Artikel

Efficiency evaluation of hotel chains: A Spanish case study

The tourism industry, in particular the hotel sector, is a highly competitive market. In this context, it is important that an hotel chain operates efficiently if it wants to improve or maintain its market position. The objective of this work is to compare the relative efficiency of hotel chains operating in Spain. To do this, we have designed a stochastic frontier model to measure revenue efficiency as a function of various different inputs such as total staff or number of rooms. Given that chains vary considerably in size, both inputs and outputs are normalized by an appropriate size measure. In contrast to most previous work, we account for heterogeneity in hotel chains by introducing relevant variables, such as the proportion of hotels in the chain with three stars or fewer, into the efficiency term of the stochastic frontier model. Our results suggest that in the Spanish case, in the period of the economic crisis, hotel chains increase overall revenue by investing in fewer, big hotels rather than more, small hotels. Furthermore, in terms of revenue efficiency, it appears better for hotel chains to invest in hotels of three or fewer stars than in higher star rated hotels. Finally, there is no clear evidence of a relationship between the size of a hotel chain and its efficiency.

Language
Englisch

Bibliographic citation
Journal: SERIEs - Journal of the Spanish Economic Association ; ISSN: 1869-4195 ; Volume: 10 ; Year: 2019 ; Issue: 2 ; Pages: 115-139

Classification
Wirtschaft
Bayesian Analysis: General
Estimation: General
Tourism Economics: General
Subject
Bayesian inference
Efficiency
Heterogeneity
Revenue function
Stochastic frontier analysis

Event
Geistige Schöpfung
(who)
Deng, Yaguo
Veiga, Helena
Wiper, Michael P.
Event
Veröffentlichung
(who)
Springer
(where)
Heidelberg
(when)
2019

DOI
doi:10.1007/s13209-019-0188-6
Last update
10.03.2025, 11:43 AM CET

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Object type

  • Artikel

Associated

  • Deng, Yaguo
  • Veiga, Helena
  • Wiper, Michael P.
  • Springer

Time of origin

  • 2019

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