Harnessing stakeholder input on Twitter: A case study of short breaks in Spanish tourist cities. (April 2019)

• Record Type: Journal Article
• Authors: Bigné, Enrique; Oltra, Enrique; Andreu, Luisa
• Is Part Of: Tourism management. Volume 71(2019)
• Page Start: 490
• Page End: 503
• Publication Date: 2019-04
• Subjects: Social media marketing -- Destination marketing organisations -- Twitter -- Text mining -- Artificial neural network -- Hotel occupancy -- Short-break holidays; Tourism -- Periodicals; 338.4791
• DOI: 10.1016/j.tourman.2018.10.013
• Languages: English
• ISSNs: 0261-5177

Abstract

Abstract: Knowledge of how destination marketing organisations (DMOs) use Twitter is still limited. This study aimed to assess how DMOs' Twitter activity affects hotel occupancy in short-break holidays. Key dimensions of Twitter that may affect hotel occupancy in tourist destinations were first identified. A longitudinal study using data for 10 Spanish DMOs was conducted to forecast hotel occupancy. Twitter application programming interfaces were used to gather data on tweets by DMOs and retweets and likes by users. Text mining was used to analyse the tweets by DMOs, differentiating between tweets related to events, attractions, socialisation, and marketing. Data were analysed using artificial neural networks. The best fit was achieved with a multilayer perceptron artificial neural network. Findings suggest that the number of retweets and replies by users and the number of event tweets, tourist attraction tweets, and retweets by DMOs can predict the hotel occupancy rate for a given destination. Graphical abstract: Highlights: A combined method based on text mining and ANNs identified dimensions of DMOs' Twitter activity affecting hotel occupancy. A longitudinal study to forecast hotel occupancy in tourist destinations based on dimensions of DMOs' Twitter use. Data on different dimensions of 10 Spanish DMOs' Twitter activity and occupancy rate at two times. An ANN was used to test the effects of DMOs' Twitter account management on hotel occupancy in tourist destinations.