A systemic and cybernetic perspective on causality, big data and social networks in tourism

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/88587
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Title: A systemic and cybernetic perspective on causality, big data and social networks in tourism
Authors: Lloret-Climent, Miguel | Montoyo, Andres | Gutiérrez, Yoan | Muñoz, Rafael | Alonso-Stenberg, Kristian
Research Group/s: Sistémica, Cibernética y Optimización (SCO) | Acústica Aplicada | Procesamiento del Lenguaje y Sistemas de Información (GPLSI)
Center, Department or Service: Universidad de Alicante. Departamento de Matemática Aplicada | Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos
Keywords: Big data | Attractor | Invariant set | Orbits | Tourist variables
Knowledge Area: Matemática Aplicada | Lenguajes y Sistemas Informáticos
Issue Date: 2019
Publisher: Emerald
Citation: Kybernetes. 2019, 48(2): 287-297. doi:10.1108/K-02-2018-0084
Abstract: Purpose – The purpose of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on an algorithm and applying an interpretation of chaos theory developed in the context of General Systems Theory and Big Data. Design/methodology/approach – Tourism is one of the most digitalized sectors of the economy, and social networks are an important source of data for information gathering. However, the high levels of redundant information on the Web and the appearance of contradictory opinions and facts produce undesirable effects that must be cross-checked against real data. This paper sets out the causal relationships associated with tourist flows to enable the formulation of appropriate strategies. Findings – The results can be applied to numerous cases, for example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups, as well as analysing tourist behaviour in terms of the most relevant variables. Originality/value – The technique presented here breaks with the usual treatment of the tourism topics. Unlike statistical analyses that merely provide information on current data, the authors use orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.
Sponsor: This research has been is partially funded by the Office of the Vice President of Research and Knowledge Transfer, University of Alicante, supported this paper under project (GRE15-13). This research has been is partially funded by the University of Alicante, Generalitat Valenciana, Spanish Government (“Ministerio de Economía y Competitividad”) through the projects REDES (TIN2015-65136- C2-2-R) and “Plataforma inteligente para recuperaci on, análisis y representación de la información generada por usuarios en Internet” (GRE16-01).
URI: http://hdl.handle.net/10045/88587
ISSN: 0368-492X (Print) | 1758-7883 (Online)
DOI: 10.1108/K-02-2018-0084
Language: eng
Type: info:eu-repo/semantics/article
Rights: © Emerald Publishing Limited
Peer Review: si
Publisher version: https://doi.org/10.1108/K-02-2018-0084
Appears in Collections:INV - Acústica Aplicada - Artículos de Revistas
INV - GPLSI - Artículos de Revistas
INV - SCO - Artículos de Revistas

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