Social Network Analysis and Qualitative Interviews for Assessing Geographic Characteristics of Tourism Business Networks.

• Published in: PLOS ONE
• Main Authors: Ilan Kelman, Tobias Luthe, Romano Wyss, Silje H Tørnblad, Yvette Evers, Marina Martin Curran, Richard J Williams, Eric L Berlow
• Format: Article in Journal/Newspaper
• Language: English
• Published: Public Library of Science (PLoS) 2016
• Subjects: Medicine; R; Science; Q; Arctic; Longyearbyen; Svalbard; Arctic Archipelago
• Online Access: https://doi.org/10.1371/journal.pone.0156028; https://doaj.org/article/6d99bd5e9725407fa15ee8b0576712e8

This study integrates quantitative social network analysis (SNA) and qualitative interviews for understanding tourism business links in isolated communities through analysing spatial characteristics. Two case studies are used, the Surselva-Gotthard region in the Swiss Alps and Longyearbyen in the Arctic archipelago of Svalbard, to test the spatial characteristics of physical proximity, isolation, and smallness for understanding tourism business links. In the larger Surselva-Gotthard region, we found a strong relationship between geographic separation of the three communities on compartmentalization of the collaboration network. A small set of businesses played a central role in steering collaborative decisions for this community, while a group of structurally 'peripheral' actors were less influential. By contrast, the business community in Svalbard showed compartmentalization that was independent of geographic distance between actors. Within towns of similar size and governance scale, Svalbard is more compartmentalized, and those compartments are not driven by geographic separation of the collaboration clusters. This compartmentalization in Svalbard was reflected in a lower density of formal business collaboration ties compared to the communities of the Alps. We infer that the difference is due to Svalbard having higher cultural diversity and population turnover than the Alps communities. We propose that integrating quantitative network analysis from simple surveys with qualitative interviews targeted from the network results is an efficient general approach to identify regionally specific constraints and opportunities for effective governance.