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Development of a Destination Image Recovery Model for Enhancing the Performance of the Tourism Sector in Zimbabwe Just Before Covid-19

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  • Kanokanga Phillip Farayi (DPhil)

    (Department of Hospitality and Tourism, P. Bag 1119, Mt Pleasant, Zimbabwe, Zimbabwe Open University (ZOU))

Abstract

This study sought to develop a destination image (DI) recovery model for enhancing the performance of the tourism sector in developing countries with particular reference to Zimbabwe. This study was conducted just before the outbreak of the Covid-19 pandemic. This study allows tourism stakeholders to separate the current state of Zimbabwe’s tourism industry after it was exposed to the pandemic from the one it was in just before Covid-19. Many countries across the world are prioritizing tourism because of the role it plays as one of drivers of inclusive growth, job creation, forex generation and environmental preservation. Tourism is one of Africa’s engines of growth and development. The study was prompted by the failure of African tourism destinations to develop destination image recovery models for enhancing tourism performance and yet a number of them require destination image recovery. The study adopted a mixed method approach rooted in the pragmatist paradigm. It used the convergent parallel mixed methodology research approach and a cross sectional survey. Probability and non-probability sampling methods were employed in order to derive the sample from the population. The triangulation of sampling methods was meant to add rigor and enable a full exploration of the research problem. Data were collected in person from a sample of three hundred and nineteen respondents comprising international tourists, service providers and key informants. A structured, semi-structured questionnaire and semi-structured interview guide were used respectively. Quantitative data was analysed using the Statistical Package for Social Sciences (SPSS) and AMOS version 25 while qualitative data was analysed using NVivo version 12. Tests were conducted using descriptive statistics, exploratory factor analysis, and confirmatory factor analysis. Structural Equation Modelling (SEM) was used to analyze the multiple independent variables which included accessibility, amenities ancillary services and prices as well as dependent variables which were affective image and performance. Quantitative data were presented using tables and figures while themes were used to present qualitative data. The major findings of the study were that price, ancillary services and amenities significantly influenced affective image. Ancillary services significantly influenced destination performance. The study recommended that the Ministry of Environment, Tourism and Hospitality organizes workshops to train tourism stakeholders on the management of these destination attributes and include the generality of the host community in image recovery. The study concluded that there was need to adopt the stakeholder approach in order to achieve sustainable destination image recovery.

Suggested Citation

  • Kanokanga Phillip Farayi (DPhil), 2021. "Development of a Destination Image Recovery Model for Enhancing the Performance of the Tourism Sector in Zimbabwe Just Before Covid-19," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 8(10), pages 26-39, October.
  • Handle: RePEc:bjc:journl:v:8:y:2022:i:10:p:26-39
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    References listed on IDEAS

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    1. Stylidis, Dimitrios & Shani, Amir & Belhassen, Yaniv, 2017. "Testing an integrated destination image model across residents and tourists," Tourism Management, Elsevier, vol. 58(C), pages 184-195.
    2. Hosany, Sameer & Ekinci, Yuksel & Uysal, Muzaffer, 2006. "Destination image and destination personality: An application of branding theories to tourism places," Journal of Business Research, Elsevier, vol. 59(5), pages 638-642, May.
    3. Stylos, Nikolaos & Vassiliadis, Chris A. & Bellou, Victoria & Andronikidis, Andreas, 2016. "Destination images, holistic images and personal normative beliefs: Predictors of intention to revisit a destination," Tourism Management, Elsevier, vol. 53(C), pages 40-60.
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