The previous sections have given an overview of the preference uncertainty literature based on the psychological perspective of the violation of choice theory axioms, the causes of preference uncertainty, the method of preference elicitation, the effect of preference uncertainty on valuations as well as the different forms of uncertainty representations. From the psychological insight on choice theory, it is evident that individual’s preferences are neither always known or consistent or clear. Moreover, several causes affecting choice are outlined in psychology literature. This research aims to test descriptive invariance by examining the effect of different attribute representation techniques on respondent’s choice.
While accounting for respondent’s preference uncertainty is not a common practice in environmental SP exercise, several examples can nonetheless be found in the literature. Though the cause of preference uncertainty in CV literature has been more due to hypothetical bias, literature on CE has identified that choice set characteristics can affect the level of preference uncertainty. The choice set characteristics mostly examined in the CE literature have been attribute difference level across the alternatives as it plays an important factor on the level of task complexity. In case of environmental valuation and especially noise, different
methods of attribute representation can have significant effect on respondent’s understanding of the choice set and hence any empirical research to examine these effects in light of preference level can provide pivotal valuation and experimental design recommendations.
While examination of different preference elicitation techniques has been relatively well studied in CVM, this area of research has not received significant attention in CE while the preference data have commonly been recoded or eliminated.
Moreover, the causes and effect of different error structure in the preference data analysis needs further implementation within CE. Thus, the literature on preference elicitation methods and its analyses show a severe need to compare different methods of preference elicitation as well as to examine the effectiveness of models based on flexible error assumption.
The concept of vagueness as one of the representations of uncertainty can be extended to the cause of preference uncertainty. While previous research conducted in this area has focussed on choice-set and respondent characteristics on preference uncertainty, distinction on level of uncertainty needs to be made based on the role of the stochastic error. Thus, it is vital to know whether uncertainty arises from stochastic effects or whether the respondent’s stated level of uncertainty is a true reflection of the respondent’s willingness to commit towards the choice of an alternative. Relating this concept with that of the choice set characteristics, it is expected that when the choice set is easier for respondents to understand, there will be lesser dependence on the stochastic effects to explain the level of preference uncertainty.
Based on the research implications arising from the literature review, the following research hypotheses relating to the concept of preference uncertainty will be tested in the thesis:
Hypothesis 1b: The type of choice set is expected to have an effect on the level of respondent’s preference certainty with choice sets that are easier to understand will result in lower preference uncertainty than those that are more difficult
Hypothesis 2: Stated level of preference certainty can be due to deterministic as well as random effects. Thus, respondents’ stated preference certainty could either be due to their true level of commitment or arising from respondent or choice-set characteristics which affects the random error
Hypothesis 3: Different methods of preference elicitation can have varying capabilities to capture preference information
3.6 Conclusions
The purpose of this chapter was to provide an overview of the concept of preference uncertainty in SP, the underlying psychological reasons for inconsistency in choice, causes of preference uncertainty commonly found in the literature as well as the method of preference elicitation and types of uncertainty representation along with the effect of different preference elicitation and attribute representation methods on valuation. It was seen that experimental psychologists have acknowledged the inconsistency in preferences as well as have pointed out several circumstances where the assumptions underlying choice theory have been violated. Taking this into consideration, studies examining preference uncertainty were critically reviewed based on the causes of preference uncertainty they have focussed on as well as on the methods of preference elicitation and its subsequent analysis. The literature reviewed indicated a significant lack in the examination of different attribute representation methods on preference uncertainty, a comparative analysis of the effects of different methods of preference elicitation within CE, as well as the application of different modelling techniques where the preference uncertainty information is explicitly included in the model. Based on this observed lack as well as the different forms of uncertainty representation that can be found in the literature, this chapter also outlined the research hypotheses which will be tested in the subsequent chapters.
4 ANALYTICAL METHODS
4.1 Introduction
The purpose of this chapter is to provide an analytical framework for the experimental design and the subsequent data analysis. To this end, this chapter serves as a theoretical bridge between the basis of the research and the methods to test the hypotheses. The chapter will provide an introduction to the Stated Preference (SP) methods which forms an important basis of the experimental design and the survey while giving an overview of the various analytical methods applied in the thesis.
Section 4.2 will give an overview of the SP method along with the common methods of experimental design while Section 4.3 will detail the various logit models relevant to the analysis in this research. This section will also give an overview of the relevance of the specific models to capture preference uncertainty.
Section 4.4 will provide theoretical methods and application of the fuzzy logic technique.