Seokjun Youn

Interests

Research

[Domains] Healthcare Operations and Payment Models; Clinical Practice Variation; Capacity Planning and Scheduling in Healthcare; Logistics Optimization for Food Safety; Economics of Information Systems. [Methodologies] Applied Econometrics; Discrete Optimization; Stochastic/Robust Programming; Heuristics; Statistical Inference; Analytical Modeling.

Teaching

Business Analytics; Big Data Analytics; Operations Management; Supply Chain Management; Healthcare Operations; Decision Support Modeling; Business Statistics.

Courses

Scholarly Contributions

Journals/Publications

• Lee, B., Youn, S., & Fredendall, L. (2025). Deadline Effect in Stroke Patient Care: A Temporal Motivation Theory Perspective of Process Management. Journal of Operations Management, 71(Issue), 670-699. doi:10.1002/joom.1360
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  Stroke is a highly time-sensitive medical emergency, and earlier treatment is crucial. Drawing on Temporal Motivation Theory, we investigate a “deadline effect” in stroke care and analyze how two deadlines, that is, a medically oriented one (administering Tissue Plasminogen Activator, TPA, within 4.5 h of symptom onset) and a goal-oriented one (the 60-min in-hospital target from Target:Stroke), shape care consistency. We define a deadline effect as a variable task processing rate under time pressure from a pending task completion deadline, which can cause inconsistent care. Clinicians may work more slowly when patients arrive soon after symptom onset, given ample time remains before the 4.5-h TPA window. Using an accelerated-failure-time model and addressing patient selection bias, we find that shorter onset-to-door times correlate with longer door-to-needle times, and vice versa, confirming the medically oriented deadline effect. As a result, care time may vary considerably based on how much of the TPA window remains. Under Target:Stroke, a goal-driven national initiative in the United States to improve stroke care quality, stroke teams face an additional 60-min in-hospital deadline. Our findings show that the initiative prompts stroke teams to prioritize the tighter goal and maintain a more consistent care pace, regardless of patients' arrival times. Our mechanism analyses reveal two boundary conditions for the main findings: (i) when the downstream time segment ends with a mid-point patient care milestone rather than the strict TPA administration deadline or (ii) when the system congestion level is high, the main findings do not hold, advancing the deadline effect literature from an operational standpoint. Furthermore, our major findings are robust to other confounding factors and model assumptions, ruling out alternative explanations. Notably, post hoc analyses confirm that Target:Stroke fosters consistent time performance without adversely affecting other health outcomes, advocating its efficacy. In sum, we highlight the operational implications of multiple deadlines in stroke care, extending the broader deadline effect literature. For hospital clinicians, properly set goals can stabilize care processes and strengthen overall performance, emphasizing the strategic value of well-designed deadlines in time-critical healthcare settings.
• Hutson, L., Barton, I., Hill, L., Stavast, W., & Youn, S. (2024). Automated Population and Validation of Geologic Logging Fields: An Approach to Autopopulate Select Logging Parameters and Rapidly Identify Mis-Logged Interval Candidates. Mining, Metallurgy and Exploration, 41(Issue 6). doi:10.1007/s42461-024-01130-y
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  Geological characterization of drillholes is a crucial source of exploration data, but is a time-consuming, laborious, and manual process. This paper tests two ways that automation can help speed up drill core logging and assessing core log accuracy: (1) autopopulation of interpretive parameters from entered descriptions and (2) autovalidation, or automatic identification and flagging of potentially mis-logged intervals. These two approaches were tested using geologic logging data from 15 + years of drilling at the Morenci copper porphyry deposit. Autopopulation of an interpretive field (rock type) from the values entered in a descriptive field, including, e.g., grain size, color, texture, and mineralogy, with a Complementary Naïve Bayes classifier resulted in 89% accuracy. The autovalidation test applied two methods. The first used text mining to extract the rock type description from within a comment field and cross-referenced it to the manually logged rock code parameter, testing the rock code for inconsistency with the rock type description. The second used the Apriori algorithm to develop association rules ranking the commonness of mineral combinations in the same logging interval. The rarest mineral combinations may be erroneous and were automatically flagged for further review. Both autovalidation methods combined resulted in approximately 4300 logged intervals identified as potentially inaccurate. Eliminating typographical errors and similar minor problems narrowed this down to ~ 1000 potentially mis-logged intervals. Review by geologists confirmed that 350 of them were incorrectly logged. This study demonstrates the viability of using automation as a complement to the conventional manual core logging process, even in the absence of sophisticated automated logging systems. While the benefits of such approaches are incremental, they may still yield significant time savings for the operation given the volume of core and time and labor intensity of logging it.
• Geismar, H. N., Huang, Y., Pillai, S. D., Sriskandarajah, C., & Youn, S. (2020). Location-Routing with Conflicting Objectives: Coordinating eBeam Phytosanitary Treatment and Distribution of Mexican Import Commodities. Production and Operations Management, 29(6), 1506-1531. doi:10.1111/poms.13170
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  Authors’ names are listed in alphabetical order.Journal Submission History: Submitted to Manufacturing & Service Operations Management 6/18/2018; Reject & Resubmit 9/11/2018; Resubmitted 1/10/2019; Reject 5/22/2019; Submitted to Production and Operations Management 6/3/2019; Major R&R 7/25/2019; Resubmitted 10/11/2019; Major R&R 11/21/2019; Resubmitted 12/26/2019; Accepted 2/4/2020.
• Youn, S., Heim, G. R., Kumar, S., & Sriskandarajah, C. (2021). Examining Impacts of Clinical Practice Variation on Operational Performance. Production and Operations Management, 30(4), 839-863. doi:10.1111/poms.13256
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  Journal Submission History: Submitted to Production and Operations Management invited special issue on healthcare 3/1/2016; Reject & Resubmit 6/21/2016; Resubmitted 10/17/2017; Major R&R 1/31/2018; Resubmitted 8/31/2018; Major R&R 2/11/2019; Resubmitted 11/6/2019; Minor R&R 3/20/2020; Resubmitted 7/8/2020; Accepted 8/4/2020.

Proceedings Publications

• Youn, S., & Heim, G. R. (2021, August). Unwarranted Variation in Healthcare: Impacts of Test-Order Practice Variation on Care-Delivery Cost. In Academy of Management (AoM) Annual Meeting.
• Youn, S., Agrawal, A., Kumar, S., & Sriskandarajah, C. (2020, August). Provider Selection Framework for Bundled Payments in Healthcare Services. In Americas Conference on Information Systems (AMCIS).

Presentations

• Lee, B., Youn, S., & Fredendall, L. (2022, Summer). Deadline E€ect in Stroke Patient Care: Paradox of Arriving Too Early. Conference on Health IT and Analytics (CHITA) 2022.
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  Conference on Health IT and Analytics (CHITA) 2022
• Youn, S., & Heim, G. R. (2021, July). Does Underuse Variation in Test-Ordering Practice Relate to Higher Care-Delivery Cost?. INFORMS Healthcare Conference. Virtual.
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  INFORMS Healthcare Conference 2021
• Kim, Y. I., Youn, S., Jung, K. S., & Kwark, Y. (2021, May). Information Sharing Enforcement: Does It Come to Fruition in the Marketplace?. POMS Annual Meeting. Virtual.
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  POMS Annual Meeting 2021
• Kim, Y. I., Youn, S., Jung, K. S., & Kwark, Y. (2021, November). Information Sharing Enforcement: Does It Come to Fruition in the Marketplace. INFORMS Annual Meeting. Anaheim, CA (Hybrid).
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  INFORMS Annual Meeting 2021
• Lee, B., Youn, S., & Fredendall, L. (2021, November). Deadline E€ect in Stroke Patient Care: Paradox of Arriving Too Early. INFORMS Annual Meeting. Anaheim, CA (Hybrid).
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  INFORMS Annual Meeting 2021
• Youn, S. (2021, November). Overview of Health Insurance and Payment Reform Initiatives in the U.S.. Korean Global Health Forum (KGHF), London, United Kingdom. Virtual.
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  Korean Global Health Forum (KGHF), London, United Kingdom (Virtually Delivered); Talk Titles: 1. Overview of Health Insurance and Payment Reform Initiatives in the U.S., 2. Does Underuse Variation in Test-Ordering Practice Relate to Higher Care-Delivery Cost?
• Youn, S., & Heim, G. R. (2021, June). Does Underuse Variation in Test-Ordering Practice Relate to Higher Care-Delivery Cost?. MIS Quarterly Virtual Author Development Workshop. Virtual.
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  MIS Quarterly Virtual Author Development Workshop 2021
• Youn, S., & Heim, G. R. (2021, June). Does Underuse Variation in Test-Ordering Practice Relate to Higher Care-Delivery Cost?. Manufacturing & Service Operations Management (MSOM) Conference. Virtual.
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  Manufacturing & Service Operations Management (MSOM) Conference 2021
• Youn, S., & Heim, G. R. (2021, November). Does Underuse Variation in Test-Ordering Practice Relate to Higher Care- Delivery Cost?. Decision Sciences Institute (DSI) Annual Meeting. Virtual.
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  Decision Sciences Institute (DSI) Annual Meeting 2021
• Youn, S., & Heim, G. R. (2021, October). Does Underuse Variation in Test-Ordering Practice Relate to Higher Care- Delivery Cost?. INFORMS Annual Meeting. Anaheim, CA.
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  INFORMS Annual Meeting 2021
• Youn, S., Geismar, H. N., Sriskandarajah,, C., & Vikram, T. (2021, March). Adaptive Capacity Planning for Ambulatory Surgery Centers. Doctoral Seminar at Texas A&M University. Virtual.
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  Doctoral Seminar at Texas A&M University
• Kim, Y. I., Youn, S., Jung, K. S., & Kwark, Y. (2020, December). Information Sharing Enforcement: Does It Come to Fruition in the Marketplace?. Korean Association for Information Systems (KrAIS) Research Workshop.
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  Korean Association for Information Systems (KrAIS) Research Workshop 2020, Presented by a Co-author.
• Kim, Y. I., Youn, S., Jung, K. S., & Kwark, Y. (2020, November). Thanks, But No Thanks: Does Information Sharing Enforcement Come to Fruition to the Marketplace?. INFORMS Conference on Information Systems and Technology (CIST).
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  INFORMS Conference on Information Systems and Technology (CIST) 2020, Presented by a Co-author.
• Kim, Y., Youn, S., Jung, K. S., & Kwark, Y. (2020, April). Feed Your Hungry Seller: Information Sharing in Online Marketplaces. POMS 2020 Annual Meeting (cancelled due to COVID-19). Minneapolis, MN.
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  POMS 2020 Annual Meeting (cancelled due to COVID-19)
• Kim, Y., Youn, S., Jung, K. S., & Kwark, Y. (2020, June). Feed Your Hungry Seller: Information Sharing in Online Marketplaces. IFORS 2020 Conference (cancelled due to COVID-19). Seoul, South Korea.
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  IFORS 2020 Conference (cancelled due to COVID-19)
• Lee, B., Youn, S., & Fredendall, L. (2020, April). Deadline Effect in Stroke Patient Care: Paradox of Arriving Too Early. POMS 2020 Annual Meeting (cancelled due to COVID-19). Minneapolis, MN.
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  POMS 2020 Annual Meeting (cancelled due to COVID-19)
• Youn, S., & Heim, G. R. (2020, November). Does Underuse Variation in Test-Ordering Practice Relate to Higher Care-Delivery Cost?. Decision Sciences Institute (DSI) 2020 Annual Meeting. Virtual.
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  Decision Sciences Institute (DSI) 2020 Annual Meeting
• Youn, S., & Heim, G. R. (2020, November). Does Underuse Variation in Test-Ordering Practice Relate to Higher Care-Delivery Cost?. INFORMS 2020 Annual Meeting. Virtual.
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  INFORMS 2020 Annual Meeting
• Youn, S., & Heim, G. R. (2020, October). Does Underuse Variation in Test-Ordering Practice Relate to Higher Care-Delivery Cost?. Conference on Health IT and Analytics (CHITA).
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  Conference on Health IT and Analytics (CHITA) 2020
• Youn, S., Geismar, H. N., Sriskandarajah, C., & Vikram, T. (2020, November). Adaptive Capacity Planning for Ambulatory Surgery Centers: A Bottom-up Strategy based on Patient Flow. INFORMS Workshop on Data Mining and Decision Analytics. Virtual.
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  INFORMS Workshop on Data Mining and Decision Analytics (DMDA) 2020
• Youn, S., Geismar, N., Sriskandarajah, C., & Vikram, T. (2020, October). Adaptive Capacity Planning for Ambulatory Surgery Centers. Conference on Health IT and Analytics (CHITA).
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  Conference on Health IT and Analytics (CHITA) 2020
• Youn, S., Heim, G. R., Kumar, S., & Sriskandarajah, C. (2020, June). Examining Impacts of Clinical Practice Variation on Operational Performance. The 9th Annual Koç University Healthcare Operations Workshop (cancelled due to COVID-19). İstanbul, Turkey.
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  The 9th Annual Koç University Healthcare Operations Workshop (cancelled due to COVID-19)
• Youn, S., Heim, G. R., Kumar, S., & Sriskandarajah, C. (2020, November). Practice Variation in Healthcare: Impacts on Operational Performance and Intervening Effects of Quality Evaluations. INFORMS Workshop on Data Mining and Decision Analytics. Virtual.
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  INFORMS Workshop on Data Mining and Decision Analytics (DMDA) 2020
• Youn, S., Geismar, H. N., Sriskandarajah, C., & Vikram, T. (2019, December). Adaptive Capacity Planning for Ambulatory Surgery Centers. Modeling and Computation Seminar, Program in Applied Mathematics, University of Arizona. Department of Mathematics, University of Arizona.
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  Modeling and Computation Seminar, Program in Applied Mathematics, University of Arizona
• Youn, S., Geismar, H. N., Sriskandarajah, C., & Vikram, T. (2019, December). Adaptive Capacity Planning for Ambulatory Surgery Centers. Workshop on Information Technologies and Systems (WITS) 2019. Munich, Germany.
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  Workshop on Information Technologies and Systems (WITS) 2019
• Youn, S., Geismar, H. N., Sriskandarajah, C., & Vikram, T. (2019, October). Adaptive Capacity Planning for Ambulatory Surgery Centers. INFORMS Annual Meeting 2019. Seattle, WA.
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  INFORMS Annual Meeting 2019
• Youn, S., Heim, G. R., Kumar, S., & Sriskandarajah, C. (2019, October). Examining Impacts of Clinical Practice Variation on Operational Performance. INFORMS Annual Meeting 2019. Seattle, WA.
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  INFORMS Annual Meeting 2019
• Youn, S., Heim, G. R., Kumar, S., & Sriskandarajah, C. (2017, November). Examining Impacts of Clinical Practice Variation on Operational Performance. Conference on Health IT and Analytics (CHITA). Washington, D.C..
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  Conference on Health IT and Analytics (CHITA) 2017