1. The article focuses on the complex structure of tourist destinations, which can be described as a network system with local participants and organizations as nodes and their relationships as links.
2. The study uses the horizontal visibility graph algorithm to analyze ten tourist destinations in Trentino-Alto Adige, Italy, and confirms two hypotheses: that tourist destinations tend to avoid chaotic behavior and that their ability to change over time varies.
3. The article emphasizes the relevance of nonlinear models for analyzing tourist destinations and highlights the importance of social capital in building and updating destination competitiveness.
The article "Complexity features and dynamics of tourist destinations" focuses on the complex structure of tourist destinations and their evolution over time. The authors use the horizontal visibility graph algorithm to analyze ten nighttime time series from tourist destinations in Trentino-Alto Adige, Italy. The investigation reveals that these destinations exhibit complex features but do not display chaotic behavior. The analysis of their turning points also confirms that different destinations have different evolutions over time.
The article is rooted in network science and aims to fill two gaps: measuring the complexity structure of tourist destinations and exploring their evolution over time by plotting turning points. The investigation proposes ten new analyses that allow researchers to test two hypotheses: (i) tourist destinations tend to move away from the chaos threshold regarding complex structures, and (ii) different destinations show different abilities to evolve over time regarding turning points.
The article provides a comprehensive overview of the complexity structure of tourist destinations, emphasizing the importance of both nodes and links in creating tourism products. However, it does not consider potential biases or sources of partiality in its analysis. For example, the study only focuses on one region in Italy, which may limit its generalizability to other regions or countries.
Moreover, while the authors acknowledge the importance of social capital as a source for relationships between local participants, they do not explore how power dynamics may influence these relationships. Additionally, they do not address potential risks associated with tourism development or how these risks may affect local communities.
Overall, while the article provides valuable insights into the complexity structure and evolution of tourist destinations, it could benefit from a more critical examination of potential biases and limitations in its analysis.