Dr. Jennifer Pazour’s research and teaching interests focus on the development and use of mathematical models to guide decision making for supply chain and logistics challenges. Her research has made contributions to military logistics, distribution and transportation systems, healthcare logistics, on-demand supply chains, and peer-to-peer resource sharing systems. To close the gap between current distribution operations and customer expectations, a recent focus of her team is rethinking supply chain design to meet the demands of modern distribution. For more information, please see Dr. Pazour's publications and website: https://jenpazour.wordpress.com/
Jen fundamentally considers herself a modeler, whose core intellectual strength is in the development of mathematical representations of complex systems and processes to better understand the implications of their design and operation. Thus, her research approach is (1) to develop models encompassing the primary trade-offs in the system, (2) to understand structural properties and to discover solution approaches to solve the models, and then (3) to conduct experiments that use the developed models and approaches to provide policy recommendations and managerial insights.
Military Logistics: Sea-basing is a strategy implemented by the United States Military that allows the Joint Forces to be supported from the sea. From a logistics perspective, sea-basing will transform a set of vessels into floating distribution centers that are responsible for fulfilling supply orders from troops on shore. Sea-based logistics operate in a challenging and uncertain environment and have unique mission characteristics; consequently, sea-based logistics require the development of specific logistics models. Through a Young Investigator Award from the Office of Naval Research, Dr. Pazour's team of graduate and undergraduate researchers conducted research on the design of responsive sea-based logistics delivery systems with imperfect visibility. In doing so, they developed descriptive models to characterize and to understand how and why cargo holds evolve from a highly organized state to a disorganized state. Given imperfect information about the location, quantity, and expected delivery requests, the research team developed prescriptive models to determine which items, and in what quantity, should be pre-staged on the flight deck. They then use their developed models, solution algorithms, and structural results to quantify and evaluate logistics system design, to analyze the trade-offs associated with operating in a complex and uncertain environment, and to inform direction for future technology and process innovations.
Peer-to-Peer Resource Sharing Systems: A novel way to increase resource efficiency is through the use of existing, idle capacity. A Peer-to-Peer Resource Sharing System is one where a resource owned by an individual is collectively shared with a group of users. The shared resource can be a physical resource (like a power drill) or a human resource (like the ability to perform a task). Peer-to-Peer Resource Sharing Systems are one aspect of the sharing economy and collaborative consumption. A long-term research goal is to improve understanding of Peer-to-Peer Resource Sharing Systems through the development and use of novel mathematical models. Intial funding of this work is through a National Science Foundation EAGER grant. A Faculty Early Career Development (CAREER) grant from NSF supports her research focusing on novel methods to coordinate decentralized distribution resources on-demand through customized recommendations made to multiple suppliers simultaneously and to quantify the impact of supplier choice on platform efficiency, effectiveness, and equity.
Distribution and Transportation Systems: Dr. Pazour's research in distribution systems includes analyzing automated storage and retrievals systems with multiple pick points in the aisle, batch processes in stock-to-picker order-fulfillment systems, reshuffling policies for warehouses, and pallet management strategies. This research has been funded by a Material Handling Institute Start-Up Grant. Research on transportation has focused on the design of a high-speed rail network for freight distribution in the United States, the development of an improved routing and scheduling methodology that has been successfully implemented at J.B. Hunt Transport, and development of models to analyze and recommend policies in
rental vehicle networks (awarded an honorable mention for best applications paper in the 2016 IIE Transactions Focused Issue on Design and Manufacturing).
Healthcare Logistics: Dr. Pazour's dissertation research focused on analytical modeling and understanding the impact of piece-level, order-ful llment technology in the pharmaceutical supply chain and was supported through a Doctoral Dissertation Enhancement Project from the National Science Foundation. Her research was strongly guided by involvement with the University of Arkansas's Center for Innovation in Healthcare Logistics, which provided access to numerous healthcare facilities, data, and experts.
Her research has been funded through a National Science Foundation Early Career Development (CAREER) grant (2018), a Johnson & Johnson WiSTEM2D fellowship (2018), a National Academies of Science Engineering and Medicine Gulf Research Program Early-Career Research Fellowship (2016), a Startup Grant from the Material Handling Institute (2014), a Young Investigator Award from the Office of Naval Research (2013), a Doctoral Dissertation Enhancement Project from the National Science Foundation (2010), and national fellowships from Tau Beta Pi (2006), the Institute of Industrial and Systems Engineers (IISE) (2005, 2007, 2009), and the Material Handling Education Foundation (2007 – 2010). She is the 2017 recipient of the Dr. Hamed K. Eldin Outstanding Early Career IE in Academia Award, and the 2018 recipient of the Logistics and Supply Chain Division Teaching Award, both national awards from IISE. She teaches courses on Supply Chain Design, Operations Research, and Facility Logistics, and is involved in a number of programs to encourage youth to pursue engineering and supply chain professions.
Ph.D. Industrial Engineering, University of Arkansas, 2011
M.S. Industrial Engineering, University of Arkansas, 2008
B.S. Industrial Engineering, Mathematics Minor, South Dakota School of Mines and Technology, 2006