Farrell (1957) pioneered dividing cost efficiency into technical efficiency and allocative efficiency. The technical efficiency evaluates the ability of a firm to obtaining maximal output from a given set of inputs and the allocative efficiency the ability of a firm to use the inputs in optimal proportions, given their respective prices and the production technology. These two measures are combined to provide a measure of total economic efficiency. The theories of efficiency measurement are very important in economics, and also commonly and extensively used for other industrial applications. For example, studies of hotel efficiency are currently being conducted.
In general, the two primary methods that have been used in efficiency estimation are the stochastic frontier approach (SFA) and data envelopment analysis (DEA). The literatures reviewed are grouped according to these two methods.
3.1 Papers based on SFA
A few papers that used SFA in the hotel industry are summarized as follows:
Anderson et al. (1999) employed a stochastic frontier technique to estimate managerial efficiency of 48 hotels in the United States in 1994. They defined inputs as the number of full-time equivalent employees, the number of rooms, total gaming related expenses, total food and beverage expenses, and other expenses, while defining output as the total revenue generated from rooms, gaming, food and beverages, and others.
The price of labor was calculated as the total hotel revenue per full-time equivalent employee. The room price was measured by hotel revenues divided by the product of the number of rooms, the occupancy rate, and days per year. The price of gaming, food and beverages, and other expenses were all calculated by measuring each as a percentage of total revenue. They found the hotel industry to be operating at an 89%
efficiency level. In particular, the average efficiency was estimated at 89.4%, with the most and least efficient hotels operating at 92.1% and 84.3% efficiency levels,
respectively.
Anderson et al. (1999) applied both DEA and SFA to estimate the efficiency of 31 corporate travel management departments. They defined three inputs: the total expense of air, hotel, and car; labor expense, which includes the cost of exempt labor, hourly labor, and part-time labor; and other expenses, which include fee expense, technology costs, and building and occupancy expense. Their inputs were transformed into prices by dividing the three input categories by the number of trips. The output was the number of trips.
Barros (2004) employed a stochastic cost frontier in Portugual’s hotel industry.
He used a balanced-panel data during 1999-2001 to estimate a stochastic generalized Cobb-Douglas cost function with three inputs and two outputs. Those three inputs were prices of labor, capital and food while the two outputs were sales and nights occupied. In addition, a dummy variable was used to account for the distinction between historical Pousadas and regional Pousadas. The research found that the results were at best mixed, since the efficiency scores were low and not time-varying.
For this reason, the author suggested an alteration of management procedures to enable an increase in efficiency, based on a governance environment framework.
Wang et al. (2007) used a one-stage stochastic frontier approach to measure the relative efficiency of 66 international tourist hotels in Taiwan during 1992-2002 and to investigate the determinants of technical efficiency. They also added the Malmquist productivity index to estimate the range and the cause of the productivity change.
They used the following four inputs, salaries, the area of food and beverage, the number of rooms, and other operating expenses, and the following three outputs, the number of room occupied, food and beverage revenue, and other operating revenue. Their empirical results revealed that the government policy increasing weekend vacation time has fostered domestic travel and expanded hotel industry. The local government’s
other expenditures had a significantly positive effect on international tourist hotel’s efficiency.
Chen (2007) adopted a stochastic cost frontier to analyze the cost efficiency of 55 international tourist hotels in Taiwan. He used three inputs (labor, food and beverage, and materials) and one output (the total revenue) to measure hotel efficiency. In his result, the factor of operation type not only can affect hotel efficiency significantly, but also can be used to analyze whether the efficiency of the chain hotels is higher than that of independent hotels.
3.2 Papers based on DEA
DEA has been employed by a good number of studies. They are summarized as follows:
Bell and Morey (1995) adopted DEA to analyze the efficiency of 31 corporate travel departments. The inputs used are the actual levels of expenditure for travel, i.e., air, hotel and rental cars, nominal levels of other expenditure, the level of environmental factors, i.e., ease of negotiating discounts, percentage of legs with commuter flights required and actual levels of support cost for labor, technology, fees, space, etc. One output used is the level of service provided, which is either excellent or average.
Morey and Dittman (1995) also used DEA with nine inputs and four outputs to analyze the efficiency of 54 hotels in the United States. The nine inputs used are room division expenditure, energy costs, salaries, non-salary expenses for property, salaries and related expenses for variable advertising, non-salary expenses for variable advertising, fixed market expenditures, payroll and related expenses for administrative work, and non-salary expenses for administrative work. The four outputs used are total revenue, level of service delivered, market share, and the rate of growth.
Anderson et al. (2000) employed DEA with their input-output data to analyze the efficiency of 48 hotels in the United States and to estimate the allocative, technical, pure
technical levels. The inputs used are full-time equivalent employees, the number of rooms, total gaming-related expenses, total food and beverage expenses, and other expenses. One output used is total revenue, which is generated from rooms, gaming, food and beverages, and other revenues. Their results indicated that the hotel industry was inefficient with a mean overall efficiency measure of approximately 42%.
Literatures that adopted DEA to analyze the efficiency of the hotel industry in Taiwan included Tsaur (2001), Hwang and Chang (2003), and Chiang et al. (2004).
These papers are reviewed as follows:
Tsaur (2001) employed DEA with seven inputs and six outputs to analyze 53 international tourist hotels in Taiwan during 1996-1998. The seven inputs used were total operating expenses, the number of employees, the number of guest rooms, the total floor space of the catering division, the number of employees in the room division, the number of employees in the catering division, and catering cost. The six outputs used were total operating revenues, the number of rooms occupied, average daily rate, the average production value per employee in the catering division, total operating revenues of the room division, and total operating revenues of the catering division. Their results showed that the average operating efficiency score is 0.8733. However, 71.7%
of the international tourist hotels in Taiwan present relative inefficiency.
Hwang and Chang (2003) adopted DEA and added the Malmquist productivity index to measure and analyze the managerial performance in 45 Taiwanese hotels in 1998. They also explored the cause of efficiency change during 1994-1998. Their results revealed that the managerial efficiency of Taiwan’s international tourist hotels was related to the level of internationalization of the hotels.
The research of Chiang et al. (2004) was aimed at using DEA to measure hotel performance under three operational styles of international tourist hotels commonly seen in Taiwan since 2000: independently owned and operated, franchise licensed, and
managed by international hotel operators. The four inputs chosen by the hoteliers were hotel rooms, food and beverage capacity, number of employees, and total cost of the hotel. The three outputs were yielding index, food and beverage revenue, and miscellaneous revenue. They expected their results to provide hoteliers with a basis for constructing strategies and promotion plans. In addition, these results illustrated that not all of Taipei’s franchised or managed international tourist hotels performed more efficiently than the independent ones.
3.3 Tabular Summary
It is apparent that the above-mentioned bibliography is quite thin for such a major tourism issue. This paper departs from the previous literature in that it uses panel data of international tourist hotels in Taiwan, related to the years 1997–2006. Table 2 summarizes the previous studies on hotel efficiency.
Table 2. Recapitulation of studies on the hotel frontier efficiency
Paper Method Units Inputs Outputs
Bell and Morey (1995) DEA 31 corporate travel departments
Actual level of travel expenditure nominal level of other
expenditure
level of environmental factors actual level of labor costs
Level of service provided, qualified as excellent and average
Morey and Dittman (1995)
DEA 54 U.S. hotels Room division expenditure energy costs
Anderson et al. (1999a) Stochastic frontier approach
48 U.S. hotels Number of full-time equivalent employees
number of rooms
total gaming-related expenditure total food and beverage expenses other expenses
Anderson et al. (2000) DEA 48 U.S. hotels Full-time equivalent employees the number of rooms
total gaming-related expenses total food and beverage expenses other expenses the number of guest rooms the total floor space of catering division
the number of employees in the room division
the number of employees in the catering division value per employee in the catering division
Number of full time employees number of guest rooms total area of catering department operating expenses
Wang et al. (2007) Stochastic frontier approach
66 Taiwan hotels
Salaries
the area of food and beverage the number of rooms
price of food and beverage price of materials
Total revenue of hotel