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Affective Forecasting: Predicting Future Satisfaction with Public Transport

<p>Affective forecasting refers to the process of predicting future emotions in response to future events. The overall aim of the present thesis was to investigate, by applying the framework of Affective forecasting, how car users predict their satisfaction with public transport services. Study 1, Part 1 revealed a satisfaction gap between users and non-users of public transport, whereby non-users reported lower satisfaction than users, in overall satisfaction as well as in two quality factors resulting from a factor analysis of a major survey on satisfaction with public transport. It was hypothesized that non-users were biased in their satisfaction reports, something which was subsequently investigated in Study 1, Part 2, where a field experiment revealed that car users suffer from an impact bias in their predictions about future satisfaction with public transport due to being more satisfied with the services after a trial period than they initially predicted they would. Addressing the question of whether or not a focusing illusion is the psychological mechanism responsible for the impact bias, two experiments containing critical incidents were conducted during Study 2, in order to investigate whether or not car users exaggerate the impact of specific incidents upon their future satisfaction with public transport. For car users with a stated intention to change their current travel mode, in Study 2, Part 1, as well as for car users with no stated intention to change their travel mode, in Study 2, Part 2, the negative critical incident generated lower predicted satisfaction with public transport, in support of the hypothesis that the impact bias in car users’ predictions about future satisfaction with public transport is caused by a focusing illusion.</p>

Identiferoai:union.ndltd.org:UPSALLA/oai:DiVA.org:kau-4868
Date January 2009
CreatorsPedersen, Tore
PublisherKarlstad University, Faculty of Economic Sciences, Communication and IT, Karlstad : Karlstads universitet
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeLicentiate thesis, comprehensive summary, text
RelationKarlstad University Studies, 1403-8099 ; 2009:50

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