The DOI matches its Crossref record; 94 of the 94 references it cites were found in a registry or an index.
Demystifying the effects of perceived risk and fear on customer engagement, co-creation and revisit intention during COVID-19: A protection motivation theory approach
Abstract
Abstract Applying protection motivation theory, the purpose of this study is to investigate the effects of social media on customer brand engagement (CBE) and their consequent impact on co-creation and revisit intention in pandemic environment. This study also examines the moderation impact of fear of COVID-19 and perceived risk on associations between social media, CBE, and co-creation/revisit intention, thus further contributing to existing literature. Partial least squares structural equation modeling (PLS-SEM) was adopted to examine the data collected from key tourism-destinations in Jammu/Kashmir. The findings propose that social media positively and significantly effects the CBE, which subsequently affects co-creation and revisit intention in COVID-19 times. Second, findings found that CBE's positive impact on co-creation and revisit intention. Third, findings indicated the social media's indirect effect on co-creation and revisit intention, as mediated via CBE. Thus, social media's effect on co-creation and revisit intention are more prominent under elevated CBE in pandemics. Finally, fear of COVID-19 and perceived risk negatively moderates the linkage between social media, CBE, and co-creation/revisit intention. This study concludes with key implications arising from the analyses and further research opportunities.
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Cites
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194
A primer on partial least squares structural equation modeling (PLS-SEM)
Leguina, A. (2015) · International Journal of Research & Method in Education · doi:10.1080/1743727x.2015.1005806 · Cited by 18,921
Evolving to a New Dominant Logic for Marketing
Vargo, S. L., & Lusch, R. F. (2004) · Journal of Marketing · doi:10.1509/jmkg.68.1.1.24036 · Cited by 14,779
(2014) · DigitalCommons - Kennesaw State University (Kennesaw State University) · Cited by 12,785
Estimating Nonresponse Bias in Mail Surveys
Armstrong, J. S., & Overton, T. S. (1977) · Journal of Marketing Research · doi:10.2307/3150783 · Cited by 12,222
Estimating nonresponse bias in mail surveys
Armstrong, J. S., & Overton, T. S. (1977) · Journal of Marketing Research · doi:10.1177/002224377701400320 · Cited by 10,390
Using pls path modeling in new technology research: updated guidelines
Henseler, J., Hubona, G., & Ray, P. A. (2016) · Industrial Management & Data Systems · doi:10.1108/imds-09-2015-0382 · Cited by 7,173
Introduction to mediation, moderation, and conditional process analysis :
Hayes, A. F., & names (2015) · Cited by 7,004
A Protection Motivation Theory of Fear Appeals and Attitude Change1
Rogers, R. W. (1975) · The Journal of Psychology · doi:10.1080/00223980.1975.9915803 · Cited by 6,805
Cited by
Naeem, M., & Ozuem, W. (2022) · Information Technology & People · doi:10.1108/itp-01-2021-0061 · Cited by 94
Metadata
- Authors
- Rather, R. A.
- Venue
- Journal of Destination Marketing & Management
- Publisher
- Elsevier BV
- Published
- 2021-06
- Volume
- 20
- Pages
- 100564
- ISSN
- 2212-571X (ISSN-L)
- OpenAlex
- W3131634966
- Cited by
- 303
- References
- 94
- FWCI
- 86.80
- Type
- journal article
- Language
- en
- Open access
- closed
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- Rather, R. A. (2021). Demystifying the effects of perceived risk and fear on customer engagement, co-creation and revisit intention during COVID-19: A protection motivation theory approach. Journal of Destination Marketing & Management. https://doi.org/10.1016/j.jdmm.2021.100564
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