Digital transformation and tourist experience co-design: Big social data for planning cultural tourism

Maria Teresa Cuomo, Debora Tortora, Pantea Foroudi, Alex Giordano, Giuseppe Festa and Gerardino Metallo

Technological Forecasting and Social Change, 2021, vol. 162, issue C

Abstract: Digital transformation has completely changed the demand/offering interaction in the travel industry, as well as largely affecting the customer journey. In this direction, “big social data” and user-generated content have become key sources of well-timed and rich knowledge supporting data driven decision approaches addressed the managing of complex relationships. Based on this theoretical framework, the paper suggests how to apply “big social data” in the tourist experience co-design, providing an increased value for the visitors and a better decision making approach for managers. In this respect, the field analysis concentrated specifically on user-generated content regarding the Pompeii Archaeological Site (P.A.S.), to trace valuable insights for the tourist experience. Based on double stage of research – netnographic analysis and a supplementary online survey – the study aimed to detect: (a) tourist perception on the P.A.S.; (b) random chat on the part of internet users (tourists and other browsers, not necessarily visitors) on the topic of the P.A.S.; (c) the main characteristics of the P.A.S. that attract internet user attention; (d) the main topics debated by influencers/opinion leaders managing online discussions on the P.A.S. managerial and theoretical implications were investigated highlighting the main limitations of the study as well.

Keywords: Digital transformation; Tourist experience; Big social data; Social change; Cultural tourism (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:162:y:2021:i:c:s0040162520311719

DOI: 10.1016/j.techfore.2020.120345

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