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Measuring Tsunami Museum Visitor Satisfaction: An Importance Performance Map Analysis

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  • Cut Aprilia
  • Yusra Yusra
  • Ida Rosnita Ismail

Abstract

This paper aims to develop a natural-disaster theme museum visitor satisfaction model by integrating authenticity, involvement, and destination image by applying Arnolds’ theory of emotion. This study takes place at Aceh Tsunami Museum, Indonesia. An Importance-Performance Map Analysis is applied to identify the performance and the importance of the museum attributes in determining visitor satisfaction. Using an adapted questionnaire, 199 usable data gathered from the Aceh Tsunami Museum were analyzed using Partial Least-Squares Structural Equation Modelling (PLS-SEM). The result showed that authenticity, involvement, and destination image as the predictors of visitor satisfaction with image as the highest predictor of visitor satisfaction. This study also found that image plays as a mediator in the relationship between authenticity, involvement and satisfaction. Subsequently, this study identifies two paths to reach visitor satisfaction in the natural-disaster theme museum. They are authenticity-image-satisfaction and involvement-image-satisfaction with the latter path have higher contribution to the visitor satisfaction. From IPMA analysis, it is found that activities that adding knowledge to the visitors are deemed important to create visitors satisfaction.

Suggested Citation

  • Cut Aprilia & Yusra Yusra & Ida Rosnita Ismail, 2022. "Measuring Tsunami Museum Visitor Satisfaction: An Importance Performance Map Analysis," Cogent Business & Management, Taylor & Francis Journals, vol. 9(1), pages 2020398-202, December.
    • Handle: RePEc:taf:oabmxx:v:9:y:2022:i:1:p:2020398
    DOI: 10.1080/23311975.2021.2020398
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    Cited by:

    1. Wang, Zhan-ao & Samuel, Ribeiro-Navarrete & Chen, Xiao-qian & Xu, Bing & Huang, Wei-lun, 2023. "Central bank digital currencies: Consumer data-driven sustainable operation management policy," Technological Forecasting and Social Change, Elsevier, vol. 196(C).

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