<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>

The general aim of this thesis was to investigate affective forecasting in the context of public transport. Paper I, Study 1 revealed that non-users of public transport were less satisfied with the services than users. It was hypothesised that non-users were biased in their satisfaction ratings, a claim that was subsequently investigated in Paper I, Study 2, where a field experiment revealed that car users suffer from an impact bias, due to being more satisfied with the services after a trial period than they predicted they would be. To address the question of whether a focusing illusion is the psychological mechanism responsible for this bias, two experiments containing critical incidents were conducted in Paper II. These experiments investigated whether car users exaggerate the impact that specific incidents have on their future satisfaction with public transport. A negative critical incident generated lower predicted satisfaction with public transport, both for car users with a stated intention to change their current travel mode (in Paper II, Study 1) and for car users with no stated intention to change their travel mode (in Paper II, Study 2), which support the hypothesis that the impact bias in car users’ predictions about future satisfaction with public transport is caused by a focusing illusion. Paper III showed that car users misremember their satisfaction with public transport as a result of their recollections of satisfaction with public transport being lower than their on-line experienced satisfaction. Additionally, the desire to repeat the public transport experience is explained only by remembered satisfaction, not by on-line experienced satisfaction. Paper IV investigated whether a defocusing technique would counteract the focusing illusion by introducing a broader context, thereby generating higher predicted satisfaction. A generic defocusing technique, conducted in Paper IV, Study 1, did not generate higher predicted satisfaction, whereas a self-relevant defocusing technique conducted in Paper IV, Study 2 generated higher predicted satisfaction with public transport. Additionally, it was found that car-use habit accounts for the level of predicted satisfaction regardless of defocusing; the stronger the car-use habit, the lower the predicted satisfaction. The conclusions from this thesis are that non-users of public transport rate the services lower than users do, and that car users become more satisfied when using the services than they predicted. These mispredictions are a result of over-focusing on a limited range of aspects in public transport (i.e., a focusing illusion). Car users’ desire to repeat the public transport experience is influenced by their inaccurate memories of the services and not by their actual experiences. However, defocusing techniques may help car users make more accurate predictions about future satisfaction with public transport; this could facilitate a mode switch from using the car to using public transport services more often. Switching to a more sustainable transport mode could be beneficial for the individual and for society.

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.

Empowered by information technology, modern consumers increasingly rely upon online word-of-mouth (WOM--e.g., product reviews) to guide their purchase decisions. This dissertation investigates how WOM information is processed by consumers and its downstream consequences. First, the value of specific types of word-of-mouth information (e.g., numeric ratings, text commentary, or both) was explored for making forecast. After proposing an anchoring-and-adjustment framework for the utilization of WOM to inform consumer forecasts, I support this framework with a series of experiments. Results demonstrate that the relative forecasting advantage of different information types is a function of the extent to which consumer and reviewer have similar product-level preferences ('source-receiver similarity'). Second, I investigate the process by which dispersion--the degree to which opinions are divided for a product or service--in WOM is interpreted. Using an attribution-based approach, I argue that the effect of WOM dispersion is dependent on the perceived cause of that dispersion, which is systematically related to perceptions of preference heterogeneity in a product category. For products for which preferences are expected to vary, dispersion is likely to be attributed to the reviewers rather than the product itself, and therefore tolerated. I provide evidence for my hypotheses in a series of experiments where WOM dispersion is manipulated and respondents make choices and indicate purchase intentions.

Im Rahmen des Leistungsansatzes von emotionaler Intelligenz sehen Mayer und Salovey (1997) Emotionsverstaendnis als Voraussetzung für Emotionsregulation. Es sollte nützlich sein zu wissen, wie man sich in bestimmten Situationen fühlen wird. Zur Messung werden unter anderem Vignetten eingesetzt, in denen Emotionen für hypothetische Situationen vorhergesagt werden. Im Gegensatz dazu postulieren Gilbert und Wilson (2003) charakteristische Fehler bei affektiven Vorhersagen, die motivational günstig sind. In der vorliegenden Arbeit wird die Akkuratheit emotionaler Vorhersagen im natürlichen Umfeld untersucht, um dessen adaptiven Wert zu beurteilen. Zunächst sollten Beamtenanwärter ihre Emotionen in einer bedeutenden Testsituation vorhersagen (N=143). Dann wurden studentische Arbeitsgruppen (180 Mitglieder in 43 Gruppen) gebeten, Gefühle zwischen den Mitgliedern zu prognostizieren (Zuneigung, Zufriedenheit mit der Zusammenarbeit, Freude und Ärger). Akkuratheit wurde als geringer Bias (euklidische Distanz) und hohe Korrespondenz (Profilkorrelation) definiert. Das Round Robin Design der zweiten Studie ermöglichte die Varianzzerlegung der Akkuratheit nach Cronbach (1955). In beiden Studien ist ein niedriger Bias adaptiv in Hinblick auf harte Kriterien, auch inkrementell über Intelligenz und Persönlichkeit hinaus. Bias hing teilweise mit Allgemeinwissen zusammen, aber nicht mit Intelligenz. Zusammenhänge zu emotionaler Intelligenz waren inkonsistent. Die Akkuratheit als Korrespondenz ist theoretisch interessant aber deutlich weniger reliabel. Auf Gruppenebene konnte die Korrespondenz Kriterien vorhersagen, aber es zeigte sich keine inkrementelle Validität. Zukünftige Forschung sollte sich auf spezifische Situationen und spezifische Emotionen konzentrieren sowie die Prozesse untersuchen, die emotionalen Vorhersagen zugrunde liegen. / In the ability model of emotional intelligence by Mayer and Salovey (1997), emotional understanding is a prerequisite for emotion regulation. Knowing which emotions occur in which situations should be beneficial and adaptive. One of the subtests for emotional understanding asks for likely emotional reactions in hypothetical situations. In contrast, Gilbert and Wilson (2003) argue that characteristic biases in affective forecasting are adaptive. The current thesis aims to measure accuracy of emotional predictions in a natural setting and examines its adaptive value. In the anxiety study, public officials were asked to predict future emotions in an important test (N=143). The second study focused on freshman student work-groups (N=180 in 43 groups). Group members predicted interpersonal feelings for each other (affection, satisfaction with the collaboration, fun, and anger). In both studies, accuracy of emotional predictions is defined as low bias (i.e. Euclidean distance) and high correspondence (i.e. profile correlation). The round robin design in the work-group study also allows to decompose accuracy following Cronbach (1955). In both studies, a low bias was adaptive in terms of strong criteria, also incrementally over and above intelligence and personality alone. Accuracy was partly related to general knowledge but not to intelligence. Associations to emotional intelligence were inconsistent. Accuracy as correspondence is theoretically interesting but much less reliable. There is some evidence for its adaptive value on a group level but no indication of incremental validity. Future research should focus on specific situations and specific emotions. Also, processes underlying affective forecasts should be evaluated in detail.