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      Big data and analytics in hospitality and tourism: a systematic literature review

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      International Journal of Contemporary Hospitality Management
      Emerald

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          Abstract

          Purpose

          The purpose of this work is to survey the body of research revolving around big data (BD) and analytics in hospitality and tourism, by detecting macro topical areas, research streams and gaps and to develop an agenda for future research.

          Design/methodology/approach

          This research is based on a systematic literature review of academic papers indexed in the Scopus and Web of Science databases published up to 31 December 2020. The outputs were analyzed using bibliometric techniques, network analysis and topic modeling.

          Findings

          The number of scientific outputs in research with hospitality and tourism settings has been expanding over the period 2015–2020, with a substantial stability of the areas examined. The vast majority are published in academic journals where the main reference area is neither hospitality nor tourism. The body of research is rather fragmented and studies on relevant aspects, such as BD analytics capabilities, are virtually missing. Most of the outputs are empirical. Moreover, many of the articles collected relatively small quantities of records and, regardless of the time period considered, only a handful of articles mix a number of different techniques.

          Originality/value

          This work sheds new light on the emergence of a body of research at the intersection of hospitality and tourism management and data science. It enriches and complements extant literature reviews on BD and analytics, combining these two interconnected topics.

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          Most cited references169

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          Is Open Access

          Software survey: VOSviewer, a computer program for bibliometric mapping

          We present VOSviewer, a freely available computer program that we have developed for constructing and viewing bibliometric maps. Unlike most computer programs that are used for bibliometric mapping, VOSviewer pays special attention to the graphical representation of bibliometric maps. The functionality of VOSviewer is especially useful for displaying large bibliometric maps in an easy-to-interpret way. The paper consists of three parts. In the first part, an overview of VOSviewer’s functionality for displaying bibliometric maps is provided. In the second part, the technical implementation of specific parts of the program is discussed. Finally, in the third part, VOSviewer’s ability to handle large maps is demonstrated by using the program to construct and display a co-citation map of 5,000 major scientific journals.
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            Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review

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              Is Open Access

              From Louvain to Leiden: guaranteeing well-connected communities

              Community detection is often used to understand the structure of large and complex networks. One of the most popular algorithms for uncovering community structure is the so-called Louvain algorithm. We show that this algorithm has a major defect that largely went unnoticed until now: the Louvain algorithm may yield arbitrarily badly connected communities. In the worst case, communities may even be disconnected, especially when running the algorithm iteratively. In our experimental analysis, we observe that up to 25% of the communities are badly connected and up to 16% are disconnected. To address this problem, we introduce the Leiden algorithm. We prove that the Leiden algorithm yields communities that are guaranteed to be connected. In addition, we prove that, when the Leiden algorithm is applied iteratively, it converges to a partition in which all subsets of all communities are locally optimally assigned. Furthermore, by relying on a fast local move approach, the Leiden algorithm runs faster than the Louvain algorithm. We demonstrate the performance of the Leiden algorithm for several benchmark and real-world networks. We find that the Leiden algorithm is faster than the Louvain algorithm and uncovers better partitions, in addition to providing explicit guarantees.
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                Author and article information

                Journal
                International Journal of Contemporary Hospitality Management
                IJCHM
                Emerald
                0959-6119
                0959-6119
                November 12 2021
                January 03 2022
                November 12 2021
                January 03 2022
                : 34
                : 1
                : 231-278
                Article
                10.1108/IJCHM-03-2021-0301
                b4629d8a-7afe-4bcc-a3f4-f9ca75554e20
                © 2022

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