This paper proposes a procedure for analysing tourism productivity. The procedure is based on the Luenberger productivity indicator for estimating and decomposing productivity change into efficiency change and technological change. The authors expand the procedure and further decompose the process of technological change to study the sources of bias within it. Therefore, a clearer and more enlightening view emerges of the productivity of travel agencies. The Portuguese travel agency sector is used as an application. Some managerial implications are developed.
AndersonR.I.FishM.XiaY.MichelloF. (1999a), ‘Measuring efficiency in the hotel industry: A stochastic frontier approach’, International Journal of Hospitality Management, Vol 18, No 1, pp 45–57.
2.
AndersonR.I.LewisD.ParkerM.E. (1999b), ‘Another look at the efficiency of corporate travel management departments’, Journal of Travel Research, Vol 37, No 3, pp 267–272.
3.
AndersonR.I.FokR.ScottJ. (2000), ‘Hotel industry efficiency: An advanced linear programming examination’, American Business Review, Vol 18, No 1, pp 40–48.
4.
BarneyJ. (1991), ‘Firm resources and sustained competitive advantage’, Journal of Management, Vol 17, No 1, pp 99–120.
5.
BarrosC.P. (2004), ‘A stochastic cost frontier in the Portuguese hotel industry’, Tourism Economics, Vol 10, No 2, pp 177–192.
6.
BarrosC.P. (2005), ‘Measuring efficiency in the hotels: An illustrative example’, Annals of Tourism Research, Vol 32, No 2, pp 456–477.
7.
BarrosC.P. (2006), ‘Analyzing the rate of technical change in the Portuguese hotel industry’, Tourism Economics, Vol 12, No 3, pp 325–346.
8.
BarrosC.P.AlvesP. (2004), ‘Productivity in tourism industry’, International Advances in Economic Research, Vol 10, No 3, pp 215–225.
9.
BarrosC.P.DiekeP.U.C. (2007), ‘Analyzing the total productivity change in travel agencies’, Tourism Analysis, Vol 12, No 1–2, pp 27–37.
10.
BarrosC.P.MascarenhasM.J. (2005), ‘Technical and allocative efficiency in a chain of small hotels’, International Journal of Hospitality Management, Vol 24, No 3, pp 415–436.
11.
BarrosC.P.MatiasA. (2006), ‘Assessing the efficiency of travel agencies with a stochastic cost frontier: A Portuguese case study’, International Journal of Tourism Research, Vol 8, No 5, pp 367–379.
12.
BarrosC.P.BottiL.PeypochN. (2009), ‘A framework to analyse productivity changes: Theoretical aspects and applications to the Portuguese travel agencies sector’, Tourism Analysis, Vol 14, pp 325–335.
13.
BellR.A.MoreyR.C. (1995), ‘Increasing the efficiency of corporate travel management through macro-benchmarking’, Journal of Travel Research, Vol 33, No 3, pp 11–20.
14.
BriecW.PeypochN. (2007), ‘Biased technical change and parallel neutrality’, Journal of Economics, Vol 92, pp 281–292.
15.
BriecW.ChambersR.G.FäreR.PeypochN. (2006), ‘Biased technical change and parallel neutrality’, Journal of Economics, Vol 87, pp 285–305.
16.
BrownJ.R.RagsdaleC.T. (2002), ‘The competitive market efficiency of hotel brands: An application of data envelopment analysis’, Journal of Hospitality and Tourism Research, Vol 26, No 4, pp 332–360.
17.
BuhalisD.CostaC. (2006), Tourism Business Frontiers, Elsevier Butterworth-Heinemann, Oxford.
18.
ChambersR. (1996), ‘A new look at exact input, output, and productivity measurement’, Department of Agricultural and Resource Economics Working Paper 96-05, University of Maryland, College Park, MD.
19.
ChambersR.G.ChungY.FäreR. (1996), ‘Benefit and distance functions’, Journal of Economic Theory, Vol 70, No 2, pp 407–419.
20.
ChiangW.E.TsaiM.H.WangL.S.M. (2004), ‘A DEA evaluation of Taipei hotels’, Annals of Tourism Research, Vol 31, No 3, pp 712–715.
21.
FäreR.GrosskopfS. (1996), Intertemporal Production Frontiers: With Dynamic DEA, Kluwer Academic Publishers, Boston, MA.
22.
FäreR.GrosskopfS.LindgrenB.RoosP. (1989), ‘Productivity developments in Swedish hospitals: A Malmquist output index approach’, in. CharnesA.CooperV.W.LewinA.SeifordL., eds, Data Envelopment Analysis: Theory, Methodology and Applications, Kluwer Academic Publishers, Boston, MA.
23.
HwangS.N.ChangT.Y. (2003), ‘Using data envelopment analysis to measure hotel managerial efficiency change in Taiwan’, Tourism Management, Vol 24, No 4, pp 357–369.
24.
JohnsN.HowcroftB.DrakeL. (1997), ‘The use of data envelopment analysis to monitor hotel productivity’, Progress in Tourism and Hospitality Research, Vol 3, pp 119–127.
25.
KöksalC.D.AksuA.A. (2007), ‘Efficiency evaluation of A-group travel agencies with data envelopment analysis (DEA): A case study in the Antalya region, Turkey’, Tourism Management, Vol 28, No 3, pp 830–834.
26.
KumbhakarS.LovellC.A.K. (2000), Stochastic Frontier Analysis, Cambridge University Press, New York.
27.
MoreyR.C.DittmanD.A. (1995), ‘Evaluating a hotel GM's performance: A case study in benchmarking’, Cornell Hotel Restaurant and Administration Quarterly, Vol 36, No 5, pp 30–35.
28.
MoutinhoL. (2002), Strategic Management in Tourism, CAB International, Wallingford.
29.
PeypochN. (2007), ‘On measuring tourism productivity’, Asia Pacific Journal of Tourism Research, Vol 12, No 3, pp 237–244.
30.
PeypochN.SolonandrasanaB. (2006), ‘A note on technical efficiency in tourism industry’, Tourism Economics, Vol 12, No 4, pp 653–657.
31.
PeypochN.SolonandrasanaB. (2008), ‘Aggregate efficiency and productivity analysis in the tourism industry’, Tourism Economics, Vol 14, pp 45–56.
32.
ReynoldsD. (2003), ‘Hospitality-productivity assessment using data envelopment analysis’, Cornell Hotel and Restaurant Administration Quarterly, Vol 44, No 2, pp 130–137.
33.
ReynoldsD.ThompsonF.M. (2007), ‘Multinunit restaurant productivity assessment using three-phase data envelopment analysis’, International Journal of Hospitality Management, Vol 26, No 1, pp 20–32.
34.
RumeltR. (1991), ‘How much does industry matter?’, Strategic Management Journal, Vol 12, No 2, pp 167–185.
35.
ShephardR.W. (1970), Theory of Cost and Production Functions, Princeton University Press, Princeton, NJ.
36.
WernerfeltB. (1984), ‘A resource-based view of the firm’, Strategic Management Journal, Vol 5, No 2, pp 171–180.