4,044
Views
66
CrossRef citations to date
0
Altmetric
Original Articles

The relevance of mobile tourism and information technology: an analysis of recent trends and future research directions

, ORCID Icon, &
Pages 732-748 | Received 26 Jun 2015, Accepted 25 Jul 2016, Published online: 01 Dec 2016
 

ABSTRACT

Although there have been studies concerning information and communication technologies adoption in the tourism industry, the research trends of mobile tourism (m-tourism) are still not very clear due to the short development time and emerging nature of the technologies. To fill this gap, this study reviewed and analyzed articles related to online reviews of tourism and hospitality published in academic journals between 2002 and 2015. Through a keyword-driven search and content analysis, 92 articles are identified as relevant and classified into three topics. Our findings contribute to a better understanding of this promising research direction by presenting the interesting classification methods used by relevant publications and their insights. This paper also discusses significant topical and methodological trends, and contributes to an overall understanding of existing research and its limitations.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by a grant from the The Hong Kong Polytechnic University [Grant Number 1-ZE3K].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 309.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.