Tourism and Big Data in a post-COVID-19 world: the utopian and dystopian rhetoric
| Autor: | Maria João Vaz, Helena Machado |
|---|---|
| Rok vydání: | 2022 |
| Zdroj: | International Conference on Tourism Research. 15:546-552 |
| ISSN: | 2516-3612 2516-3604 |
| DOI: | 10.34190/ictr.15.1.127 |
| Popis: | The tourism sector has been significantly impacted by the COVID-19 pandemic, making it one of the most affected economic areas worldwide. Simultaneously, the pandemic created contexts for the expansion and consolidation of trends already experienced in the recent past, namely the increasing adaptation of tourism to the digital society. One prominent example is the use of techniques known as “Big Data”, which carry out a massive mining of data from different sources, in order to define “profiles” of tourist consumption. This paper aims to map the social and ethical controversies associated with the use of Big Data by addressing the “technological optimism” that tends to surround the use of these techniques in the tourism sector. Through a review of literature about Big Data in tourism, we conclude that the rhetoric surrounding the use of Big Data techniques is both utopian and dystopian. On the one hand, according to literature in disciplinary areas related to the development of technology, Big Data is considered an indispensable tool for improving competitiveness in the tourism sector and for helping to understand the tourist more effectively. On the other hand, however, social sciences tend to frame Big Data as an astute representation of Big Brother, challenging the protection of personal privacy in tourism consumption and highlighting the lack of awareness and legal regulations, as well as the possibility of decontextualisation and false correlations that may jeopardize the touristic experience. For this reason, it has become urgent to develop a critical reflection on the ethical challenges posed by the uses of Big Data in tourism and consider routes of an anticipatory governance of these technologies. |
| Databáze: | OpenAIRE |
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