Modelling consumers' heterogeneous preferences: a case study with Chilean wine consumers

Background and Aims: Understanding consumers' preferences is key to making a successful product, but preferences are heterogeneous. We compare three approaches to consider preference heterogeneity in discrete choice models: (i) systematic preference variations based on socio‐demographic characteristics; (ii) latent classes; and (iii) hybrid choice models with latent variables measuring consumers' attitudes. Methods and Results: Data from a stated choice survey of Chilean wine consumers were analysed using three different approaches; these agreed on average trends but differed in fit and implied different trade‐offs. For example, socio‐demographic characteristics correlate poorly with preferences. Latent classes offer a good fit but do not link preference heterogeneity to consumer characteristics. The hybrid choice model provides the best fit but requires more data, making it more difficult to use this approach in forecasting. Conclusions: The best approach might depend on the research objectives. Using latent classes on a representative sample is the best approach if forecasting is paramount. Modelling attitudes is helpful when more insight into consumers' preferences is sought. Systematic preference variations based on socio‐demographic characteristics are a good choice when only average trends are relevant. Significance of the Study: We make recommendations on how to model preference heterogeneity when studying wine preferences, an issue often overlooked

Understanding the preferences for different types of urban greywater uses and the impact of qualitative attributes

Greywater reuse can allow substantial improvements in the efficiency of potable water systems. However, widespread uptake of greywater reuse depends on its acceptability by the population. Previous studies have assessed the implementation costs of greywater reuse technology, and considered its acceptability in principle. Although cost is clearly very important in terms of adopting/installing the technology, the actual perception of greywater reuse is crucial in driving the acceptability of use and the long-term success of the technology. This study uses discrete choice models to quantify, for the first time, the preferences of different socio-economic groups for greywater of different quality (colour, odour) and for different uses inside homes. A stated choice survey that removed the influence of installation costs was developed, and implemented in Santiago, Chile. Although legislation allows greywater use in Santiago, it does not take place at any meaningful scale. Results show that, in decreasing order of preference, there is an overall acceptance for using high quality treated greywater for toilet flushing, laundry, garden irrigation, hand washing and, shower/bathtub use, but not for drinking. When the quality of appearance in terms of colour and odour gets worse, monetary incentives could be needed even for those uses that do not involve human contact. Gender, age, educational level, water expenditure level, and in particular previous knowledge about greywater reuse, are important determinants of acceptability and thus willingness to pay for greywater use; however, their importance varies according to the type of use. Our results provide important insights for understanding the conditions that would precipitate rapid and wide uptake of greywater reuse in cities, and thereby make better use of limited water resources

Modelling choice when price is a cue for quality: a case study with Chinese consumers

Experience products are those the quality of which cannot be ascertained until after consumption, forcing consumers to base their purchase decision on an expectation of the product's quality. This expected quality is based on cues available before purchase, among which price is noteworthy, as consumers tend to believe that higher prices imply higher quality. But price also stresses the consumers' budget restriction, inducing a double -and conflicting- global effect on purchase probability. Using the traditional formulation of Random Utility Models for experience goods (i.e. introducing all attributes directly in the utility function) can lead to an endogeneity problem due to the omission of expected quality, introducing bias on the results. Using a stated wine choice experiment conducted in China as a case study, we correct for endogeneity by modelling each alternative's expected quality as a latent variable, explained by all available quality cues, including price. Then we explain choice as a trade-off between price and expected quality. This allows us to separate both effects of price and correct for at least one source of endogeneity while being consistent with behavioural theory; this has either been ignored or not treated correctly in previous literature. Moreover, as the model requires only a single quality indicator for each alternative to achieve identification, the respondents’ burden increases marginally. Our results show that the use of latent variables reduces endogeneity and effectively allows to measure both effects of price separately, obtaining higher significance and correct signs for its parameters

Reconstructing the 2003/2004 H3N2 influenza epidemic in Switzerland with a spatially explicit, individual-based model

ABSTRACT: BACKGROUND: Simulation models of influenza spread play an important role for pandemic preparedness. However, as the world has not faced a severe pandemic for decades, except the rather mild H1N1 one in 2009, pandemic influenza models are inherently hypothetical and validation is, thus, difficult. We aim at reconstructing a recent seasonal influenza epidemic that occurred in Switzerland and deem this to be a promising validation strategy for models of influenza spread. METHODS: We present a spatially explicit, individual-based simulation model of influenza spread. The simulation model bases upon (i) simulated human travel data, (ii) data on human contact patterns and (iii) empirical knowledge on the epidemiology of influenza. For model validation we compare the simulation outcomes with empirical knowledge regarding (i) the shape of the epidemic curve, overall infection rate and reproduction number, (ii) age-dependent infection rates and time of infection, (iii) spatial patterns. RESULTS: The simulation model is capable of reproducing the shape of the 2003/2004 H3N2 epidemic curve of Switzerland and generates an overall infection rate (14.9 percent) and reproduction numbers (between 1.2 and 1.3), which are realistic for seasonal influenza epidemics. Age and spatial patterns observed in empirical data are also reflected by the model: Highest infection rates are in children between 5 and 14 and the disease spreads along the main transport axes from west to east. CONCLUSIONS: We show that finding evidence for the validity of simulation models of influenza spread by challenging them with seasonal influenza outbreak data is possible and promising. Simulation models for pandemic spread gain more credibility if they are able to reproduce seasonal influenza outbreaks. For more robust modelling of seasonal influenza, serological data complementing sentinel information would be beneficia

Using hybrid choice models to capture the impact of attitudes on residential greywater reuse preferences

The reuse of treated greywater in a residential setting could contribute substantially to easing problems with water scarcity. This paper argues that preferences in relation to reusing greywater for different uses within the home vary across households and can be driven at least in part by psychological constructs, such as attitudes and perceptions, which might appear irrational at face value from an economic perspective. To better understand heterogeneity in behaviour in a greywater reuse context, data from a stated choice survey were analysed using a hybrid choice model with latent variables, allowing us to incorporate measurable characteristics of the decision makers as well as other elements that cannot be measured directly (e.g. attitudes towards greywater reuse). Our results provide evidence on the preferences for different uses of treated greywater, and about the heterogeneity of choices among individuals and uses. The model suggests that heterogeneity in the acceptance of greywater reuse can be linked back mainly to underlying attitudes, for all uses except drinking. This knowledge can be used as an input to evaluate diffusion strategies to increase greywater reuse acceptability focused on messages about its direct (i.e. water bill savings) and indirect benefits (environmental benefits, water security, autonomy)

Fifty years of Transportation Research journals: A bibliometric overview

© 2018 Elsevier Ltd Transportation Research (TR) was established in 1967 with the vision of promoting multi-disciplinary (economics, engineering, sociology, psychology) research on transport systems. The journal has continuously expanded its wings becoming a world-leading journal, now publishing research work through six parts, A to F, respectively addressing Policy and Practice, Methodological, Emerging Technologies, Transport and Environment, Logistics and Transportation Review, and Traffic Psychology and Behaviour. This study aims to celebrate the first half century of the journal through a bibliometric study of the publications on all six parts between 1967 and 2016. It uses the most reliable database for academic research, the Web of Science Core Collection, to identify the leading trends in all TR journals in terms of impact, topics, authors, universities, and countries. Moreover, it uses the Visualization of Similarities (VOS) viewer software to analyse bibliographic coupling, co-citation, citation, co-authorship, and co-occurrence of keywords

From mathematical models to policy design: Predicting greywater reuse scheme effectiveness and water reclamation benefits based on individuals’ preferences

The residential reuse of greywater has attracted interest in recent years as a strategy to face water security problems. Nowadays, some cities such as Santiago de Chile are seeking to promote new laws that allow residential greywater reuse and make the incorporation of the necessary infrastructure (machinery and a parallel pipe system) mandatory for new buildings. The success of any such schemes, in terms of the amount of mains water that can be saved, is clearly influenced by the decision that individual consumers make on whether or not to use the parallel system, as they will also be the ones to face the potential externalities produced by the system (e.g., odours, noise from technology). Understanding and anticipating the behaviour of individuals is not an easy task, especially in the context of systems not yet widely implemented, but the groundwork has been laid with the application of approaches that allow analysts to determine the heterogeneity in consumer preferences based on the qualities of the product or service. However, there has been a lack of focus on making predictions that quantify the impact of acceptability on the volume of water recovered, driven in part by methods that been applied. This paper presents a way of predicting policy effectiveness and potential greywater reclaim benefits based on individuals' preferences. For this, we use two existing models that allow us to make predictions of greywater reuse for different domestic purposes. In a case study application to the city of Santiago de Chile, we carry out scenario tests to predict the potential uptake under potential future policy settings and show how allowing for an additional permitted use of greywater could save several hundred litres of water per month per household

Injury severity models for motor vehicle accidents: a review

“Permission is granted by ICE Publishing to print one copy for personal use. Any other use of these PDF files is subject to reprint fees" (www.transport-ice.com). http://dx.doi.org/10.1680/tran.11.00026Modelling of traffic accidents injury severity is a complex task. In the last few years the number and variety of studies that analyse injury severity of traffic accidents have increased considerably. In this paper 19 modelling techniques used to model injury severity of traffic accidents where at least a 4-wheeled vehicle is involved have been analysed. The analysis and the comparison between models was performed based on seven criteria (modelling technique, number of records, number of variables, area type, features, injury level and model fit). In general, it is not possible to recommend a method that could be identified as the best one. Each modelling technique has its own limitations and characteristics, awareness of which will help analysts to decide the best method to be used in each particular modelling problem. However, some general conclusions can be established: in most cases the results of models’ fits are found to be satisfactory, though not excellent; in the case of data mining models, accuracy improves with balanced datasets; and no correlation was found to exist between the number of accident records and the number of analysed variables.TRYSE Research Group, Department of Civil Engineering, University of Granada, Spai