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Italian tourism intermediaries: a social network analysis exploration

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  • Marco Valeri
  • Rodolfo Baggio

Abstract

The purpose of this paper is to analyse the application of Social Network Analysis (SNA) to the Italian tourism system. The research question is: do relationships among tourist enterprises affect the organizational asset of the Italian travel system? The research takes as unit of analysis the Italian travel agencies and tour operators system and represents quite a significant disclosure for organizational theses because it offers a different view over the structure and governance of a hospitality intermediaries’ network. SNA is helpful indetecting genuine proficiency and therefore in foreseeing possible losses determined by poor or inefficient configurations. Furthermore, it will help delineate new roles within the organizational networks and evaluate the relation between formal and informal organizational structures. This paper provides a structural analysis of the Italian travel agencies network and highlights its self-organization characteristics (typical of a complex system) that lead to the development of informal communities. The methods of network science proved useful and effective and, together with more traditional approaches and a qualitative knowledge of the system, can provide a deeper and more extensive understanding of the system.

Suggested Citation

  • Marco Valeri & Rodolfo Baggio, 2021. "Italian tourism intermediaries: a social network analysis exploration," Current Issues in Tourism, Taylor & Francis Journals, vol. 24(9), pages 1270-1283, May.
    • Handle: RePEc:taf:rcitxx:v:24:y:2021:i:9:p:1270-1283
    DOI: 10.1080/13683500.2020.1777950
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    Cited by:

    1. Howells, Jeremy, 2024. "Innovation intermediaries in a digital paradigm: A theoretical perspective," Technovation, Elsevier, vol. 129(C).
    2. Gutierrez, Eylla Laire M., 2023. "Re-examining the participation and empowerment nexus: Applications to community-based tourism," World Development Perspectives, Elsevier, vol. 31(C).
    3. Wang, Changlin, 2024. "Social media platform-oriented topic mining and information security analysis by big data and deep convolutional neural network," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    4. Crabolu, Gloria & Font, Xavier & Eker, Sibel, 2023. "Evaluating policy complexity with Causal Loop Diagrams," Annals of Tourism Research, Elsevier, vol. 100(C).
    5. Chenjun Zhang & Hailiang Huang & Changfeng Shi & Jingru Xu & Yung-ho Chiu, 2024. "Spatial pattern and driving factors for interprovincial water use in China: Based on SNA and LMDI," Energy & Environment, , vol. 35(4), pages 2198-2227, June.

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