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Hotel Performance and Research Streams: A Network Cluster Analysis

Sainaghi, Ruggero, Baggio, Rodolfo, Phillips, Paul A., Mauri, Aurelio G. (2018) Hotel Performance and Research Streams: A Network Cluster Analysis. International Journal of Contemporary Hospitality Management, 30 (8). ISSN 0959-6119. (doi:10.1108/IJCHM-05-2017-0260)

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Abstract

Purpose: This article provides a review of hotel performance within the hospitality and tourism research domain. We use network analysis to examine two research questions. The first relates to ascertaining general trends within the hotel performance literature, and the second focuses on identifying the salient streams and sub-topics. Methodology: Articles were selected according to three criteria: keywords, journals, and year of publication. The analysis embraces 20 years (1996-2015). These choices assure a wide coverage of the literature. Using these three criteria, the sample includes 1,155 papers. For the analysis, we created a network of papers designated as nodes, and the citations among the papers as links. A network approach recognizes the internal structure of the network by identifying groups of nodes (papers) that are more densely connected between themselves than to other nodes within the network (modules, clusters or communities). Findings: We found 761 papers that were “connected” studies within the network. By contrast, 34% of sample (394 papers) consists of “unconnected” studies. Excluding outliers, the net sample was 734 articles. We identify 14 clusters, which we break down into several sub-topics. We conclude by providing some conclusions regarding trends and future research directions. With regards to salient topics, cross-citation and network analysis provide a detailed picture of where the literature comes from and where it currently stands. Conclusions are articulated at the theoretical and empirical levels. Originality: Compared to previous hotel performance reviews, the approach followed by this study enables the discovery of an analytical research map, which is able to identify both clusters and sub-topics populating each segment. Researchers are able to position their work and identify issues that are in growth and decline.

Item Type: Article
DOI/Identification number: 10.1108/IJCHM-05-2017-0260
Uncontrolled keywords: Hotel; Performance; Network cluster analysis; Cross-citation analysis
Subjects: H Social Sciences > HF Commerce > HF5351 Business
Divisions: Faculties > Social Sciences > Kent Business School > International Business and Strategy
Depositing User: Paul Phillips
Date Deposited: 10 Apr 2018 11:15 UTC
Last Modified: 15 Jul 2019 09:22 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/66679 (The current URI for this page, for reference purposes)
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