Mohamad Soltani

About

Mohamad Soltani is an Assistant Professor of Operations Management in the Department of Accounting and Business Analytics at the Alberta School of Business. He also holds an Honorary Fellow appointment with the Department of Emergency Medicine at the University of Wisconsin-Madison School of Medicine and Public Health.

His research interests lie in the empirical analysis of service operations, with a primary focus on healthcare operations. In particular, he employs data-driven approaches to uncover latent interactions between healthcare policymakers, service providers, and patients to provide a systematic perspective on healthcare delivery that ultimately impacts service efficiency and care quality. Mohamad's research has been published in prestigious academic journals such as Manufacturing & Service Operations Management (M&SOM). The Production and Operations Management Society (POMS) College of Healthcare Operations Management awarded him its Best Paper Award in 2020, and his research was a runner-up at the POMS College of Behavioral Operations Management Junior Scholar Paper Competition in 2022. Mohamad's research has also been featured in various media outlets, including CBC, Global News, CTV, and the Edmonton Journal.

Mohamad earned his PhD in Operations Management from the Wisconsin School of Business at the University of Wisconsin-Madison. He also holds Master of Science and Bachelor of Science degrees in Industrial Engineering from Amirkabir University of Technology (Tehran Polytechnic) and Isfahan University of Technology, both in Iran.

At the Alberta School of Business, he teaches Predictive Business Analytics and Operations Management to both graduate and undergraduate students.

Research

• Healthcare operations management
• Service operations management
• Empirical studies in operations management
• Data analytics

OM 502 - Operations Management

This course focuses on (1) the competitive advantage that a business unit can derive from innovative and efficient production and delivery of its goods and services and on (2) analytical approaches that are useful in understanding and improving an organization's operations. Specific modules include process diagramming and analysis; measuring and managing flow times; inventory control and optimization; supply chain coordination and operations strategy. Cases will be used to illustrate operational efficiency and its significance to the profitability of a firm. Prerequisite: MGTSC 501. Not to be taken by students with credit in MGTSC 502.

OM 620 - Predictive Business Analytics

Application of predictive statistical models in areas such as insurance risk management, credit risk evaluation, targeted advertising, appointment scheduling, hotel and airline overbooking, and fraud detection. Students will learn how to extract data from relational databases, prepare the data for analysis, and build basic predictive models using data mining software. Emphasizes the practical use of analytical tools to improve decisions rather than algorithm details. Prerequisite: MGTSC 501.

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