Estimating deprivation cost functions for power outages during disasters
A discrete choice modeling approach
Bibliographic Data
| ID | 22028022 |
|---|---|
| Authors | Xiangpeng Li (0009-0006-9700-3575, Texas A&M University, corresponding author), Mona Ahmadiani (0000-0002-1269-5685, Texas A&M University), Richard T Woodward (0000-0001-6185-9255, Texas A&M University), Bo Li (0000-0002-7801-0319, Texas A&M University), Arnold Vedlitz (0000-0002-2070-2697, Texas A&M University), Ali Mostafavi (0000-0002-9076-9408, Texas A&M University) |
| Year | 2025 |
| Volume | 130 |
| Pages | 105854 |
| Publication date | 2025-11-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Disaster Risk Reduction (JOURNAL) |
| Journal identifiers | ISSN: 2212-4209 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.ijdrr.2025.105854 |
| OpenAlex | W4414904168 |
| Language | EN |
| Citations received | 2 |
| References cited | 55 |
Systems for the generation and distribution of electrical power represents critical infrastructure and, when extreme weather events disrupt such systems, this imposes substantial costs on consumers. These costs can be conceptualized as deprivation costs—an increasing function of time without service—quantifiable through individuals' willingness to pay for power restoration. Despite widespread recognition of outage impacts, a gap in the research literature exists regarding the systematic measurement of deprivation costs. This study addresses this deficiency by developing and implementing a methodology to estimate deprivation cost functions for electricity outages, using stated preference survey data collected from Harris County, Texas. This study compares multiple discrete choice model architectures, including multinomial logit and mixed logit specifications, as well as models incorporating Box–Cox and exponential utility transformations for the deprivation time attribute. The analysis examines heterogeneity in deprivation valuation through sociodemographic interactions, particularly across income groups. Results confirm that power outage deprivation cost functions are convex and strictly increasing with time. Additionally, the study reveals both systematic and random taste variation in how individuals value power loss, highlighting the need for flexible modeling approaches. By providing both methodological and empirical foundations for incorporating deprivation costs into infrastructure risk assessments and humanitarian logistics, this research enables policymakers to better quantify service disruption costs and develop more equitable resilience strategies
Discrete choice · Electricity · Empirical research · Extreme value theory · Mixed logit · Multinomial logistic regression · Willingness to pay · Disaster Management and Resilience · Facility Location and Emergency Management · Infrastructure Resilience and Vulnerability Analysis
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| Unique citing works | 2 |
|---|---|
| Citations per year | 2 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 2 |