This paper analyses the technical efficiency of a Portuguese state-owned hotel chain, Pousadas de Portugal, in order to investigate the chain's performance. A stochastic cost frontier model is used to generate hotel efficiency scores, assuming that efficiency is time-varying. The author investigates the efficiency and finds that the results are at best mixed, since the efficient scores are low and not time-varying. He therefore proposes an alteration of management procedures to enable an increase in efficiency, based on a governance-environment framework.
AignerD.J.LovellC.A.K.SchmidtP. (1977), ‘Formulation and estimation of stochastic frontier production function models’, Journal of Econometrics, Vol 6, pp 21–37.
2.
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.
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.
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.
5.
BakerM.RileyM. (1994), ‘New perspectives on productivity in hotels: Some advances and new directions’, International Journal of Hospitality Management, Vol 13, No 4, pp 297–311.
6.
BatteseG.E.CoelliT.J. (1988), ‘Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data’, Journal of Econometrics, Vol 38, pp 387–399.
7.
BatteseG.E.CoelliT.J. (1992), ‘Frontier production functions, technical efficiency and panel data: With application to paddy farmers in India’, Journal of Productivity Analysis, Vol 3, pp 153–169.
8.
BatteseG.E.CoelliT.J. (1995), ‘A model for technical inefficiency effects in a stochastic frontier production function for panel data’, Empirical Economics, Vol 20, pp 325–332.
9.
BatteseG.E.CorraG.S. (1977), ‘Estimation of a production frontier model: With application to the pastoral zone of Eastern Australia’, Australian Journal of Agricultural Economics, Vol 21, pp 169–179.
10.
BaumJ.HavemanH. (1997), ‘Love thy neighbor? Differentiation and agglomeration in the Manhattan hotel industry, 1898–1990’, Administrative Science Quarterly, Vol 42, No 2, pp 304–339.
11.
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.
12.
BrothertonB.MooneyS. (1992), ‘Yield management progress and prospects’, International Journal of Hospitality Management, Vol 11, No 1, pp 23–32.
13.
CanoM.DrummondS.MillerC. (2001), ‘Learning from others: Benchmarking in diverse tourism industries’, Total Quality Management, Vol 12, No 7/8, pp 974–980.
14.
ChungW.KalninsA. (2001), ‘Agglomeration effects and performance: A test of the Texas lodging industry’, Strategic Management Journal, Vol 22, pp 969–988.
15.
CornwellC.SchmidtP.SicklesR.C. (1990), ‘Production frontiers with cross section and time series variation in efficiency levels’, Journal of Econometrics, Vol 46, pp 185–200.
16.
DalborM.C.AndrewW. P. (2000), ‘Agency problems and hotel appraisal accuracy: An exploratory study’, International Journal of Hospitality Management, Vol 19, No 4, pp 353–360.
17.
DonaghyK.McMahonU.McDowellD. (1995), ‘Yield management: An overview’, International Journal of Hospitality Management, Vol 14, No 2, pp 1339–1350.
18.
FarrellM.J. (1957), ‘The measurement of productive efficiency’, Journal of the Royal Statistical Society, Series A, Vol 120, No 3, pp 253–290.
19.
IngramP.BaumJ. (1997), ‘Chain affiliation and failure of Manhattan hotels, 1898–1980’, Administration Science Quarterly, Vol 42, pp 68–102.
20.
JensenM.C.MecklingW. (1976), ‘Theory of the firm: Managerial behaviour, agency costs and capital structure’, Journal of Financial Economics, Vol 3, pp 305–360.
21.
JondrowJ.LovellC.A.K.MaterovI.S.SchmidtP. (1982), ‘On estimation of technical inefficiency in the stochastic frontier production function model’, Journal of Econometrics, Vol 19, pp 233–238.
22.
KhumbakarC.LovellC.A.K. (2000), ‘Stochastic frontier analysis’, Cambridge University Press, New York.
23.
LeeY.H.SchmidtP. (1993), ‘A production frontier model with flexible temporal variation in technical inefficiency’ in FriedH.P.O.LovellC.A.K.SchmidtS.S., eds, The Measurement of Productive Efficiency: Techniques and Applications, Oxford University Press, New York.
24.
LeibensteinH. (1966), ‘Allocative efficiency vs “X-efficiency”’, American Economic Review, Vol 56, No 3, pp 392–414.
25.
MeeusenW.van den BroeckJ. (1977), ‘Efficiency estimation from Cobb–Douglas production function with composed error’, International Economic Review, Vol 18, pp 435–444.
26.
MoreyR.C.DittmanD.A. (1995), ‘Evaluating a hotel GM's performance: A case study in benchmarking’, Cornell Hotel Restaurant & Administration Quarterly, Vol 36, No 5, pp 30–35.
27.
OlsonM. (1965), Logic of Collective Action, Harvard University Press, Cambridge, MA.
28.
PhillipsP.A. (1999), ‘Performance measurement systems and hotels: A new conceptual framework’, International Journal of Hospitality Management, Vol 18, No 2, pp 171–182.
29.
VogelH. (2001), Travel Industry Economics: A Guide to Financial Analysis, Cambridge University Press, London.
30.
WijeysingheB.S. (1993), ‘Breakeven occupancy for hotel operation’, Management Accounting, Vol 71, No 2, pp 23–33.
31.
WilliamsonO. (1998), ‘The institutions of governance’, American Economic Review, Vol 88, No 2, pp 75–79.