Complexity and non-compensatory behaviour : an empirical investigation in health economics using choice experiments
Recent years have seen a development in the application of stated choice experiments (CE) as a method to directly evaluate different policy relevant attributes of non-market goods such as publicly provided health care interventions. The most common format of CE presents respondents with the task of choosing one option from among multiple alternatives, each described in terms of a set of attributes. A critical underlying assumption of such experiments is that of a fully compensatory decision process whereby individuals weight and “trade-off” all information provided and then choose the alternatives with the highest utility, independent of context, learning, fatigue, etc. The extensive use of this supposition has been explained by the fact that it results in formulations of choice processes that are amenable to mathematical analysis and statistical applications. However, extensive work in behavioural sciences makes it clear that individuals utilize a variety of information-processing strategies to solve preferential choice problems contingent upon context. Often the information-processing strategies do not involve the making of trade-offs, i.e. they are non-compensatory. If non-compensatory strategies are indeed used by a significant proportion of the population, the use of Cost Benefit Analysis, based upon the concept of compensating for welfare losses, would be questionable. The doctoral thesis attempts to answer the question of how do people evaluate and choose among the set of multi-attribute alternatives in a choice experiment. The implications of this for the design and analysis of responses to choice experiments are considered.