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Benchmarking tourist hotels performance for strategies development

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  • Tien-Chin Wang
  • Shu-Li Huang

Abstract

The marked decrease in the number of mainland tourists visiting Taiwan may turn from a temporary phenomenon to a normalized one because of the potential harm it represents to the Taiwan tourism industry. The purpose of this study is to use hierarchical cluster analysis combined with entropy to derive clustering and to identify appropriate performers by measuring operational performance levels. These clusters may serve as the benchmarks for under-performing tourist hotels (classified into five groups according to the numbers of employees) to improve in response to the reduced number of Chinese tourists coming to Taiwan. This study provides a different insight into the tourist hotels industry in benchmarking comparable to previous research groups. The measurement of five criteria has been both statistically different and significant for the clusters in order to support a view that the clusters contain hotels with a similar numbers of employees while maintaining distinct performance profiles and developing strategies for improvement.

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  • Tien-Chin Wang & Shu-Li Huang, 2021. "Benchmarking tourist hotels performance for strategies development," Current Issues in Tourism, Taylor & Francis Journals, vol. 24(3), pages 424-441, February.
    • Handle: RePEc:taf:rcitxx:v:24:y:2021:i:3:p:424-441
    DOI: 10.1080/13683500.2020.1718065
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    Cited by:

    1. Chin‐wei Huang & Hsiao‐Yin Chen, 2023. "Using nonradial metafrontier data envelopment analysis to evaluate the metatechnology and metafactor ratios for the Taiwanese hotel industry," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(4), pages 1904-1919, June.

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