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Developing a data envelopment analysis model for measuring and isolating the impact of contextual factors on hotel productivity

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  • Marianna Sigala
  • John Mylonakis

Abstract

Low productivity has been a major issue in the hospitality industry, but this situation is unlikely to improve without a general change in the way productivity is measured and managed. However, attempts to identify satisfactory productivity monitoring procedures as well as hotel productivity benchmark studies have been heavily criticised, while the use of management science techniques by hospitality professionals is scarce, if not unknown. This research aims to address the theoretical and practical urgency of research on hotel productivity by developing and illustrating the value of a Data Envelopment Analysis (DEA) methodology for productivity measurement and improvement. The paper also extends current DEA applications by presenting a DEA methodology based on the theory of performance frontiers that isolates the productivity impact of hotel contextual factors. The applicability and usefulness of the DEA methodology are demonstrated in a dataset of hotels in the UK, and managerial implications are discussed.

Suggested Citation

  • Marianna Sigala & John Mylonakis, 2005. "Developing a data envelopment analysis model for measuring and isolating the impact of contextual factors on hotel productivity," International Journal of Business Performance Management, Inderscience Enterprises Ltd, vol. 7(2), pages 174-190.
    • Handle: RePEc:ids:ijbpma:v:7:y:2005:i:2:p:174-190
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    Cited by:

    1. Fuentes, Ramón, 2011. "Efficiency of travel agencies: A case study of Alicante, Spain," Tourism Management, Elsevier, vol. 32(1), pages 75-87.
    2. Yin, Pengzhen & Chu, Junfei & Wu, Jie & Ding, Jingjing & Yang, Min & Wang, Yuhong, 2020. "A DEA-based two-stage network approach for hotel performance analysis: An internal cooperation perspective," Omega, Elsevier, vol. 93(C).

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