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.     

Flexible substitution patterns in models of mode and time of day choice: new evidence from the UK and the Netherlands

Modelling the temporal response of travellers to transport policy interventions has rapidly emerged as a major issue in many practical transport planning studies and is recognised to hold particular challenges. The importance of congestion and its variation over the day, together with the emergence of time-dependent road user charging as a policy tool, emphasise the need to understand whether and how travellers will change the timing of their journeys. For practical planning studies, analysts face a major issue of relating temporal changes to other behavioural changes that are likely to result from policy or exogenous changes. In particular, the relative sensitivity of time and mode switching has been difficult to resolve. This paper describes a study undertaken to determine the relative sensitivity of mode and time of day choice to changes in travel times and costs and to investigate whether evidence exists of varying magnitudes of unobservable influences in time of day switching. The study draws on data from three related stated preference studies undertaken over the past decade in the United Kingdom and the Netherlands and uses error components logit models to investigate the patterns of substitution between mode and time of day alternatives. It is concluded that the magnitude of unobserved influences on time switching depends significantly on the magnitudes of the time switches considered. With time periods of the magnitude generally represented in practical modelling, i.e. peak periods of 2–3 hours, time switching is generally more sensitive in these data than mode switching. However, the context of the modelling and the extent to which relevant variables can be measured will strongly influence these results.     

New appraisal values of travel time saving and reliability in Great Britain

Transportation - This paper provides an overview of the study ‘Provision of market research for value of time savings and reliability’ undertaken by the Arup/ITS Leeds/Accent consortium...     

Making use of respondent reported processing information to understand attribute importance: a latent variable scaling approach

In recent years we have seen an explosion of research seeking to understand the role that rules and heuristics might play in improving the predictive capability of discrete choice models, as well as delivering willingness to pay estimates for specific attributes that may (and often do) differ significantly from estimates based on a model specification that assumes all attributes are relevant. This paper adds to that literature in one important way—it explicitly recognises the endogeneity issues raised by typical attribute non-attendance treatments and conditions attribute parameters on underlying unobserved attribute importance ratings. We develop a hybrid model system involving attribute processing and outcome choice models in which latent variables are introduced as explanatory variables in both parts of the model, explaining the answers to attribute processing questions and explaining heterogeneity in marginal sensitivities in the choice model. The resulting empirical model explains how lower latent attribute importance leads to a higher probability of indicating that an attribute was ignored or that it was ranked as less important, as well as increasing the probability of a reduced value for the associated marginal utility coefficient in the choice model. The model does so by treating the answers to information processing questions as dependent rather than explanatory variables, hence avoiding potential risk of endogeneity bias and measurement error.     

Revisiting reference point formation,gains–losses asymmetry and non-linear sensitivities with an emphasis on attribute specific treatment

In contrast with expected utility theory, empirical findings indicate that decision-makers are sensitive to departures from reference points rather than states. Several tests of the reference-dependent preference framework have been carried out in experimental economics, and to a smaller extent in a choice modelling setting, to date. However, these empirical applications have generally focussed on a single behavioural phenomenon using uniform modelling approaches. This paper aims to broaden existing work by presenting a multi-attribute framework, allowing contemporarily for gains–losses asymmetry, non-linearity and testing for several possible reference points. The framework is applied in the context of commuter choices and reveals important gains in model fit and further insights into behaviour compared to standard modelling approaches. Of particular relevance for future research is the functional form of fare sensitivity that varies significantly with the reference point used.     

Allowing for heterogeneous decision rules in discrete choice models: an approach and four case studies

The study of respondent heterogeneity is one of the main areas of research in the field of choice modelling. The general emphasis is on variations across respondents in relative taste parameters while maintaining the assumption of homogeneous utility maximising decision rules. While recent work has allowed for differences in the utility specification across respondents in the context of looking at heterogeneous information processing strategies, the underlying assumption that all respondents employ the same choice paradigm remains. This is despite evidence in the literature that different paradigms work differently well on given datasets. In this article, we argue that such differences may in fact extend to respondents within a single dataset. We accommodate these differences in a latent class model, where individual classes make use of different underlying paradigms. We present four applications using three different datasets, showing mixtures between “standard” random utility maximisation models and lexicography based models, models with multiple reference points, elimination by aspects models and random regret minimisation models. In each of the case studies, the behavioural mixing model obtains significant gains in fit over the base structure where all respondents are hypothesised to use the same rule. The findings offer important further insights into the behavioural patterns of respondents. There is also evidence that what is retrieved as taste heterogeneity in standard models may in fact be heterogeneity in decision rules.     

Conservation and development in Oregon's coastal zone

Abstract

Coastal zone management in Oregon is based on the state's general land‐use law. This body of law is designed to deal with population increase, urbanization, and preservation of agricultural land, as well as with other problems throughout the state. Early planning and policy recommendations for the coast were in the hands of a commission having predominantly local membership. This commission produced an extensive series of studies, policies, and recommendations which were assembled as a proposed management tool for natural resources. Staff of the commission was then absorbed into the state land‐management agency, which developed final goals and guidelines for compliance with the Coastal Zone Management Act. Adoption of the coastal goals in December 1976 has triggered deadlines for local government compliance within the coastal zone. The management program is now undergoing federal review.     

Random covariance heterogeneity in discrete choice models

In this paper, we extend the standard discrete choice modelling framework by allowing for random variations in the substitution patterns between alternatives across respondents, leading to increased model flexibility. The paper shows how such a Mixed Covariance model can be specified either with purely random variation or with a mixture of random and deterministic variation. Additionally, the model can be based on an underlying GEV or ECL structure. Finally, the model can be specified as a continuous mixture or as a discrete mixture. An application on Stated Preference data for the choice of departure time and travel mode shows that important gains in model performance can be obtained by allowing for random covariance heterogeneity. Furthermore, the approach leads to significant differences in the implied willingness to pay measures, and the substitution patterns between alternatives.