Information and Decision-making for Major Accident Prevention – A concept of information-based strategies for accident prevention

Abstract

With wide application of sensors and digitalization for accident prevention and safety management of sociotechnical systems, distributed decision-makers rely on information supplied for their decision-making more than ever. “If we know an accident is going to happen, we can try to avoid it; if we know the risk is too high, we can try to reduce it”. In other words, decisions can be made to initiate an action for risk reduction and/or accident prevention after the risk of a hazardous event is perceived through information. Following such an idea, the thesis promotes a concept of information-based strategy for major accident prevention. An information-based accident prevention strategy involves creating a state of knowing and subsequently reduces probability of accidents and/or their consequence indirectly through decision-making, where the decision-makers are relevant actors in complex and dynamic sociotechnical systems. An information-based strategy can be considered as a new barrier for safety management and reduce risk further in combination with other barriers. The objective of this thesis is to increase the stock of knowledge, and to devise new applications of available knowledge, that can contribute to the theoretical foundation of information-based strategies for accident prevention. This is done by investigating several issues related to risk information. The issues include: • Need for risk information in resolving risk-related decision problems. • Contextual factors which impact decision-makers’ information retrieval, processing and utilization when resolving risk-related decision problems. • Prediction of information needs through decision analysis. • Accumulation and integration of information for accident prediction • Optimal response time for threat handling that is bounded by available information. In terms of contribution, this PhD work provides: • A theoretical and analytical framework for a systematic elicitation of information needs. • Increased knowledge about the roles of risk information, which are to create a state of knowing about: 1) the existence and formulation of risk-related decision problems, 2) the severity and urgency of decisions, 3) requirements and constraints of workable solutions, 4) attributes of alternatives for comparing and evaluating, and 5) rules to maintain safety or control risk. • An overview of contextual factors that impact the human decision-making activity, especially information retrieving, processing and utilization on the operation of highly autonomous ships. • A proposed multi-dimensional approach to analyze risk-related decision problems. • A verification of accident prediction possibility by information accumulation and integration with an accident prediction model. • A proposed “value of prediction” model based on information value theory to calculate the optimal response time for threat handling. • A confirmation that information produced from imperfect prediction can reduce risk, at the same time lower the risk tolerance threshold and raise the maximum response investment. In conclusion, the thesis provides novel knowledge for more effective utilization of risk information for major accident prevention in sociotechnical systems, thus contributing to the development of information-based accident prevention strategies. For the industry, the results can be used to support the implementation of hazard detection, accident prediction and prognosis, the resolving of risk-related decision problems, the design of decision support systems in complex collective modern work environments, the design of digitalization etc. With those efforts, information can contribute to major accident prevention and risk reduction more effectively in the industry.