An Experimental Usability Test for different Destination Recommender Systems

  • Hildegard Rumetshofer

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

The present paper outlines the experimental evaluation of travel recommendations systems. First, theoretical concepts concentrating on the influencing factors for human-computer interaction, system usage and satisfaction are reviewed. An introduction of various methods dealing with usability evaluation is given and an overview of different standard survey instruments is provided. Second, a case study, the assessment of a travel recommender system currently under development, is presented. The evaluation considers aspects such as design and layout, functionality or ease of use. These measures obtained by a user questionnaire are combined with user interaction logging data. Different variants of the travel recommendation system and a baseline system were used for assessment. This promising approach complements subjective ratings by objective tracking data to obtain a more thorough picture of the systems´s weaknesses. Finally, findings are presented and an explanatory model for user/system satisfaction is proposed.
Original languageEnglish
Title of host publicationConference Proceedings Information and Communication Technologies in Tourism (ENTER) 2004
Editors Andrew J. Frew
Place of PublicationWien, New York
PublisherSpringer Verlag
Pages228-238
Number of pages11
VolumeENTER 2004
ISBN (Print)3-211-20669-8
Publication statusPublished - Jan 2004

Publication series

NameSpringer Computer Science

Fields of science

  • 102001 Artificial intelligence
  • 102006 Computer supported cooperative work (CSCW)
  • 102010 Database systems
  • 102014 Information design
  • 102015 Information systems
  • 102016 IT security
  • 102028 Knowledge engineering
  • 102019 Machine learning
  • 102022 Software development
  • 102025 Distributed systems
  • 502007 E-commerce
  • 505002 Data protection
  • 506002 E-government
  • 509018 Knowledge management
  • 202007 Computer integrated manufacturing (CIM)
  • 102033 Data mining
  • 102035 Data science

Cite this