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Mining big data in tourism

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Abstract

Knowledge discovery from various sources of information based on different data types for decision and accurate prediction can be rather complex and costly without a statistical information system. In Big Data Era, Statistical Tourism Observatory needs to be revised. This paper introduces a conceptual model of Digital Tourism System (DTS) where various types of standard and non-standard data can be processed by actors and spectators in tourism sector. Particularly, big data can be very useful and the figure of Data Scientist within the tourism industry becomes prominent. DTS allows to emphasize four knowledge areas of interest for different purposes, specifically, destination management, research and innovation, market analysis, labor market, in order to improve tourism management and research. Key steps of the knowledge discovery pyramid are exploited to provide an added value in decision-making on the basis of statistical learning methods. Two examples are shown, mining online textual and photo data respectively.

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Authors and Affiliations

  1. Department of Industrial Engineering, University of Naples Federico II, Naples, Italy

    Carmela Iorio, Giuseppe Pandolfo & Roberta Siciliano

  2. Department of Economics and Statistics, University of Naples Federico II, Naples, Italy

    Antonio D’Ambrosio

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  1. Carmela Iorio
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  2. Giuseppe Pandolfo
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  3. Antonio D’Ambrosio
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  4. Roberta Siciliano
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Correspondence to Roberta Siciliano.

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Iorio, C., Pandolfo, G., D’Ambrosio, A. et al. Mining big data in tourism. Qual Quant 54, 1655–1669 (2020). https://doi.org/10.1007/s11135-019-00927-0

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