The Role of Travel Motivations and Social Media Use in Consumer Interactive Behaviour: A Uses and Gratifications Perspective

Round 1

Reviewer 1 Report

Personally, I like to know:

The characteristics of the sample

How the sample was selected 

The authors claim the sample comprised heavy users - but the criterion noted in the paper are fairly "average" to my mind.  Are we all heavy users now?  Age might be a factor in use, but we have no detailed breakdown of variance of social media usage rates.

Equally, I like to know the descriptive statistics as well.  Which were the items considered to be most important, or unimportant - and the factors, etc can all be related at high levels if the scores on observed variables are "high" - or "low".  The nature of the questions implies little likelihood of non-response - but equally, it does appear that respondents were not expected to opt-out of answering. The actual questionnaire is not provided. The paper seems to imply the questioning was of a fairy generic nature. I think the research design could have better specificity - e.g Please consider the last time you went on holiday ... Considering that holiday - when was it - where was it too.  If such specificity is not considered, I could answer to a holiday taken some years ago (my last holiday) or I might answer in general - in which case the answers do not possess any specific content - are just "in general" - and might actually apply to any recent trip.

The literature review is well done. the idea has value in introducing the concept of stickiness. I am not sure the discussion at the end actually reveals anything that is particularly startling - indeed many of the findings could be anticipated from the literature review.

If we accept the validity of the data - then the analytical steps are quite conventional.  It is workmanlike, the authors provide a standard justification for the use of PLS as against CB-CFA techniques. 

The paper is fairly representative of papers that do get published - it does not particularly "excite" me - but I have no real reason to inhibit publication. I just wish I could have more trust in the quality of the data - reference to statistical correlations etc no longer "does it" for me any longer!

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 2 Report

Dear authors,

Your article is interesting and studies: The Role of Travel Motivations and Social Media Use in Consumer Interactive Behavior: A Uses and Gratifications Perspective. The authors conducted a two-step research.

However, I have some recommendations:
- it's needed to improve the analysis of the literature for the research hypotheses;
- for hypotheses H4, H5 and H6 it's needed to add secondary hypotheses, especially since "travel motivations" was based on 4 dimensions: leisure, relaxation, learning / discovery and social bonding. Probably, the research model will be rethought.
- for quantitative results, is needed to be presented and discussed in more detail.
- I propose to add the validation of the structural model - o figure with research model and resultes for research hypotheses.

I hope that my recommendations will be increase the scientific value of this article.

Best wishes,

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 3 Report

sustainability-954076

Thank you for giving this opportunity to read this interesting study, I would suggest following comments to improve quality of manuscript.

Author/s need to decide whether use ‘Intention to Follow Advice’ or ’eWOM Adoption’ and use a single label throughout. I strongly recommend use the label that match with original study that developed the scale items. As you know in quantitative method, we are not allowed to simply change the labels of the scale as there is an established process for development and validation of the scale.  Please ensure all scale items are used in the model are extracted from validated sources.

I would suggest recent publications on travel motivations to not only rich section 2.3, but also present it in a critical way by reviewing both drivers and barriers of travel.

• (2020). Determinants of canal boat tour participant behaviours: An explanatory mixed-method approach. Journal of Travel & Tourism Marketing, 37(1), 112-127. Doi: https://doi.org/10.1080/10548408.2020.1720890
• (2020). Antecedents of space traveler behavioral intention. Journal of Travel Research, 59(3), 528-544. Doi: https://doi.org/10.1177/0047287519841714
• (2019). What are the triggers of Asian visitor satisfaction and loyalty in the Korean heritage site?. Journal of Retailing and Consumer Services, 47, 195-205. Doi: https://doi.org/10.1016/j.jretconser.2018.11.002.

There are many outdated citations that you may need to either delete them or update the references with recent publications.

Please note that the critique over functionality of PLS-SEM appears in business and management research (e.g., Guide and Ketokivi, 2015; Rönkkö et al., 2016). For example, Rönkkö et al. (2016) argued that use of an incorrect estimator leads to biased (inaccurate – invalid) results. The many problems that arise from using PLS can be overcome and avoided by using a less controversial estimator (eg AMOS, LISREL, MPLUS). Guide and Ketokivi (2015, p. vii) indicated that “use of PLS is (incorrectly) justified by saying that PLS is suitable for small samples, that it should be used when one has formative indicators in a measurement model, or that it is suitable when the Maximum Likelihood estimator fails to converge to a solution. All are poor excuses for using PLS. Claiming that PLS fixes problems or overcomes shortcomings associated with other estimators is an indirect admission that one does not understand PLS.” Hence, I would suggest to use another estimator if possible.

• Guide Jr, V. D. R., & Ketokivi, M. (2015). Notes from the Editors: Redefining some methodological criteria for the journal. Journal of Operations Management, 37(1), v-viii.
• Rönkkö, M., McIntosh, C. N., Antonakis, J., & Edwards, J. R. (2016). Partial least squares path modeling: Time for some serious second thoughts. Journal of Operations Management, 47, 9-27

Hope you find these comments helpful. 

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Authors successfully addressed my comments