Encourages creative and innovative thinking.
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Kate Li is an Associate Professor in the Information Systems and Operations Management department at Suffolk University's Sawyer Business School. She joined Suffolk University in September 2009 as an Assistant Professor and was promoted to Associate Professor in July 2016. Holding a PhD, her research specializations include supply chain management with a focus on sustainability, data analytics, healthcare management, and technology innovation. Professor Li serves as a Fellow of the Center for Innovation and Change Leadership and has directed the M.S. in Business Analytics program. She has led hands-on workshops, such as an introduction to Power BI functionalities for business applications.
Professor Li's scholarship has earned her the Dean’s Award for Excellence in Research in 2021, recognizing her consistently strong performance. She has received three research grants from Suffolk University, along with awards from the Wharton Customer Analytics Institute and the Decision Sciences Institute. Key publications demonstrate her impact: 'The potential for cannibalization of new products sales by remanufactured products' (Decision Sciences, 2010), cited over 420 times and named one of the Top 20 Most Downloaded Papers in the journal's 50-year history; 'Early Financial Impact of the COVID-19 Pandemic on U.S. Hospitals' (2023); 'Is there an association between hospital staffing levels and inpatient-COVID-19 mortality rates?' (2022); 'Were hospitals with sustained high performance more successful at reducing mortality during the pandemic’s second wave?' (2022); 'Hospitalists staffing levels and hospital performance' (2020); 'Building Mini-Categories in Product Networks' (2015); and 'Bayesian Inference for Assessing Effects of Email Marketing Campaigns' (2016). Her work has amassed over 700 citations, influencing operations management, healthcare analytics, and supply chain strategies. Through these contributions, Professor Li advances understanding of hospital performance, staffing effects, electronic medical records adoption, value-based purchasing, and product network analysis.
