Unravelling tourism destination's competitiveness using big data analytics: a comparative analysis

PurposeThe competitiveness of destinations is crucial for tourism. In this context, the study aims to uncover customer satisfaction, experiences, feelings, and thoughts by conducting a comparative analysis of social media comments from various competitive tourism destinations.Design/methodology/approachBig data research was conducted to answer the research questions. The data was collected on a social media platform focusing on three destinations in the Mediterranean region. Three methods were employed to analyse the data: sentiment analysis, topic modelling, and named-entity recognition.FindingsThis study addressed traveller satisfaction levels. It identified the topics concerning each destination, examined the emotions expressed by travellers about these topics, explored the potential impact on future behaviour, and investigated the features of the destinations and satisfaction levels about these features. It also identified the prominent food and beverage names in destinations and explored tourists' preferences regarding these foods and beverages.Research limitations/implicationsThe limitations of this study relate to the sample. The data used in this study was solely obtained from a single social media platform and focused on English-only comments. Further research that includes different social media platforms for hotel categories and considers reviews in local languages could capture a broader range of customer opinions and experiences.Practical implicationsPolicymakers can gain insight into a destination's position in the competitive landscape. This study has numerous implications for policymakers in the relevant destinations and managers in the design and implementation of services.Social implicationsThe findings of this study can have broader societal implications if considered and implemented by decision-makers and tourism businesses in the context of competitiveness.Originality/valueThe study's originality lies in integrating multiple disciplines and comparing tourism destinations using big data. This study improves the understanding of competitiveness in three specific Mediterranean destinations. Previous research has focused on different contexts in these Mediterranean destinations. Therefore, the study fills this gap by focusing simultaneously on all three destinations in the context of competitiveness.