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Contribution to Book
Towards Identifying Contextual Factors on Parking Lot Decisions
Information Systems and Analytics
  • Klaus Goffart
  • Michael Schermann, Santa Clara University
  • Christopher Kohl
  • Jörg Preißinger
  • Helmut Krcmar
Document Type
Book Chapter
Publication Date
7-7-2014
Publisher
Springer
Abstract

The relevance of contextual factors that adapt in-car recommendations to the driver’s current situation is not yet fully understood. This paper presents a field study that has been conducted in order to identify relevant contextual factors of in-car parking lot recommender systems. Surprisingly, most contextual factors examined, i.e., weather, luggage, and traffic conditions, did not have a significant effect on the parking lot decision in the conducted field study. Only the urgency of the trip and the willingness to walk have significant effects on the decision outcome. Therefore, automobile manufacturers should focus on understanding the relevance of different contextual factors when developing user models for in-car recommender systems.

Chapter of
User Modeling, Adaptation, and Personalization: 22nd International Conference, UMAP 2014, Aalborg, Denmark, July 7-11, 2014. Proceedings
Part of
Lecture Notes in Computer Science
Editor
Vania Dimitrova
Tsvi Kuflik
David Chin
Francesco Ricci
Peter Dolog
Geert-Jan Houben
Citation Information
Goffart, K., Schermann, M., Kohl, C., Preißinger, J., and Krcmar, H. (2014): ”Towards Identifying Contextual Factors on Parking Lot Decisions” in User Modeling, Adaptation, and Personalization, Dimitrova, V., Kuflik, T., Chin, D., Ricci, F., Dolog, P. and Houben, G.-J. (eds.). Berlin, Germany: Springer, pp. 320-325.