This study was conducted to analyse the influence of technological differences on hotel efficiency in the Canary Islands (Spain), with particular regard to the heterogeneity observed in hotel ownership and size. A metafrontier approach, based on non-parametric deterministic efficiency methods (data envelopment analysis and free-disposal hull) and robust non-parametric estimators (order-α), is used. This empirical analysis considered a panel data sample selection model of Canary Islands hotels for the period 2002–2015. The results obtained show that the frontiers against which the hotels are compared (metafrontier or group) and the consideration or otherwise of outliers are factors of crucial importance. We find that efficiency depends on hotel size (large hotels are more efficient than small ones), but not on the type of ownership. The results also show that the impact of the global financial crisis on the average technical efficiency of these hotels was slight or non-existent. Finally, the technological gap narrowed over time, especially in large hotels and those with no majority shareholder.
AragonYDaouiaAThomas-AgnanC (2005) Nonparametric frontier estimation: a conditional quantile based approach. Econometric Theory21: 358–389.
4.
ArbeloAPérez-GómezPArbelo-PérezM (2017a) Cost efficiency and its determinants in the hotel industry. Tourism Economics23(5): 1056–1068.
5.
ArbeloAPérez-GómezPGonzález-DávilaE, et al. (2017b) Cost and profit efficiencies in the Spanish hotel industry. Journal of Hospitality & Tourism Research41: 985–1006.
6.
ArbeloAArbelo-PérezMPérez-GómezP (2020) Technological heterogeneity and hotel efficiency: a Bayesian approach. Cornell Hospitality Quarterly61(2): 170–182.
7.
ArbeloAArbelo-PérezMPérez-GómezP (2021) Heterogeneity of resources and performance in the hotel industry. Journal of Hospitality & Tourism Research, 45(1): 68–89.
8.
AshrafiASeowHVLeeLS, et al. (2013) The efficiency of the hotel industry in Singapore. Tourism Management37(1): 31–34.
9.
AssafABarrosCPJosiassenA (2010) Hotel efficiency: a bootstrapped metafrontier approach. International Journal of Hospitality Management29(3): 468–475.
10.
AssafAG (2012) Benchmarking the Asia Pacic tourism industry: a Bayesian combination of DEA and stochastic frontier. Tourism Management33(5): 1122–1127.
11.
AssafAGBarrosCP (2013) A global benchmarking of the hotel industry. Tourism Economics19(4): 811–821.
12.
AssafAGTsionasM (2018) Measuring hotel performance: toward more rigorous evidence in both scope and methods. Tourism Management69: 69–87.
13.
BankerRDCharnesACooperWW, et al. (1989) An introduction to data envelopment analysis with some of its models and their uses. In: ChanJLPattonJM (eds) Research in Governmental and Nonprofit Accounting. Connecticut, CT: Jai Press125–163.
14.
BarneyJ (1991) Firm resources and sustained competitive advantage. Journal of Management17: 99–120.
15.
BarrosCP (2004) A stochastic cost frontier in the Portuguese hotel industry. Tourism Economics10: 177–192.
16.
BarrosCP (2005a) Measuring efficiency in the hotels: an illustrative example. Annals of Tourism Research32: 456–477.
17.
BarrosCP (2005b) Evaluating the efficiency of a small hotel chain with a Malmquist productivity index. International Journal of Tourism Research7: 173–184.
18.
BarrosCP (2006) Analysing the rate of technical change in the Portuguese hotel industry. Tourism Economics12: 325–346.
19.
BarrosCPAlvesFP (2004) Productivity in the tourism industry. International Advances in Economic Research10: 215–225.
20.
BarrosCPSantosC (2006) The measurement of efficiency in Portuguese hotels using data envelopment analysis. The Journal of Head Trauma Rehabilitation30: 378–400.
21.
BarrosCMatiasA (2007) Efficiency in a chain of small hotels with a stochastic production frontier model. In: Álvaro MatiasPNNetoP (eds) Advances in Modern Tourism Research. Heidelberg (Germany): Physica-Verlag, A Springer Company, 107–132.
22.
BarrosCPDiekeP (2008) Technical efficiency of African hotels. International Journal of Hospitality Management27: 438–447.
23.
BarrosCPDiekePSantosCA (2010) Heterogeneous technical efficiency of hotels in Luanda, Angola. Tourism Economics16(1): 137–151.
24.
BarrosCBottiLPeypochN, et al. (2011) Managerial efficiency and hospitality industry: the Portuguese case. Applied Economics43(22): 2895–2905.
25.
BatteseGCoelliT (1992) Frontier production functions, technical efficiency and panel data: with application to paddy farmers in India. Journal of Productivity Analysis3(1): 153–169.
26.
BatteseGCoelliT (1995) A model for technical inefficiency effects in a stochastic frontier production function for panel data. Environmental Entomology20: 325–332.
27.
BatteseGRaoD (2002) Technology gap, efficiency, and a stochastic metafrontier function. International Journal of Business and Economics1(2): 87–93.
28.
BatteseGRaoDO’DonnellC (2004) A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies. Journal of Productivity Analysis21(1): 91–103.
29.
BerniniCGuizzardiA (2015) Improving performance measurement and benchmarking in the accommodation sector. International Journal of Contemporary Hospitality Management27: 980–1002.
30.
BottiLBriecWCliquetG (2009) Plural forms versus franchise and company-owned systems: a DEA approach of hotel chain performance. Omega37: 566–578.
31.
BrownJRRagsdaleCT (2002) The competitive market efficiency of hotel brands: an application of data envelopment analysis. Journal of Hospitality & Tourism Research26: 332–360.
32.
CazalsCFlorensJPSimarL (2002) Nonparametric frontier estimation: A robust approach. Journal of Econometrics106: 1–25.
33.
ChenCF (2007) Applying the stochastic frontier approach to measure hotel managerial efficiency in Taiwan. Tourism Management28(3): 696–702.
34.
ChiangWTsaiHWangL (2004) A DEA evaluation of Taipei hotels. Annals of Tourism Research31: 712–715.
35.
ChoT-YWangT-Y (2018) Estimations of cost metafrontier Malmquist productivity index: using international tourism hotels in Taiwan as an example. Environmental Entomology55: 1661–1694.
CoelliTJPrasadaRBatteseGE (1998) An Introduction to Efficiency and Productivity Analysis. Boston: Kluwer.
38.
CooperWWSeifordLMToneK (2007) Data Envelopment Analysis: A Com- Prehensive Text with Models, Applications, References and DEA-Solver Software. 2nd edition. New York, NY: Springer.
39.
CorderoJMTzeremesNG (2017) Evaluating hotel productivity growth in Balearic and Canary Islands. Tourism Economics23(5): 1146–1154.
40.
CorderoJMTzeremesNG (2018) Financial crisis and hotels’ labour productivity growth: evidence from Spanish islands. Applied Economic Letters25(19): 1376–1382.
41.
CruzMMP (2017) The operational efficiency and sustainability of selected deluxe class hotels in metro Manila. European Journal of Business Management27(9): 135–149.
42.
DaouiaASimarL (2007) Nonparametric efficiency analysis: a multivariate conditional quantile approach. Journal of Econometrics140(2): 375–400.
43.
DaraioCSimarL (2007) Advanced Robust and Nonparametric Methods in Efficiency Analysis: Methodology and Applications. New York: Springer.
44.
De WitteKMarquesR (2009) Capturing the environment, a metafrontier approach to the drinking water sector. International Transactions in Operational Research16(2): 257–271.
45.
DengYVeigaHWiperMP (2019) Efficiency evaluation of hotel chains: a Spanish case study. SERIEs10: 115–139.
46.
DengZGaoYLiangB, et al. (2020) Efficiency evaluation of hotel operations in mainland China based on the superefficiency SBM model. Tourism Economics26(2): 276–298.
47.
DeprinsDSimarLTulkensH (1984) Measuring labor-efficiency in post offices. In: MarchandMPestieauPTulkensH (eds) The Performance of Public Enterprises: Concepts and Measurement. Amsterdam: North-Holland, 243–267.
48.
DevesaMJPeñalverLF (2013) Research note: size, efficiency and productivity in the Spanish hotel industry–independent properties versus chain-affiliated hotels. Tourism Economics19(4): 801–809.
49.
DysonRGAllenRCamanhoA, et al. (2001) Pitfalls and protocols in DEA. European Journal of Operational Research132(2): 245–259.
50.
FernándezMABecerraR (2015) An analysis of Spanish hotel efficiency. Cornell Hospitality Quarterly56(3): 248–257.
51.
FilippiniMGreeneW (2016) Persistent and transient productive inefficiency: a maximum simulated likelihood approach. Journal of Productivity Analysis45(2): 187–196.
52.
GreeneW (2005) Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Journal of Econometrics126: 269–303.
53.
HalkosGETzeremesNG (2007) Productivity efficiency and firm size: an empirical analysis of foreign owned companies. International Business Review16: 713–731.
54.
HomburgC (2001) Using data envelopment analysis to benchmark activities. International Journal of Production Economics73(1): 51–58.
55.
HwangSNChangTN (2003) Using data envelopment analysis to measure hotel managerial efficiency change in Taiwan. Tourism Management24: 357–369.
56.
HuangCJHuangT-HLiuN-H (2014) A new approach to estimating the metafrontier production function based on a stochastic frontier framework. Journal of Productivity Analysis42: 241–254.
57.
HuangC-WTingC-TLinC-H, et al. (2013) Measuring non-convex metafrontier efficiency in international tourist hotels. The Journal of the Operational Research Society64(2): 250–259.
58.
Inchausti-SintesFVoltes-DortaA (2020) The economic impact of the tourism moratoria in the Canary Islands 2003–2017. Journal of Sustainable Tourism28(3): 394–413.
59.
JorgeJSuárezC (2014) Productivity, efficiency and its determinant factors in hotels. The Service Industries Journal34(4): 354–372.
60.
KimS (2011) Factor determinants of total factor productivity growth in the Malaysian hotel industry: a stochastic frontier approach. Cornell Hospitality Quarterly52(1): 35–47.
61.
KrügerJJ (2012) A Monte Carlo study of old and new frontier methods for efficiency measurement. European Journal of Operational Research222: 137–148.
62.
LovellCAKRouseAPB (2003) Equivalent standard DEA models to provide super-efficiency scores. Journal of the Operational Research Society54: 101–108.
63.
Moreno GilS (2003) Tourism development in the Canary Islands. Annals of Tourism Research30(3): 744–747.
64.
MoreyRDittmanD (1995) Evaluating a hotel GM’s performance: A case study in benchmarking. Cornel Hotel Restaurant and Administration Quarterly36(5): 30–35.
65.
O’DonnellCJRaoDSPBatteseGE (2008) Metafrontier frameworks for the study of firm‐level efficiencies and technology ratios. Environmental Entomology34: 231‐255.
66.
Parte-EstebanLAlberca-OliverP (2015) Determinants of technical efficiency in the Spanish hotel industry: regional and corporate performance factors. Current Issues in Tourism18(4): 391–411.
67.
Pérez-RodríguezJVAcosta-GonzálezE (2007) Cost efficiency of the lodging industry in the tourist destination of Gran Canaria (Spain). Tourism Management4(4): 993–1005.
68.
Pérez-RodríguezJVAcosta-GonzálezE (2021) Transient and Persistent Cost Efficiency in Hotels in the Canary Islands. Journal of Hospitality & Tourism Resarch. DOI: 10.1177/10963480211032254.
69.
PeterafMA (1993) The cornerstones of competitive advantage: a resource-based view. Strategic Management Journal14(3): 179–191.
70.
RaabRLichtyR (2002) Identifying sub-areas that comprise a greater metropolitan area: the criterion of country relative efficiency. Journal of Regional Science42(3): 579–594.
71.
RaoDSPO’DonnellCJBatteseGE (2003). Metafrontier Functions for the Study of Inter‐regional Productivity Differences. Brisbane, Australia: School of Economics, University of Queensland. Available at: https://economics.uq.edu.au/files/5364/WP012003.pdf (accessed 16 February 2020)
72.
ReynoldsDThompsonG (2007) Multiunit restaurant productivity assessment using three phase data envelopment analysis. International Journal of Hospitality Management26: 20–32.
73.
Santana-JiménezYHernándezJM (2011) Estimating the effect of overcrowding on tourist attraction: the case of Canary Islands. Tourism Management32: 415–425.
74.
Sellers-RubioRCasado-DiazAB (2018) Analyzing hotel efficiency from a regional perspective: the role of environmental determinants. International Journal of Hospitality Management75: 75–85.
75.
ShangJ-KWangF-CHungW-T (2010) A stochastic DEA study of hotel efficiency. Applied Economics42(19): 2505–2518.
76.
ShangJKHungWTLoCF, et al. (2008) E-commerce and hotel performance: three-stage DEA analysis. The Service Industries Journal28: 529–540.
77.
SimarL (1996) Aspects of statistical analysis in DEA-type frontier models. Journal of Productivity Analysis7: 177–186.
78.
TauchmannH (2012) Partial frontier efficiency analysis. The Stata Journal12(3): 461–478.
79.
TulkensH (1993) On FDH analysis: some methodological issues and applications to retail banking, courts and urban transit. Journal of Productivity Analysis4(1): 183–210.
80.
WangFHungWTShangJK (2006) Measuring the cost efficiency of international tourist hotels in Taiwan. Tourism Economics12: 65–85.
81.
TsionasEG (2002) Stochastic frontier models with random coefficients. Journal of Applied Econometrics17(2): 127–147.
82.
TzeremesNG (2019) Hotel productivity: A robust Luenberger productivity indicator. Tourism Economics25(6): 987–996.
83.
TzeremesNG (2020) Robust Malmquist productivity measurement: evidence from Spanish hotel industry during the Great Recession. International Journal of Productivity and Performance Management. Epub ahead of print. DOI: 10.1108/ijppm-01-2019-0037
84.
TzeremesPTzeremesNG (2021) Productivity in the hotel industry: an order-α Malmquist productivity indicator. Journal of Hospitality & Tourism Research45(1): 133–150.
85.
WernerfeltB (1984) A resource-based view of the firm. Strategic Management Journal5(2): 171–180.
86.
YuM-MChenL-H (2016) Productivity growth of Taiwanese international tourist hotels in a metafrontier framework. Cornell Hospitality Quarterly57(1): 38–50.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
