control variable in percent that represents the local demand conditions for lodging within the same area of hotel i at time t (measured by hotel occupancy rate); PAi,t is the value of a physical asset in year t constant dollars for hotel i at time t scaled by the number of rooms; SCi,t is the expenditure on management fees in year t constant dollars of hotel i at time t scaled by the number of rooms; CCi,t is the expenditure on marketing, branding, franchising fees in year t constant dollars of hotel i at time t scaled by the number of rooms; HCi,t is the expenditure on employees in year t constant dollars of hotel i at time t scaled by the number of rooms.
3.4 Variables Definition
To perform the estimation, three measures of intellectual capital were applied. Except these measures, numerous control variables were formulated to control for environment conditions and tangible assets investments. Besides, it is widely known that there is a positive relationship between property size and earnings, and this study examines hotels of various sizes (different number of rooms available in the property), so all hotel property specific variables, including dependent and independent ones, were scaled by the annual number of rooms available for sale in each hotel.
Dependent variable
Firm performance in the model was measured by the annual operating income before interest expense, depreciation, amortization and taxes (EBITDA), scaled by the number of rooms available for sale (Lev and Sougiannis, 1996; P. 111). It is intended to measure and enable profitability comparison between different companies by canceling the effects of different asset bases (by cancelling depreciation), different takeover histories (by cancelling amortization), effects due to different tax structures, as well as the effects of different capital structures (by cancelling interest payments).
EBITDA of a company gives an indication on the operational profitability of the business, how much profit does it make with its present assets and its operations on the products it produces and sells, taking into account possible provisions that need to be carried out. It is widely viewed by service industry analysts, researchers and practitioners as the predominant measure of performance (Schimgall, 2006).
Independent variables
Intellectual capital was categorized into three measures by the expenditures associated with investment in human capital, customer capital and structural capital.
Customer capital was measured by the annual expenditure on marketing, advertising and promotion plus fees hotels pay to their external brand franchisors for marketing services or royalty fees.
Systems capital was measured by using the annual management fee in financial reports, which each hotel pays to an external management company for technical and design advisory, consultancy, management services, establishment and maintenance of all operational systems, policies and procedures.
Human capital in hospitality industry and other customer service firms is principally an investment into employee salaries, wages and retirement program for both service and professional employees (including employees working in revenue-generating departments: front desk, restaurant; non-income-producing departments: laundry, engineering; and back-office support departments: accounting, human resources, marketing).
Control variables
Even though all the sampling hotels come from the same country, environmental conditions of different cities or areas still differ, what can influence firm performance, so local economic factors were controlled.
Variation in the cost of living influences not only the comparison of hotels in different areas or measurement of human capital investment, such as employee salaries and wages, but also impacts the pricing structure of a hotel. Through influencing the price, it also shapes the revenue, furthermore revenue depends on both price and volume, and eventually EBITDA of a property is also impacted. Given the upper reasoning, we find it essential to control the cost of living for each hotel, what in the current research was made using Consumer Price Index, obtained from Directorate General of Budget, Accounting and Statistics, Executive Yuan, R.O.C.
Geographical location is a factor that directly influences local market demand for lodging and impacts rooms’ revenue through turnover rate (volume in revenue formula), hence has to be controlled. In some geographic areas hotels are always full,
however in other areas the rooms might be half-empty. To control for differences in market demand across geographic locations the annual local occupancy rates for lodging in different geographic areas where the sample hotels operated was obtained from Tourism Bureau in Taiwan.
The data we use in our research model is not only cross-sectional (hotel properties), but also represents time series (2009-2011), thus year-specific heterogeneity has to be controlled. So, dummy variables were devised over the period from 2009 to 2011.
Probably one of the most critical variables that have to be controlled is the tangible asset- property by itself. To significantly study the impact of intellectual capital on hotel profitability, the researcher had to control for physical asset. Eventually we used the book value of the property.
To control the effect of firm size on its profitability can be completed through two different approaches. One is to scale each variable (dependent and independent, control variables) by the number of rooms in a property. In this case the comparison would be presented through profitability per room and investments done per room.
The second way is to accomplish control through another control variable- number of employees. However in this case we would compare the performances per rooms and investments per rooms. This approach is more suitable to our research model, because we are focused not only on the employees and their outcome, but also on customer capital and structural capital. Besides, it is a reasonable assumption that recruited number of employees has positive linear correlation with the size of hotel. Hence by scaling the variables by number of rooms, including measures of physical property of a hotel and environment influences reassure that the research model is appropriately specified and noises are finely controlled.
Chapter Four
Analysis of Empirical Research
This chapter presents the analysis and results of data collected from the financial annual reports of Taiwan listed hotels. The sections in this study include: (1) description of the research participants, (2) analysis of correlation between firm performance and intellectual capital given different strategic orientation, (3) analysis of inter-correlation between different types of intellectual capital, (4) analysis of intellectual capital impact on hotel profitability for firms with different strategic orientation.
4.1 Descriptive Data Analysis
The Table 4.1 summarizes descriptive results of hotels pursuing low-cost leadership and differentiation strategic orientation. First of all, the table shows cost advantage of low-cost leaders over differentiators (operating expense ratio mean = 0.613 vs. 0.964 respectively), overall, minimum coefficient of operating expense ratio is 0.4263 and maximum is 1.33, while average mean of 33 observations = 0.8363, what indicates that low-cost leaders’ cost advantage mean (0.613) is lower than average industry result, on the opposite side, cost advantage mean of differentiators (0.964) is greater than the average result. The difference in cost advantage mostly results from difference in operating expenses scaled by net sales. Differentiators spend more on categories unrelated directly to producing or manufacturing a good or service.
Secondly, Table 4.1 illustrates the difference of room pricing of the hotels pursuing different strategic orientation. The prices of differentiators are higher than prices of cost-leaders (mean difference is 831 NTD). Results are consisted with the theory that hotels with differentiation strategies orientation are charging higher prices. However, we should notice that prices per room are highly distributed, especially of hotels pursuing differentiation strategic orientation (SD= 2655).
So, there were 4 hotels, whose operating expense ratio was lower than average mean of 0.8363 and three of them charged a price lower than total sample mean price (NTD5075).
Table 4.1
Descriptive Statistics
Low-cost leaders (n=12) Differentiators (n=21) Differentiation- Cost Leadership
In hypothesis 1 we predicted that there would be difference in profitability between differentiation-oriented and cost leadership-oriented firms. According to comparative analysis summarized in Table 4.1, Hypothesis 1 is accepted. Net operating income, which represents firm profitability, differed greatly between cost-leaders and differentiators (350.8 vs. 1350 respectively). Result indicated that hotels pursuing differentiation strategic orientation succeeded to gain greater financial profitability than those who practiced low-cost strategy (mean difference = NTD 999.2).
As for the intangible assets, then investment differs impressively. Standard deviation of intellectual capital expenditure (especially for differentiators) is greatly distributed, meaning that some hotels spend more, some- less. However the investment difference
between hotels with different strategic orientation is very big. For example, investment in structural capital has the mean of 834 and represents the biggest amount among investment categories, differs from 12 to 2975 and has standard deviation of 1003. Additionally, expenditure on systems capital is much bigger of hotels that pursue differentiation strategy than low-cost strategy (mean of 834 vs. 156.1).
For low-cost oriented lodgers the highest mean among three intellectual capital investment categories is 166.3 for investment in human capital. It is also a variable with relatively low compared to other intellectual capital representatives standard deviation equal to 38.7.
In general, the descriptive statistics of the variables in the study show that high expenditure on intangible assets is more a characteristic of the differentiation oriented hotels than low-cost leaders. There is a significant difference that must be noticed.
Descriptive statistics showed that for both groups physical asset is the category that requires the highest capital input. Physical assets are the variables with the greatest standard deviation. Differentiation oriented hoteliers’ mean of tangible assets is about 400% higher than of low-cost leaders (mean difference = 4542), indicating that expenditure not only on intangible, but also on tangible assets is a characteristic of hotels pursuing differentiation strategic orientation.
Results estimated no difference in location-specific cost of living category for two groups of hotels; the reason is one country focus - Taiwan. Besides, the majority of Taiwanese listed hotels are situated in the down town area, where location-specific cost of living is the same. Still there is an internal difference in deviation of the estimates: differentiators’ standard deviation is only 0.215, but cost-leaders’ standard deviation is equal to 1.004 which shows that low-cost leaders are more distributed in terms of location with higher and lower consumer price index, while differentiators are gathered in those places with higher cost of living.
Descriptive statistics analysis showed that even though there is no big difference between the market demand for low-cost lodging and differentiated accommodation on average, there is still difference inside. It seems that demand for low-cost leaders is
more deviated than for differentiators, meaning that occupancy rate of the second group is more consistent.