Title

Tour Guides’ Communication Ecosystems: An Inferential Social Network Analysis Approach

Keywords

Communication ecosystems; Exponential random graph models (ERGM); Social network analysis; Tour guides; World Federation of Tourist Guide Associations

Abstract

Successful performance by tour guides depends highly on their networking activities and interpersonal skills. Membership in related associations can provide opportunities for establishing and expanding a supportive network in the tour guiding profession. This study explores communication ecosystems used among the members of the largest professional tour guides organization, the World Federation of Tourist Guide Associations (WFTGA). Using the data collected from the 17th WFTGA convention in Tehran, Iran, we investigated five types of tour guides’ communications ecosystems (i.e. in-person, online-call, text-message, e-mail, and social networks) and compared them to tour guides’ networks of colleagues (i.e., the network that shows how people know one another and how they are linked). Moreover, we included the complementary no-contact network to enhance the internal validity of the study. Using exponential random graph modeling, all seven networks have been modeled using demographic characteristics such as age, gender, education, marital status, and tenure along with the history of participation in previous WFTGA conventions and WFTGA membership status. The analyses of virtual/digital (i.e., online-call, text-message, e-mail, and online social networks) and natural/traditional (i.e., in-person) communication ecosystems showed interesting similarities and differences among the seven networks, providing valuable insights for practitioners as well as academicians. Findings revealed the formation of networks based on homophily as well as heterophily effects is a function of types of communication ecosystem.

Publication Date

12-1-2018

Publication Title

Information Technology and Tourism

Volume

20

Issue

1-4

Number of Pages

103-130

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/s40558-018-0114-y

Socpus ID

85058825105 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85058825105

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