A comparison of generalized multinomial logit, random parameters logit, wtp-space and latent class models to studying consumers' preferences for animal welfare

The European societies are requiring that animals to be raised as closely as possible to their natural conditions. The growing concerns about animal welfare is resulting in continuous modifications of regulations and policies that led to ban of a number of intensive farming methods. The European authorities consider the pig welfare as a priority issue. They are studying to ban surgical pig castration by 2018, which may seriously affect markets and consumers due to boar tainted-meat. This study analysed consumers’ preferences and acceptance regarding an alternative to castration of high-level boar-taint frankfurter sausages. Non-hypothetical discrete choice experiments was applied by creating a real shopping scenario before and after tasting the products. Data were collected for a sample of 150 consumers from the metropolitan area of Madrid, Spain. Different modelling approaches (Generalized Multinomial Logit-GMNL, Random Parameters Logit-RPL, WTP-space and Latent Class-LC models) were applied to figure out which model have the best goodness of fit. Results showed the appropriateness of the proposed alternative by using a new flavour as a masking strategy. When consumers tasted the products, they showed their willingness to pay a premium for this flavour. The WTP space model showed the best goodness of fit in terms of likelihood, Akaike information criterion and McFadden Pseudo R2. Furthermore, the degree of randomness identified by the scale parameter is also estimated. Uncertainty in selection decreased significantly after the sensory experiencePostprint (published version

Traveller Behaviour: Decision making in an unpredictable world

This paper discusses the nature and consequences of uncertainty in transport systems. Drawing on work from a number of fields, it addresses travellers’ abilities to predict variable phenomena, their perception of uncertainty, their attitude to risk and the various strategies they might adopt in response to uncertainty. It is argued that despite the increased interest in the representation of uncertainty in transport systems, most models treat uncertainty as a purely statistical issue and ignore the psychological aspects of response to uncertainty. The principle theories and models currently used to predict travellers’ response to uncertainty are presented and number of alternative modelling approaches are outlined. It is argued that the current generation of predictive models do not provide an adequate basis for forecasting response to changes in the degree of uncertainty or for predicting the likely effect of providing additional information. A number of alternative modelling approaches are identified to deal with travellers’ acquisition of information, the definition of their choice set and their choice between the available options. The use of heuristic approaches is recommended as an alternative to more conventional probabilistic methods

Allowing for intra-respondent variations in coefficients estimated on repeated choice data

Partly as a result of the increasing reliance on Stated Choice (SC) data, the vast majority of discrete choice modelling applications are now estimated on data containing multiple observations for each respondent. At the same time there has been growing interest in the representation of unexplained heterogeneity in choice data, using random coefficients models such as Mixed Multinomial Logit (MMNL). The presence of multiple observations for each respondent can indeed be a great asset in the identification of such variations in tastes. However, in this paper, we question the validity of the common assumption that tastes vary across respondents but stay constant across repeated choices for the same respondent. We extend the existing framework for the MMNL analysis of panel data by allowing for intra-respondent heterogeneity on top of inter-respondent heterogeneity. An empirical analysis making use of a SC dataset for route choice confirms our hypotheses and shows that superior performance is obtained by our more general model

Learning styles and courseware design

In this paper we examine how (courseware) can accommodate differences in preferred learning style. A review of the literature on learning styles is followed by a discussion of the implications of being able to accurately classify learners, and key issues that must be addressed are raised. We then present two courseware design solutions that take into account individual learning‐style preference: the first follows on from traditional research in this area and assumes that learners can be classified in advance. The second solution takes account of the issues raised previously. We conclude by discussing the feasibility of adapting learning to suit the needs of individual learners, and suggest further research investigating the relationship between preferred learning style and the design of effective interactive learning environments

A critical look at power law modelling of the Internet

This paper takes a critical look at the usefulness of power law models of the Internet. The twin focuses of the paper are Internet traffic and topology generation. The aim of the paper is twofold. Firstly it summarises the state of the art in power law modelling particularly giving attention to existing open research questions. Secondly it provides insight into the failings of such models and where progress needs to be made for power law research to feed through to actual improvements in network performance.Comment: To appear Computer Communication

Robust Processing of Natural Language

Previous approaches to robustness in natural language processing usually treat deviant input by relaxing grammatical constraints whenever a successful analysis cannot be provided by ``normal'' means. This schema implies, that error detection always comes prior to error handling, a behaviour which hardly can compete with its human model, where many erroneous situations are treated without even noticing them. The paper analyses the necessary preconditions for achieving a higher degree of robustness in natural language processing and suggests a quite different approach based on a procedure for structural disambiguation. It not only offers the possibility to cope with robustness issues in a more natural way but eventually might be suited to accommodate quite different aspects of robust behaviour within a single framework.Comment: 16 pages, LaTeX, uses pstricks.sty, pstricks.tex, pstricks.pro, pst-node.sty, pst-node.tex, pst-node.pro. To appear in: Proc. KI-95, 19th German Conference on Artificial Intelligence, Bielefeld (Germany), Lecture Notes in Computer Science, Springer 199