Complexity traits and dynamics of tourism destinations |
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| Institution: | 1. Dipartimento di Economia, studi giuridici e aziendali, IULM University, Via Carlo Bo, 1, I - 20143 Milan, Italy;2. Master in Economics and Tourism, Bocconi University, via Röntgen, 1, 20136 Milan, Italy;1. Linnaeus University, Department of Organisation and Entrepreneurship, 391 82, Kalmar, Sweden;2. University of North Texas, Mayborn School of Journalism, 1155 Union Circle #311460, Denton, TX 76203, USA;3. University of Georgia, Warnell School of Forestry and Natural Resources, Natural Resources, Recreation and Tourism Program, Athens, GA 30602, USA;1. Tourism School, Central South University of Forestry and Technology, Changsha, Hunan, 410004, China;2. Business School, University of Aberdeen, Aberdeen, AB24 3FX, UK;1. Dep. Economia Aplicada I, Universidad de Sevilla, Avda. Ramon y Cajal 1, 41018 Sevilla, Spain;2. Dep. Empresa, Universidad San Pablo-CEU, Julián Romea 23, 28003 Madrid, Spain;1. Reader in Tourism, Hospitality & Events, Sunderland Business School, Department of Tourism Hospitality & Events, University of Sunderland, Sir Tom Cowie Campus, St. Peter''s Way, SR6 0DD, Sunderland, UK;2. Professor in Industrial and Spatial Economics with Emphasis on Tourism, Department of Business Administration, University of the Aegean, Chios, 82 132, Greece |
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| Abstract: | This paper is rooted in network science and contributes to filling two gaps, developing multiple case studies in order i) to measure the complex structure of tourism destination and ii) to explore its evolution over time, by mapping turning points. The findings put forward ten new analyses, allowing the research team to test two hypotheses: i) concerning the complex structure, the tendency of tourism destinations to remain far from the chaos threshold, ii) concerning turning points, the ability of different destinations to show also different evolution through time. The paper uses the Horizontal Visibility Graph Algorithm and applies it to a sample of ten tourism destinations in the second leading Italian tourism region per size: Trentino-Alto Adige. Findings confirm both hypotheses. Limitations and research implications are drawn. |
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| Keywords: | Complex systems Time series Horizontal visibility graph algorithm Turning points Multiple case studies |
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