Characterizing the Resilience of Public Service Systems during Disasters

Duygu Pamukçu

This study investigates the resilience of public service systems during disasters by proposing a novel theoretical framework that explicitly links resilience capacities (absorptivity, adaptivity, and susceptivity) to actual resilience behaviors during a crisis event. We develop an empirical model, using Service Level Agreement (SLA) compliance rate data from the Miami-Dade County 311 system during Hurricane Irma, and introduce a simple approach for characterizing different service types according to their pre-disaster resilience capacities. Using this classification, we then analyze the post-disaster performance of service types to assess how the inherent capacities influence resilience outcomes. Our findings show that inherently absorptive systems tend to maintain performance levels during crises, and adaptive systems tend to improve performance, whereas susceptive systems more often exhibit performance degradation. This distinction provides a practical tool for decision-makers to anticipate system responses, guide resource allocation, and enhance disaster preparedness. The study contributes to the operations management literature by bridging the gap between resilience capacity and observed behavior, offering a dynamic and operational perspective on resilience measurement.

Short Bio

Duygu Pamukçu is an Assistant Professor at Providence College School of Business in Providence, United States. Prior to this position, she was a postdoctoral research fellow in the Department of Logistics and Operations Management at HEC Montréal in Canada. Dr. Pamukçu holds a Ph.D. in Business Information Technology from Virginia Tech and a master's and bachelor's degrees from the Industrial Engineering Department of Middle East Technical University. Her research interests focus on advancing the operations of organizations in humanitarian and crisis settings using exact and heuristic approaches, along with data-driven methods such as econometric analysis and statistics.

Venue

Friday, November 21st, 2025, 4:00 pm

Online

The link for the seminar is: https://teams.microsoft.com/l/meetup-join/19%3ameeting_NzNlZWE0ZWItYWY2Z...

Meeting ID: 366 860 059 269 87

Passcode: sR2XG9Q9