Purpose: The aim of the paper is to examine and analyse the thematic literature on tourism seasonality and the causes and effects thereof.Design/methodology/approach: The paper is based on a review of scientific and theoretical research by various authors on tourism seasonality, in order to systematically analyse the causes and effects of the seasonal patterns in tourism activity.Findings: Seasonality is one of the most important features of tourism demand, and it has a significant effect on many aspects of the tourism industry. The literature review suggests that tourism seasonality is caused by natural and anthropogenic factors that have a very significant bearing on the geographical location of a tourist destination, as well as institutional and economic factors. Assessments of the effects of seasonality in the scientific literature differ. The effects of seasonality analysed in the relevant literature can be divided into four major categories: economic, employment, social and cultural as well as ecological.Originality/value: The paper presents a systematic literature review on tourism seasonality and the causes and effects thereof.

Purpose: This study aims to examine the main aspects of innovation development regarding digital tools used in the tourism industry in a local area.Design/methodology/approach: A qualitative approach and the descriptive analysis technique was employed to analyse completed semi-structured expert survey questionnaires created in Google Forms. The aim is to examine the opportunities and potential for digital innovation in tourism in the Baltic region. Specialists representing tourism and hotel businesses, the guide profession as well as the disciplines of business and economics were selected as experts.Findings: The experts indicated that digital marketing was very important for tourism development, and it is still considered a new field of science with huge potential. The research results showed that when introducing/developing digital innovations in a local area, tourism companies were faced with low-quality or no data analytics at all. In addition, long-term maintenance of digital tools was not considered, and the investment outweighed the benefits of implementing the technologies.Originality/value: The study contributes to the development of digital innovation and the identification of problems in a local area.

Purpose: The purpose of this study is to provide a thematic literature analysis of smart tourism and the role of stakeholders and synergy relating to the implementation of smart tourism.Design/methodology/approach: The study is based on a review of prior research by various authors on smart tourism and the role of stakeholders and synergy relating to the implementation of smart tourism.Findings: Research studies define the concept of smart tourism as a form of technological, economic and social evolution, which is influenced by such elements as the Internet, social media, smart devices and mobile applications, among others. Stakeholder theory is based on the organizational context, and various individuals and groups within an organization are mutually supported and influenced by the same organizational goals. The research studies have found that cooperation between internal and external stakeholders could involve designing a tourism strategy, coordinating tourism promotion and branding, raising local tourism awareness, standardizing tourist facilities, making ticket price policies and communicating with tourism stakeholders.Originality/value: The paper provides a thematic literature review of smart tourism, the role of stakeholders and synergy from the perspective of the implementation of smart tourism.

Purpose: The present research study aims to conduct a thematic literature review of the negative impacts of artificial intelligence (AI) on the tourism industry.Design/methodology/approach: The research study is based on a comprehensive review of prior research by various authors on AI and its negative consequences in the tourism industry.Findings: Research indicates that integrating AI technologies in the tourism industry leads to negative consequences. While AI enhances operational efficiency and personalizes customer experiences, it also presents significant challenges, for example, AI replaces labor and the interaction between the tourist and the service provider decreases. New risks are emerging in various areas of tourism that need to be managed to ensure that they do not have negative impacts.Originality/value: The paper provides a comprehensive review of the negative impacts of AI technologies on the tourism industry, highlighting the need for a balanced approach that integrates human elements with technological advancements. It offers valuable insights into the potential drawbacks of AI, urging stakeholders to consider these challenges when implementing AI-driven solutions in tourism.

Purpose: This article aims to adopt a thematic approach to a review of the literature relating to sustainability and its challenges in destinations that highly depend on tourism.Design/methodology/approach: The paper provides a review of scientific and theoretical research studies on the concept and principles of sustainable tourism, the effects of tourism on society and sustainable tourism strategy.Findings: The basic principles of sustainable tourism development apply to all destinations, including Cyprus. The development of tourism is associated with the observance of the principles of sustainable tourism development, which takes the form of balanced environmental and economic development and involves the observance of public interest.Originality/value: The paper offers a broad-ranging review-based perspective on sustainable tourism and the principles and development thereof.

Food waste is a global problem, which becomes apparent at various stages of the food supply chain. The present research study focuses on the optimization of food consumption in schools and effective food management through data-driven decision making within the trends: zero food waste and digital transformation. The paper presents a plate waste forecasting system based on mathematical modeling and simulation using the Monte Carlo method, which showed an RMSE equal to ±3% and a MAPE of 10.15%. The solution based on the simulator provides a possibility to better understand the relationship between the parameters investigated through data visualization and apply this knowledge to train managers to make decisions that are more effective. The developed system has multi-disciplinary application: forecasting, education and decision making targeted to reduce food waste and improve public health and food management in schools.