Modeling ambiguity in expert elicitation surveys: Theory and application to solar technology R&D

Optimal R&D investment is defined by deep uncertainty that can only partially be addressed through historical data. Thus, expert judgments expressed as subjective probability distributions are seen as an alternative way of assessing the potential of new technologies. In this paper we propose a simple decision-theoretic framework that takes into account ambiguity over expert opinion and helps decision makers visualize the full range of R&D outcomes given a particular level of ambiguity. Our model is intuitive, captures decision makers' ambiguity attitudes, and enables simple sensitivity analysis across levels of ambiguity. We apply our framework to original data from a recent expert elicitation survey on solar technology. The analysis suggests that ambiguity plays an important role in assessing the potential of a breakthrough in solar technology given different R&D investments.