Cheap and expensive alternatives in stated choice experiments: are they equally considered by respondents?

When analysing choice experiments respondents are assumed to attend all attributes and alternatives in the same way. However, because of the important role that the price of the alternatives can play in the decision-making process, the level of price of a specific alternative may have consequences on the level of consideration given to the remaining attributes of the alternative. In this article, we propose the use of a discrete mixtures logit approach to accommodate respondents ignoring alternatives in stated choice experiments. Our results indicate a higher propensity for respondents to ignore attributes when they face cheap rather than expensive alternatives. We also find that allowing for this leads to substantial improvements in the model performance.

Food miles or carbon emissions? Exploring labeling preference for food transport footprint with a stated choice study

The ecological footprint of food transport can be communicated using carbon dioxide emissions (CO2 label) or by providing information about both the length of time and the mileage travelled (food miles label). We use stated choice data to estimate conventional unobserved taste heterogeneity models and extend them to a specification that also addresses attribute nonattendance. The implied posterior distributions of the marginal willingness to pay values are compared graphically and are used in validation regressions. We find strong bimodality of taste distribution as the emerging feature, with different groups of subjects having low and high valuations for these labels. The best fitting model shows that CO2 and food miles valuations are much correlated. CO2 valuations can be high even for those respondents expressing low valuations for food miles. However, the reverse is not true. Taken together, the results suggest that consumers tend to value the CO2 label at least as much and sometimes more than the food miles label.

Random Regret Minimization: Exploration of a New Choice Model for Environmental and Resource Economics

This paper introduces the discrete choice model-paradigm of Random Regret Minimization (RRM) to the field of environmental and resource economics. The RRM-approach has been very recently developed in the context of travel demand modelling and presents a tractable, regret-based alternative to the dominant choice-modelling paradigm based on Random Utility Maximization-theory (RUM-theory). We highlight how RRM-based models provide closed form, logit-type formulations for choice probabilities that allow for capturing semi-compensatory behaviour and choice set-composition effects while being equally parsimonious as their utilitarian counterparts. Using data from a Stated Choice-experiment aimed at identifying valuations of characteristics of nature parks, we compare RRM-based models and RUM-based models in terms of parameter estimates, goodness of fit, elasticities and consequential policy implications.

Stated choices and benefit estimates in the context of traffic calming schemes:Utility maximization, regret minimization, or both?

This paper proposes a discrete mixture model which assigns individuals, up to a probability, to either a class of random utility (RU) maximizers or a class of random regret (RR) minimizers, on the basis of their sequence of observed choices. Our proposed model advances the state of the art of RU-RR mixture models by (i) adding and simultaneously estimating a membership model which predicts the probability of belonging to a RU or RR class; (ii) adding a layer of random taste heterogeneity within each behavioural class; and (iii) deriving a welfare measure associated with the RU-RR mixture model and consistent with referendum-voting, which is the adequate mechanism of provision for such local public goods. The context of our empirical application is a stated choice experiment concerning traffic calming schemes. We find that the random parameter RU-RR mixture model not only outperforms its fixed coefficient counterpart in terms of fit-as expected-but also in terms of plausibility of membership determinants of behavioural class. In line with psychological theories of regret, we find that, compared to respondents who are familiar with the choice context (i.e. the traffic calming scheme), unfamiliar respondents are more likely to be regret minimizers than utility maximizers. © 2014 Elsevier Ltd.

A question of taste: Recognising the role of latent preferences and attitudes in analysing food choices

There has long been substantial interest in understanding consumer food choices, where a key complexity in this context is the potentially large amount of heterogeneity in tastes across individual consumers, as well as the role of underlying attitudes towards food and cooking. The present paper underlines that both tastes and attitudes are unobserved, and makes the case for a latent variable treatment of these components. Using empirical data collected in Northern Ireland as part of a wider study to elicit intra-household trade-offs between home-cooked meal options, we show how these latent sensitivities and attitudes drive both the choice behaviour as well as the answers to supplementary questions. We find significant heterogeneity across respondents in these underlying factors and show how incorporating them in our models leads to important insights into preferences. 

It's not that I don't care, I just don't care very much: confounding between attribute non-attendance and taste heterogeneity

With the growing interest in the topic of attribute non-attendance, there is now widespread use of latent class (LC) structures aimed at capturing such behaviour, across a number of different fields. Specifically, these studies rely on a confirmatory LC model, using two separate values for each coefficient, one of which is fixed to zero while the other is estimated, and then use the obtained class probabilities as an indication of the degree of attribute non-attendance. In the present paper, we argue that this approach is in fact misguided, and that the results are likely to be affected by confounding with regular taste heterogeneity. We contrast the confirmatory model with an exploratory LC structure in which the values in both classes are estimated. We also put forward a combined latent class mixed logit model (LC-MMNL) which allows jointly for attribute non-attendance and for continuous taste heterogeneity. Across three separate case studies, the exploratory LC model clearly rejects the confirmatory LC approach and suggests that rates of non-attendance may be much lower than what is suggested by the standard model, or even zero. The combined LC-MMNL model similarly produces significant improvements in model fit, along with substantial reductions in the implied rate of attribute non-attendance, in some cases even eliminating the phenomena across the sample population. Our results thus call for a reappraisal of the large body of recent work that has implied high rates of attribute non-attendance for some attributes. Finally, we also highlight a number of general issues with attribute non-attendance, in particular relating to the computation of willingness to pay measures.

Regret minimisation and utility maximisation in a freight transport context

This study is the first to compare random regret minimisation (RRM) and random utility maximisation (RUM) in freight transport application. This paper aims to compare RRM and RUM in a freight transport scenario involving negative shock in the reference alternative. Based on data from two stated choice experiments conducted among Swiss logistics managers, this study contributes to related literature by exploring for the first time the use of mixed logit models in the most recent version of the RRM approach. We further investigate two paradigm choices by computing elasticities and forecasting choice probability. We find that regret is important in describing the managers’ choices. Regret increases in the shock scenario, supporting the idea that a shift in reference point can cause a shift towards regret minimisation. Differences in elasticities and forecast probability are identified and discussed appropriately.

Ordering effects and choice set awareness in repeat-response stated preference studies

We present an experiment designed to investigate the presence and nature of ordering effects within repeat-response stated preference (SP) studies. Our experiment takes the form of a large sample, full-factorial, discrete choice SP exercise investigating preferences for tap water quality improvements. Our study simultaneously investigates a variety of different forms of position-dependent and precedent-dependent ordering effect in preferences for attributes and options and in response randomness. We also examine whether advanced disclosure of the choice tasks impacts on the probability of exhibiting ordering effects of those different types. We analyze our data both non-parametrically and parametrically and find robust evidence for ordering effects. We also find that the patterns of order effect in respondents' preferences are significantly changed but not eradicated by the advanced disclosure of choice tasks a finding that offers insights into the choice behaviors underpinning order effects. © 2011 Elsevier Inc.