Addressing common method variance in country- and destination-image research

Author(s)
Hans Baumgartner, Alessandro De Nisco, Adamantios Diamantopoulos
Abstract

Self-administered surveys are a widespread data collection method in tourism research. However, survey-based data are prone to what is widely referred to as common method variance (CMV). Common method variance represents systematic error variance which can potentially have a substantial confounding influence on empirical findings, since it can lead to incorrect assessments of construct validity and reliability as well as biased parameter estimates. Surprisingly, addressing common method variance issues is still an exception in tourism research. This study advocates the use of two approaches and it demonstrates the practical implementation of these approaches by drawing on a seven-country online survey of tourists’ perceptions of and intentions to visit Italy conducted on a sample of 4550 respondents intercepted in Brazil, China, India, Indonesia, Russia, South Africa, and Turkey.
Findings clearly reveal that common method variance is not a trivial issue that can be safely ignored when estimating models aimed at assessing country and destination images and at explaining tourists’ intentions to visit and/or positive word of mouth. Therefore, the study provides concrete insights and directions to tourism researchers seeking to address this issue in their empirical endeavors.

Organisation(s)
Department of Marketing and International Business
External organisation(s)
Pennsylvania State University, Universitá degli Studi Internazionali di Roma
Journal
Journal of Destination Marketing & Management
Volume
33
Pages
1-10
No. of pages
10
ISSN
2212-5752
DOI
https://doi.org/10.1016/j.jdmm.2024.100906
Publication date
06-2024
Peer reviewed
Yes
Austrian Fields of Science 2012
502019 Marketing
Keywords
ASJC Scopus subject areas
Strategy and Management
Portal url
https://ucrisportal.univie.ac.at/en/publications/addressing-common-method-variance-in-country-and-destinationimage-research(5cbd5923-9783-4bf8-b7c8-9cf402b73739).html