Tourism and Big Data at brazilian scientific research - Silva, Natalya Reis da; Koga, Erika Sayuri (Brazilian Journal of Production Engineering, 2022)
The increase in storage capacity and computer processing speed, combined with fast internet connections, development of algorithms and availability of large volumes of data on the network are factors that drive the era of big data. Considering the growth and diversity of possibilities for the use of big data for tourism research carried out worldwide, this investigation proposes to carry out a systematic review on the use of big data in tourism research, conducted by Brazilian researchers and published in national and international journals. After filtering 76 articles extracted from the Web of Science, Scopus and Tourism articles databases, this review analyzed 19 articles that met the criteria established in the protocol. It was found that studies on the use of big data in tourism are recent, starting in 2000, with a peak of studies published in 2019; carried out by a variety of researchers (57), allocated in different Research/Education Institutions (16), distributed across Brazil, Portugal and Spain, who published in different national and international scientific journals (15). The analyzed research contributes to several fields of tourism knowledge, according to Jafari's Interdisciplinary Model, especially for business management, tourism planning and development and tourist motivation, demonstrating a research niche that is still expanding and with few highlights. The results also showed that 47.4% of the articles have a qualitative-quantitative methodological approach, 63.2% carried out research whose data sources were generated by users and that the universities with the largest number of publications are in the region northeast of Brazil and are federal. Furthermore, this study can contribute to the recognition of the scientific production of Brazilians who have developed research using big data and foster the exchange of techniques, software, collection processes, analyzes and obtaining results that strengthen studies in tourism and overcome challenges both procedural and conceptual, as well as theoretical and methodological.
Keywords: Big data; Tourism; Interdisciplinary model; Systematic Review of Literature