Tuesday, 05 Dec, 2023




Revisit Intention: A Preliminary Investigation of GCC Tourists Electronic Word of Mouth, Destination Image, and Perceived Risk

International Journal of Hospitality and Tourism Systems

Volume 15 Issue 2

Published: 2022
Author(s) Name: R. A. Alfaisaly, Y. Kani, A. Y. M. Atiquil Islam, A. S. Alalyani, N. Abd Aziz | Author(s) Affiliation: College of Business Administration, Taif University, Taif 21944, Saudi Arabia.
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Despite the substantial economic contribution of the tourism sector globally, studies on revisit intention have been rather scarce, particularly within the Malaysian context. Addressing that, the present study aimed to determine the determinants that influence revisit intention among Gulf Cooperation Council (GCC) tourists in Malaysia. A conceptual model that comprised of electronic word of mouth (eWOM), destination image, perceived risk, and revisit intention was proposed for testing. Furthermore, destination image was assessed in terms of cognitive image, affective image, and unique image. The study successfully sampled 401 GCC tourists, specifically from Saudi Arabia, Oman, Kuwait, and the UAE, in several popular tourist spots in Malaysia. AMOS (version 18) was used to perform the main analysis of the present study, specifically structural equation modelling (SEM). Based on the obtained results, eWOM was found to directly influence cognitive image, affective image, and unique image. These three dimensions of destination image were also found to directly influence revisit intention. Surprisingly, only affective image was found to mediate the relationship between eWOM and revisit intention whereas perceived risk did not directly influence destination image and revisit intention. Overall, this study provided pertinent insights on revisit intention and its significant determinants, which were expected to largely benefit researchers and practitioners in the tourism sector.

Keywords: Revisit Intention, Electronic Word of Mouth, Destination Image, Perceived Risk, Structural Equation Modelling

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