Quantifying how user-interaction can modify the perception of the value of climate information: A Bayesian approach

The growing attention user relevance is receiving in the context of climate services is giving new light to engagement activities. However, while there is an almost unanimous consensus that these are important to the delivery of usable services, there is relatively little quantitative evidence of their impact on the usefulness of the service or its value as perceived by the users and decision-makers. Using a simple Bayesian decision theoretic framework, we have analysed how the perceived value of the service changes as a function of the user's belief in the accuracy of the forecast. Based on this, we conclude, that, at least for the generic users adopted for our analysis, 30 or more repeated forecasts may be needed to ascertain the real user value of a predictive service. However, we argue that engagement between users and service providers can play a significant role in modifying the perceived accuracy and value of the service, bringing it closer in line with the objective evaluation. This requires feedback from users on both the specific climate information content and its presentation, alongside exploring the user's attitude to risk. If appropriate engagement can be achieved, this work suggests that it has the potential to alter the overall perceived cost-benefit ratio over a relatively short period of time, enabling users to make best use of the available climate information.