Differentiated duopoly with 'elimination by aspects'

"Elimination by aspects" (EBA) is a discrete model of probabilistic choice worked out by Tversky in 1972 which supposes that decision makers follow a particular heuristic during a process of sequential choice. Options are described by their attributes and, at each decision stage, the individuals eliminate all the options not having an expected given attribute, and so until only one option remains. In this paper, probabilities resulting from the EBA model are used to construct demands of a differentiated duopoly with imperfect rationality. These demands are consistent with partial heterogeneity of tastes and may be linked with a spatial framework in which consumers have convex perception of distance. In this model, a Nash price equilibrium in pure strategies exists if the cost of the highest attributes level firm is not too low. In this case, the "differentiation by attributes" form retained here is both horizontal and vertical, which is not very frequent in the literature. When the equilibrium does not exists, the interaction of best response functions of the firms induces an Edgeworth cycle instead of an exit of the lowest attributes level firm. This result underlines the role of cost difference in the existence of such a cycle.discrete choices ; product differentiation ; imperfect competition ; elimination-by-aspects ; Edgeworth cycles

Consumer Preferences for Water Supply? An Application of Choice Models to Urban India

Water supply, Consumer preferences, Discrete choice, Lexicographic preferences

Revisiting consistency with random utility maximisation: theory and implications for practical work

While the paradigm of utility maximisation has formed the basis of the majority of applications in discrete choice modelling for over 40 years, its core assumptions have been questioned by work in both behavioural economics and mathematical psychology as well as more recently by developments in the RUM-oriented choice modelling community. This paper reviews the basic properties with a view to explaining the historical pre-eminence of utility maximisation and addresses the question of what departures from the paradigm may be necessary or wise in order to accommodate richer behavioural patterns. We find that many, though not all, of the behavioural traits discussed in the literature can be approximated sufficiently closely by a random utility framework, allowing analysts to retain the many advantages that such an approach possesses

Assessing the Value of Time Travel Savings – A Feasibility Study on Humberside.

It is expected that the opening of the Humber Bridge will cause major changes to travel patterns around Humberside; given the level of tolls as currently stated, many travellers will face decisions involving a trade-off between travel time, money outlay on tolls or fares and money outlay on private vehicle running costs; this either in the context of destination choice, mode choice or route choice. This report sets out the conclusions of a preliminary study of the feasibility of inferring values of travel time savings from observations made on the outcomes of these decisions. Methods based on aggregate data of destination choice are found t o be inefficient; a disaggregate mode choice study i s recommended, subject to caveats on sample size

Models for Paired Comparison Data: A Review with Emphasis on Dependent Data

Thurstonian and Bradley-Terry models are the most commonly applied models in the analysis of paired comparison data. Since their introduction, numerous developments have been proposed in different areas. This paper provides an updated overview of these extensions, including how to account for object- and subject-specific covariates and how to deal with ordinal paired comparison data. Special emphasis is given to models for dependent comparisons. Although these models are more realistic, their use is complicated by numerical difficulties. We therefore concentrate on implementation issues. In particular, a pairwise likelihood approach is explored for models for dependent paired comparison data, and a simulation study is carried out to compare the performance of maximum pairwise likelihood with other limited information estimation methods. The methodology is illustrated throughout using a real data set about university paired comparisons performed by students.Comment: Published in at http://dx.doi.org/10.1214/12-STS396 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Paths on a website: research on customers’ online search and purchase behaviours using clickstream data

This dissertation is comprised of three chapters studying customers’ online search and purchase behaviours using clickstream data collected from the context of air travel. The first chapter explores how choice overload effect influences customers’ purchase decisions under different time pressure conditions. Two studies yield two findings. The first finding is that larger choice sets result in purchase deferral, which is consistent with choice overload effects. Time pressure significantly moderates this effect, because more deferrals occur when the purchase deadline is further away. The second finding is that it is not the real, physical time passing per se that creates a sense of time pressure; instead, time pressure appears to be defined by customers’ perception of time limit, which moderates the choice overload effect by shifting customers’ regulatory focus. The second chapter develops the modelling approaches of using path data to predict purchases. We develop the concepts of two types of sequence of browsing behaviours: the sequence of search strategies and the sequence of viewing behaviours. We find that viewing behaviour is a better indicator of purchase tendencies. We develop the modelling approaches of predicting the next viewing behaviour and using this predicted viewing behaviour to predict the purchase probability. Our approach improves current methods of predicting purchases by overcoming two disadvantages: inflexibility in adaption to different websites and missing detailed information of customers’ behaviours. We provide managerial insights on customising information shown to customers according to predicted viewing behaviours in order to improve purchase conversion rates. The third chapter reveals the relationship between customers’ online search strategies and decision strategies. Our first finding is that the search strategy of filtering can be viewed as a decision strategy characterised by Elimination by aspects (EBA) strategy, while flexible searches can be viewed as a decision strategy featured by Satisficing strategy. Our second finding is that the goal-related variable has the predominate effect on choice of decision strategies in the studied context. Customers choose the decision strategy that can enable them to fulfil the goal of finding a good price, instead of the strategy that simplify the choice task.Open Acces

Embedding Decision Heuristics in Discrete Choice Models: Assessing the MERITS of Majority of Confirming Dimensions, Extremeness Aversion, and Reference Revision

Contrary to the usual assumption of fixed, well-defined preferences, it is increasingly evident that individuals are likely to approach a choice task using decision heuristics that depend on the choice environment. These include heuristics defined by the local choice context, such as the gains or losses of an attribute value relative to the other attributes. Recent empirical findings also demonstrate that previous choices and previously encountered choice tasks can affect the current choice outcome, indicating a form of inter-dependence across choice sets. A number of these heuristics, namely the majority of confirming dimensions (MCD), the extremeness aversion and the reference revision heuristics, are analysed. These heuristics are not new, but their application, using the discrete choice modelling framework, to the transportation field has only barely begun. In particular, arising from the extremeness aversion heuristic, three models are discussed. The first is a recently developed model of context dependence known as the random regret minimisation (RRM) model. The second model is a non-linear utility model that makes reference to the worst attribute level in a choice set. The third model is a “relative advantage maximisation” (RAM) model, with an updated version of the existing RAM model introduced in this thesis. All these models are compared against one another and with the standard random utility maximisation (RUM) model. The results strongly indicate that incorporating context dependency into existing models should be a key consideration for the practitioner. Moreover, having identified some heuristics of special interest, the role of multiple heuristics in choice behaviour is also analysed. Interestingly, the heuristics themselves can be embedded directly into the utility functions by means of heuristic weighting functions, which weight the contribution of each heuristic to overall utility. The thesis examines the validity of such an approach

The Demand for Passenger Transport

Series: Discussion Papers of the Institute for Economic Geography and GIScienc