4.7 Article

Evaluation tool for assessing the influence of structural health monitoring on decision-maker risk preferences

出版社

SAGE PUBLICATIONS LTD
DOI: 10.1177/1475921721992016

关键词

Structural health monitoring; decision-making; risk attitude; risk preference; human factors; survey; risk aversion; asset management

资金

  1. USDOT OST-R UTC Program through the Center for Advanced Infrastructure and Transportation (CAIT) at the Rutgers University [69A3551847102, 0615]

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Different rational individuals may make different decisions under the same conditions due to their risk preferences, which can have significant effects on the feasibility of implementation in multi-stakeholder decision-making regarding structural health monitoring. Understanding stakeholders' risk attitudes is crucial for decision-making in structural health monitoring, as shown in previous research using the expected utility theory.
Different rationally behaving individuals can make different decisions even under same conditions. Concept of risk preference is one way of describing this discrepancy. Risk preference refers to the way decision-makers weight different risky options. Expected utility theory is a popular way to treat this weighting mathematically. Previous research in the field of structural health monitoring has shown that in a multi-stakeholder decision-making, discrepancies in risk preferences between the stakeholders can have large effects on the feasibility of structural health monitoring implementation. Results from that previous research obtained using expected utility theory showed that under certain conditions, differences in stakeholder risk attitudes can make the value of structural health monitoring system even negative. As the overall aim of structural health monitoring is to enable systematic data-based management of infrastructure, understanding of risk preferences and their effect on the structural health monitoring decision-making is of paramount importance. In this work, we created a risk preference assessment tool that is derived from Domain-Specific Risk-Taking scale. We propose the tool and explain its development and validation. The validation results indicate that the proposed assessment tool is technically sound and has high potential in the future valuation of human factors influencing decision-making based on structural health monitoring.

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