This study proposed a utility-driven two-stage stochastic mixed-integer linear programming model to understand how the patient preferences impact the additive manufacturing (AM) supply chain design decisions. The goal of the mathematical model is to maximize the utilities derived from the customer preferences by appropriately allocating the AM facilities in the targeted region under customer decision and demand uncertainty. The mathematical model is visualized and validated by developing a real-life case study that utilizes the biomedical implants data for the state of Mississippi. A number of sensitivity analyses are conducted to understand how the patients' behavioral decisions (e.g., price-centric versus time- or quality-centric customers) to purchase biomedical implants impact the AM supply chain design decisions. The results revealed key managerial insights that could be utilized by healthcare service providers and interested stakeholders to provide quality healthcare services by managing patient-centric AM facility siting decisions.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-6222 |
| Date | 06 August 2021 |
| Creators | Ranta, Julekha Hussain |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
Page generated in 0.1287 seconds