Page 1 of 8
Archives of Business Research – Vol. 10, No. 8
Publication Date: August 25, 2022
DOI:10.14738/abr.108.12916. Ferreira, N. R. (2022). Untangling the Inefficiency of Hotel Industry: The Portuguese Teixeira Duarte Hotel Chain Analysis. Archives
of Business Research, 10(8). 133-140.
Services for Science and Education – United Kingdom
Untangling the Inefficiency of Hotel Industry: The Portuguese
Teixeira Duarte Hotel Chain Analysis
Nuno Rafael Ferreira
IBS-ISCTE IUL, Quantitative Methods, Lisbon, Portugal
ABSTRACT
In this study the technical efficiency was analyzed for four hotels of the Teixeira
Duarte Group - a renowned Portuguese hotel chain. An efficiency ranking was
established for these four Portuguese hotels units using Stochastic Frontier
Analysis. This methodology allowed discriminating between measurement error
and systematic inefficiencies, enabling the identification of the main inefficiency
causes. The results showed that distance to the airport and higher price of
accommodations promote efficiency. Additionally, hotels with many standard
rooms and sea views are likely to achieve higher levels of efficiency. These results
should be carefully considered when aiming at improving hotel's efficiency,
especially in Portuguese units with similar typology and location of the ones
considered in this analysis.
Keywords: Hotel industry; Efficiency; Stochastic Frontier Analysis (SFA)
INTRODUCTION
The tourism industry has great strategic significance for the Portuguese economy due to its
capability to generate wealth and create employment opportunities [1]. This is an economic
sector where Portugal has clear competitive advantages due to the existing high-quality
infrastructures, highly qualified human resources, natural diversity and pristine environments.
Portugal has exceptional resources in terms of geographic location, temperate climate, security,
historical and cultural heritage, high-quality beaches, biological variety (of species and
environments), and a highly competitive quality coastal touristic development.
According to [2], the Portuguese touristic market is highly segmented, with hotel groups
owning 63.8% of integrated housing units, while the remaining 36.2% belong to independent
entrepreneurs.
The hotel sector is an essential component of the tourism industry, challenged by a competitive
atmosphere managed by different pressure factors and driven by supply and demand ([3]-
GDFHTS/2010, 2010).
Teixeira Duarte (TD), a renowned Portuguese hotel chain, was founded in 1921 as a family
company and today is one of the largest Portuguese economic groups. Teixeira Duarte has a
successful trajectory established through sustainable growth in the civil construction sector.
Expanding the hotel industry in Portuguese-speaking countries consolidates its privileged
financial situation. In fact, outside Portugal, there are TD Hotels in the main cities of Angola and
Mozambique. In contrast, in Portugal, its central hotels are located in the southern region of the
Page 2 of 8
134
Archives of Business Research (ABR) Vol. 10, Issue 8, August-2022
Services for Science and Education – United Kingdom
Algarve region. However, several units can also be found on the coast of Alentejo (Southwest
coast) and in the centre area of the country.
(see Teixeira Duarte in the World in the homepage of Teixeira Duarte, 2016).
Despite the competitiveness and excellence displayed by the Group, it is essential to guarantee
that performance levels are improved or at least maintained. In fact, for management purposes,
maintaining efficiency involves using scarcer inputs and producing additional outputs. It also
means performing the assigned roles and preventing possible inaccuracies that can impede the
progress of industry.
In this context, this study aims to analyze the efficiency of the four TD Group hotel units based
in Portugal, namely: The Lagoas Park Hotel, the Sinerama Aparthotel, the Eva Hotel and the
Oriental Hotel, to identify factors affecting efficiency and analyze what must be altered to
promote better performances.
LITERATURE REVIEW
The efficiency analysis within the touristic hotel sector has been widely studied over the years.
Among available literature on this subject, the Stochastic Frontier Analysis (SFA) methodology
must be emphasized as a systematic approach. Authors such as [4]analyzed the estimation of
the managerial efficiency of 48 hotels in the USA during 1994. In a subsequent paper,[5] applied
both Data Envelopment Analysis (DEA) and SFA to estimate the efficiency of 31 corporate travel
management departments. Also, [6] used a one-stage SFA approach to analyze the technical
efficiency of 66 international hotels in Taiwan from 1992 to 2002 and incorporated the
Malmquist productivity index in the results. Likewise, [7] examined the cost efficiency of 55
international hotels in Taiwan using an SFA model.
The use of the SFA approach can be found in many other studies and is often combined with
different methodologies (e.g.[6];[8-10].
Different perspectives can drive the approaches to hotel industry efficiency analysis. For
example, [11] analyzed other tourist markets and the relationship between the hotel industry
and its macroeconomic contribution, e.g.[12-16]. Concerning the Portuguese hotel industry, the
efficiency analysis has been addressed by different approaches, primarily by Barros
(e.g.[17];[18];[19-20]; [21-22]and [23]).
TEIXEIRA DUARTE (TD) GROUP
The Teixeira Duarte Group currently employs more than 13,000 workers. It operates in 16
countries in seven different sectors: construction, concessions and services, Real Estate, hotel
services, distribution, energy, and automobile.
Page 3 of 8
135
Ferreira, N. R. (2022). Untangling the Inefficiency of Hotel Industry: The Portuguese Teixeira Duarte Hotel Chain Analysis. Archives of Business
Research, 10(8). 133-140.
URL: http://dx.doi.org/10.14738/abr.108.12916
Table 1 - The main indicators of Teixeira Duarte Group's business (the book values are
expressed in million euros. Total Equity includes non-controlled interests)
In non-consolidated terms, and in order to provide an overall view of the total activity of the
TD Group during 2014, we disclose that its operating income in the Construction sector
reached the total value of 1,027,221€, reflecting an overall slight decrease of 0.7% regarding
2013 (source: TD Annual Reports (2012, 2013, 2014)).
Disregarding new contracts that may arise, the Group has already assured business levels in
the construction sector for the foreign markets, which, despite the current adverse
circumstances of the domestic market, achieve 904,808€ for 2015; 649€ for 2016; and
339,281€ for 2017 (source: TD Annual Reports).
After the first experience in 1974 in the Algarve, the Teixeira Duarte Group resumed its activity
in the Hotel Services sector in the 1990s in Sines and currently operates 10 hotels, four of which
are located in Portugal, three in Angola and three in Mozambique, covering a total of 2,908 beds
and 1,465 rooms. TD Group's services are based on Tradition, Quality, Comfort and Kindness
(see hotel services from TD homepage, 2016).
Table 2 – Location (city and country) of the hotels of the Teixeira Duarte (TD) Group
Eva Hotel (4 star hotel) is acknowledged as a quality benchmark in Faro, both for leisure and
business stays. The hotel was recently renovated to be architectonically integrated into Faro's
historical and commercial downtown area. The Oriental Hotel, with a characteristic oriental
style, is situated in one of the most popular sun and sea Portuguese touristic destinations. The
Lagoas Park Hotel (4-star hotel) is located in one of the largest business centres of the country,
providing all conditions needed for business meetings and for leisure, given its congress centre
and its privileged location, fairly close to the beaches of Cascais, to Sintra, as well as to several
other interesting touristic sites. Sinerama Hotel (3 star hotel) is located in Bay of Sines, in the
vicinities of the Castle of Sines, and of the Vasco da Gama Museum. The hotel provides a family
and quiet environment (www.tdhotels.com/pt).
Business Indicators (Teixeira Duarte Group) 2010 2011 2012 2013 2014
Average number of workers 13036 11182 10853 12011 13261
Turnover 1380 1200 1383 1581 1680
Operating income 1445 1263 1440 1630 1716
Net debt 1067 927 990 1176 1293
Total equity 562 333 326 361 485
Total net assets 2721 2753 2767 2779 2954
Year
Hotels in Africa Hotels in Portugal
Angola Mozambique
Hotel Alvalade, Luanda Hotel Avenida, Maputo Hotel Eva, Faro
Hotel Baía, Luanda Hotel Tivoli Maputo, Maputo Hotel Oriental, Portimão
Hotel Trópico, Luanda Tivoli Hotel Beira, Beira Lagoas Park Hotel, Oeiras
Sinerana, Sines
Page 4 of 8
136
Archives of Business Research (ABR) Vol. 10, Issue 8, August-2022
Services for Science and Education – United Kingdom
METHODS AND MATERIALS
Dataset
For the stochastic frontier analysis, the data collected from Teixeira Duarte Group database
comprises data from 01/01/2011 to 30/06/2015 (Table 1), and relates only to the Portuguese
Hotels, to incorporate hotels facing similar seasonality patterns and having standard
operational periods and homogenous quality of services. A total of 216 observations was
gathered, corresponding to the 54 months (since January 2011 to June 2015) per hotel. The
chosen output variable was the Operating profits. Table 3 defines the remaining inputs and
exogenous variables.
Table 3 - Output, Inputs and Exogenous variables used in the stochastic frontier model.
DATA ANALYSIS
Using a stochastic frontier model, where i denote each Decision Maker Unit (DMU), the
individual operating profit is obtained using the following production function ([24]):
ln(�!) = �!� + (�! − �!) (1),
where i = 1, 2,..., N; yi measures the operating profits of the ith hotel; xi is a 1 x K vector
corresponding to the inputs (operating costs and employees), and β is a 1 x K vector of unknown
scalar parameters to be estimated. For this model, the traditional error term ε is composed of
two distinct terms (vi-ui) for each DMU where the error term vi, similarly to traditional
regression models, is assumed to be independent and identically distributed as �(0, �"
#) .
Random variation in output caused by factors beyond DMUs control, such as measurement
errors in dependent variables or explanatory variables eventually omitted, is captured by the
vi error term. The error term ui is a non-negative random variable, accounting for the existence
of technical inefficiency in production following a half-normal ui ~ |N(0,σ2)| distribution.
According to [24], the inefficiency distribution parameter can also be specified as the
inefficiency model:
�! = �$ + �!� + �! (2),
where δ represents a vector of parameters to be estimated, zi is a vector of DMU specific effects
(lodging price range, standard room, existence of sea view and airport distance), that determine
technical inefficiency, and ωi is distributed following N(0, σω2). All observations either lie on or
are beneath the stochastic production frontier, which is assured by ui ≥ 0 in Equation (2). The
Output
Operating profits (euros)
Inputs
Operating costs (euros)
Employees (number)
Exogenous variables
Lodging price-range (euros)
Standard rooms (number)
Sea view (0=no; 1=yes)
Airport distance (Kms)
TD Hotels SFA model
Page 5 of 8
137
Ferreira, N. R. (2022). Untangling the Inefficiency of Hotel Industry: The Portuguese Teixeira Duarte Hotel Chain Analysis. Archives of Business
Research, 10(8). 133-140.
URL: http://dx.doi.org/10.14738/abr.108.12916
variance terms are parameterized by replacing σv
2 and σu2 with �# = �"
# + �%
# and � = &!
"
(&#
"(&!
") ,
according to [24]. The value of γ ranges between 0 and 1, where 1 indicates that all of the
deviation from the frontier is entirely due to technical inefficiency [26]. The technical
efficiency (TE) of each DMU is expressed as follows:
��! = *(+$|%$,.$)
*(+$|%$/$,.$) = �0%$ (3),
where E is the expectation operator; thus, the measure of technical efficiency is based on a
conditional expectation given by Equation (3), considering that the value of vi – ui evaluated at
the maximum value of Yi is conditional on ui = 0[24].
The parameters of the stochastic frontier model (1) and the technical inefficiency model (2)
were estimated using the FRONTIER version 4.1 software [25].
RESULTS
The SFA model results confirms that the inclusion of the inefficiency effects is highly significant
(at the 1% significance level) in the analysis of Operating Profits (the estimate for the variance
is close to one – γ = 0.999 in Table 5), indicating that 99.9% of the random variation in Operating
Profit is due to inefficiency.
The mean efficiency of the four hotel units is presented in Table 4, and indicates that the Lagoas
Park Hotel is the more efficient hotel unit, contrasting with the Oriental Hotel (the less efficient
one).
Analyzing the yearly evolution, Eva and Lagoas Park recorded an increase in efficiency.
Nevertheless, for the last one the efficiency level has decreased slightly during the analyzed 6
months of 2015.
Moreover, it must be emphasized that the Sinerama Hotel has been losing efficiency since 2011,
whereas the Oriental Hotel did not indicate any pattern regarding the variation on the efficiency
levels from 2011 to 2015.
Table 4 – Mean efficiency scores per hotel unit and per year (from 2011 to 2015) of the
Portuguese hotels of Teixeira Duarte (TD) Group
The SFA and the inefficiency models results are presented in Table 5.
Hotel 2011 2012 2013 2014 2015
mean efficiency
per hotel
Eva 0.542 0.545 0.558 0.602 0.625 0.569
Lagoas 0.597 0.633 0.643 0.669 0.650 0.637
Oriental 0.414 0.411 0.465 0.502 0.485 0.453
Sinerama 0.662 0.632 0.524 0.570 0.418 0.577
TD hotels' mean efficiency per year 0.556 0.559 0.547 0.586 0.545 0.560
Page 6 of 8
138
Archives of Business Research (ABR) Vol. 10, Issue 8, August-2022
Services for Science and Education – United Kingdom
Table 5 - The results of the SFA and of the inefficiency models from 2011 to 2015 for the
Portuguese hotels of Teixeira Duarte (TD) Group
In both models all variables are statistically significant at the 1% significance level. The SFA
results indicate that the hotels with higher "operating costs" and less "employees" are the ones
that achieved higher operating profits.
Concerning the Inefficiency model, the "airport distance" is the most important factor that
contributes to inefficiency (highlighted by the positive coefficient).
With negative coefficients, the "lodging price range" has a positive impact, meaning that more
expensive prices contribute positively to efficiency.
Similarly, a hotel with many "standard rooms" and "sea view" also achieves higher levels of
efficiency.
CONCLUSIONS AND FINAL REMARKS
The present research aimed to evaluate the efficiency of the Teixeira Duarte hotel chain on the
Portuguese mainland. Using SFA allowed for assessing the efficiency level of each DMU (hotel
unit). It simultaneously highlighted the factors that significantly affect the performance of the
hotel units.
The results showed that an efficient hotel should be placed in the vicinity of an airport and be
equipped with standard rooms and – preferentially – sea view. High lodging price range
revealed not to be a problem to efficiency levels since high prices favour efficiency
improvement.
It would be an asset to this analysis to add some factors regarding tourist experience valuation,
such as satisfaction and length of stay ([13];[26]).
Results should be carefully considered in the management strategies adopted by the TD Hotel
Group.
Variable Coef. Std. Error
Stochastic frontier model
constant 2.790 ** 0.116
ln(operating costs) 0.841 ** 0.278
ln(employees) -0.343 ** 0.126
Inefficiency model
constant -0.125 ** 0.014
Lodging price-range -0.042 ** 0.010
Standard rooms -0.024 ** 0.008
Sea view -0.034 ** 0.008
Airport distance 10.953 ** 1.603
Variance parameter
g 0.999 ** 0.000
** significant at 1%.
Page 7 of 8
139
Ferreira, N. R. (2022). Untangling the Inefficiency of Hotel Industry: The Portuguese Teixeira Duarte Hotel Chain Analysis. Archives of Business
Research, 10(8). 133-140.
URL: http://dx.doi.org/10.14738/abr.108.12916
References
[1] World Tourism Organization (2011). Investing in energy and resource efficiency. World Tourism
Organization. Available at
http://www.unep.org/resourceefficiency/Portals/24147/scp/business/tourism/greeneconomy_tourism.pdf
[2] Atlas Hospitality (2015). Available at
http://atlasdahotelaria.com/2015/downloads/deloitte_atlas_da_hotelaria_2015_web_en.pdf. Consulted in
February 19, 2016.
[3] International Labour Office - Developments and challenges in the hospitality and tourism sector - Issues
paper for discussion at the Global Dialogue Forum for the Hotels, Catering, Tourism Sector, Genova (2010).
Available at http://www.ilo.org/wcmsp5/groups/public/---ed_dialogue/---
sector/documents/meetingdocument/wcms_162202.pdf
[4] Anderson, R.I., Lewis, D., & Parker, M.E. (1999a). Another look at the efficiency of corporate travel
management departments. Journal of Travel Research, 37, 267-272.
[5] Anderson, R.I., Fish, M., Xia, Y., & Mixhello, F. (1999b). Measuring efficiency in the hotel industry: a stochastic
approach. International Journal of Hospitality Management, 18, 45-57.
[6] Wang, Y.H., Lee, W.F., & Wong, C.C., (2007), Productivity and efficiency analysis of international tourist hotels
in Taiwan: an application of the stochastic frontier approach. Taiwan Economic Review, 35, 87-114.
[7] Chen, C.F. (2007). Applying the stochastic frontier approach to measure hotel managerial efficiency in
Taiwan. Tourism Management, 28, 696-702.
[8] Pérez-Rodriguez, J.V. & Acosta-González, E. (2007). Cost efficiency of the lodging industry in the tourist
destination of Gran Canaria (Spain). Tourism Management, 28, 993-1005.
[9] Assaf, A., Barros, C.P. & Josiassen, A. (2010). Hotel efficiency: A bootstrapped metafrontier approach.
International Journal of Hospitality Management, 29(3), 468-475.
[10] Hu, J.L., Chiu, C.N., Shieh, H.S. & Huang, C.H. (2010). A stochastic cost efficiency analysis of international
tourist hotels in Taiwan. International Journal of Hospitality Management, 29, 99-107.
[11] Narayan, P., & Sharma, S. (2013). Does tourism predict macroeconomic performance in Pacific Island
countries? Economic Modelling. Elsevier.
[12] Kreishan, F. M. (2011). Time-series evidence for tourism-led growth hypothesis: A case study of Jordan.
International Management Review, 7(1), 89–93.
[13] Assaf, A. & Josiassen, A. (2012). Time-varying production efficiency in the health care foodservice industry: a
Bayesian method? Journal of Business Research, 65(5), 617-625.
[14] Assaf, A.G. & Barros, C. (2011). Bayesian cost efficiency of Luanda, Angola hotels. The Service Industries
Journal, 31(9), 1549-1559.
[15] Hathroubi, S., Peypoch, N. & Robinot, E. (2014). Technical efficiency and environmental management: The
Tunisian case. Journal of Hospitality and Tourism Management, 21, 27-33.
[16] Jarboui, S., Guetat, H. & Boujelbène, Y. (2015). Evaluation of hotels performance and corporate governance
mechanisms: Empirical evidence from Tunisian context. Journal of Hospitality and Tourism Management, 25, 30-
37.
[17] Barros, C.P. (2004). A stochastic cost frontier in the Portuguese hotel industry. Tourism Economics, 10, 177-
192.
[18] Barros, C.P. & Alves, P. (2004). Productivity in tourism industry. International Advances in Economic
Research, 10, 215-225.
[19] Barros, C.P. (2005a). Measuring efficiency in the hotels: An illustrative example. Annals of Tourism
Research, 32(2), 456-477.
[20] Barros, C.P. (2005b). Evaluating the efficiency of small hotel chain with a Malmquist productivity index.
International Journal of Tourism Research, 7(3), 173-184.
Page 8 of 8
140
Archives of Business Research (ABR) Vol. 10, Issue 8, August-2022
Services for Science and Education – United Kingdom
[21] Barros, C.P. & Mascarenhas, M.J, (2004). Technical and allocative efficiency in a chain of small hotels.
International Journal of Hospitality Management, 24(3), 415-436.
[22] Barros, C.P. & Mascarenhas, M.J, (2006). The measurement of efficiency in Portuguese hotels with DEA.
Journal of Hospitality & Tourism Research, 30(3), 378-400.
[23] Oliveira, R., Isabel Pedro, M., & Cunha Marques, R. (2013). Efficiency and its determinants in Portuguese
hotels in the Algarve. Tourism Management, 36, 641–649.
[24] Battese, G.E. & Coelli, T.J. (1995). A model for technical inefficiency effects in a stochastic frontier production
function for panel data. Empirical Economics, 20, 325-332.
[25] Coelli, T.J. (1996). A guide to FRONTIER version 4.1: a computer program for stochastic frontier production
and cost function estimation.
[26] Coelli, T., Prasada, R. & Battese, G. (1998). An introduction to efficiency and productivity analysis. Boston,
Massachusetts, USA: Kluwer Academic Press.