Bounded rationality and RUM-based research

Bounded rationality’s critique of RUM theory is neither new nor esoteric, so it is no surprise to find that this critique has had some effect on RUM-based discrete choice modelling research. The Hybrid Choice Model (Ben-Akiva et al., 2001) is in part an attempt to

incorporate bounded rationality into discrete choice theory by ‘relaxing the basic RUM core, such as incorporating non-RUM decision protocols, in an effort to relax simplifying

assumptions and enrich underlying behavioral characterizations’ (p. 4). This statement

appears to suggest that boundedly rational decision protocols should be considered in discrete choice research. It is important to note, however, that the specific extensions of standard discrete choice research proposed in Ben-Akiva, et al. (2001) are: making error terms more flexible, modelling attitudes and perceptions, and including latent population segments. These specific extensions discussed in relation to the HCM do not appear to address decision-

making protocols or their potential impacts on discrete choice modelling. Thus, the specific research agenda outlined does not seem to incorporate bounded rationality’s criticisms of neoclassical and RUM theory.

Most references to heuristic strategies in the discrete choice literature see them as mental shortcuts that respondents use because of task complexity, learning effects, or respondent fatigue (Adamowicz & Boxall, 2001). Task complexity is generally avoided by design in CE research because decision tasks are simplified to promote compensatory decision-making

(Louviere et al., 2000). In research that has tested for effects from learning or fatigue, no effects have been found (V. Foster & Mourato, 2002; R. M. Johnson & Orme, 1996). Thus, if complexity, learning, and fatigue effects can be minimised, observed use of heuristics might represent respondents’ preferred decision-making strategies.

Discrete choice theorists are in fact hesitant to incorporate alternative decision protocols (Bolduc & McFadden, 2001):

A second reason for caution in moving away from

compensatory RUM-based models is that these models can approximate many behavioural patterns, even if they arise from cognitive effects that do not appear to be consistent with

preference maximisation. For example, rule-driven behaviour is likely to be broadly consistent with self-interest, and hence well-approximated by a RUM model, even if the selection process that leads to the use of such rules is quite different than utility maximisation….Non-compensatory models may be fully consistent with random preference maximisation, and may be approximated well by RUM models that mix over utility functions of different features of alternatives (p. 233).

This position is predicated on three ideas: behaviour can be modelled as maximisation, regardless of psychological motivation; the market impact of individuals’ use of heuristics is negligible; and heuristic decision-making can be modelled by integrative linear models. The first idea, that something is being maximised, has been shown to be a metaphysical statement, a declaration of the researcher’s paradigm rather than a statement with empirical content (Boland, 1981). Rabin (2002) further states that ignoring the behavioural accuracy of

modelling assumptions is ‘bad social science’. The second idea, that the use of heuristics does not affect market results, seems to be at odds with established practice of CE research. The accepted practice is to identify respondents who seem to be using decision heuristics and exclude their responses from the dataset, because the use of heuristic strategies may affect the estimated model parameters (Blamey et al., 2001). It is thus difficult to reconcile these two ideas: either heuristics are at base motivated by and indistinguishable from compensatory preference maximisation, as Bolduc & McFadden contend, or heuristics-based choices have the power to bias experimental results. Both contentions cannot be true. These conflicting statements thus argue for more study of the potential impacts of heuristic decision making. The third idea, that RUM models can approximate non-compensatory decisions, has been empirically studied. In fact, compensatory models do not necessarily accurately model

choices made with non-compensatory decision rules, and the fit between a RUM-based model and a heuristic decision protocol is sensitive to the correlational structure of the choice

environment (E. J. Johnson et al., 1989). The reasons for being cautious in moving away from RUM-based models of decision making thus seem insufficient, and, when interrogated, seem to suggest the importance of empirical work on the question of the use and impacts of

heuristic strategies.

Little empirical research has compared heuristic and RUM models for discrete choice analysis. One example of such research (Arentze et al., 2001) examined three models, including one rule-based model, one RUM model, and a hybrid model. The RUM model had better predictive power than the other two, but the researchers found the results inconclusive. Importantly, the results of different models were not directly comparable because they required different data for their estimation. The researchers could not determine whether the difference in performance were due to the different datasets or the models themselves.

This review of research that uses theories of bounded rationality to model decision making has considered several different aspects of the literature. First, a number of different models were considered, but satisficing and EBA were shown to be inappropriate choices for CE research on GMF. Satisficing is in part a theory of focusing attention on which alternatives should be included in the choice set, but a CE survey has already narrowed the choice set and obviated the need for a focusing strategy. EBA, for its part, can be replicated by nested RUM models, so it might not be as useful an example of a boundedly rational decision process as other models. However, a lexicographic or TTB model, based on research into fast and frugal heuristics, appears to offer possible ways to analyse consumer reactions to GMF. Secondly, the relationship between bounded rationality and maximisation was considered from several perspectives. Some research on bounded rationality closely follows a neoclassical framework, but assumes additional cognitive constraints on optimisation. Other research professes to focus not on optimisation but on the performance of decision heuristics. This research,

however, often makes reference to some presumed optimal state, which keeps the focus on the potential existence of an optimum.

One strand of bounded rationality research offers a different perspective on the motivation for consumers’ choices to that offered by the neoclassical framework. This strand focuses on the decision tools that people use without trying to evaluate their optimality. It is this research that may provide a basis for considering the issues regarding discontinuous preferences and market-level aggregation.

4.6 Conclusion

This literature review has provided the background for an empirical examination of consumer responses to genetically modified food. It has first determined that such an examination would need to rely on a stated preference method, because of the limited availability of market data on consumption of GMF. It has also suggested that an attribute-based stated preference

method is appropriate, and identified a choice experiment survey as the method of choice. CE surveys allow responses to different product attributes to be studied efficiently and are

consistent with neoclassical economic theory.

This literature review has also indicated areas where prior research may be extended. One such area concerns the separability of preferences. If preferences are assumed to be separable, then the resulting utility function is additive (Deaton & Muellbauer, 1980). The extant

literature that uses CE techniques to investigate WTP for GMF appears to assume that preferences over food attribute are separable (Burton & Pearse, 2002; Burton et al., 2001; S. James & Burton, 2003; Onyango et al., 2004). Both the survey designs and the resulting analysis in this literature appear to reflect such an assumption. It may be possible to test empirically the separability of preferences over the attributes of GMF by building on the CE research discussed in this literature review.

A second area where further research could be conducted concerns the assumption of preference continuity. The Archimedean axiom that guarantees continuity has been widely discussed in the theoretical, mathematical, and empirical literature. Many solutions have been proposed to accommodate discontinuous, that is, lexicographic, preferences. However, despite the suggestions of lexicographic preferences from some research regarding consumer

reactions to GMF, these accommodations do not appear to have been considered in the context of GMF. As a result, SP research regarding GMF has shown large percentages of protest responses. In addition, many potentially lexicographic choice patterns have been treated as continuous.

By not explicitly considering lexicographic preferences, GMF research may not be fully representing aggregate welfare or demand impacts of GMF. Some research has considered the aggregation issue in a practical manner, for example, estimating the percentage of consumers

who are ‘out of the market’ for GMF. Such estimates in effect represent an upper bound for market penetration of GMF. Nevertheless, CE research on GMF could be extended so as to attempt to provide a picture of the whole market. This would be valuable, for example, if one is considering the possible impacts on a particular product of a wholesale shift to production using gene technology or considering the welfare impacts of different policy options.

A final subject in CE research that might bear further investigation is the possibility of rule- based, heuristic, or boundedly rational decision-making in responses to surveys. The

possibility that decisions might be rule-based has been raised by discrete choice researchers and identified as a potential area of future research (Ben-Akiva et al., 2001). There is literature explicitly comparing rule-based and utility maximising behaviour. There may be further scope for exploring the connexions between bounded rationality and CE research. In particular, the issues surrounding demand for GMF suggest that a rule-based approach to choice behaviour may be an interesting avenue for research on consumers’ choices regarding GMF.

These issues – separability, continuity, aggregation, and maximisation – could be addressed by building on the current literature, especially through consideration of CE survey design and models for data analysis. The methodology for this will be considered in the next chapter.

Chapter 5