Evaluation of hotel industry performance and corporate governance: A stochastic frontier analysis

Tourism Management Perspectives 15 (2015) 128–136

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Case study

Evaluation of hotel industry performance and corporate governance: A stochastic frontier analysis Hazar Guetat a, Sami Jarboui a,b,⁎, Younes Boujelbene c a b c

URECA, Faculty of Economics and Management, University of Sfax, Airport Road Km 4, Sfax 3018, Tunisia Laboratory of Transport Economics (LET), ENTPE, Rue Maurice Audin, 69518 Vaulx-en-Velin, Lyon, France Faculty of Economics and Management of Sfax, University of Sfax, Tunisia

a r t i c l e

i n f o

Article history: Received 12 December 2014 Received in revised form 11 May 2015 Accepted 26 May 2015 Available online xxxx Keywords: Tunisian hotel industry Corporate governance Nonfinancial and financial performance measures Efficiency Stochastic frontier function

a b s t r a c t The aim of this paper is to investigate the impact of corporate governance on Tunisian hotels' performance. This study introduces different variables associated to corporate governance in the hotel industry to measure the association between corporate governance and Tunisian hotels' performance. Thus, this paper evaluates the efficiency of 63 hotels during 2011–2012 and adopts a stochastic frontier function with 16 inputs (size of board of directors, number of outside directors, institutional participation in the capital, board independence, stock ownership of board members, CEO — chair separation…). Six outputs as performance measures (financial performance, social and human performance, organizational performance, commercial performance and global performance) are specified and used to estimate hotel efficiency. The results reveal that corporate governance measures are positively and significantly associated with hotel performance, and that hotels in Tunisia are on average operating at 65.02% efficiency. Crown Copyright © 2015 Published by Elsevier Ltd. All rights reserved.

1. Introduction The growth of tourism worldwide continues to be a major socioeconomic phenomenon of our present time. Nowadays, tourism is deservedly acknowledged to have unquestionable importance marked by a considerable contribution in currency, a contribution to the equilibrium of the trade balance. This finding has been mentioned and proved many times and this has been made clear by Narayan and Sharma (2013) in their investigation carried out in 6 Pacific Islands wherein they studied the relationship between the hotel industry and its macroeconomic contribution. And this was also done before them by Tang and Jang (2009) when they studied the case of U.S. hotel business, or also by Kreishan (2011) for Jordan, Chen and Chiou-Wei (2009) for Taiwan, Kaplan and Celik (2008) for Turkey, Dritsakis (2004) for Greece, Balaguer and Jorda (2002) for Spain, and Oliveira, Isabel Pedro and Cunha Marques (2013) for Portuguese. In this context and given the current state of Tunisian tourism and more particularly the hotel industry we noticed that this sector suffers from the inside: Poor quality of service, lack of product diversification, debt, mismanagement … (Weigert, 2012). This sector is characterized by a situation of cognitive heterogeneity, but also of information ⁎ Corresponding author at: Laboratory of Transport Economics (LET), ENTPE, Rue Maurice Audin, 69518 Vaulx-en-Velin, Lyon, France. E-mail addresses: [email protected] (H. Guetat), [email protected], [email protected] (S. Jarboui).

http://dx.doi.org/10.1016/j.tmp.2015.05.004 2211-9736/Crown Copyright © 2015 Published by Elsevier Ltd. All rights reserved.

asymmetry between the manager of the hotel establishment and the members of the board who do not know, in some cases, even the specifics of the trade. Thus, it is expected that the relational aspect of individuals within the board of directors and in the presence of the establishment director, improves or degrades the quality of the strategic decision and hence the performance of the company, hence the importance of the existence of a “good” system of corporate governance. The approach to corporate governance in tourism seems vital and reliable for more than one reason. Guillet and Matilla (2010) show the importance of corporate governance in the hotel industry, in that it positively affects performance. In this sector, the process of governance adopted differs from the system adopted by other industries, in the sense that the sector of tourism has specific characteristics such as the separation of ownership from the management function, multiplicity of actors … in their study conducted in America on a sample of 10 hotel groups over a period of 8 years. For this purpose, governance and performance are two valid concepts at the heart of the current science of management. One complements the other in the sense that the primary obsession of every organization is to create value. Several studies have focused on the study of the relationship and the link between the two phenomena. Some researchers investigated in the hotel industry, others in industrial areas, all over the world. We referred to the study performed by Wang and Zhou (2011), who opted for a correlation test followed by a linear regression to explain the performance of Chinese firms (ROA, ROE, Tobin Q) based on variables related to governance (features of the AC, dual system, outside director, ownership structure).

H. Guetat et al. / Tourism Management Perspectives 15 (2015) 128–136

Thus, this study serves as a reference for us to identify our variables and subsequently to test the validity of our assumptions. The aim of our research is to exploit the contribution of the corporate governance literature on explaining the different measures of the Tunisian hotels' performance. Next, our goal will be to present different efficiency scores to identify what kind of performance corporate governance affects the most and to what degree. In this paper, we present an original essay that seeks to explain how the corporate governance mechanism can affect the hotel industry performance, and how this approach can limit managers' mistakes leading to the inefficiency of the tourism industry. 2. Literature review According to Jarboui, Forget, and Boujelbene (2014) corporate governance mechanisms and controls are designed to reduce the inefficiencies that arise from moral hazard and adverse selection. There are both internal monitoring systems and external monitoring systems. Internal monitoring can be done, for example, by one (or a few) large shareholder(s) in the case of privately held companies or a firm belonging to a business group. Furthermore, the various board mechanisms provide for internal monitoring. Therefore, internal corporate governance controls monitor activities and then take corrective action to accomplish organizational goals. External monitoring of managers' behavior, occurs when an independent third party (e.g. the external auditor) attests the accuracy of information provided by management to investors. Therefore, external corporate governance controls encompass the controls that external stakeholders exercise over the organization. Several previous studies have investigated the role of governance mechanisms in the resolution of conflicts of interest between shareholders and managers and in the improvement of performance. The latter implies an interest in the plurality of actors. Indeed, in the field of tourism, partnership is often rigorous and must be taken into account. It is therefore important to integrate various stakeholders (banks, state, another hotel chain, suppliers, customers …) in making strategic or other decisions, with the aim of creating value. According to Cubbin and Leech (1983), conflicts of interest give rise to the particular relation between owners and firms performance. The relationship between ownership concentration and firm performance is determined by the identity of the large shareholders. This result is confirmed by Thomsen and Pedersen (2000). It is explained by fact that different types of shareholders have different levels of investment priorities. Shleifer and Vishny (1994) confirm that when government or politicians have concentrated control rights, owned firms are more closely governed and the profit generated is used to finance the national budget. According to agency literature, Jensen and Meckling (1976) confirm that ownership structure will not provide shareholders with adequate control due to lack of ability to monitor management decisions concerning capacity and motivation. For many reasons, manager/insider ownership attracts attention and interest. Firstly, owner/managers work harder and pay closer attention to the quality of work than no owners. According to Görg and Greenaway (2004), foreign ownership plays a crucial role in firm performance, particularly in developing and transitional economies. Many researchers, such as Aydin et al. (2007), state that multi-national firms are more efficient than domestically owned firms. There are many reasons for this effect of ownership on firm performance and how it encourages managers to work hardly and seriously to assure firm performance. The effect of ownership concentration on firm efficiency has been studied since Berle and Means (1932). Firms with ownership concentration are highly efficient, a result that is confirmed by Cubbin and Leech (1983). In line with this idea, Demsetz (1983) agrees with this result and argues that ownership structure is the outcome of competitiveness. According to Shleifer and Vishny (1997), the strong incentive of larger owners to monitor managers to assert their interest generates an

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inclination of managers to maximize shareholder value. To maximize total shareholder, the small shareholders have an insufficient incentive because the control and monitoring increases. Thus, particular attention should be paid to the logic of action of these actors. These guidelines on how and when to act allow us to understand how to establish links between the various stakeholders (Gerbeaux & Marcelpoil, 2003). Then we should take into account the types of relationships and forms of vertical and horizontal coordination between the different actors. Because these relationships are asymmetrical, their analysis is advocated in the hotel sector (Marcelpoil, 2002). Finally, governance emphasizes the importance of the notion of collective actor. From the time the tourism sector is perceived by customers as a functional area likened to a “black box”, the latter must put the odds on its side to prosper and ensure its sustainability. In a logic of governance, this sector will be required to meet a double challenge: on the one hand, the need for economic development and the logic of competition associated with it, and on the other hand, the fight against social exclusion. Other recent research has studied the efficiency and performance of hotels. Oliveira et al. (2013) use non-parametric techniques to investigate and compare the efficiency of Portuguese hotels in the Algarve using data envelopment analysis (DEA). Authors conclude that star rating is not a significant determinant of efficiency but location and the existence of golf courses may have some relevance. Benavides-Velasco, QuintanaGarcía and Marchante-Lara (2014) examine how the implementation of both total quality management and corporate social responsibility influences the results of hotels' stakeholders as an antecedent of business performance. For 141 Spanish hotels from the Andalusian region, this study shows that the adoption of such approaches improves the capacity of hotels to create benefits for their stakeholders, and these results have a positive effect on hotel performance. In terms of performance in the hotel industry and its close link with the phenomenon mentioned above, we are interested here in a multicriteria, multi-dimensional performance. The overall performance of a hotel business cannot be measured only on the basis of one of the financial achievements or the maximization of shareholder value. Indeed, studies focusing on this observation continue to grow; we may say that performance is only and solely financial; this statement proves incorrect, incomplete and not accurate. With reference to the results found by Lau (2011), the author, based on a sample of 121 managers that he consulted – heads of Australian companies consisting of a minimum of 100 employees – has shown that not only do the nonfinancial indicators significantly and directly affect the performance of the companies investigated, but in addition, they affect the latter in a much more pronounced and a much clearer way than financial indicators. In the same vein, Verbeeten and Boons (2009) explained the same phenomenon by surveying Dutch companies. The results of this study indicate that the latter, by using non-financial indicators, provide a more relevant and much better picture of their performance. Thus, in this study we focus on the explanation and measurement of the financial, human, social, organizational and mercantile performance, through variables related to governance mechanisms in the hotel sector. We cite the works of Wang, Lu and Lin (2012) as a reference in the study of the relationship: mechanisms of corporate governance/corporate performance, based on a study conducted in 68 banks holding companies (BHCs) in 2007. Among the mechanisms considered, we note: the Board of Directors, the dual system, the number of external directors, the committees. Our investigation is an extension of that work, expounding this question in the hotel industry and seeking to explain several performance models through the implemented governance system. 3. Hypothesis development For the relationship between the size of the Board of Directors and performance, Adams and Mehran (2005) examine this relationship by referring to Tobin's Q, and based on a sample of banks between 1959

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and 1999, the authors find that banks whose boards are large are not those that are underperforming. In the same vein, Linck and AL (2006) constructed a sample of 7000 firms of different sizes over the 1994– 2004 period. Their results are not in favor of small boards and independent boards. Hence our first hypothesis:

McConnell and Servaes (1990) confirm this fact: based on a sample of U.S. firms, they were able to demonstrate the existence of a positive relationship between the percentage of capital held by the financial institutions and corporate performance, measured by Tobin's Q. Hence our hypothesis:

Hypothesis 1. There is a positive relationship between the size of the Board and the hotel business performance.

Hypothesis 6. The proportion of capital held by the institutions positively affects the each hotel performance.

The variation in the number of outside directors also affects in a direct manner the performance of the hotel. Some authors, like Claessens and Yortoglu (2013), Byrd and Hickman (1992), Morck and Nakamura (1994) or Kaplan and Minton (1994a,b), argue that the significant presence of outside directors on the board strengthens its supervision power, thus affecting positively the performance of the firm. Hence our second hypothesis:

The formulation of our research hypotheses now leads us to test the relationship between corporate governance and multidimensional performance in the Tunisian hotel industry, through a stochastic frontier used as a basis to assess the degree of importance of governance practices and subsequently their impact on the overall performance of hotel units.

Hypothesis 2. The number of outside directors positively affects the hotel business performance.

4. Methodology

The issue of combining the positions of Chairman of the Board of Directors and that of CEO was at the heart of the news in recent years. According to Fama and Jensen (1983), Baliga et al. (1996) and Coreje (2002), holding both the post of Chairman of the Board of Directors and that of a manager has a negative effect on business performance, in the sense that they noted the persistence of branch costs. Unlike most studies on the same subject, Brickley, Coles and Jarrell (1997) find no results that confirm the negative effect of holding both the post of Chairman of the Board of Directors and that of a manager on accounting and financial returns. We will follow the first school of thought, hence our hypothesis: Hypothesis 3. The separation of the positions of Chairman of the Board and CEO positively affects the hotel business performance. The literature emphasizes the importance of integrating committees within the Board of Directors. Wang et al. (2012) and Klein (1998) argue that the establishment of specialized committees could enhance the activity of the Board, in the sense that they represent an additional source of supervision for the manager (appointment committee, compensation committee…). In a study conducted on non-financial listed companies located in 10 countries of sub-Saharan Africa in 2009, Munisi and Randøy (2013) give evidence that the presence of a compensation committee in the Board does not affect the financial performance of the firms under study. Several controversies persist on the subject, hence our interest in the study of this relationship in the Tunisian hotel industry. Hence our hypothesis: Hypothesis 4. Integration of committees within the Board positively affects the hotel business performance. Concerning the capital share of the manager, some studies suggest that the more shares the manager holds in the capital, the more he is expected to improve the performance of the company seeing that, thus, his interests converge with those of the shareholders (Jensen & Meckling, 1976; Bhagat & Bolton, 2008). Other authors argue the opposite: a manager whose managerial ownership is high seeks to get further entrenched and subsequently evades control by pursuing his own goals that go against those of the providers of capital (Shleifer and Vishny, 1997). Hence our hypothesis: Hypothesis 5. The proportion of capital held by the manager positively affects the performance of the hotel unit. The rising power of the institutional investors in the capital of companies has aroused several controversies. Duggal and Miller (1999) show that there is a positive relationship between the presence of non-bank financial institutions and corporate performance (an additional control exercised by the institutions, or a modification in the mechanisms of governance positively affects performance). Like them,

The contribution of this study consists essentially in the implementation of the stochastic frontier analysis to evaluate the performance of the hotel businesses, on the one hand, and to compare their different levels of efficiency by identifying the governance mechanisms that contribute most in the Tunisian hotel industry, on the other. We adopt a parametric approach using the stochastic frontier analysis (SFA) model of production function for the panel data developed by Battese and Coelli (1995). As an alternative approach to the Data Envelopment Analysis (DEA), according to Jarboui, Forget, and Boujelbene (2013a,b)and Jarboui et al. (2014), the great advantage of SFA is that it can measure not only technical inefficiency, but also recognizes the fact that random shocks, beyond the control of producers, can affect production. For this reason, the essential concept of SFA is that the error term is composed of two parts: one unilateral component that captures the effects of the relative inefficiency of the stochastic frontier, and a symmetric component that allows a random variation of the frontier between companies and includes the effects of measurement error, other statistical noise, and random error (Jarboui, 2014b; Jarboui et al., 2013a). Thus, the main attraction of the stochastic frontier approach, in contrast to deterministic approaches such as the DEA, is that it isolates the influence of factors to inefficient behavior, thus correcting possible upward bias of the inefficiency of deterministic methods. In addition, it allows us to study the determinants of inefficiency. 4.1. The stochastic frontier approach (SFA) A recent work has drawn our attention, and we used it as a basis to develop this model: the investigation conducted by Hu, Chiu, Shieh and Huang (2010) on a sample of 66 Taiwanese hotels during the period 1997–2006. They chose as input the cost of the service provided, the cost of food and other miscellaneous expenses to determine the outputs (income/bedroom, the profit of the food service and the income from other miscellaneous operations). They said that 91.15% of the study sample is found to be efficient. Unlike non-parametric methods, the SFA has two advantages: firstly, it allows differentiating the effects of noise (measurement error) from inefficiency effects and thus takes into account the presence of exogenous shocks. The error is then decomposed into two terms: an inefficiency component (pure) and a random component which includes measurement errors and exogenous shocks (Battese & Coelli, 1995). In a second step, this method is found to be less sensitive to outliers than the DEA1 method. This concept called “frontier” is based on the deviation from the best performance in a group. Thus, the gap between the production function of a given entity and the frontier is called technical inefficiency. The interest we have in this notion is explained by the fact 1 Kablan.S (2007), Measuring the performance of banks in developing countries: the case of EMUWA (Economic and Monetary Union of West Africa).

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that it will facilitate for us the comparison of hotel units on the basis of their efficiency scores, resulting in their performance levels explained through governance practices. We employ the parametric approach using the stochastic frontier production function for the panel data proposed by Battese and Coelli (1995). The starting point of this parametric approach is to estimate a stochastic production frontier. This frontier can be written as follows: Yit ¼ expðxit β þ Vit −Uit Þ

ð1Þ

where Yit is the output of the i-th hotel's performance (i = 1, 2, …, N) in the t-th period (t = 1, 2,…, T); xit is a (1 ∗ k) vector of input variables attributed to corporate governance in t-th period; β is a (k ∗ 1) vector of unknown parameters to be estimated; Vit is a random variable which is assumed to be iid N (0, σ2V) and independent of Uit; the Uit is a non-negative random variable, associated with technical inefficiency of production, which is assumed to be independently distributed as truncations at zero of the N (μ, σ2U) distribution; where μ = zitδ and variance σ2U; and zit is a (1 ∗ p) vector of explanatory variables associated with technical inefficiency of hotel industry production over time; where δ is a (p ∗ 1) vector of unknown parameters. Eq. (1) specifies the stochastic frontier production function in terms of the original production values. However, the technical inefficiency effects, Uit, are assumed to be a function of a set of explanatory variables, zit, and an unknown vector of coefficients, δ. Thus, we have six dependent variables, all aimed at measuring performance. 4.2. Estimated performance models Model 1: PF ¼ expðxit β þ εit Þ

ð2Þ

PF refers to the financial performance of the tourism business. This independent variable is derived from a principal component analysis aimed to summarize the information about the financial aspect of performance that includes the variable measuring the increase in turnover on a Likert scale, the reduction of costs and improvement of services, the increase in returns on assets (ROA) and the increase in returns on equity (ROE). Our second model is as follows; Model 2: AVPM ¼ expðxit β þ εit Þ

ð3Þ

denoting increased sales and market share, determined from a PCA (Principal Component Analysis) including the variable of increased market share on a 5-level Likert scale, increased sales to existing customers, the proportion of sales to new customers compared to the total turnover and the degree of customer satisfaction. The same analysis revealed another dependent variable other than the increase in sales; it represents our third model and it is the degree of customer satisfaction; Model 3: DSC ¼ expðxit β þ εit Þ

ð4Þ

The following model aims to measure performance from the point of view of internal communication, innovation and training; Model 4:

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sales service it offers and also the degree of importance of continuous training of its staff. All these performance indicators are measured on a Likert scale. As for the performance of human resources, we have devoted our 5th model to it; Model 5: PSPCCTM ¼ expðxit β þ εit Þ

ð6Þ

The PCA showed a single axis strongly correlated with key performance indicators of the human factor in the hotel industry, namely, the importance of staff turnover measured on a 5-level Likert scale, absenteeism as an indicator of underperformance, taking into account the suggestions of employees, collective competence, turnover, and finally motivation. Our sixth and final model of performance measurement as a dependent variable: this is the overall performance, which includes all the variables that are derived from the PCAs made and that revolve around the financial, economic, and social aspects and the internal process of tourism in Tunisia; Model 6: PG ¼ expðxit β þ εit Þ

ð7Þ

The explanatory variables, the inputs for the 6 models representing the Xi, the number of directors on the Board (TCA), the number of outside directors (NAEXT), the number of Board meetings per year (NRCA), the term of office of the director (DMAD), the number of years of work of the manager in the hotel unit (NATDEH), the age of the manager (AGED), the proportion of managerial ownership (PPM), the proportion of institutional ownership (PPINSTI), the share of ownership of the manager (PACTD), the existence of a corporate governance committee within the Board (CGEASCA), the existence of a strategy committee within the Board (CSTRAASCA), the existence of an appointing committee within the Board (CNOMMI), the separation between the positions of CEO and Chairman of the Board of Directors (SFPDGPCA), and the experience of the managers in connection with their positions (EXPACP). These exogenous variables are the same for the six models of performance measurement. We also take into account two control variables, the variable “is PGH” gives us an insight into whether the studied hotel unit is part of a hotel group or not and the variable “Number unit” for the exact number of units that make up the group. 4.3. The functional form After presenting the stochastic efficiency frontier of Tunisian hotels' performance the discussion has concentrated on the error component part of the models. However, it is important to note that the functional form of the production function is another issue that has attracted considerable interest in the literature (Jarboui, 2014b; Jarboui et al., 2013a; Karlaftis & Tsamboulas, 2012). The stochastic frontier estimation requires a specific functional form of the production function. Different functional forms of the production function frontier are available. Many authors have estimated the stochastic frontier production function using the form of Cobb–Douglas function (Cobb & Douglas, 1928): ln Yit ¼ α0 þ

M X

αit lnxit þ Vit −Uit :

ð8Þ

i¼1

DICIFC ¼ expðxit β þ εit Þ

ð5Þ

The variables introduced in the PCA revolve around internal communication, the degree of innovation of the lodging facility, the after-

Many studies have shown that the underlying technologies are flexible (not of a Cobb–Douglas form) and have proposed other more flexible functional forms, such as the widely-used translog formulation

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(Karlaftis, 2009; Jarboui, 2014b; Jarboui et al. 2013a). Translog form is a relatively flexible functional form because it does not require assumptions about production constant elasticity or substitution elasticity between the inputs. Baten et al. (2009) and Jarboui et al. (2013a,b, 2014b) have shown that the translog production function form is preferable to the Cobb–Douglas form. The translog form allows the data to indicate the real curve of the function, rather than imposing a priori assumptions. This can be expressed as Eq. (4). XM α ln x jit lnYit ¼ α0 þ j¼1 j 1 XM XM þ α ln x jit ln xkit þ Vit −Uit : j¼1 K¼1 jk 2

ð9Þ

Therefore, we adopt the stochastic frontier analysis (SFA) model and a translog functional form of production function; also we introduce the governance variables to explain the hotel's performance.

4.4. Data To empirically test our research hypotheses, we used a sample of 63 hotel units, located throughout the Tunisian coast, some belonging to hotel groups and others not, belonging to the category of 4-and-5-star hotels. The institutions under study were selected from a comprehensive list of hotels located in Tunisia provided by the Tunisian National Office of Tourism. Our data collection tool was the questionnaire during 2011– 2012 period, with some open questions and other closed ones sent to hotel managers and, where appropriate, the administrative staff present, also followed by interviews with managers, key players in our investigation, subsequently to the submission of the questionnaire. We note that, on average, the firms in our sample have Boards of Directors composed of six directors, including two outside directors; the latter have the experience required in the context of their positions up to 79%. The results also show that the maximum number of Board meetings is 6 meetings per year, whereas for most hotel businesses, the average number of annual meetings is 3. As regards the term of office of the director, it is 3 years on average. We find that the average number of years of presence of the same manager in the same hotel firm is 9 years. For the entire sample, the youngest manager at the head of the business is 45 years old, while the eldest of all directors is 80 years old. We note that the average managerial participation is 23% equity versus 17% for institutional managers and 21% shareholding managers. Regarding changes in the structure of the Board and for the 63 hotels surveyed, the descriptive statistics show that 69% of tourist firms have a strategy committee versus 31%. The results below testify that 38 tourist establishments have a committee of GEs in their Boards of Directors versus 25 firms that do not have one. We note that in 60% of the hotel businesses, there is a clear separation between the positions of CEO and Chairman of the Board. We note that 80% of the firms in our sample are from groups consisting of at least 2 units and a maximum of 80 firms, which gives us an average of 7 hotels per group, versus 20% which are Tunisian tourism businesses established by and belonging to a single owner.

5. Results and discussion The coefficients and the efficiency scores of hotels are estimated using the program “Frontier 4.1” (Battese & Coelli, 1995). This program provides the parameter estimates of equations and measures the efficiency scores of each hotel.

5.1. Results and discussion of the analysis of the stochastic frontier In our study, we will base ourselves on the method of maximum likelihood which consists in selecting for an estimate, the value that has the highest probability of causing the appearance of values actually observed in the sample. The “Size of Board of Directors” “TCA” exogenous variable is not significant for any kind of performance; hence the rejection of our first hypothesis. Indeed, in our context, the positive impact of the size of the Board on the performance of the firm does not hold, contrary to what has been reported in the literature including Adams and Mehran (2005). In this case, this could be explained by the fact that the larger the Board, the greater the existence of problems of asymmetric information, poor coordination and conflicts of interest that may be mentioned. Therefore, the latter constitute an obstacle to social performance, and subsequently to organizational and overall performance. Our second hypothesis dealing with the relationship between the number of outside directors present in the Board, and the performance of the hotel business is verified. In fact, and in accordance with our theoretical background (Jarboui et al., 2014; Rosenstein & Wyatt, 1990), the integration of a new outside director is a source of success. With reference to the above table, we see that this variable records a positive and significant impact at the threshold of 1% on the overall performance (2.832). The latter is our sixth model, which includes all the variables explaining the different performance measurements. Different estimates of the frontiers representing the performance models tell us that the variable “SFPDGPCA” affects positively and significantly at the threshold of 1% the performance relating to internal process of the hotel firm (2.331), the social performance (2.763) and the overall performance (3.103). Not surprisingly, our third hypothesis is true; in the hotel industry, the separation of these two functions greatly reduces the agency problems, in the sense that the information asymmetry is reduced. The CEO will be more devoted to taking into account the suggestions of staff, which will result in an improvement in collective competence, a boost in motivation, and obviously a reduction in turnover. Our result shows that the third hypothesis is verified. According to Table 2, we can remark that the various estimated frontiers teach us that the variable “separation of functions CEO/Chairman of the Directors Board” affects positively and significantly at 1% the performance relative to the internal process (2.331), social performance (2.763) and overall performance (3.103). Not surprisingly, in the hotel industry the separation of these two functions significantly reduces the agency problems. The CEO will focus more to the consideration of staff suggestions which will result in improving the collective competence, the emphasis of motivation and probably reducing turnover. Hypothesis 4 is amply verified since the exogenous variable showing the presence of an appointing committee within the hotel firm affects positively and significantly at the threshold of 1% the financial performance (4.993), the economic performance (3.646), the social performance (2.453) and thus, the overall performance (12.40). Our fifth hypothesis being verified deals with the subject of the shareholding of the manager and its close connection with the performance of the firm concerned. With reference to our results, we find that the variable “share of ownership of the manager” affects positively and significantly at the threshold of 1% (2.412) the financial performance. Indeed, and in line with our theoretical background, we note that in the hotel industry, and in the tourist businesses surveyed, the more the share of the manager in the capital grows, the more the financial performance of the latter improves. This proves that the primary concern of the director is increased revenue, reduced costs, higher returns on assets and equity. As for the performance related to the increase of market share, the “shareholding manager” variable affects it significantly but rather negatively at the threshold of 5% (2.142). The objective of the shareholders to acquire new market shares is rather a goal for the long

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Table 1 Descriptive statistics of the variables related to the mechanisms of corporate governance. Variables

Minimum

Maximum

Average

Standard deviation

TCA (number of directors on Board) NAEXT (number of outside directors) NRCA (number of Board meetings/year) DMAD (term of office of director) NATDEH (years of manager's work/hotel) AGED (age of the manager) PPM (proportion of managerial ownership) PPINSTI (proportion of institutional ownership) PACTID (share of ownership of manager) CGEASCA (existence of a corporate governance committee within the Board) CSTRAASCA (existence of a strategy committee within the Board) CNOMMI (existence of an appointing committee) SFPDGPCA (separation between the positions of CEO and Chairman of the Board of Directors) EXPACP (experience of the managers in connection with their positions) FAIT PGH (studied hotel unit is part of a hotel group or not) Nr UNIT (number of units that make up the group)

0.00 0.00 0.00 0.00 0.00 45.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.00

12.00 4.00 6.00 5.00 25.00 80.00 100.00 80.00 100.00 1.00 1.00 1.00 1.00 1.00 1.00 80.00

5.8889 1.7778 3.2857 3.0000 9.5079 59.3492 23.0635 16.8889 21.7619 .6190 .6984 .5397 .6032 .7937 .8095 6.7937

2.57852 1.21076 1.39618 1.20483 6.22656 7.39476 25.30770 16.19848 23.35402 .48952 .46263 .50243 .49317 .40793 .39583 11.09658

term. In this case, this is not in line with the intentions of the manager, the latter, seeking to get further entrenched, rather opts for short-term performance. The marked increase in institutional holdings in business capital pushes us to seek the why and how of things. Given the progress in the literature, the emergence of this phenomenon proves to be fruitful, in the sense that the larger the share of the institutional grows, the more

the company concerned is likely to significantly improve its performance (Duggal & Miller, 1999). Indeed, seeking above all to recoup their investments, the institutional bodies act in the same manner as the main shareholders of the firm. From the table above, we find that the variable (PPINSTI) significantly, but negatively, affects at the threshold of 10% (1807) the financial performance, hence the rejection of our sixth hypothesis. This is explained by the fact that certain

Table 2 Estimated parameters for the performance models. Variables

Parameter

M1 (PF)

M2 (AVPM)

M3 (DSC)

M4 (DICIFC)

M5 (PSPCCTM)

M6 (PG)

CONSTANT

Β0

TCA

Β1

NAEXT

Β2

NRCA

Β3

DMAD

Β4

NATDEH

Β5

1.140 (2.057) −0.066 (−1.169) −0.154 (−1.326) 0.365 (3.890)⁎⁎⁎ −0.0837 (−0.673) −0.054 (3.920)⁎⁎⁎

3.176 (3.282) −0.082 (−1.150) 0.023 (0.209) −0.055 (−0.892) −0.172 (−1.127) 0.0699 (5.910)⁎⁎⁎

−2.10 (−1.372) −0.104 (−1.348) 0.132 (1.043) −0.164 (−1.251) 0.059 (0.353) 0.072 (3.751)⁎⁎⁎

Β6

PPM

Β7

PPINSTI

Β8

PACTD

Β9

CGEASCA

Β10

CSTRAASCA

Β11

CNOMMI

Β12

SFPDGPCA

Β13

EXPACP

Β14

FAIT PGH

Β15

UNIT NR

Β16

0.025 (1.719) 0.005 (0.866) −0.003 (−0.490) −0.006 (−0.905) 0.125 (0.382) −0.348 (−1.037) 0.444 (1.591) 0.719 (2.331)⁎⁎⁎ −0.274 (−0.859) 0.304 (1.055) 0.027 (2.611)⁎⁎⁎

Gamma

(Y)

−0.025 (−1.832)⁎ 0.006 (1.249) −0.005 (−1.006) −0.011 (−1.20) −0.295 (−0.667) −0.594 (−1.319) 0.346 (1.50) 0.424 (1.229) 0.142 (0.411) 0.242 (0.722) −0.001 (−0.194) 0.999

−0.474 (−0.583) −0.069 (−0.979) −0.078 (−0.660) −0.146 (−1.191) −0.042 (−0.273) 0.039 (2.118)⁎⁎ 0.004 (0.315) −0.003 (−0.482) 0.003 (0.433) 0.008 (1.217) 0.087 (0.208) −0.185 (−0.450) 0.731 (2.453)⁎⁎⁎

1.043 (2.786) 0.051 (1.677) 0.238 (2.832)⁎⁎⁎ 0.132 (2.849)⁎⁎⁎ −0.009 (−0.141) −0.079 (6.835)⁎⁎⁎

AGED

−0.434 (−0.395) −0.067 (−0.962) −0.050 (−0.437) 0.031 (0.267) 0.142 (0.951) −0.066 (3.385)⁎⁎⁎ 0.011 (0.944) 0.018 (3.385)⁎⁎⁎ 0.002 (0.388) −0.0134 (2.147)⁎⁎

See Table 1 with fuller labels. t statistics is presented between brackets. ⁎ Significant at the 10% level. ⁎⁎ Significant at the 5% level. ⁎⁎⁎ Significant at the 1% level.

−0.007 (−0.751) 0.003 (1.610) −0.012 (1.807)⁎ 0.005 (2.412)⁎⁎⁎ 0.224 (0.915) 0.482 (1.727) 1.024 (4.993)⁎⁎⁎ 0.069 (0.264) −0.708 (2.614)⁎⁎⁎ −0.136 (−0.656) 0.0001 (0.010) 0.999

0.368 (1.249) 0.311 (1.020) 0.899 (3.646)⁎⁎⁎ −0.178 (−0.642) −0.382 (−1.321) −0.282 (−1.060) −0.022 (2.315)⁎⁎⁎ 0.861

0.635

0.826 (2.763)⁎⁎⁎ 0.185 (0.616) 0.507 (1.739) 0.014 (1.365) 0.758

−0.002 (−0.295) 0.011 (13.764)⁎⁎⁎ −0.002 (−0.745) −0.002 (−0.982) 0.545 (2.415)⁎⁎⁎ −0.086 (−0.362) 1.254 (12.40)⁎⁎⁎ 0.278 (3.103)⁎⁎⁎ −0.267 (−1.591) −0.304 (2.709)⁎⁎⁎ −0.018 (10.801)⁎⁎⁎ 0.999

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institutional bodies prefer to remain passive about the control procedures related to the manager. They do not interfere there under the pretext that this task generates cost, as was demonstrated by Cosh and Hughes (1997) in their study. As part of our research, this result could possibly be explained by the fact that, within the hotel units studied, there is a complete separation between power and property. We note that the control variable (done PGH) significantly but negatively affects at the threshold of 1% the overall performance of each hotel. Thus, if the tourist business is an integral part of a large hotel group, this is not really an asset to achieve the desired performance. However, it should focus on its strategic policy, on the implementation of a “good” corporate governance in order to achieve its goals, regardless of membership or not in a hotel group. With regard to the second control variable, it is the number of units in the group. From our results, we find that this variable significantly and negatively affects at the threshold of 1% (2.315) the possibility for the company to increase its market share. Indeed, the fact that we are concerned with hotels offering similar services at close prices causes the market shares where the target audience is situated to be divided among the units of a single group. To gain ground against its counterparts, a hotel business should therefore distinguish and differentiate itself to ensure a monopoly position. However, this variable affects significantly and positively at the threshold of 1% (2.611) social performance. This seems to us quite logical; when a hotel group is composed of several units that work together in the right direction and aims to achieve a single objective, there should be an excellent internal communication between executives, a sufficiently developed and updated sense of innovation and continuous training should be guaranteed for all personnel, hence the positive relationship between the control variable and human performance. 5.2. Estimation of efficiency scores The inefficiency calculated for each hotel unit varies between 0 and infinity. The efficiency in turn is measured by its opposite that varies between 0 and unity. The variation of efficiency scores based on the type of performance measured over the period of study varies from a hotel firm to another, as we can see in Table 3. We can say that the Tunisian tourism sector is reaching its maximum level of efficiency, particularly at the level of social performance (0.9967), followed by economic performance (0.9943), financial performance (0.7896) and finally, the internal process performance. Our exogenous variables relative to hotel corporate governance explain to the best the social and human performance. The figure below as well as our results show that the degree of efficiency of financial performance is less important than the human and organizational social performance (Fig. 1). This is explained by the fact that the financial indicators now reflect more the actual situation of the hotel business. Relying on and referring only to figures to assess the success or non-success of an enterprise is now insufficient. The efficiency of the overall performance of our 63 hotel units covering all the aspects mentioned in the literature on the concept of performance is as follows (Fig. 2): On the sample of 63 tourist businesses, some are perfectly efficient and are therefore on the straight line of efficiency we see in the graph above. For underperforming hotel units, the efficiency indices are beyond the line of efficiency. The index varies between 0.105 and 1; the observed inefficiency is the result of events beyond the control of the manager, beyond the governance mechanisms aimed at establishing order, or simply emanating from the environment. 6. Conclusion The purpose of this study is to measure the overall performance of 63 hotel units in our sample, and explain it in terms of the corporate

Table 3 Estimation of efficiency scores. Hotel unit

M1

M2

M3

M4

M5

M6

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 Average efficiency

1 1 0.343 0.102 2.495 0.881 1 1 0.529 0.999 0.616 1 1 1.766 0.973 1.783 1 0.534 0.157 0.83 0.47 0.509 1 1 1 1 0.182 1 1.828 1 0.783 0.528 0.217 0.279 0.636 0.246 0.995 0.189 0.545 0.493 0.994 0.459 0.619 0.578 0.912 0.639 0.698 0.939 1 0.873 1 0.226 1 0.556 0.634 0.833 0.946 0.498 0.566 0.633 0.234 1 1 0.7896

1 1 1 1 1 0.997 1 1 0.989 1 1 1 1 1 1 1 1 0.997 0.993 0.995 1 0.986 1 1 1 1 1 1 0.896 1 1 0.997 0.996 0.998 1 0.994 0.996 1 0.997 0.997 0.992 0.997 0.993 0.995 0.986 0.996 0.996 0.994 1 0.99 1 0.997 1 0.966 1 0.997 0.995 0.996 0.993 0.994 0.986 0.969 0.964 0.9943

0.135 0.827 0.969 0.696 0.26 0.82 0.727 0.469 0.279 0.972 0.115 0.975 0.694 0.99 0.173 0.827 0.437 0.502 0.686 0.958 0.542 0.459 0.154 0.323 0.335 0.14 0.104 0.498 0.546 0.316 0.999 0.819 0.387 0.298 0.732 0.122 0.465 0.166 1 0.107 0.611 1 0.324 0.967 0.558 0.819 0.519 0.433 1 1 1 0.336 1 1 0.549 0.657 0.899 1 0.536 0.47 0.425 1 0.799 0.6019

0.994 0.995 1 0.998 0.998 0.996 0.995 0.999 1 1 1 1 0.998 1 1 0.996 1 1 0.99 0.988 0.967 0.994 0.996 0.997 1 0.998 0.998 0.998 0.998 0.997 0.999 0.993 0.993 0.998 0.995 1 1 1 1 0.994 0.995 1 1 1 0.998 1 1 1 0.994 1 1 1 1 1 1 0.982 1 0.948 1 1 1 1 1 0.9967

0.118 0.646 0.265 0.814 0.0143 0.719 0.367 0.865 1 0.205 1 1 0.511 0.43 0.747 0.149 1 0.392 0.641 0.278 0.266 0.726 0.464 0.691 0.705 0.172 0.6 0.639 0.667 0.965 0.161 0.304 0.514 0.856 0.847 0.421 1 0.112 1 0.205 0.784 0.297 0.413 0.436 0.214 0.454 0.106 0.616 0.871 1 1 0.121 1 1 1 0.161 0.641 0.17 0.612 0.124 0.676 1 0.191 0.5613

1 1 0.15 1 1 0.998 1 1 0.354 0.175 0.998 0.139 1 0.823 0.981 1 1 0.283 0.159 0.961 0.105 0.358 1 0.168 1 0.324 0.32 1 0.154 1 0.144 0.635 0.272 0.413 0.997 0.14 0.819 0.649 0.632 0.567 0.999 0.561 0.701 0.972 0.999 0.588 0.362 0.587 0.992 0.985 1 0.108 1 0.487 0.892 0.826 0.821 0.524 0.452 0.307 0.351 0.209 0.527 0.6502

governance mechanisms implemented. To this end, we used a stochastic frontier model to assess the degree of efficiency of each lodging facility. During the presentation of the model parameters, we assumed that the inefficiency generated is constant over time for all firms. Thus, this analysis helped to present the 6 models, measuring their performance, which is in the case of multi-criteria species,

H. Guetat et al. / Tourism Management Perspectives 15 (2015) 128–136

References

Average efficiency 1.2 1 0.8 0.6 0.4 0.2 0 M1

M2

M3

M4

M5

M6

Fig. 1. Evolution of efficiency depending on the type of performance measured.

and to highlight the variables attributed to corporate governance that affect it considerably. The empirical results of our research show that the improved level of firm efficiency depends on board characteristics, ownership structure and CEO characteristics. As for the evolution of efficiency, results suggest that corporate governance mechanisms have an impact on hotels' performance. After estimation by maximum likelihood, we found factors explaining firm efficiency such as the independent directors' board and dual structure which improve the competence and commitment of leaders to foster to greater hotel performance. Other factors such as managerial characteristics increasingly appear to influence firm efficiency. The results of these studies corroborate our predictions, necessarily drawn from the literature review and shape the practice, which is here the Tunisian hotel sector. The close and direct link between corporate governance and its impact on the overall performance indeed exists. We can say that practicing good governance, which hitherto has been neglected, strengthens performance as a whole. Like any research, this study has some limitations that should be noted: the first one is the relatively small size of our sample. The second limitation concerns the small number of factors utilized to explain the level of hotels' performance. Nevertheless, this work can be considered a starting point for further research. More specifically, two main research perspectives can be outlined; the first is to add other governance variables, macro-economic variables and structural variables in the firm inefficiency term, given the importance of these variables in explaining the level of firm efficiency. A comparison could also be conducted with what is practiced in other countries, particularly emerging countries.

overall efficiency 1.2 1 0.8 0.6 0.4 0.2 0 0

20

40

135

60

Fig. 2. Scatter plot describing the overall performance.

80

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Wang, J., & Zhou, H. (2011). Corporate governance and operating performance of Chinese listed firms. Journal of International Accounting, Auditing and Taxation, 152, 9–17. Weigert, M. (2012). Le tourisme en Tunisie: Les défis à l'heure de la transition démoncratique. IPEMED. Hazar Guetat is a Ph.D. in the field of management and a member in Unit of Research in Applied Economics (URECA) Sfax — Tunisia. Her current research interests include Tourism studies, efficiency and productivity analysis, and corporate governance.

Sami Jarboui is a researcher in Transport Economics, Laboratory of Transport Economics (LET), ENTPE, University of Lyon, France; and a member in Unit of Research in Applied Economics (URECA) Sfax — Tunisia. He is an Assistant professor of Economics at the Faculty of Economics and Management, University of Sfax — Tunisia. His main field of interest is transport policies evaluation through the issues of mobility behavior, accessibility, energy consumption and Environmental Economics.

Younes Boujelbene is a professor of quantitative methods and Economics at the Faculty of Economics and Management, University of Sfax — Tunisia. His main research interests are Efficiency and performance of public sector, Transport Economics, environmental-energy economics and applied econometrics. He is the Director of Unit of Research in Applied Economics (URECA), University of Sfax — Tunisia.