Diversity in statistical research techniques: An analysis of refereed research articles in the Journal of Travel & Tourism Marketing between 1992 and 2010

Lee, Hee Andy and Law, Rob (2012) Diversity in statistical research techniques: An analysis of refereed research articles in the Journal of Travel & Tourism Marketing between 1992 and 2010. Journal of Travel and Tourism Marketing, 29 1: 1-17. doi:10.1080/10548408.2012.638556


Author Lee, Hee Andy
Law, Rob
Title Diversity in statistical research techniques: An analysis of refereed research articles in the Journal of Travel & Tourism Marketing between 1992 and 2010
Journal name Journal of Travel and Tourism Marketing   Check publisher's open access policy
ISSN 1054-8408
1540-7306
Publication date 2012-01-01
Sub-type Article (original research)
DOI 10.1080/10548408.2012.638556
Volume 29
Issue 1
Start page 1
End page 17
Total pages 17
Place of publication Philadelphia, United States
Publisher Routledge
Language eng
Formatted abstract
This article reports the findings of a study that analyzes the statistical methods used in articles published in the Journal of Travel & Tourism Marketing (JTTM) in the period 1992–2010. A content analysis of 462 articles identified 68 different statistical methods, grouped into 17 categories. Factor analysis and ANOVA/MANOVA were the most commonly used methods, following descriptive statistics. There was a substantial increase in the use of structural equation modeling (SEM) in recently published papers. While a diverse range of statistical methods was used in the articles studied, their application was somewhat unbalanced. More use of multivariate statistical methods for further development of the travel and tourism marketing field is thus proposed. This article is of use to readers seeking to understand the development of statistical methods in travel and tourism marketing research, using JTTM as a case study.
Keyword Travel and tourism marketing
Content analysis
Statistical methods
Journal review
Destination image
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: UQ Business School Publications
 
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