Risk Measure for Centralized Systems With Storage Capabilities, Operations Research Letters, 50(6): 660-666, November 2022, https://doi.org/10.1016/j.orl.2022.10.005.
S. Selcuklu, M. Rodgers, A. Movlyanov, Economically and Environmentally Sustainable Power System Expansion: A Case Study for Turkey, Computers & Industrial Engineering , 164: 107892, February 2022, https://doi.org/10.1016/j.cie.2021.107892.
X. Xu, M. Rodgers, W. Guo. A Hub-and-spoke Design for Ultra-cold COVID-19 Vaccine Distribution, Vaccine 39(41): 6127-6136, October 2021, https://doi.org/10.1016/j.vaccine.2021.08.069.
M. Rodgers, Pathways to Eliminate Carbon Emissions via Renewable Energy Investments at Higher Education Institutions, The Electricity Journal, 34(5): 106952, June 2021, http://dx.doi.org/10.1016/j.tej.2021.106952.
S. Tsianikas, N. Yousefi, J. Zhou, M. Rodgers, D. Coit, A Sequential Resource Investment Planning Framework using Reinforcement Learning and Simulation-Based Optimization, Applied Energy, 290: 116778, May 2021, https://doi.org/10.1016/j.apenergy.2021.116778.
M. Rodgers, D. Coit, F. Felder, A.G. Carlton, A Metamodeling Framework for Quantifying Health Damages of Power Grid Expansion Plans, International Journal of Environmental Research and Public Health, 16(10): 1-21, 2019, https://doi.org/10.3390/ijerph16101857.
M. Rodgers, D. Coit, F. Felder, A.G. Carlton. Assessing the Effects of Power Grid Expansion on Human Health Externalities, Socio-Economic Planning Sciences, 66: 92-104, 2019, https://doi.org/10.1016/j.seps.2018.07.011.
M. Rodgers, D. Coit, F. Felder, A.G. Carlton. Generation Expansion Planning Considering Health and Societal Damages – A Simulation-Based Optimization Approach, Energy, 164: 951-963, 2018, https://doi.org/10.1016/j.energy.2018.09.004.
C.M. Farkas, M.D. Moeller, F. Felder, K.R. Baker, M. Rodgers, A.G. Carlton, Temporalization of Peak Electric Generation PM Emissions during High Energy Demand Days, Environmental Science & Technology, 49(7): 4696-4704, 2015, https://doi.org/10.1021/es5050248.
Supply Chain Analytics
Analytics for Societal Good
Analytics for Societal Good
These projects deploy analytical solutions to enable researchers and practitioners to make strategic decisions under uncertainty.
M. Rodgers, S. Mukherjee, B. Melamed, A. Baveja, A. Kapoor. Solving Business Problems: The Business-Driven Data-Supported Process, Ann Oper Res, 2024, https://doi.org/10.1007/s10479-023-05770-z.
K. G, Mun, W. Cai, M. Rodgers, S. Choi, A data-driven resilient supply chain design for energy security and economic prosperity, International Journal of Production Research, 2023, https://doi.org/10.1080/00207543.2023.2254414.
X. Xu, M. Rodgers, W. Guo. Hybrid Simulation Models for Spare Parts Supply Chain Considering 3D Printing Capabilities, Journal of Manufacturing Systems, 59: 272-282, April 2021, https://doi.org/10.1016/j.jmsy.2021.02.018.
X. Xu, W. Guo, M. Rodgers. A Real-time Decision Support Framework to Mitigate Quality Degradation in Perishable Supply Chains, Computers & Industrial Engineering, 150: 106905, 2020, https://doi.org/10.1016/j.cie.2020.106905.
M. Rodgers, D. Singham, A Framework for Assessing Disruptions in a Clinical Supply Chain Using Bayesian Belief Networks, Journal of Pharmaceutical Innovation, 2019, https://doi.org/10.1007/s12247-019-09396-2.
M. Rodgers, R. Oppenheim, Ishikawa Diagrams and Bayesian Belief Networks for Continuous Improvement Applications, The TQM Journal, 31(3): 294-318, 2019, https://doi.org/10.1108/TQM-11-2018-0184.