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Contaduría y administración

Print version ISSN 0186-1042

Contad. Adm vol.64 n.1 México Jan./Mar. 2019 


The Spanish hotel corporations: Internal and external performance drivers

Rubén Lado-Sestayo1 

Milagros Vivel-Búa2  * 

1 Universidad de La Coruña, España.

2 Universidad de Santiago de Compostela, España.


This paper analyses the performance’s drivers of Spanish hotel groups in a sample of 1,019 hotels affiliated to hotel chains and time horizon is 2005-2011. The results suggest that demand and the market structure significantly affect the hotel performance. This highlights the importance of the management of the tourist destination where the hotels is located. Also, at the hotel level, results also confirm the effect of variables that are representative of the market share, the asset level and the indebtedness. Consequently, both hotel and tourist destination managers are responsible of hotel performance.

Keywords: Performance; Hotel group; Spain; Location; Hotel

JEL codes: M13; M21; L83


The positive evolution of the demand for hotel services has boosted the role of hotel corporations in the Spanish hotel offer to the detriment of independent hotels. In fact, according to the data of Hotelmarket for 2015, the vast majority of the Spanish hotel offer is in the hands of hotel corporations in a percentage close to 80%. However, this type of large companies has also been affected by the recent economic crisis that began in 2007, although its impact has not been homogeneous. While some hotel groups have had to declare bankruptcy or carry out refinancing of their liabilities, as is the case of Hoteles Foxá, the Urvasco group, and High-tech Hotels, others have boosted their plans for international expansion, especially in Latin America, as is the case of Meliá Hoteles, NH hotels, and Room Mate.

This change in the general structure of the sector has consequences for different interest groups given that, as a general rule, hotel groups have a greater dimension and, consequently, their decisions and actions have effects on a wider community of agents. In this line, it should be noted that tourism, where the hotel sector is its main component, represented 10.2% of Spanish GDP in 2010 and increased to 11.1% in 2015, according to data published by the National Statistics Institute.

The consequences of the prominence achieved by hotel corporations in the Spanish offer reach other more particular factors, such as the management of their performance. This is due to the fact that, generally speaking, in this type of companies it is their asset management model and their possibility of generating and taking advantage of synergies that-for example-are translated into economies of scale, which have an impact on their profitability. Furthermore, it must be considered that the very survival of the hotel is affected by the very management given by these large companies, which is not without complexity and requires an in-depth study of the factors that may influence it (Li and Sun, 2012). Thus, the focus of this work is on analyzing business performance, measured through economic profitability because this indicator relates business results with investment and is the measure most used in previous studies (Sainaghi et al., 2017; Lado-Sestayo et al., 2016a).

The competitive environment is also not alien to the structural change caused by the greater presence of hotel groups (Becerra et al., 2013; Sami and Mohamed, 2014). This may be related to the emergence of integration processes that seek to maintain or strengthen the competitive position of hotel establishments in a market that, as is the case of Spain, currently has an offer dominated by this type of companies that generate a high volume of employment (Vivel-Búa et al., 2016).

In short, this scenario justifies the relevance of focusing a study on this type of hotel companies. Thus, the objective of this empirical study is to analyze the performance, measured through economic profitability, of hotels integrated in hotel corporations within the Spanish market during the 2005-2011 period. In particular, it evaluates the factors that may influence this economic indicator, considering both those intrinsically related to the hotel establishment and others more closely related to the tourist spot where it is located. Thus, the consideration of these two dimensions (hotel and location) constitutes one of the main contributions of this research, as most previous studies focus on variables at a company level (Ivanov and Zhechev, 2012). At the same time, given the international importance of Spain as a tourist market, this country is the focus of outstanding analysis in order to obtain results that can be extrapolated to other markets. According to the World Tourism Organization (WTO), it should be noted that Spain is among the five most important international destinations in both tourist arrivals and income generated by tourism. In addition, it is the first country in the world in tourism competitiveness according to the ranking of the World Economic Forum for 2015.

The work is organized in five sections. After this first introductory section, the second section exposes the theoretical framework to which this research subscribes, showing the related literature and the hypothesis approach. The third section identifies the database used and explains the empirical study carried out. This work ends with a fourth section presenting the conclusions and, subsequently, the compilation of bibliographical references in the fifth section.

Theoretical framework

Despite the importance of hotel corporations in the supply of tourism services, there are few studies focused on evaluating the determinants of their performance. Nevertheless, the previous literature does recognize the existence of multiple differences between hotels integrated in these business groups and independent hotels (Gursoy and Swanger, 2007; Botti et al., 2009). For example, Sami and Mohamed (2014) find that hotel chains perform better than other types of hotel companies, although they also show a negative relationship between their size and performance. In fact, focusing on the nature of the determinants of hotel performance, it should be noted that the characteristics of the hotel have been the main factors analyzed in the previous literature (Ivanov and Zhechev, 2012).

From the point of view of business models, there are differences between independent hotels and those integrated into a hotel corporation (Yeung and Lau, 2005; Damonte et al., 1997). This can be related to the knowledge economies obtained by hotels already integrated into the corporation, and even to the increase in performance obtained by increasing the market share resulting from affiliation (Yeap, 2011; Sinclair and Stabler, 1997; Zhao, 1994). In this respect, previous studies have found that the higher market share may have strategic consequences by increasing the ability of the hotel corporation to influence price in the interrelations with its competitors (Yeap, 2011). Consequently, the market share will be the first factor considered in this study and the following hypothesis will be posed:

  • H1: Market share positively impacts performance.

One of the variables analyzed as a determinant of performance is the number of stars, which presents a positive relationship with price and consequently increases profitability (Lado-Sestayo et al., 2017; Becerra et al., 2013). Becerra et al. (2013) find that hotels affiliated with hotel corporations have higher prices and lower discounts, although these authors affirm that this horizontal differentiation is less effective than the differentiation in the level of quality (vertical). Consequently, because the competitive environment is exogenous, hotels must design strategies to reduce competition and increase their performance, for example, by enhancing their differentiation (Graff, 2011). Thus, the number of stars will be the second factor considered and according to previous literature the following hypothesis is explored:

  • H2: Hotel quality positively impacts performance.

A very popular horizontal differentiation strategy is the affiliation of a hotel to hotel corporations. According to previous studies, this can lead to a reduction in the probability of insolvency and favor greater economies of scale (Baum and Ingram, 1998; Sinclair and Stabler, 1997). Moreover, this integration can generate externalities (Lee and Jang, 2015; Tsang and Yip 2009). In fact, these may refer to knowledge sharing, or the concentration of employees with a higher degree of specialization and productivity (Glaeser and Resseger, 2010; Halling and Marnburg, 2008; Desrochers, 2001). At the same time, these externalities may create an environment conducive to the sharing of infrastructure or social capital between hotels within the same corporation (Kalnins and Lafontaine, 2004). However, it should be noted that, according to recent previous studies, this positive effect requires incurring costs derived from the lower efficiency associated with larger size (Sami and Mohamed, 2014). Likewise, hotel corporations have higher fixed costs, which, although they imply economies of scale in periods of growth, can also, in periods of low demand, cause greater difficulties and compromise the survival of the hotel (Lado-Sestayo et al., 2016b). Consequently, the size of the hotel, as a proxy for the possible existence of economies of scale, is the third factor considered in this work and, according to Lee and Jang (2015), the following hypothesis is considered:

  • H3: Economies of scale positively impact performance.

Within the hotel factors that determine profitability, previous studies have considered a set of control variables. Thus, the level of debt due to pressure on the strategic decisions of the company affects performance (Liu & Hung, 2006; Vivel-Búa et al., 2018). Another variable considered is the level of liquidity, because a deficit or excess can have significant consequences on hotel management (Borde, 1998; Jensen, 1986). This relationship has been examined in numerous studies, although the sign of its effect is not conclusive (Kim et al., 2012; Chen, 2013). Therefore, both variables (indebtedness and liquidity) together with an indicator of the ability of a company to meet its short-term payments, measured through working capital, will be considered in this study.

External factors can also significantly affect performance, according to the literature. In fact, Sami and Mohamed (2014) find a notable effect of such variables on performance, and Sainaghi (2011, 2010) stresses the need to consider the geographic location of the hotel establishment in assessing its performance in a sample of independent hotels. Similarly, Yang et al. (2015) show that it is necessary to incorporate characteristics related to the destination where the hotel is located to analyze its performance. Thus, the level of demand has been shown to have a positive impact on performance (Lado-Sestayo et al., 2016; Lado-Sestayo et al., 2017). The level of demand will be the fourth factor considered in this study based on the following hypothesis:

  • H4: The level of demand positively impacts performance.

In order to reflect the heterogeneity in hotel demand between tourist destinations, due to the fact that in Spain sun and beach destinations with high seasonality coexist with urban, cultural, and rural destinations, the level of seasonality has been considered as a study variable (Ridderstaat et al., 2014). According to Vivel Búa et al. (2017), seasonality has a negative impact on performance due to the fact that the sector has high fixed costs. Therefore, in contexts of high seasonality, managers must adapt resources to market demands (Karamustafa and Ulama, 2010). This is particularly difficult in independent hotels and, consequently, affiliated hotels may have an advantage in sharing infrastructure. In addition, the temporary concentration of demand may result in an increase in prices that, together with the better development in these contexts of affiliated hotels due to their capacity to reduce resources and have a better income management, would have a positive effect on their performance (Vives et al., 2018). Thus, the following hypothesis is considered:

  • H5: Greater variability in demand positively impacts performance.

Finally, the last factor to consider is the competitive environment. Thus, the existence of a concentrated competitive environment, where collusive practices can be carried out, could increase profitability (Lee, 2015). According to these results, hotel corporations competing in multiple markets could present greater incentives for collusion and, therefore, better performance (Mauri, 2016). Consequently, market structure will be the fifth factor considered in this study. In this line, the affiliation processes could contribute to the establishment of entry barriers against new competitors, which could favor the increase of the price level and, consequently, of the performance of the affiliated hotels (Lado-Sestayo et al., 2016a; Lee, 2015; Conlin and Kadiyali, 2006; Zhao, 1994; Suzuki, 2013).

According to the postulates of the Structure-Conduct-Result (SCP), the existence of collusion among the installed companies would justify the relationship between market concentration and performance (Cowling and Waterson, 1976; Davies, 1999). This paradigm establishes an analytical framework on which business results depend on the behavior of companies, which in turn depend on the structure of the market. Thus, the structure of the market characterized by the degree of concentration of supply, the degree of concentration of demand, the level of product differentiation, and entry barriers determines the competitive intensity. Within this framework, companies and consumers decide on their strategies, which determines the business outcome.

The Chicago School also finds a positive relationship between market concentration and performance, although this is based on efficiency, which is higher in large companies (Demsetz, 1973; Williamson, 1975, 1985). Given that this research uses a proxy of economies of scale (company size), it is feasible to validate the SCP approach in line with previous studies including the market structure as a determining factor (Lado-Sestayo et al., 2016a), since the effect of size is collected through the proxy of economies of scale:

  • H6: Market concentration level positively impacts performance

The hypotheses presented will allow a better understanding of the determinants of the performance of hotels affiliated to hotel chains, helping to identify the main differences between these and independent hotels.

Empirical analysis


The study sample has been constructed based on the following information sources:

  • Database of the Iberian Balance Sheet Analysis System (SABI, for its acronym in Spanish); used to obtain the economic and financial information of the hotel.

  • Database of Alimarket; used to obtain information about the characteristics of the hotel. Alimarket is a company that generates sectorial contents, which has a database of hotels among other sectors.

  • Hotel Occupancy Survey of the National Institute of Statistics from Spain; used to identify the characteristics of the tourist spots where the hotels are located.

The time period analyzed corresponds to the 2005-2011 interval. The choice of this study horizon is due, firstly, to the fact that there is no publicly available information on the tourist spot where the hotel is located in years prior to 2005. Secondly, the unavailability of complete economic-financial information after 2011 in the databases consulted at the time of carrying out this research. For example, SABI can present a period of up to two years in the incorporation of all the data of each company in its database. To this, we must add the possibility, as was the case for some of the analyzed corporations, of own delays caused by the company in the publication of its information. In general, this meant seeking a balance between the inclusion of complete data for each hotel and the number of hotels that make up the final study sample. Thirdly, this period of study is relevant for research purposes because it is representative of a stage characterized by an intensification in the processes of affiliation to hotel corporations in Spain, which illustrates the current situation of the sector.

Definition of variables and econometric approach

The dependent variable to be analyzed, given the object of study, is the performance of each hotel integrated in the hotel group. It is approximated through its economic profitability, that is, the quotient between its EBIT (Earnings Before Interest and Taxes) and its total income. This indicator is used because it does not present variations derived from the capital structure of the company and, therefore, allows evaluating its impact on performance.

Regarding the hypotheses put forward for the hotel-level variables, the following are the variables that will be used for each of them:

  • H1: The market share of each hotel is calculated as the percentage of income at the tourist spot.

  • H2: The quality of the hotel is measured by the number of stars it has.

  • H3: The economies of scale are approximated by the size of the hotel, calculated as the Neperian logarithm of its asset volume on balance sheet.

The volume of indebtedness, the number of employees, the level of liquidity approximated by cash flow, and the working capital have been used as hotel control variables.

In relation to the hypotheses put forward for the tourist destination variables, the following are the variables that will be used for each of them:

  • H4: The demand volume of the hotel is measured as the annual number of visitors in millions of individuals at each tourist spot.

  • H5: The level of seasonality is the variable used to measure the variability of demand. This is defined as the variance of the average monthly occupancy level.

  • H6: A Herfindahl index is used to measure the level of market concentration, as was done in previous studies (Lado-Sestayo et al., 2016; Pan, 2005; Davies, 1999). This index is calculated as the sum of the square market shares of the hotels in each tourist destination. Higher values mean higher concentration and, therefore, a lower level of competition.

The validation of the work hypotheses is done through the estimation of the following model:



i = hotel

j = tourist spot

t = temporary instant

c = constant

Tt = temporary effect, which through dummy variables synthetizes the impact of the macroeconomic variables and punctual events.

Xit = observed variables at a hotel level

Xjt = observed variables of the tourist spot

The estimates are organized in three phases. First, an estimate has been made by Ordinary Least Squares (OLS). Subsequently, the estimation was performed by Generalized Least Squares (GLS) using panel data with random and fixed effects, using Hausman’s test to select the most appropriate model.

Statistical-descriptive analysis

Table 1 identifies the descriptive statistics of the variables that characterize the hotel and the tourist spot where it is located. As the most outstanding results, it can be identified that the dispersion of market share decreased significantly in the 2008-2010 period, which could be linked to the economic crisis of these years. On the other hand, the number of workers has decreased considerably since 2008. This could be related, together with the evolution of the market share, to the disappearance or bankruptcy of hotel groups. Average hotel liabilities increase from 2008 to 2011. At the same time, during this four-year period, cash flows and working capital fell drastically. Again, these data could explain the bankruptcy of some hotel groups, due to the greater difficulties in repaying a larger liability in a context of lower liquidity.

Table 1a Descriptive statistics of the characteristics of the hotel. 

Quote Size* Debt Employment Liquidity Working Capital# Star Rating
% of income in the tourist spot Asset value (thousands of €) Debt / Total assets N° of employees Clash flow (thousands of €) Working Capital N° of stars
2005 Mean 0.020 3,230.024 53.094 29.506 248.247 329.366 Median 3
SD 0.034 536.613 32.508 35.503 582.370 870.064 Quartiles 3-4
2006 Mean 0.018 3,882.539 53.188 31.414 271.624 356.367 Median 3
SD. 0.032 649.478 34.141 40.116 688.973 1,040.282 Quartiles 3-4
2007 Mean 0.019 4,360.076 53.695 31.359 292.828 345.886 Median 3
SD 0.035 715.271 39.533 39.022 1317.653 941.136 Quartiles 3-4
2008 Mean 0.018 4,008.790 54.446 29.085 183.313 275.249 Median 3
SD 0.031 662.331 49.121 32.818 476.271 546.04 Quartiles 3-4
2009 Mean 0.017 4,299.460 59.37 27.98 98.003 297.194 Median 3
SD 0.026 727.367 59.074 33.612 511.613 610.66 Quartiles 3-4
2010 Mean 0.017 4,457.060 58.373 27.35 108.129 284.032 Median 3
SD 0.026 754.003 44.826 33.581 596.834 708.974 Quartiles 3-4
2011 Mean 0.019 4,189.115 55.656 26.445 164.198 256.142 Median 3
SD 0.033 704.413 40.342 33.764 546.234 568.35 Quartiles 3-4
Global Mean 0.018 4,049.079 55.492 29.006 192.762 306.198 Median 3
SD 0.031 676.532 43.996 35.568 723.172 774.933 Quartiles 3-4

Notes: *Variable without log transformation. SD = standard deviation

Source: own elaboration

Table 1b Statistical descriptions of the characteristics of the tourist destination. 

Visitors Concentration* Seasonality
N° of visitors Herfindahl Index Variance of monthly occupancy
2005 Mean 1.057 0.033 0.229
SD 1.443 0.032 0.103
2006 Mean 1.263 0.033 0.21
SD 1.724 0.034 0.096
2007 Mean 1.342 0.032 0.209
SD 1.879 0.033 0.091
2008 Mean 1.336 0.032 0.228
SD 1.932 0.031 0.096
2009 Mean 1.299 0.029 0.232
SD 1.926 0.023 0.101
2010 Mean 1.458 0.030 0.255
SD 2.217 0.024 0.099
2011 Mean 1.508 0.036 0.257
SD 2.292 0.031 0.092
Global Mean 1.323 0.032 0.232
SD 1.938 0.030 0.099

Notes: *Variable without log transformation. SD = standard deviation

Source: own elaboration

At the tourist spot level, it can be observed that the number of visitors grew during the 2005-2011 period, with a punctual decrease in the years 2008 and 2009. Therefore, on the one hand, there is an increase or maintenance of the level of demand, on the other hand, as indicated above, there is a contraction of cash flow in hotels. Perhaps the fall in the level of market concentration could justify that the positive evolution of demand is not transferred directly to the treasury. Finally, it should be noted that seasonality falls during 2005-2007 but increases significantly from 2008 onwards.

Results analysis

Table 2 presents the results obtained through the econometric estimates made. In particular, model 1 refers to the estimation by OLS, model 2 to the estimation of panel data with random effects, and model 3 to the estimation with fixed effects. According to the statistics calculated to validate these estimates, it can be concluded that the model with fixed effects is preferable to the rest of the estimates (model 3). This is due to the fact that the Fixed Effects F Test confirms that these have statistical significance, just as the Random Effects LM test confirms the significance of random effects. Therefore, both models (fixed effects and random effects) are preferable to the model estimated by OLS. In order to select between the fixed-effects model and the random-effects model, the Hausman test was performed. Its results suggest that the fixed-effects model is preferable to the random-effects model.

Table 2 Econometric estimations 

OLS Random Effects Fixed effects
Coef. Coef. Coef.
Visitors 0.362*** 0.564*** 1.414***
(0.138) (0.122) (0.589)
Concentration 0.317*** 0.540*** 0.800***
(0.030) (0.092) (0.093)
Seasonality 2.642 2.903 0.416
(2.597) (4.031) (4.861)
Quota 17.335*** 33.284*** 58.980***
(6.592) (10.377) (21.788)
Size 1.001*** 3.715*** 6.105***
(0.223) (0.431) (0.663)
Stars 00039 -0.688 -0.879
(0.265) (0.701) (0.821)
Debt -0.201*** -0.217*** -0.207***
(0.005) (0.006) (0.007)
Employment -0.042*** -0.077*** -0.084***
(0.008) (0.013) (0.017)
Liquidity 0.004*** 0.004*** 0.004***
(0.000) (0.000) (0.000)
Working Capital 0.000 -0.000 -0.000
(0.000) (0.000) (0.000)
2006 0.493 0.335 0.037
(0.794) (0.548) (0.570)
2007 0.298 0.554 0.322
(0.802) (0.556) (0.583)
2008 -2.149*** -2.187*** -2.474***
(0.791) (0.548) (0.567)
2009 -4.517*** -4.418*** -4.712***
(0.782) (0.546) (0.561)
2010 -3.654*** -4.065*** -4.563***
(0.788) (0.546) (0.597)
2011 -4.363*** -5.115*** -5.918***
(0.819) (0.603) (0.655)
Constant 3.387 -12.095*** -30.402***
(2.186) (4.075) (5.825)
Obs. (groupo) 5 560 5 560(1 019) 5 560 (1 019)
0.304 0.290 0.256
Test F (all) 151.44*** 103.6***
Wald ( 1.967*** -
LM test (Breushc-Pagan) 877.66*** -
Test F (Fixed Effects) - - 7.516***
Hausman () 52.90***
VIF 1.60

Notes: Coef. Represents the coefficients with heteroscedastically robust standard errors in brackets below. VIF is yhe average od the inflation factor of the variance, which is used as an indicator of multicollinearity, obtaining an appropriate value given that it has a value lower than two. *** ** * significant at 1%, 5%, and 10%, respectively.

Source: own elaboration

The results show that demand and market structure are relevant variables that influence the performance of Spanish hotel groups. Therefore, this stresses the relevance of the characteristics of the tourist spot when evaluating hotel performance.

Focusing on the characteristics of the hotel, the estimates confirm the effect of market share and economies of scale. With respect to the former, this result confirms that the market share does not necessarily have to be increased by sacrificing the profit margin. In relation to economies of scale, these can be individually exploited by each hotel establishment integrated in a hotel group.

No evidence has been found for the quality of the hotel measured by its star rating. Perhaps this is due to the fact that quality not only influences price but also costs. This could mean that other factors apart from the quality considered are the only ones that can have an impact on hotel performance.

Focusing on control variables, the volume of debt has a negative effect on performance. This could relate to the influence that debt can have on strategic decisions and price related tactics, which could be oriented towards generating cash flow rather than improving performance.

For its part, employment has a negative relationship with hotel performance. This could be justified by the associated costs or even by the marginal efficiency associated with the increase in staff.

With regard to cash flow, this has a positive impact on the performance of the hotels integrated in the hotel corporations.

Finally, the method proposed by Billor et al. (2000) has been used to detect the possible existence of outliers with incidence in the estimated parameters. The results confirm the absence of outliers.


This work has studied the determinants of the performance of 1,019 hotels affiliated to hotel corporations in Spain in the 2005-2011 period. To this end, both variables that individually characterize each hotel and variables that characterize the Spanish tourist destination where the hotel is located have been considered. The incorporation of both dimensions, i.e., hotel and tourist spot, means that this work contributes to the low number of studies that include variables external to the hotel in the study of its performance. Likewise, the majority of previous studies have focused on independent hotels despite the fact that notable differences have been found between these and hotels affiliated with hotel corporations.

The results obtained have contributed to the support of the hypotheses regarding the positive effect of market share, economies of scale, level of demand, and market concentration on performance. This means that hotels with a large presence in the market and a larger size have a better performance, which is in line with what was obtained in previous studies. Therefore, those actions aimed at improving market share are a way to improve results. This result confirms the strategic impact of the market share on competitors highlighted in previous studies. Likewise, with regard to the positive impact of size, the existence of economies of scale is confirmed, which is in line with the existence of positive externalities evidenced in previous literature, justifying the greater presence of hotel corporations in the market through the study horizon considered. This could be explained by the fact that the affiliated hotels share advertising and management costs, as well as having greater negotiating power vis-a-vis marketers and particularly vis-à-vis online travel agencies, which concentrate a large part of the hotel offer.

Regarding the hypotheses that have not been verified, no evidence has been obtained that supports the existence of a positive effect of the level of quality or of the variability of demand on performance. This could be due to the horizontal differentiation presented by affiliation, which could compensate for the absence of differentiation in quality via a greater number of stars. Vertical differentiation (greater number of stars) implies costs in line with the greater income it generates. In summary, the divergence in this result with previous research analyzing independent hotels could be found in the fact that the level of quality is an indicator that favors greater demand in independent hotels, although the image of the hotel corporation acts as an indicator in the affiliated hotels. With regard to the absence of the effect of seasonality, the results indicate that the best position of affiliated hotels to adapt resources to market demands according to previous literature is not sufficient to compensate for the effect of fixed costs.

In relation to the control variables used, the results point to the level of indebtedness negatively affecting performance, while liquidity contributes to its increase. Given the lack of previous studies that-from a theoretical point of view-support this relationship in the sector, these results point to the need to deepen the impact of the financial management of the hotel, given that it could play an important role in generating positive results. Among other aspects, this could be explained by the cost structure in the sector, very dependent on fixed costs and by the fact that the product offered is perishable.

The results show that the analysis of the performance of hotel corporations must consider variables of the hotel and tourist destination and that, consequently, the models proposed for independent hotels in previous literature may not be valid for affiliated hotels. In addition, these results present areas of common interest for hotel managers and tourist destinations, for example, for the promotion of tourist destination demand. However, they also point out that when faced with other types of actions-for example, those aimed at reducing seasonality-, affiliated hotels may not have incentives to collaborate with destination managers.

There were some limitations to the development of this work. Despite the effort made to obtain complete information on the hotel corporations to be analyzed, this was limited by the availability of data, conditioning and limiting the study period. Likewise, it was not possible to have information on the tourist spot in the period prior to 2005.


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Received: January 15, 2017; Accepted: August 27, 2018

*Autor para correspondencia. Correo electrónico: (M. Vivel-Búa)

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