Measurement of individual risk preference for decision-making in SHM

Antti Valkonen, Branko Glisic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Effective decision-making methods have a large importance for sustainable management of infrastructure. Modern decision-making processes are increasingly data-based and sensor technologies enable data-based decision-making processes to be implemented in infrastructure management. In all decision-making, data-based or not, risk preferences of decision maker are a key consideration, and can explain why even rationally acting individuals could end up making different decisions under the same circumstances. Previous work in the field has shown that when using expected utility framework in a multi-stakeholder setting, differences in stakeholder risk preferences have large impacts on the optimal decisions. A key result in literature establishes the importance of risk-attitude measurement in infrastructure manager selection by showing that large discrepancies in risk attitudes can create a situation where a SHM system has a negative monetary value. As a first step in developing better decision procedures we have created a risk attitude measurement scale for infrastructure management purposes. The scale is derived from a widely utilized Domain-Specific Risk-Taking (DOSPERT) Scale, which utilizes a risk-return framework where risk taking is decomposed using perceived risks and benefits. We conducted a pre-test of the scale with a select student population. The pre-test results are encouraging in terms of quality of our scale and also give early evidence that SHM decision-making differs from ordinary maintenance decision-making.

Original languageEnglish (US)
Title of host publicationStructural Health Monitoring 2019
Subtitle of host publicationEnabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring
EditorsFu-Kuo Chang, Alfredo Guemes, Fotis Kopsaftopoulos
PublisherDEStech Publications Inc.
Pages1487-1495
Number of pages9
ISBN (Electronic)9781605956015
StatePublished - Jan 1 2019
Event12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019 - Stanford, United States
Duration: Sep 10 2019Sep 12 2019

Publication series

NameStructural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring
Volume1

Conference

Conference12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019
CountryUnited States
CityStanford
Period9/10/199/12/19

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Health Information Management

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