Determinants of tourism hotel profitability in Tunisia

Abstract

This study uses panel regression tests to examine the impact of the economic performance on the financial one. The retained measures for the economic performance and the financial one are, respectively, the operational efficiency score estimated with data envelopment analysis and the return on assets. This investigation leads to four major conclusions. First, the test results confirm that hotel financial performance is linked to its economic performance that is evaluated by its technical efficiency. Second, hotels affiliated to an international chain, hotels operating under a franchise contract, and hotels located in coastal areas or situated in scenic areas present a better financial performance than others. Third, the managers’ high intellectual level positively affects financial performance. However, hotel size and indebtedness have negative impacts. Fourth, hotel financial performance is linked to its contextual factors such as the tourism region attractiveness. Finally, this study ensures the significant impact of national and international crises, such as terrorist attacks on hotel financial performance.

Keywords

Hotel profitability efficiency franchise size indebtedness hotels’ characteristics managers’ characteristics destination attractiveness crisis

Introduction

After operational management and business strategies’ implementation, managers have to evaluate the organizational effectiveness using adequate performance measurements. Management performance may be evaluated according to the stakeholders’ visions and may vary over the firm’s life cycle (Tse, 1991). A successful managerial performance could be achieved if the adopted strategies were effective enough to achieve the planned objectives.

Effectiveness specifies objectives by focusing on the result of the behavior using performance targets. In addition, given the many benefits that profitable and well-run companies provide for the society and especially for their appropriate stakeholders, the use of financial performance is adequate and acceptable for comprehending organizational effectiveness (Randolph and Dess, 1984; Snow and Hambrick, 1980). This performance can be affected by several external and internal factors. For the first, both economic variables and noneconomic events, such as presidential elections, wars, natural disasters, terrorist attacks, and sports mega-events (Chen, 2009). For the second, several internal factors, such as staff skills, amenities investment, and financial option availability, have a direct and indirect impact on hotel performance. Hotels are yet influenced by some destination characteristics such as the international attraction, amenities, location, and market competition, which sometimes result in competitive advantages for their hotels. Furthermore, organizational assets, such as organizational structure and human resource management or reputational assets, such as company reputation, customer service reputation, and product reputation, have a significant influence on hotel performance (Sharma and Upneja, 2005).

Literature review

Some techniques have been developed considering different aspects of hotel performance. We cite the works of Anderson et al. (1999a, 1999b, 2000), Barros (2005), Barros and Alves (2004), Barros and Mascarenhas (2005), Barros and Santos (2006), Botti et al. (2009), Brown and Ragsdale (2002), Chen (2002, 2007), Chiang (2006), Chiang et al. (2004), Cracolici et al. (2006), Gunjan (2007), Hwang and Chang (2003), Reynolds (2003), Reynolds and Thompson (2007), Tsaur (2001), Wang et al. (2006), and Yang and Lu (2006), who discussed the overall or some parts of operational efficiency of hotels. It will be also interesting to investigate on the economic and financial performances relationship and the financial performance determinants.

Hotel efficiency and hotel financial performance

Nonfinancial and financial measures of hotel performance relationship are examined in several studies, with a complementary status being concluded by Amir and Lev (1996), Banker et al. (2000), Cumby and Conrod (2001), Frigo (2002), and Said et al. (2003). Managerial actions produce such results as quality, innovation, or customer satisfaction, which ultimately lead to financial performance. Frigo (2002) concluded that nonfinancial indicators are the determinants (drivers) of financial indicators. Thus, the financial indicators should be considered as general (or final) indicators of performance. They are determined or linked to more related “operational” indicators that directly measuring the efficiency for specific resources (Fernandez, 2000). To the best of our knowledge, the relationship between hotel efficiency and financial indicators has not yet been empirically evaluated. Thus, we attempt in this paper to examine this relationship.

H1: Hotel efficiency has a significant and positive impact on hotel profitability.

Size and hotel financial performance

On the one hand, several studies have confirmed the direct and positive impact of the hotel size on its performance (Barros and Mascarenhas, 2005; Chen and Tseng, 2005; Israeli, 2002; Rodríguez and Cruz, 2007). Claver-Cortés et al. (2007) demonstrated that hotel size through a competitive advantage can have a positive influence on hotel performance. Moreover, Kim et al. (2013) identified that hotel size influences occupancy rates per room and GOP, which is generally accepted as hotel performance measurements. They argued that medium- or large-sized hotels are well performing than smaller hotels. O’Neill and Mattila (2006) added that resorts and urban hotels are significantly higher than that of airport, suburban, and highway hotels. Pine and Phillips (2005) also confirmed this result using revenue per available room as a performance measurement for hotel data grouped by stars rating and ownership form.

Conversely, although the internal factor hotel size can have a positive impact on occupancy rate, several studies have concluded there is a negative influence of hotel size on the related profitability. In other words, large hotels receive more revenues but worse corporate performance in terms of profitability. The PricewaterhouseCoopers Hospitality Directions, cited by Withiam (2000), examined the size impact on hotel financial performance for a sample of 2616 hotel properties. Using income before fixed charges per available room as a hotel profitability measure, this study also confirmed the same influence on hotel operational performance. The study revealed that the most profitable size of hotels is this with between 400 and 500 rooms. However, this result was confirmed only for certain types of hotels, such as resorts and airport hotels.

Based on these results, we propose to examine the impact of hotel size on Tunisian hotels. Given the previous results, the following hypothesis was developed:

H2: Hotel size is negatively related to hotel profitability.

Indebtedness and hotel financial performance

There is a huge knowledge void in the hotel financing field despite its importance in financing large investments. Despite their importance as profitable and long-lasting firm, hotel companies have received little attention in the hospitality research field.

According to Elgonemy (2000), throughout the last two decades, capital structure and the financing in the hotel industry have been considerably altered based upon available financing alternatives and upon market conditions. Lenders and mortgage investors consider the hotel industry as a high-risky business, so it is important to finance the sustainable growth of hotel companies to reduce the financial risk. Barclay and Smith (2003) highlight the capacity of large companies compared to small companies to afford the high fixed costs of long-term debt. In addition, larger companies have an easier time of securing debt at lower cost, given their lower bankruptcy risk. A positive relationship between firm size and financial indebtedness level has been concluded by some studies, such as Barclay and Smith (2003), Sheel (1994), and Wald (1999). Furthermore, Tang and Jang (2007) searched for the determinants of capital structure by comparing lodging companies and software companies and then concluded that fixed assets are a significant determinant for long-term debt in the lodging industry. Growth investments for lodging firms, which have a high amount of fixed assets such as land, buildings, and properties, should be low cost, regardless of the low risks associated with these investments.

H3: Hotel indebtedness has a negative influence on hotel profitability.

Chain integration and hotel financial performance

There is a subset of contractual organizational forms preferred by hoteliers for a vertical integration (Shook and Shook, 1993). Several studies have compared the performance of hotels presenting different characteristics and examining the impact of the international affiliation to an international chain on their performance. Chang (2003), Chen (2000, 2002, 2007a, 2007b), Chen and Huang (2001), Chiang et al. (2004), He (2003), Hwang and Chang (2000), and Wang (2002) affirmed that hotel chains are more efficient than independent hotels. Furthermore, on average, plural network hotels are more efficient than strictly franchised and wholly owned chains (Botti et al., 2009). In fact, hotel efficiency depends on operation type (Chen, 2007a, 2007b; Chiang, 2006).

H4: Chain integration increases hotel profitability.

Franchising and hotel financial performance

There is a subset of contractual organizational forms preferred by hoteliers for vertical integration (Shook and Shook, 1993). Internationally branded hotels have to establish vertically integrated operations or franchises, whereas for independent hoteliers, they have the choice of an alliance with a voluntary chain.

The contractual organizational forms for the hotel industry include voluntary hotel chains, franchises, and vertically integrated hotel chains. These governance structures represent degrees of the level of integration. Vertically owned hotels are more integrated than franchises, which are more integrated than voluntary groups (Coughlan et al., 2001).

In addition, plural networks hotels are, on average, more efficient than strictly franchised and wholly owned chains (Botti et al., 2009). The local independent hotel may not be able to attract international visitors, but entering into an agreement with a hotel chain results in access to a recognized brand name, acquiring managerial competence and an international reservation system (Bradach and Eccles, 1989). Hotel chains, in its turn, acquire a market development without incurring investments (Carney and Gedajlovic, 1991) and (Combs and Ketchen, 1999).

H5: Financial performance of franchised hotels is superior to other contract forms and independent hotels.

Hotel location and hotel financial performance

The location where a firm operates definitely influences the managerial decisions. Location is so a key competitive variable in the lodging sector (Baum and Haveman, 1997). Chen (2003) and He (2003) found that hotels located in the scenic areas of Taipei are more efficient than others.

H6: Hotels located in scenic areas are more profitable than others.

H7: Hotels located in coastal areas are more profitable than others.

International attraction of the destination and hotel profitability

The international attractiveness of a particular hotel is generally considered as one of the measurements of hotels performance, but few papers have empirically examined this factor. Rosenbaum and Spears (2006) affirmed that international tourists stay longer and spend more. Attracting international tourists can, in fact, boost reservation rates. Bernard and Jensen (1999) and Wagner (2005) confirmed that international customer orientation is a determinant of firms’ revenue and more productive than domestically oriented firms simply receiving foreign customers. An international orientation improves hotel performance through new productivity knowledge (Bernard and Jensen, 2004).

In Tunisia, the number of international tourist arrivals grows constantly and exceeded 6.9 million in 2010. The future focus will be on Asian markets, especially in those countries that experienced rapid growth over the last few years.

H8: International attractiveness of the destination has a positive effect on hotel profitability.

Manager education and hotel financial performance

Well-educated managers are able to ameliorate the hotel performance and the client satisfaction that depends on employee skills. High-quality education and training appears to be increasingly important for improving hotel performance. Campos et al. (2005) concluded that hotels adopting high-quality training are more important than those focusing on production optimization. Education and training approaches have to reflect hotel specifications. They should also reflect the diverse demands and opportunities that tourism brings to a hotel. The relationship between tourism education and high-quality tourism skills was confirmed by Barron and Prideaux (1998), Baum (1995), and Thomas and Long (2001). Moreover, Campos et al. (2005) suggest that they are even more important than production optimization for improving hotel performance.

Accordingly, hotel organizational performance can acquire competitive advantages through human resources management practices (Kim and Oh, 2004; Wang and Shyu, 2008). As the hospitality sector is becoming increasingly complex and requires greater skills, many hotels are attempting to improve manager retention by offering education and rewards and increasing the general skill level of all employees (Olsen et al., 2008).

H9: Hotels that operate under managers with a high education level have higher profitability.

Crisis events and hotel financial performance

Hotel stock returns can be affected by both economic variables and noneconomic events. Taiwanese hotel firm sales earnings for example were remarkably harmed by the SARS outbreak in March 2003 and the earthquake in Taiwan on September 21, 1999 (Chen et al., 2007). This result is confirmed Pine and McKercher (2004) and Chien and Law (2003) for Hong Kong’s tourism industry. The unfavorable impact of the SARS outbreak in 2003 on Taiwanese hotel stock prices was mentioned by Chen et al. (2007). During the SARS outbreak in Taiwan, the stock prices of publicly traded hotel companies plunged. Furthermore, hospitality stock performance was significantly damaged by numerous other crises affecting the hospitality industry. Chen et al. (2005) mentioned that the hotel stock performance in Taiwan was remarkably affected by the terrorist attacks of 11 September 2001 in the U.S. as well as the earthquake of 21 September 1999.

The same results for China were reported by Chen (2007a, 2007b) for the SARS outbreak, sports mega-events (e.g. the 2000 Sydney Olympics and the 2002 Japan/Korea World Cup), the 1997–1998 Asian financial crisis, and the Iraqi war in 2003 and by Chen (2009) for the impact of crises such as the earthquake on 21 September 1999, the terrorist attacks of 11 September 2001 in the U.S., and the SARS outbreak on 22 April 2003 on different hotel performance indicators.

H10: Hotel profitability is influenced by crisis events.

Methodology and results

Data

To examine the impact of the mentioned hotel internal and external characteristics on financial performance, we perform panel regression tests using unbalanced panel data of 27 Tunisian hotel companies in the period covering 2001–2010. Data were collected directly from independent hotels or from hotel chains operating in Tunisia like ACCOR, RIU, LAICO, or IBEROSTAR chains. Hotel data are extracted from their financial statements.

Corporate performance measures

Returns on assets (ROA) is generally accepted in the literature as a financial performance measurement. ROA, computed as net income divided by total assets, is a measure of profit per dollar of assets:

ROA = \frac{Net income}{Total assets} * 100 % .

ROA reflects the ability of a firm’s management to generate profits from the firm’s assets (Athanasoglou et al., 2008). Kang and Stulz (1997) affirmed that investors prefer firms with a high ROA because it is an indication of their future returns. ROA is also commonly used to measure corporate performance (Capon et al., 1990; Gonzalez-Hermosillo et al., 1997, Hall and Weiss, 1967, Kesner, 1987, Persons, 1999; Thomson, 1991).

Determinants of financial hotel performance

The model has a large number of predictors; some of them are time invariant, like location. For this purpose, and according to Baltagi (2005), we use panel data, which give more variability and less collinearity among the variables. Therefore, there is a gain in efficiency with more degrees of freedom. Besides, panel data are able to control for individual heterogeneity and for time invariant variables whereas a cross-section data or a time series analysis cannot. Therefore, the following panel regression tests are performed

{ROA}_{it} = β_{0} + β_{1} {EFF}_{it} + β_{2} {SIZE}_{it} + β_{3} {DE}_{it} + β_{4} INT - {CHAIN}_{it} + β_{5} {FRANCHISE}_{it} + β_{6} SCENIC - {AREA}_{it} + β_{7} COASTAL - {AREA}_{it} + β_{8} {ATTRACTION}_{it} + β_{9} EDU - {GM}_{it} + β_{10} EDU - {FM}_{it} + β_{11} CRISE - 01_{it} + β_{12} CRISE - 02_{it} + μ_{i} + ɛ_{it}

(1)

CRISE-01 and CRISE-02 denote, respectively, the dummy variables of terrorist attacks on 11 September 2001 in the U.S. and the terrorist attacks of 11 April 2002 in Tunisia (Djerba), with a value of 1 for the related year and 0 otherwise. µ_i is a random effect model controlling the individual heterogeneity in the tourism industry, such as managers' schooling or hotels characteristics.

According to the aforementioned studies examining the impact of hotel and environment characteristics on hotel performance, we select the following variables: EFF which is an aforementioned efficiency score measuring operational activities performance; SIZE is the hotel size. Following Chen (2009), it is estimated by the natural logarithm of the average total assets; DE is the debt–equity ratio or leverage ratio;

DE = \frac{Total Debts}{Total Equity} * 100 %;

INT-CHAIN is the affiliation of the hotel with an international chain. It is a dummy variable that takes 1 for a chain-affiliated hotel (vertically integrated hotel, voluntary chain, or franchise agreements) and 0 for an independent hotel; FRANCHISE is the management style of the hotel. It is a dummy variable that takes 1 for the franchised hotel and 0 for the independent hotel; ATTRACTIVITY is the destination capability to attract international tourists. The former is measured by dividing the number of international tourist arrivals at the tourism destination of the hotel by the total number of arrivals in the country; EDU-GM is the number of years of study after a bachelor’s degree of the general manager; EDU-FM is the number years of study after bachelor’s degree of the financial manager.

Location in which each firm operates will influence proposed decisions to such an extent that location is a key competitive variable in the lodging sector (Baum and Haveman, 1997): SCENIC-AREA is a dummy variable which takes 1 for a hotel situated in scenic areas and 0 for a hotel located in outside areas. COASTAL-AREA is a dummy variable that takes 1 for hotels situated in coastal areas and 0 for those in outside areas.

Estimation of efficiency scores

Data envelopment analysis (DEA) approach is used to estimate efficiency scores for each observation. This approach supposes outputs and inputs. We assume that transformation of inputs on outputs is made with the same technology T, defined as

T = {(X, Y) \in {IR}_{+}^{N} * {IR}_{+}^{M} : X \in {IR}_{+}^{N} can produce Y \in {IR}_{+}^{M}}; (X : Input; Y : Output) .

Supposing that all DMU access to the same technology, DMUs can perhaps be on the frontier of this technology; this depends on various exogenous variables characterizing economic environment specific to the DMU. The distance separating the DMU and the frontier corresponds to the DMU inefficiency.

Assuming that a hotel aims to maximize its performance, we use the Farrell/Debreu-type output-oriented technical efficiency measure and we try to estimate efficiency score for each DMU j (j = 1,…, n)

TE (X^{j}, Y^{j}) = max_{θ} {θ : (X^{j}, θ Y^{j}) \in T}

(2)

In reality, T is unobserved and so we replace it by its DEA estimate $\overset{\land}{T}$

\hat{T} = {(X, Y) \in {IR}_{+}^{N} * {IR}_{+}^{M} : \sum_{k = 1}^{n} Z_{k} Y_{m}^{k} \geq Y_{m}, m = 1, \dots, M, \sum_{k = 1}^{n} Z_{k} X_{i}^{k} \leq X_{i}, i = 1, \dots, N, Z_{k} \geq 0, k = 1, \dots, n}

(3)

where Z_k ≥ 0 (k = 1,…, n) are the intensity variables over which optimization (2) is made and

\overset{\land}{T}

is the smallest convex free disposal cone in (X,Y)-space. By replacing T with

\overset{\land}{T}

in equation (2), the estimations of the efficiency scores

T {\overset{\land}{E}}_{j} (j = 1, \dots, n)

are consistent estimations of the corresponding true efficiency scores,

{TE}_{j} (j = 1, \dots, n)

given by equation (2).

Each unit has to reach the unity (score = 100%) to succeed the transformation of the given inputs on outputs. The characteristics of the retained inputs and the retained outputs for the 27 hotels from 2000 to 2010 are presented in Table 1.

Table 1.

Characteristics of the inputs and outputs in 27 examined hotels from 2000 to 2010.

Variables	Obs	Min	Max	Mean	Std. Dev.
Total turnover	169	1,208,095	18,644,700	5,386,773	4,779,307
Direct fees	169	264,843	7,260,382	1,734,153	1,674,431
Indirect fees	169	1,208,095	11,644,700	5,386,773	4,779,307

According to the different studies using the DEA such as those of Hu et al. (2010), the retained outputs and inputs are argued by the data availability. Benefiting of the totality of operational information in the used data for this study, we use the total turnover of the hotel as the output and the direct and indirect expenses as input.

Empirical results and policy implications

Based on the results of the technical efficiency scores in Table 2, we conclude that Tunisian hotels are far from high efficiency. We can also observe a large difference among the various estimated scores. Efficiency scores range from 46% for the poor performing unit and reach 99% for the best performing unit. Despite being in the same country and presenting, in general, the same product for business hotels or resort hotels, management efficiency still appears to be influenced by internal and external factors. However, based on Figure 1, we can observe a maintained efficiency average of 65% despite of light variations down to 51% in 2003 and reaching 70% in 2008.

Figure 1.

Average efficiency of data hotels for the period 2000–2010.

Table 2.

DEA technical efficiency scores for data hotels, 2000–2010.

Hotel	Average (%)	Hotel	Average (%)
1	99	15	62
2	98	16	62
3	93	17	61
4	84	18	60
5	84	19	57
6	80	20	56
7	79	21	54
8	77	22	51
9	73	23	49
10	71	24	49
11	65	25	48
12	63	26	46
13	63	27	46
14	63

According to descriptive statistics provided in Table 3, hotels economic performance evaluated by the average score efficiency from 2000 to 2010 and hotel financial performance evaluated by the ROA for the same period do not represent the same ranking for regions. Both of them demonstrate so many performance differences among regions. Hotels located in Monastir-Skanés, for example represent the poor efficiency score average and the poor ROA average. Hotels located at Tunis Zaghouan operate the best performance.

Table 3.

Descriptive statistics of the data.

	Specification	Sample size (Hotels)	Average efficiency (SCORE) (%)	Average profitability (ROA) (%)
Region	Tunis–Zaghouan	24	76	14
	Sousse–Kairouan	29	68	8
	Jerba–Zarzis–Gabès	58	60	7
	Mahdia–Sfax	6	72	4
	Nabeul–Hammamet	18	59	4
	Yasmine–Hammamet	14	53	1
	Gafsa–Tozeur	10	49	1
	Monastir–Skanés	10	46	1
Size	Less than data average	16	64	7
Size	More than data average	11	60	5
Indebtedness	Less than data average	15	68	9
Indebtedness	More than data average	12	57	11
International chain affiliation	Chain affiliation	18	66	13
International chain affiliation	Local chain or independent	9	62	5
Affiliation contract	Franchise	9	85	15
Affiliation contract	Other contracts^a	18	57	5
Hotel location	Scenic areas	20	63	7
	Out of scenic areas	7	60	6
	Coastal areas	16	66	36
	Interior areas	11	60	31
General manager education	Less than 3 years	87	59	5
General manager education	More than 3 years	82	66	10
Financial manager education	Less than 4 years	70	52	2
Financial manager education	More than 4 years	99	68	9

Management contracting, renting and independent hotels.

Large hotels present better economic performance and the best financial performance. The higher indebted hotels present in average more economic performance but less financial performance than less indebted hotels. Hotels affiliated to an international chain present both a better economic and a better financial performance. Franchised hotels are more efficient (85%) and more profitable (15%) than independent hotels (57% for efficiency and 5% for profitability). Hotels located in scenic areas or in coastal areas present better economic and financial performances than hotels situated in other areas. Hotels operating under the control of well-educated general managers and financial managers have a great average score efficiency (66 and 68%, respectively) than other hotels (59 and 52%, respectively) and great profitability (10 and 9%, respectively) compared to other hotels (5 and 2%, respectively).

The impact of the cited variables on hotel performance is deduced via panel regression tests with fixed effects and random effects estimation methods. The Hausman test is used to determine if the first or the second should be considered. The null hypothesis is that μ and X are uncorrelated and thus random effects are consistent and efficient (Dimitrios, 2005; Maddala, 2001). The Hausman (1978) test results (First model: p-value = 0,833 > 5%; Second model: p-value = 0,632 > 5%) are not significant and in favor of the random effects method. We note that Franchise agreement is one of the conventions permitting an affiliation to an international chain. Presenting higher co-linearity, INT-CHAIN and FRANCHISE have to be integrated at two models including one of them. Moreover, scenic areas in TUNISIA are generally located in coastal areas. Consequently, SCENIC-AREA and COASTAL-AREA have to be introduced to avoid co-linearity problem. Descriptive statistics and correlation table are provided, respectively, in Tables 4 and 5.

Table 4.

Descriptive statistics for variables.

Variable	Obs	Min	Max	Mean	Std. Dev.
Score	169	0.295	1.000	0.621	0.180
Attractivity	169	0	0.006	0.003	0.002
Competitors	169	26	161	116.012	38.903
Rooms	169	10	51.595	35.329	14.056
Age	169	0	23	8.604	4.815
Inter-chain	169	0	1	0.036	0.186
Resort	169	0	1	0.586	0.494
Center	169	0	1	0.231	0.423
Advertising	169	169	0.115	0.789	0.420
Managers	169	5	15	9.242	2.448
Tenure	169	0	7	3.130	1.831
Education	169	0	5	2.941	1.745
Wages	169	32	920	748.454	108.819

Table 5.

Correlation table of the different variables.

	Score	Attractivity	Competitors	Rooms	Age	Inter-chain
Score	1
Attractivity	0.170	1
Competitors	0.178	0.493	1
Rooms	0.047	0.697	0.871	1
Age	0.103	0.243	0.247	0.348	1
Inter-chain	0.326	0.069	−0.018	−0.070	−0.035	1
Resort	0.143	0.193	0.325	0.389	0.331	−0.033
Center	0.010	0.136	−0.320	−0.048	0.376	−0.106
Advertising	0.171	−0.052	0.218	0.124	0.385	−0.077
Managers	0.274	−0.006	−0.114	−0.092	0.054	−0.268
Tenure	−0.463	−0.166	−0.413	−0.349	−0.283	−0.052
Education	0.558	0.364	0.469	0.414	0.384	0.116
Wages	0.211	−0.062	−0.009	−0.019	0.205	0.101
	Resort	Center	Growth	Managers	Tenure	Education	Wages
Resort	1
Center	−0.051	1
Advertising	0.058	−0.193	1
Managers	0.188	0.157	0.388	1
Tenure	−0.304	0.042	−0.198	0.043	1
Education	0.306	−0.077	0.226	0.099	−0.653	1
Wages	0.078	−0.098	−0.006	0.096	0.060	−0.140	1

Test results are presented in Table 6. First, these results demonstrate that hotel financial performance is closely related to hotel management efficiency. A significant and positive impact is identified. We can classify hotel management efficiency as one of the drivers of financial performance, which remains the first objective of every investor. Chen and Soo (2007) state that hotel companies provide many services and leisure activities that tourists demand. Those services include accommodation, food, beverages and laundry, swimming pools, and conference facilities. The quality of these services might be an important factor in ensuring operational hotel performance and in further improving hotel profitability.

Table 6.

Regression results for return on assets (ROA), fixed effects estimation, and random effects estimation results.

	Variable	Fixed Effects model		Random Effects model
	Variable	Model 1	Model 2	Model 1	Model 2
Efficiency	EFF	0.107*** (0.000)	0.105*** (0.000)	0.108*** (0.000)	0.128*** (0.000)
Hotel characteristics	SIZE	−0.055*** (0.004)	−0.050*** (0.012)	−0.041*** (0.009)	−0.033*** (0.015)
	DE	−0.017*** (0.056)	−0.013*** (0.068)	−0.023*** (0.036)	−0.018*** (0.038)
	INT-CHAIN	–	–	–	0.042*** (0.027)
	FRANCHISE	–	–	0.083*** (0.046)	–
Contextual factors	SCENIC-AREA	–	–	–	0.115*** (0.000)
	COASTAL-AREA	–	–	0.053*** (0.040)	–
	ATTRACT	0.159*** (0.000)	0.155*** (0.000)	0.148*** (0.000)	0.132*** (0.000)
Managers skills	EDU-GM	0.002*** (0.047)	0.002*** (0.019)	0.002*** (0.053)	0.004*** (0.024)
Managers skills	EDU-FM	0.014*** (0.083)	0.013*** (0.024)	0.017*** (0.003)	0.022*** (0.000)
Crises	CRISE-01	−0.009*** (0.054)	−0.008*** (0.052)	−0.009*** (0.042)	−0.009*** (0.039)
	CRISE-02	−0.017*** (0.006)	−0.016*** (0.007)	−0.017*** (0.005)	−0.015*** (0.011)
	CONSTANT	0.860 (0.006)	0.767 (0.021)	0.631 (0.009)	0.476 (0.047)
F-statistic (p-value) = 0.000	R²= 0.537	R²= 0.598	R²= 0.702	R²= 0.712

The symbols (*), (**), and (***) indicate statistical significance at the 10, 5, and 1% level, respectively.

Figures in parentheses present the p-value of each variable.

Second, hotel financial performance is significantly related to its size. There is a negative impact of hotel size on its profitability. This result can be explained by several reasons advanced by Chen (2009). Large tourist hotels enjoy high occupancy and hence sales revenue but low profitability. Net profit, in fact, is equal to total revenues minus total cost (operational or financial). Apparently, they should focus on cost control (Chen, 2009).

According to the agency theory, it may become harder for hotel owners to monitor and control managers’ abnormal behavior as hotel companies grow (Pi and Timme, 1993). The financial performance of larger companies can be inhibited because of their management complexity, scale diseconomies, or the management inefficiency in transforming inputs to outputs (Adams and Buckle, 2003). Hoteliers have to provide demanded services, including accommodation, food, beverages and laundry, swimming pools, and conference facilities. The quality of these services, which require large investments with high financial costs, might be a very important factor in ensuring corporate hotel performance (Chen and Soo, 2007).

Third, indebtedness has a negative impact on the financial performance of hotels, confirming results of Chen (2009) and Such and Parte (2007). Our sample of hotels presents an indebtedness level of an average of 44% that may reach 60% for some hotels. Given that these hotels present high levels of indebtedness, the majority of Tunisian hotels generate inhibited profitability. Consequently, managers, especially financial managers, have to follow an optimal debt policy to generate an efficient investment and disinvestment. In fact, hotel owners have to invest in new hotel generation and to present adequate services for international demanding customers.

Fourth, the results also indicate that the financial performance of affiliated hotels to an international chain is higher than independent hotels. Moreover, franchised hotels are more profitable than independent hotels or hotels operating under other contract confirming results of Barros and Dieke (2008), Chen (2007), Hwang and Chang (2003), and Wang et al. (2006) for Taiwanese and other international hotels. Tourist hotels tend to be subject to “internationalization” world-class quality service and foreign traveler targeting can facilitate the successful operation of local hotels. These results can be attributed to an efficient reservation system, sounder reputation, better brand image, internet marketing, and economy of scale for the international franchise chain hotels compared with independently operated local hotels. Despite their high quality service in some cases, independent hotels will have greater difficulties in surviving without competitive advantages. Because it facilitates a performance increase, franchise chains or membership in hotel associations will be the general trend.

Fifth, the hotel’s location has a significant impact on its financial performance. In fact, hotels located in scenic areas are more profitable than others. Moreover, hotels situated in coastal areas are more profitable than others. Scenic areas and coastal areas in Tunisia benefited from more public and more private investments that can explain their high concentration of hotels. Including more facilities and more para-tourism activities, scenic areas are better equipped to satisfy tourists. Thus, scenic area hotels can benefit from the region notoriety and the destination promotion assured by public authorities or by concurrent.

Sixth, international tourism attractiveness, indicated by the destination proportion of inbound arrivals, confirms a positive influence on hotel efficiency scores. That is, if a tourism destination receives more inbound arrivals, its hotel market tends to be active at higher efficiency. Inbound arrivals may indicate a longer duration of travel and higher travel budget than that of domestic tourists. As a result, the hotel market has to focus on the inbound arrivals segment to ameliorate the cost of hotels’ operation.

Seventh, the results also reveal that the higher the education level of hotel managers is the more efficient the hotel will be. This finding is consistent with the hypothesis that education contributes to efficiency. Xiao et al. (2008) explained this finding by pointing to the complexity of the business hotel market, which is undergoing fast changes on both the demand and supply sides. Managers with higher levels of education may have more knowledge and feel more comfortable dealing with this business complexity. This result confirms the conclusion of Li et al. (2007) that hiring employees with a better educational background appears to be an effective human resource strategy to reduce inefficiency in the hotel sector. Tourism/hospitality education and training have the challenge of conveying tourism students who support a high-quality tourism industry. To succeed in this challenge, tourism managers have to convince skilled students to choose a tourism career.

Eighth, the terrorist attacks of 11 September 2001 in the U.S. had a significant and negative impact on hotel profitability. The same result was obtained for the terrorist attacks of 11 April 2002 in Tunisia. The Tunisian hotel performance response to crisis events confirms the conclusions of previous empirical studies, which generally attributed the negative influence of crisis events on hotel profitability to be caused by the plunge in foreign tourist arrivals (Chen, 2005, 2007b, 2010; Chen et al., 2005; Drakos, 2004; Kim and Gu, 2002). As Rittichainuwat and Chakraborty (2009) noted, for international tourists, a travel decision depends on the perception of safety and security. Natural disasters, terrorism, and disease incidents can lead to an increase in the perception of travel risks by international tourists, which can cause the cancellation or change of travel plans (Chen, 2010).

Conclusions

This article dealt with the issue of the tourism and hotel determinants in Tunisia by examining the importance of management efficiency to achieve hotel profitability by studying a sample of 27 Tunisian hotel performances during the period of 2000–2010. The efficiency score was estimated using a comprehensive DEA method to evaluate the management efficiency for each DMU. DEA appears to be adequate for evaluating hotel management (Barros, 2005). Efficiency permits an effective benchmarking practice that aids in better operational decision making, which can consequently ameliorate hotel financial performance. Efficiency can be considered as a hotel profitability driver. Moreover, we extended the investigation of the decision variables by exploring the impact of hotel characteristics and manager’s characteristics on hotel profitability.

This study confirms the different aforementioned hypotheses. First, despite of its positive impact on hotel corporate performance often cited in the literature, hotel size has a negative impact on hotel profitability, which is in accordance with the results of Chen (2009). In addition, confirming the results of Barros and Dieke (2008), Chen (2007a, 2007b), Hwang and Chang (2003), and Wang et al. (2006), the performance of franchised hotels is higher than the performance of hotels operating under other contractual forms and independent hotels. Moreover, hotels affiliated to an international chain are more profitable than others. The same result is observed for hotels located in the coastal areas of Tunisia. Second, the tourism attractiveness of the tourism region where the hotel is located has also a positive effect on hotel profitability. Third, the education level of the hotel’s general or financial managers has a positive and significant impact on hotel profitability. A major challenge for tourism managers is to implement development strategies including staff knowledge and manager education. Improving such skills will provide a competitive advantage for the hotel. In addition, the educational and pedagogical knowledge related to heritage forms the basis of a local development process and the principle of sustainability through a better understanding of the issues of the local territory. This knowledge also fosters the emergence of a participatory process. Finally, this study highlights new evidence that crises, such as the 11 September 2001 terrorist attacks in the U.S. and the 11 April 2002 attack in Tunisia, can negatively affect the corporate performance of hotels.

This study should be well complemented by empirical studies examining the impact of other macro and micro-characteristics on hotel profitability.

Footnotes

Author Biographies

Ben Aissa Sami is a lecturer of finance at IHEC of Carthage. He hold a Ph.D in Economy at University of Carthage, Tunisia. Held visiting positions at the University of Higher Technological Studies in Djerbaamong other institutions. He is a member of the Research Laboratory of Applied Economics and Empirical Finance (LEFA-IHEC of Carthage). He occupied positions as management controller and financial manager in a hotel chain.

Mohamed Goaied is a professor of Applied Econometrics and Statistics at IHEC of Carthage. He holds a Ph.D in Mathematical Economics and Econometrics from University of Dijon, France. Held visiting positions at the University of Paris I among other institutions. He Headed IHEC Carthage and actually is the director of the Research Laboratory of Applied Economics and Empirical Finance. He has carried out research and consulting activities in the field of Industrial Economics and Development Economics. He is the author of several studies and publications in refereed journals. He is a Fellow at the Economic Research Forum for Mena region and a member of the Board of the Economic Analysis in Tunisia.

References

Aaker

(1996) Measuring brand equity across products and markets. California Management Rev 38: 102–13.

Adams

Buckle

(2003) The determinants of corporate financial performance in the Bermuda insurance market. Applied Financial Economics 13: 133–143.

Amir

Lev

(1996) Value-relevance of nonfinancial information: The wireless communications industry. Journal of Accounting and Economics 22: 3–30.

Anderson

Fok

Scott

(2000) Hotel industry efficiency: An advanced linear programming examination. American Business Review 18: 40–48.

Athanasoglou

Brissimis

Delis

(2008) Bank-specific, industry specific and macroeconomic determinants of bank profitability. Journal of International Financial Markets, Institutions and Money 18: 121–136.

Baltagi

(2005) Econometric Analysis of Panel Data, 3rd ed. West Sussex, England: John Wiley and Sons, Ltd.

Banker

Potter

Srinivasan

(2000) An empirical investigation of an incentive plan that includes nonfinancial performance measures. The Accounting Review 75: 65–92.

Barclay

Smith

(2003) The joint determination of leverage and maturity. Journal of Corporate Finance 9: 149–167.

Barron

Prideaux

(1998) Hospitality education in Tanzania: Is there a need to develop environmental awareness? Journal of Sustainable Tourism 6: 224–237.

10.

Barros

(2005) Measuring efficiency in the hotel sector. Annals of Tourism Research 32: 456–477.

11.

Barros

Alves

(2004) Productivity in the tourism industry. International Advances in Economic Research 10: 215–225.

12.

Barros

Dieke

(2008) Technical efficiency of African hotels. International Journal of Hospitality Management 27: 438–447.

13.

Barros

Mascarenhas

(2005) Technical and allocative efficiency in a chain of small hotels. International Journal of Hospitality Management 24: 415–436.

14.

Barros

Santos (2006) The measurement of efficiency in Portuguese hotels with DEA. Journal of Hospitality and Tourism Research 30: 378–400.

15.

Baum T (1995) Tourism in the United Kingdom. In: Vellas (ed.) Francois International Tourism Year.

16.

Baum

JAC

Haveman

(1997) Love thy neighbor? Differentiation and agglomeration in the Manhattan hotel industry. Administrative Science Quarterly 42: 304–338.

17.

Bernard

Jensen

(1999) Exceptional exporter performance: Cause, effect, or both? Journal of International Economics 47: 1–25.

18.

Bernard

Jensen

(2004) Exporting and productivity in the USA. Oxford Review of Economic Policy 20: 343–357.

19.

Botti

Briec

Cliquet

(2009) Plural forms versus franchise and company owned systems: A DEA approach of hotel chain performance. Omega 37: 566–578.

20.

Bradach

Eccles

(1989) Price, authority, and trust: From ideal types to plural forms. Annual Review of Sociology 15: 97–118.

21.

Brown

Ragsdale

(2002) The competitive market efficiency of hotel brands: An application of data envelopment analysis. Journal of Hospitality and Tourism Research 6: 332–360.

22.

Campos

Gonzalez

Ropero

(2005) Service quality and competitiveness in the hospitality sector. Tourism Economics 11: 85–103.

23.

Capon

Farley

Hoenig

(1990) Determinants of firm performance. Management Science 36: 1143–1159.

24.

Carney

Gedajlovic

(1991) Vertical integration in franchise systems: Agency theory and resource explanations. Strategic Management Journal 12: 607–629.

25.

Chang TY (2003) Effects of resource and capability on managerial performance in the international tourist hotel industry of Taiwan. Doctoral dissertation, Ming Chuan University, Taipei, Taiwan.

26.

Chen

(2007) Applying the stochastic frontier approach to measure hotel managerial efficiency in Taiwan. Tourism Management 28: 696–702.

27.

Chen

Huang

(2001) Measuring efficiencies of international tourist hotels in Taipei area. Tourism Management Research1 1: 27–45.

28.

Chen

Soo

(2007) Cost structure and productivity growth of the Taiwanese international tourist hotels. Tourism Management 28: 1400–1407.

29.

Chen

C-W

(2009) Tourism expansion, tourism uncertainty and economic growth: New evidence from Taiwan and Korea. Tourism Management 30: 812–818.

30.

Chen

Tseng

(2005) The performance of marketing alliances between the tourism industry and credit card issuing banks in Taiwan. Tourism Management 26: 15–24.

31.

Chen HY (2000) The study on operational efficiency of resort hotel in Taiwan. Master dissertation, Chaoyang University of Technology, Taichung, Taiwan.

32.

Chen KH (2003) A study on the relationships between regional factors and operational efﬁciency of the international tourist hotel in Taiwan. Master dissertation, Chaoyang University of Technology, Taichung, Taiwan.

33.

Chen

(2007a) Applying the stochastic frontier approach to measure hotel managerial efficiency in Taiwan. Tourism Management 28: 696–670.

34.

Chen

(2007b) Macro and non-macro explanatory factors of Chinese hotel stock returns. International Journal of Hospitality Management 26: 991–1004.

35.

Chen

(2010) The economy, tourism growth and corporate performance in the Taiwanese hotel industry. Tourism Management 31: 665–675.

36.

Chen

Jang

Kim

(2007) The impact of SARS outbreak on Taiwanese hotel stock returns: An event study approach. International Journal of Hospitality Management 26: 200–212.

37.

Chen

Kim

(2005) The impact of macroeconomic and non-macroeconomic forces on hotel stock returns. International Journal of Hospitality Management 24: 243–258.

38.

Chen PC (2002) A study on evaluating operation efﬁciencies among chain international tourist hotels in Taiwan. Master dissertation, Nanhua University, Chiayi, Taiwan.

39.

Chen

(2009) Performance measurement of an enterprise and business units with an application to a Taiwanese hotel chain. International Journal of Hospitality Management 28: 415–422.

40.

Chiang

Tsai

Wang

(2004) A DEA evaluation of Taipei hotels. Annals of Tourism Research 31: 712–715.

41.

Chiang

(2006) A hotel performance evaluation of Taipei international tourist hotels—using data envelopment analysis. Asia Paciﬁc Journal of Tourism Research 11: 29–42.

42.

Chiang

Tsai

Wang

LSM

(2004) A DEA evaluation of Taipei hotels. Annals of Tourism Research 31: 712–715.

43.

Chien

GCL

Law

(2003) The impact of the Severe Acute Respiratory Syndrome on hotels: A case study of Hong Kong. International Journal of Hospitality Management 22: 327–332.

44.

Claver-Cortés

Molina-Azorín

Pereira-Moliner

(2007) The impact of strategic behaviors on hotel performance. International Journal of Contemporary Hospitality Management 19: 6–20.

45.

Combs

Ketchen

JDJ

(1999) Can capital scarcity help agency theory explain franchising? Revisiting the capital scarcity hypothesis. Academy of Management Journal 42: 196–207.

46.

Coughlan

Anderson

Louis

(2001) Marketing Channels, Englewood Cliffs, NJ: Prentice Hall.

47.

Cracolici MF, Nijkamp P, and Rietveld P (2008) Assessment of Tourism Competitiveness by Analysing Destination Efficiency. Tourism Economics 14(2): 325–342.

48.

Cumby

Conrod

(2001) Non-financial performance measures in the Canadian biotechnology industry. Journal of Intellectual Capital 2: 261–272.

49.

Dimitrios

(2005) Applied Econometrics: A Modern Approach Using EViews and Microfit, Houndmills, Basingstoke, Hampshire, New York: Palgrave Macmillan.

50.

Drakos

(2004) Terrorism-induced structural shifts in financial risk: Airline stocks in the aftermath of the September 11^th terror attacks. European Journal of Political Economy 20: 435–446.

51.

Elgonemy AR (2000) The pricing of lodging stocks: A reality check. Cornell Hotel and Restaurant. Administration Quarterly, 18–28 December.

52.

Fernandez

(2000) Les nouveaux tableaux de bord des décideurs, 2nd ed. Paris: Éditions d’Organisation, 452 pp.

53.

Frigo

(2002) Nonfinancial performance measures and strategy execution. Strategic Finance 84: 6–9.

54.

Gonzalez-Hermosillo

Pazarbasioglu

Billings

(1997) Determinants of banking system fragility: A case study of Mexico. International Fund Staff Papers 44: 295–314.

55.

Gunjan

(2007) Measuring efficiency of the hotel and restaurant sector: The case of India. International Journal of Contemporary Hospitality Management 19: 378–387.

56.

Hall

Weiss

(1967) Firm size and profitability. Review of Economics and Statistics 69: 319–331.

57.

Hausman

(1978) Specification tests in econometrics. Econometrica 46: 1251–1271.

58.

He TS (2003) The technological efﬁciency of the international tourist hotels in Taiwan. Master dissertation, National Chengchi University, Taipei, Taiwan.

59.

Chiu

Shieh

(2010) A stochastic cost efficiency analysis of international tourist hotels in Taiwan. International Journal of Hospitality Management 29: 99–107.

60.

Hwang SN and Chang TY (2000) The evaluation of the efficiency change of the international tourist hotel industry in Taiwan. In: International academic seminar of prospective new century. Taipei, Taiwan: Ming Chuan University.

61.

Hwang

Chang

(2003) Using data envelopment analysis to measure hotel managerial efficiency change in Taiwan. Tourism Management 24: 357–369.

62.

Israeli

(2002) Star rating and corporate afﬁliation: their inﬂuence on room price and performance of hotels in Israel. International Journal of Hospitality Management 21: 405–424.

63.

Kang

Stulz

(1997) Why is there a home bias? An analysis of foreign portfolio equity ownership in Japan. Journal of Financial Economics 46: 3–28.

64.

Kesner

(1987) Directors stock ownership and organization performance: An investigation of Fortune 500 companies. Journal of Management 13: 499–507.

65.

Kim

(2004) How do hotel ﬁrms obtain a competitive advantage? International Journal of Contemporary Hospitality Management 16: 65–71.

66.

Kim

(2002) Impact of the 9/11 terrorist attacks on the return and risk of airline stocks. Tourism and Hospitality Research 5: 150–163.

67.

Kim WG, Cho M and Robert AB (2013) Determinants affectingcomprehensive property-level hotel performance: The moderating role of hotel type. International Journal of Hospitality Management, HYPERLINK "http://www.econbiz.de/Search/Results?lookfor=%22International+journal+of+hospitality+management.%22&type=PublishedIn&limit=20" International journal of hospitality management. Elsevier, ISSN 0278-4319, ZDB-ID 10742645. Vol. 34. pp.404–412.

68.

Tse

Xie

(2007) Hotel general manager profile in China: A case of Guangdong Province. International Journal of Contemporary Hospitality Management 19: 263–274.

69.

Maddala

(2001) Introduction to Econometrics, 3rd ed. West Sussex, England: John Wiley and Sons, Ltd.

70.

Olsen

West

Tse

ECY

(2008) Strategic Management in the Hospitality Industry, 3rd ed. New Jersey: Prentice Hall.

71.

O’Neill

Mattila

(2006) Strategic hotel development and positioning: The effect of revenue drivers on profitability. Cornell Hotel and Restaurant Administration Quarterly 47: 146–154.

72.

Persons

(1999) Using financial information to differentiate failed vs. surviving finance companies in Thailand: An application for emerging economies. Finance Journal 3: 127–145.

73.

Timme

(1993) Corporate control and bank efficiency. Journal of Banking and Finance 17: 515–530.

74.

Pine

McKercher

(2004) The impact of SARS on Hong Kong’s tourism industry. International Journal of Contemporary Hospitality Management 16: 139–143.

75.

Pine

Phillips

(2005) Performance comparisons of hotels in China. International Journal of Hospitality Management 24: 57–73.

76.

PricewaterhouseCoopers (2000) Hospitality Directions. U.S. ed. New York: PricewaterhouseCoopers.

77.

Randolph

Dess

(1984) The congruence perspective of organization design: A conceptual model of multivariate research approach. Academy of Management Review 9: 114–127.

78.

Reynolds

(2003) Hospitality–productivity assessment using data envelopment analysis. Cornell Hotel and Restaurant Administration Quarterly 44: 130–137.

79.

Reynolds

Thompson

(2007) Multinunit restaurant productivity assessment using three-phase data envelopment analysis. International Journal of Hospitality Management 26: 20–32.

80.

Rittichainuwat

Chakraborty

(2009) Perceived travel risks regarding terrorism and disease: The case of Thailand. Tourism Management 30: 410–418.

81.

Rodríguez

FJG

Cruz

YMA

(2007) Relation between social-environmental responsibility and performance in hotel ﬁrms. International Journal of Hospitality Management 26: 824–839.

82.

Rosenbaum

Spears

(2006) An exploration of spending behaviors among Japanese tourists. Journal of Travel Research 44: 467–473.

83.

Said

HassabElnaby

Wier

(2003) An empirical investigation of the performance consequences of non-financial measures. Journal of Management Accounting Research 15: 193–223.

84.

Sharma

Upneja

(2005) Factors influencing financial performance of small hotels in Tanzania. International Journal of Contemporary Hospitality Management 17: 504–515.

85.

Sheel

(1994) Determinants of capital structure choice and empirics on leverage behavior: A comparative analysis of hotel and manufacturing firms. Hospitality Research Journal 17: 3–16.

86.

Shook

(1993) Franchising: The Business Strategy That Changed the World, Englewood Cliffs, NJ: Prentice-Hall.

87.

Snow

Hambrick

(1980) Measuring organizational strategies: Some theoretical and methodological problems. Academy of Management Review 5: 527–538.

88.

Such

MJD

Parte

(2007) La financiación de la actividadproductiva:unaaproximaciónempírica a los determinantes de las decisiones de endeudamiento de las empresashotelerasespañolas. Revista Española de Financiación y Contabilidad 133: 147–174.

89.

Tang

Chang

(2007) Revisit to the determinants of capital structure: A comparison between lodging firms and software firms. International Journal of Hospitality Management 26: 175–187.

90.

Thomas

Long

(2001) Tourism and economic regeneration: The role of skill development. International Journal of Tourism Research 3: 229–240.

91.

Thomson

(1991) Predicting bank failures in the 1980s. Economic Review—Federal Reserve Bank of Cleveland, First Quarter 27: 9–20.

92.

Tsaur

(2001) The operating efficiency of international tourist hotels in Taiwan. Asia Pacific Journal of Tourism Research 6: 73–81.

93.

Tse

(1991) Stock returns volatility in the Tokyo Stock Exchange. Japan and the World Economy 3: 285–298.

94.

Wagner J (2005) Exports and Productivity: A Survey of the Evidence from Firm Level Data. Discussion paper 319. Hamburg Institute of International Economics, 2005. ISSN 1616-4814.

95.

Wald

(1999) Capital structure with dividend restrictions. Journal of Corporate Finance 5: 193–208.

96.

Wang

Shyu

(2008) Will the strategic ﬁt between business and HRM strategy inﬂuence HRM effectiveness and organizational performance? International Journal of Manpower 29: 92–110.

97.

Wang

Hung

Shang

(2006) Measuring the cost efficiency of international tourist hotels in Taiwan. Tourism Economics 12: 65–85.

98.

Wang TY (2002) Measuring the efficiency and the change in productivity of international tourist hotels sector. Master dissertation, Nanhua University, Chiayi, Taiwan.

99.

Withiam

(2000) Size matters. Cornell Hotel and Restaurant Administration Quarterly 41: 15.

100.

Xiao

O’Neill

Wang

(2008) International hotel development: A study of potential franchisees in China. International Journal of Hospitality Management 27: 325–336.

101.

Yang

(2006) Performance benchmarking for Taiwan's international tourist hotels. INFOR 44: 229–245.

Hotel	Average (%)	Hotel	Average (%)
1	99	15	62
2	98	16	62
3	93	17	61
4	84	18	60
5	84	19	57
6	80	20	56
7	79	21	54
8	77	22	51
9	73	23	49
10	71	24	49
11	65	25	48
12	63	26	46
13	63	27	46
14	63

Hotel	Average (%)	Hotel	Average (%)
1	99	15	62
2	98	16	62
3	93	17	61
4	84	18	60
5	84	19	57
6	80	20	56
7	79	21	54
8	77	22	51
9	73	23	49
10	71	24	49
11	65	25	48
12	63	26	46
13	63	27	46
14	63

Hotel	Average (%)	Hotel	Average (%)
1	99	15	62
2	98	16	62
3	93	17	61
4	84	18	60
5	84	19	57
6	80	20	56
7	79	21	54
8	77	22	51
9	73	23	49
10	71	24	49
11	65	25	48
12	63	26	46
13	63	27	46
14	63