PurposeThe purpose of this study is to examine how hotel brands communicate on social media before and during the pandemic coronavirus disease 2019 (COVID-19) in relation to the tourism season.Design/methodology/approachTo gain insights into the communication of Italian hotel brands on social media, this study applies a qualitative methodology. Using the text mining technique, topic modelling was conducted on a sample of 5,032 posts from Italian 5-star hotel brands shared on the hotels' official Facebook pages.FindingsThe results show that hotel brands used essentially the same communication strategy in the tourism seasons before and after the pandemic outbreak, but with a particular focus on trust, safety and cordiality during the pandemic. Hotel brands focussed intensively on brand awareness, customer engagement and special activities that promote memorable and authentic experiences as well as luxury service quality.Originality/valueThis study contributes to the theoretical and empirical sense by bridging the concepts of tourism and hospitality, social media and corporate communication.

Purpose – The importance of the "data gold rush" that occurs in real time on various social media platforms is recognized by various tourism stakeholders and researcher. To extract knowledge from textual data, the purpose of this study is to apply text mining techniques to social media data. Methodology – Descriptive statistical analysis is conducted to quantify the activity of hotel brands on Facebook. The topic modelling technique Latent Dirichlet Allocation (LDA) is used to extract and validate knowledge from text data of 25 Croatian four- and five- star hotel brands that were active on social media in 2019. Sentiment analysis is used to identify personal attitudes expressed through user-generated text that hotel brands promote by posting messages on Facebook pages. Findings – The LDA analysis of the Croatian hotel posts extracted 6 topics: Wellbeing, Atmosphere, Promotion, Gastronomy, Surrounding and Satisfaction. The results of the sentiment analysis indicated that Facebook page followers are more likely to express positive sentiments reflecting an overall satisfaction with the promoted products, services and staff by hotel brands. Contribution – It is a unique study that provides an analysis of textual data in Croatian hospitality research. The application of the multimodal approach contributes to a better uses of contents in possible different strategies so that effective indicators can be given to perform an effective communication. This study provides recommendations, challenges, and current insights into applied communication strategies for marketers to increase a greater number of tourists visiting destinations.

In Croatia, tourism is one of the most important economic activities, accounting for 2.1% of total tourist flows in the European Union and 18% of the total Croatian gross domestic product. Economic development and tourism flows are influenced by the increasing intensity of climate change, leading to a need to adapt to new business conditions to minimize the negative and maximize the positive effects. The objective of the current study is to empirically research the role of tourism in the Croatian economy for the period 2004-2015 and the impact of climate change on tourist flows. To investigate experts’ opinions on the impact of climate change on Croatian tourism, this study employs a qualitative approach to obtain comprehensive insights into tourism, climate change and scientific research. By conducting in-depth interviews with experts and identifying the challenges posed by the current impact of climate change on Croatian tourism, the authors gain deeper insights into tourism development and climate change that reflect the current situation in Croatia. The results indicate that climate change will not have a negative impact on Croatian tourism in the near future. However, after 2050, a number of adaptation measures will be required to maintain the current tourism status.

The purpose of this paper is to design an artificial neural network in the attempt to define the data generating process of the number of German tourist arrivals in Croatia considering the strong seasonal character of empirical data. The presence of seasonal unit roots in tourism demand determinants is analysed using the approach developed by Hylleberg, Engle, Granger and Yoo – Hegy test. The study is based on seasonality analysis and Artificial Neural Networks approach in building a model which intend to describe the behaviour of the German tourist flows to Croatia. Different neural network architectures were trained and tested, and after the modelling phase, the forecasting accuracy and model performances were analysed. Model performance and forecasting accuracy evaluation was tested using the mean absolute percentage error. Based on the augmented HEGY test procedure it can be concluded the German tourist arrivals to the Republic of Croatia have nonstationary behaviour associated with the zero frequency and seasonal frequency. Taking this into consideration, in the analysis of the phenomenon it is necessary to consider its seasonal character. Given the importance of the tourism for Croatian economic development, the research results could be useful, for both, researchers and practitioners, in the process of planning and routing the future Croatian hotel industry development and improvement of business performances.