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Heterogeneous Technical Efficiency of Hotels in Luanda, Angola

Author

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  • Carlos Pestana Barros

    (Instituto de Economia e Gestao, Technical University of Lisbon, Rua Miguel Lupi 20, 1249-078 Lisbon, Portugal)

  • Peter U.C. Dieke

    (School of Recreation, Health and Tourism, College of Education and Human Development, George Mason University, 10900 University Blvd, Manassas, VA 20110, USA)

  • Carlos M. Santos

    (University of Azores, Rua da Mãe de Deus 58, 9501-801 Ponta Delgada, Azores, Portugal)

Abstract

This paper uses a random frontier model to analyse technical efficiency in a data set of hotels in Luanda, the capital city of Angola, for 1990–2007. The hotels are ranked according to their technical efficiency, disentangling homogeneous and heterogeneous variables. This methodology attempts to account for observed and unobserved heterogeneity across hotels. The study rests on the premise that hotels in Luanda have an established role in the business market and emerging significance in the tourism market, broadly defined. Based on the analysis, the authors conclude that those hotels adopting a more strategic approach are better, and thus more efficient, than those that lack vision. They then point to the wider implications of the discussion.

Suggested Citation

  • Carlos Pestana Barros & Peter U.C. Dieke & Carlos M. Santos, 2010. "Heterogeneous Technical Efficiency of Hotels in Luanda, Angola," Tourism Economics, , vol. 16(1), pages 137-151, March.
    • Handle: RePEc:sae:toueco:v:16:y:2010:i:1:p:137-151
    DOI: 10.5367/000000010790872178
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    References listed on IDEAS

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    Cited by:

    1. Yaguo Deng & Helena Veiga & Michael P. Wiper, 2019. "Efficiency evaluation of hotel chains: a Spanish case study," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(2), pages 115-139, June.
    2. Assaf, A. George & Tsionas, Efthymios G., 2015. "Incorporating destination quality into the measurement of tourism performance: A Bayesian approach," Tourism Management, Elsevier, vol. 49(C), pages 58-71.
    3. Kristiaan Kerstens & Jafar Sadeghi & Ignace Van de Woestyne & Linjia Zhang, 2022. "Malmquist productivity indices and plant capacity utilisation: new proposals and empirical application," Annals of Operations Research, Springer, vol. 315(1), pages 221-250, August.
    4. Della Corte, Valentina & Aria, Massimo, 2016. "Coopetition and sustainable competitive advantage. The case of tourist destinations," Tourism Management, Elsevier, vol. 54(C), pages 524-540.
    5. Oliveira, Ricardo & Pedro, Maria Isabel & Marques, Rui Cunha, 2013. "Efficiency and its determinants in Portuguese hotels in the Algarve," Tourism Management, Elsevier, vol. 36(C), pages 641-649.
    6. Assaf, A. George & Tsionas, Mike G., 2019. "A review of research into performance modeling in tourism research - Launching the Annals of Tourism Research curated collection on performance modeling in tourism research," Annals of Tourism Research, Elsevier, vol. 76(C), pages 266-277.
    7. Hongwei Liu & Henry Tsai, 2018. "Total factor productivity growth and regional competitive analysis of China’s star-rated hotels," Tourism Economics, , vol. 24(6), pages 625-644, September.
    8. Antonio Arbelo & Pilar Pérez-Gómez & Marta Arbelo-Pérez, 2017. "Cost efficiency and its determinants in the hotel industry," Tourism Economics, , vol. 23(5), pages 1056-1068, August.
    9. Nicolau, Juan L., 2011. "Differentiated price loss aversion in destination choice: The effect of tourists’ cultural interest," Tourism Management, Elsevier, vol. 32(5), pages 1186-1195.
    10. Arbelo-Pérez, Marta & Arbelo, Antonio & Pérez-Gómez, Pilar, 2017. "Impact of quality on estimations of hotel efficiency," Tourism Management, Elsevier, vol. 61(C), pages 200-208.

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