265
Views
2
CrossRef citations to date
0
Altmetric
Article

Cross-cultural promotional competence: a comparison of student and DMO marketing text

Pages 171-190 | Received 27 Apr 2018, Accepted 11 Oct 2018, Published online: 24 Oct 2018
 

ABSTRACT

This paper considers whether an inductive, collaborative information and communication technology-based approach to learning promotional language may help non-native English speakers produce destination material that can be effective in a real-world context. At a Japanese university, tourism communication students collected examples of professional language from the web in a shared database which they subsequently consulted in producing domestic destination websites in English. Text written by students for a destination was compared in a survey to text from an official English website for the destination. The survey measured the reaction of potential tourists in terms of trust in accuracy, expectations of service, and destination interest. Results indicate that the student material engendered stronger overall destination image, based on source credibility, interest in travel to the destination, and higher service expectations. The study considers implications of the results in terms of the effect of writing quality on destination image, and argues for the importance of cross-cultural marketing competence in tourism education.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1. Respondents were identified through Survey Monkey’s audience targeting feature.

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 227.00 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.