Measurement techniques for organizational safety causal models: Characterization and suggestions for enhancements

Through a review of literature from diverse disciplines with actual and potential application to causal modeling of organizational safety risk, this paper explores issues regarding measurement techniques in a quantitative safety analysis context. The interdependencies of modeling perspectives, constructs, and measures are indentified, leading to (a) characterization and classification of measurement techniques, (b) suggestions on the selection of appropriate measurement methods for different types of model constructs including individual-level, global, configural, and shared, and (c) discussion of the modeling implications of interactions between measurement, constructs, and causal paths. A multi-dimensional perspective is offered through combinations of different "measurement methods" and "measurement bases". A Bayesian approach is also proposed to operationalize the multi-dimensional measurements. Examples are provided to help explain the roles of these measurements in capturing the relation between organizational factors and safety performance. This paper is a product of research which has the primary purpose of extending Probabilistic Risk Assessment (PRA) modeling frameworks to include the effects of organizational factors as the fundamental causes of accidents and incidents.