H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Business and Management H-index 65 Citations 20,990 202 World Ranking 148 National Ranking 2

Overview

What is he best known for?

The fields of study he is best known for:

  • Marketing
  • The Internet
  • Statistics

His scientific interests lie mostly in Marketing, Advertising, The Internet, Destinations and Public relations. The concepts of his Marketing study are interwoven with issues in Conceptual framework and Online participation. His study on Consumer behaviour is often connected to Pleasure as part of broader study in Advertising.

Daniel R. Fesenmaier combines subjects such as Tourism marketing, E-commerce and Convention with his study of The Internet. His Destinations research is multidisciplinary, relying on both First impression and Economic impact analysis. His Marketing management study combines topics from a wide range of disciplines, such as Marketing strategy and Marketing mix.

His most cited work include:

  • Risk Perceptions and Pleasure Travel: An Exploratory Analysis: (527 citations)
  • Pictorial element of destination in image formation (518 citations)
  • Expanding the functional information search model (443 citations)

What are the main themes of his work throughout his whole career to date?

Daniel R. Fesenmaier mainly focuses on Marketing, Advertising, The Internet, Destinations and Knowledge management. Ecotourism is closely connected to Tourism geography in his research, which is encompassed under the umbrella topic of Marketing. Daniel R. Fesenmaier has included themes like Social media, Recommender system, Travel behavior and Destination marketing in his Advertising study.

His research in The Internet intersects with topics in E-commerce, Tourist industry and Convention. His Knowledge management research incorporates themes from Process and Management information systems. His work carried out in the field of Marketing management brings together such families of science as Marketing strategy and Marketing mix.

He most often published in these fields:

  • Marketing (45.18%)
  • Advertising (35.88%)
  • The Internet (22.92%)

What were the highlights of his more recent work (between 2014-2021)?

  • Marketing (45.18%)
  • Advertising (35.88%)
  • Destinations (12.96%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Marketing, Advertising, Destinations, Social media and Knowledge management. His Marketing study frequently draws connections between related disciplines such as The Internet. As a member of one scientific family, Daniel R. Fesenmaier mostly works in the field of The Internet, focusing on Travel behavior and, on occasion, Mobile computing.

Daniel R. Fesenmaier merges Advertising with Public relations in his research. His Destinations research includes elements of Data science and Design science. His Knowledge management study integrates concerns from other disciplines, such as Tourism destinations and Behavioral economics.

Between 2014 and 2021, his most popular works were:

  • Information technology and consumer behavior in travel and tourism: insights from travel planning using the internet. (259 citations)
  • Smartphone Use in Everyday Life and Travel (249 citations)
  • Adapting to the Internet Trends in Travelers’ Use of the Web for Trip Planning (167 citations)

In his most recent research, the most cited papers focused on:

  • Marketing
  • The Internet
  • Statistics

Daniel R. Fesenmaier mostly deals with Marketing, Advertising, Social media, Destinations and The Internet. His research integrates issues of Process and Design science in his study of Marketing. His Advertising research incorporates elements of Adaptive structuration theory, Perception, Destination marketing, Mobile technology and Everyday life.

His Social media research is multidisciplinary, incorporating elements of Information searching, Variety and Social psychology. The various areas that Daniel R. Fesenmaier examines in his Destinations study include Mobile computing and Travel behavior. The study incorporates disciplines such as Trip planning, Point and Consumer behaviour in addition to The Internet.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Pictorial element of destination in image formation

Kelly J MacKay;Daniel R Fesenmaier.
Annals of Tourism Research (1997)

1140 Citations

Risk Perceptions and Pleasure Travel: An Exploratory Analysis:

Wesley S. Roehl;Daniel R. Fesenmaier.
Journal of Travel Research (1992)

940 Citations

Defining the virtual tourist community: implications for tourism marketing

Youcheng Wang;Quaehee Yu;Daniel R. Fesenmaier.
Tourism Management (2002)

842 Citations

Expanding the functional information search model

Christine A. Vogt;Daniel R. Fesenmaier.
Annals of Tourism Research (1998)

832 Citations

Factors for success in rural tourism development.

Suzanne Wilson;Daniel R. Fesenmaier;Julie Fesenmaier;John C. Van Es.
Journal of Travel Research (2001)

802 Citations

The Role of Smartphones in Mediating the Touristic Experience

Dan Wang;Sangwon Park;Daniel R. Fesenmaier.
Journal of Travel Research (2012)

801 Citations

Towards understanding members’ general participation in and active contribution to an online travel community

Youcheng Wang;Daniel R. Fesenmaier.
Tourism Management (2004)

799 Citations

Mediating tourist experiences: access to places via shared videos.

Iis P. Tussyadiah;Daniel R. Fesenmaier.
Annals of Tourism Research (2009)

769 Citations

Online information search: vacation planning process.

Bing Pan;Daniel R. Fesenmaier.
Annals of Tourism Research (2006)

651 Citations

Searching for the Future: Challenges Faced by Destination Marketing Organizations

Ulrike Gretzel;Daniel R. Fesenmaier;Sandro Formica;Joseph T. O’Leary.
Journal of Travel Research (2006)

612 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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