Document Type : Research Paper

Authors

1 PhD Student in Business Management, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran

2 Professor, Department of Business Management, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran

Abstract

Today, tourism destination branding related to sustainable development concepts has become a powerful tool for transforming regions. On the other hand, the digital reputation of a tourism destination is one of the main factors affecting its competitiveness and attraction of new tourists. Hence, managers need to control the content affecting the digital reputation of the tourism destination brand. Considering the high importance of this issue, this research aims to provide a digital reputation model for tourism destination brands. Qualitative research has designed the model using the research strategy of the Foundation's data theory and the systematic design of Strauss and Corbin. Data collection was done through semi-structured interviews. The statistical population of this research was university faculty members, managers, and tourism industry activists. Purposeful sampling was used to collect information based on 14 interviews conducted, and the basis for completing the interviews was theoretical saturation. Data analysis was performed in three stages: coding, axial, and selective coding using MAXQDA software. Accordingly, causal conditions (tourism destination capacity, technological progress, economic advantages, tourism habits), contextual conditions (digital platforms, tourism facilities, institutional structures, technical infrastructures, society and culture), intervening conditions (political, economic and managerial factors, tourist characteristics), strategies (tourism destination management, digital marketing development, destination brand analysis, training of specialized human resources), and finally consequences (economic, social, brand equity, political and national consequences) are linked in the form of a comprehensive model.

Keywords

Main Subjects

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