CHAPTER 4 PROFITABILITY IN TAIWAN’S INTERNATIONAL TOURIST HOTEL INDUSTRY . 61
4.3.2 Empirical results
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hotels are the middle size. 14.9% of international tourist hotels are resort hotels. 59.3% of international tourist hotels are chain hotels. 30.4% of international tourist hotels mainly receive individual visitors and 61.1% simultaneously receive group and individual visitors.
4.3.2 Empirical results
This paper uses the net operating profit margin as the dependent variable, as well as the degree of market concentration, market share, pure technical efficiency, scale efficiency, hotel size, market condition, hotel type, visitor type, SARS and financial tsunami as independent variables to investigate the determinants of profitability and the tests of the market power and efficient structure theories. In order to examine the market power and efficient structure theories, this paper will divide the empirical model into three parts and progressively introduce the variables of the degree of market concentration, market share, as well as pure technical and scale efficiencies. First, the empirical model only uses the degree of market concentration, hotel size, market condition, hotel type, visitor type, SARS and financial tsunami as independent variables to represent the structure-conduct-performance hypothesis and expects the coefficient of the degree of market concentration to have a positive sign (Model 7). Second, the empirical model includes the independent variables used in Model 7 and the market share to represent the relative market power hypothesis and expects the coefficient of market share to have a positive sign (Model 8). Third, the empirical model includes all independent variables to examine hypothesis of Equations (4-2) to (4-6) (Model 9). Furthermore, this paper tries to investigate whether the market share is the proxy for efficiency or not. In other words, when the efficiency is added to the empirical model, whether the coefficient of market share will be transformed into the insignificance or not.
Before proceeding to the empirical work, these values of VIF are calculated to examine the degree of multicollinearity among independent variables. The result shows that the values of VIF are all below 4.77, indicating that the multicollinearity problem among independent variables is not serious.23 Since the data are the panel data that combine cross-section and time-series data, the Hausman test is applied to judge that the empirical model suits the random effects model or fixed effects model.24 The null hypothesis of this test is that the random effects model is suitable. The Hausman test results do not reject all the null
23 The VIF value is smaller than 5 for each independent variable with no serious correlation with each other; but there exists serious multicollinearity problem if the largest VIF value exceeds 10 (Greene, 2000).
24 Hsiao (1986) indicated that the random effects model or fixed effects model could solve the problem of biased and inconsistent coefficient estimates yielded by the pooled OLS regression.
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hypotheses in three models (see Table 4.2). Hence, the random effects model is appropriate to be used in Model 7 to 9.
The empirical results are presented in Table 4.2. The degree of market concentration in Model 7 and the degree of market concentration and market share in Model 8 do not have significant effects on profitability, implying that the structure-conduct-performance and relative market power hypotheses are not supported in Taiwan’s international tourist hotel industry. No matter the market power of the whole industry or the relative market power of individual international tourist hotel can not impact the net operating profit margins of international tourist hotels. In Model 9, the degree of market concentration, market share and pure technical efficiency do not have significant effects on profitability, but the scale efficiency has a positive effect on profitability at the 1% significant level. This result supports the scale efficiency hypothesis and indicates that an increase in the profitability results from the improvement of scale efficiency in the international tourist hotel industry. However, the improvement of management efficiency can not impact the profitability. The scale efficiency is a more important determinant of profitability in Taiwan’s international tourist hotel industry than either the degree of market concentration, market share or management efficiency. In addition, the pure technical and scale efficiencies increase the explanatory power from 5.6% to 13.6% in the empirical model.
The empirical results of other exogenous variables in Model 7 to 9 are the same. The dummy TYPE 2 that mainly receives individual visitors and the dummy TYPE 3 that simultaneously receives individual and group visitors are negative on the net operating profit margin, implying that gains from specialization in receiving group visitors dominate the gains from specialization in receiving individual visitors and diversification in simultaneously serving individual and group visitors. The specialization in receiving group visitors can help international tourist hotels to obtain the higher profitability. A possible explanation for this outcome is that international tourist hotels with mainly receiving group visitor can obtain more visitors once, and further increase the occupancy rate and profits. Consistent with the findings of Huang and Min (2002), Chen et al. (2005), Kim et al. (2006), Chen (2007b), Chen et al. (2007) and Wang (2009), natural disasters, terrorism and epidemics hurt the international tourism development in Taiwan. The SARS dummy has a negative effect on the net operating profit margin at the 1% significant level, indicating that demands for accommodation and F&B in international tourist hotels could be decreased in order to avoid SARS infection during the period of SARS prevalence. Hence, the profitability will be lower.
The financial tsunami has a negative effect on the net operating profit margin at the 1%
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significant level, implying that people may reduce the unnecessary expenditure in order to face the uncertainty of economic environment during the period of financial tsunami. Hence, the profitability will be decreased. In addition, the effect of SARS dummy on the profitability is larger than financial tsunami dummy. However, SARS occurred in March 2003 and gradually eased up after June 2006, but the financial tsunami was the most serious financial crisis within ten years and caused world economic recession. A possible explanation for this outcome is that mainland tourists are allowed to visit Taiwan from 2008, and then increase demands for accommodation and F&B in international tourist hotels and weaken the effect of financial tsunami.
4.4 Conclusions
The average net operating profit margin in the international tourist hotel industry does not have consistent trend with the rising trend of travel activities and the number of international tourist hotels. It first increased and then decreased. What are the possible factors? Is the market structure in the whole industry, the relative market power of individual international tourist hotel, the efficiency of individual international tourist hotel or other factors? This paper attempts to use a more conscientious method and model to find out possible answers for the above question. Based on the 2003-2009 data conducted by the Annual Operation of the International Tourist Hotels, the pure technical and scale efficiencies evaluated by utilizing the three-stage DEA with quasi-fixed inputs are included as independent variables of the profitability equation. Then, the determinants of profitability in Taiwan’s international tourist hotel industry are investigated.
The empirical results show that the scale efficiency hypothesis is supported in Taiwan’s international tourist hotel industry. An international tourist hotel that mainly receives individual visitors and an international tourist hotel that simultaneously receives group and individual visitors have negative impacts on profitability because mainly serving group visitors can help international tourist hotels to obtain more visitors once and increase their profitability. SARS has a negative effect on the profitability because avoiding SARS infection can cause a decrease in demands for accommodation and F&B in international tourist hotels.
The financial tsunami has a negative effect on profitability because the uncertainty of economic environment can cause a decrease in demands for accommodation and F&B in international tourist hotels. In addition, the effect of SARS dummy on the profitability is larger than financial tsunami dummy because the effect of financial tsunami is weakened by allowing mainland tourists to visit Taiwan.
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Some important lessons may emerge directly from the empirical results in this chapter.
First, managers may have to pay more attention to appropriately adjusting the operating scale since an increase in scale efficiency can enhance the profitability of international tourist hotels. Second, mangers must be more careful to face the changes of external environments because the negative changes of external environments hurt the efficiency and profitability of international tourist hotels. Finally, the information about service qualities, financial structure and the data of ordinary tourist hotels might be needed for the empirical results to be more reliable and the policy implications to be more meaningful.
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Table 4.1 Descriptive Statistics of Relevant Variables
Areas Variables Observations Mean SD Maximum Minimum Net operating profit margin 0.113 0.148 0.453 -0.457
CR4 0.432 0.018 0.454 0.409
MS 0.045 0.038 0.140 0.002
PTE 0.996 0.018 1 0.966
SE 0.636 0.296 1 0.080
SIZE 1 0.550 0.499 1 0
SIZE 2 0.350 0.479 1 0
RESORT 0.050 0.219 1 0
CHAIN 0.650 0.479 1 0
TYPE 2 0.236 0.426 1 0
Taipei City
TYPE 3
140
0.643 0.481 1 0
Net operating profit margin 0.021 0.079 0.158 -0.177
CR4 0.787 0.019 0.817 0.762
MS 0.154 0.094 0.348 0.031
PTE 0.971 0.044 1 0.839
SE 0.534 0.187 0.916 0.202
SIZE 1 0.500 0.506 1 0
SIZE 2 0.500 0.506 1 0
RESORT 0 0 0 0
CHAIN 0.500 0.506 1 0
TYPE 2 0.238 0.431 1 0
Kaohsiung City
TYPE 3
42
0.714 0.457 1 0
Net operating profit margin 0.060 0.177 0.292 -0.351
CR4 0.880 0.008 0.890 0.868
MS 0.200 0.070 0.305 0.094
PTE 0.998 0.008 1 0.954
SE 0.457 0.193 1 0.223
SIZE 1 0.600 0.497 1 0
SIZE 2 0.200 0.406 1 0
Taichung City
RESORT
35
0 0 0 0
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Table 4.1 (Continued)
Areas Variables Observations Mean SD Maximum Minimum
CHAIN 0.571 0.502 1 0
TYPE 2 0.486 0.507 1 0
Taichung City
TYPE 3
35
0.514 0.507 1 0
Net operating profit margin 0.137 0.080 0.241 0.040
CR4 1 0 1 1
MS 1 0 1 1
PTE 0.930 0.044 0.999 0.869
SE 0.345 0.080 0.446 0.220
SIZE 1 1 0 1 1
SIZE 2 0 0 0 0
RESORT 0 0 0 0
CHAIN 0 0 0 0
TYPE 2 0 0 0 0
Taoyuan City
TYPE 3
7
0 0 0 0
Net operating profit margin 0.077 0.060 0.157 -0.063
CR4 1 0 1 1
MS 0.500 0.187 0.718 0.282
PTE 0.968 0.029 1 0.913
SE 0.499 0.103 0.672 0.341
SIZE 1 0.786 0.426 1 0
SIZE 2 0 0 0 0
RESORT 0 0 0 0
CHAIN 1 0 1 1
TYPE 2 1 0 1 1
Hsinchu City
TYPE 3
14
0 0 0 0
Net operating profit margin 0.022 0.064 0.102 -0.160
CR4 1 0 1 1
MS 0.319 0.121 0.504 0.206
PTE 0.998 0.004 1 0.979
Hualien City
SE
21
0.355 0.149 0.613 0.213
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Table 4.1 (Continued)
Areas Variables Observations Mean SD Maximum Minimum
SIZE 1 1 0 1 1
SIZE 2 0 0 0 0
RESORT 0 0 0 0
CHAIN 0.333 0.483 1 0
TYPE 2 0.095 0.301 1 0
Hualien City
TYPE 3
21
0.857 0.359 1 0
Net operating profit margin -0.027 0.363 0.359 -0.672
CR4 1 0 1 1
MS 0.433 0.317 0.826 0.098
PTE 1 0 1 1
SE 0.525 0.382 1 0.134
SIZE 1 0.500 0.519 1 0
SIZE 2 0 0 0 0
RESORT 0 0 0 0
CHAIN 0.500 0.519 1 0
TYPE 2 0.357 0.497 1 0
Tainan City
TYPE 3
14
0.571 0.514 1 0
Net operating profit margin -0.042 0.092 0.080 -0.210
CR4 1 0 1 1
MS 1 0 1 1
PTE 0.964 0.011 0.988 0.955
SE 0.373 0.017 0.399 0.352
SIZE 1 1 0 1 1
SIZE 2 0 0 0 0
RESORT 0 0 0 0
CHAIN 0 0 0 0
TYPE 2 0.286 0.488 1 0
Taitung City
TYPE 3
7
0.714 0.488 1 0
Net operating profit margin -0.403 0.403 0.225 -1.360 Kaohsiung
County CR4 7
1 0 1 1
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Table 4.1 (Continued)
Areas Variables Observations Mean SD Maximum Minimum
MS 1 0 1 1
PTE 1 0 1 1
SE 0.234 0.025 0.255 0.182
SIZE 1 0 0 0 0
SIZE 2 0 0 0 0
RESORT 1 0 1 1
CHAIN 1 0 1 1
TYPE 2 0 0 0 0
Kaohsiung County
TYPE 3
7
1 0 1 1
Net operating profit margin 0.167 0.052 0.226 0.103
CR4 1 0 1 1
MS 0.787 0.096 1 0.721
PTE 0.997 0.007 1 0.981
SE 0.786 0.062 0.865 0.714
SIZE 1 1 0 1 1
SIZE 2 0 0 0 0
RESORT 0 0 0 0
CHAIN 0 0 0 0
TYPE 2 0 0 0 0
Hualien County
TYPE 3
7
1 0 1 1
Net operating profit margin 0.088 0.062 0.164 -0.061
CR4 1 0 1 1
MS 0.372 0.172 0.677 0.150
PTE 0.996 0.015 1 0.943
SE 0.453 0.106 0.604 0.293
SIZE 1 0.500 0.519 1 0
SIZE 2 0 0 0 0
RESORT 1 0 1 1
CHAIN 0.500 0.519 1 0
Tainan County
TYPE 2
14
0.786 0.426 1 0
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Table 4.1 (Continued)
Areas Variables Observations Mean SD Maximum Minimum Tainan
County
TYPE 3 14 0.214 0.426 1 0
Net operating profit margin 0.073 0.057 0.144 -0.007
CR4 1 0 1 1
MS 1 0 1 1
PTE 1 0 1 1
SE 0.418 0.053 0.491 0.346
SIZE 1 0 0 0 0
SIZE 2 0 0 0 0
RESORT 1 0 1 1
CHAIN 1 0 1 1
TYPE 2 0.286 0.488 1 0
Taitung County
TYPE 3
7
0.714 0.488 1 0
Net operating profit margin 0.149 0.062 0.264 0.035
CR4 1 0 1 1
MS 0.500 0.095 0.636 0.364
PTE 0.996 0.004 1 0.989
SE 0.641 0.077 0.725 0.523
SIZE 1 0.500 0.519 1 0
SIZE 2 0.500 0.519 1 0
RESORT 1 0 1 1
CHAIN 1 0 1 1
TYPE 2 0.286 0.469 1 0
Pingtung County
TYPE 3
14
0.714 0.469 1 0
Net operating profit margin 0.068 0.177 0.453 -1.360
CR4 0.718 0.256 1 0.409
MS 0.259 0.302 1 0.002
PTE 0.990 0.026 1 0.839
SE 0.546 0.258 1 0.080
Total
SIZE 1
329
0.587 0.493 1 0
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Table 4.1 (Continued)
Areas Variables Observations Mean SD Maximum Minimum
SIZE 2 0.255 0.437 1 0
RESORT 0.149 0.357 1 0
CHAIN 0.593 0.492 1 0
TYPE 2 0.304 0.461 1 0
Total
TYPE 3
329
0.611 0.488 1 0
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Table 4.2 Parameter Estimates of Profitability Equations
Independent variable Model 7 Model 8 Model 9
Constant 0.199**
(0.091)
Adj 0.053 0.056 0.136
Hausman test Notes: 1. The numbers in parentheses are standard errors.
2. ** and *** represent that the coefficients are significantly different from 0 at the 0.05 and 0.01 levels, respectively.
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Appendix 4A
Table 4A Data Descriptions of Relevant Variables
Variables Definition Dependent variable
Net operating profit margin The ratio of the net operating profit to total operating revenues independent variables
CR4 The ratio of revenues from top 4 international tourist hotels to total revenues of all international tourist hotels in the same city or county
MS The ratio of revenues from each international tourist hotel to total revenues of all international tourist hotels in the same city or county
PTE The pure technical efficiency estimated by the third stage of the three-stage DEA with the quasi-fixed input in Chapter 2
SE The scale efficiency estimated by the third stage of the three-stage DEA with the quasi-fixed input in Chapter 2
SIZE The dummy variable SIZE 1=1 indicates that the number of guest rooms is between 201 to 400 rooms; otherwise, SIZE 1=0. The dummy variable SIZE 2=1 indicates that the number of guest rooms is more than 401 rooms; otherwise, SIZE 2=0
RESORT The dummy variable RESORT=1 indicates that an international tourist hotel is the resort hotel; RESORT=0 indicates that an international tourist hotel is the city hotel
CHAIN The dummy variable CHAIN=1 indicates that an international tourist hotel is the international and/or domestic chain hotel; CHAIN=0 indicates that an international tourist hotel is the independent hotel
TYPE The dummy variable TYPE 2=1 indicates that international tourist hotels mainly receive individual visitors; otherwise, TYPE 2=0. The dummy variable TYPE 3=1 indicates that international tourist hotels simultaneously receive group and individual visitors; otherwise, TYPE 3=0.
SARS The dummy variable SARS=1 indicates the year 2003; otherwise, SARS=0 FT The dummy variable FT=1 indicates the year 2008 and 2009; otherwise, FT=0
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CHAPTER 5 CONCLUDING REMARKS
Three empirical studies are presented in chapters 2 to 4 on the basis of the 2003-2009 data of international tourist hotel industry in Taiwan. The empirical results in chapter 2 indicate that, in the first stage, the DEA models without quasi-fixed and adjusted inputs overestimate the technical and pure technical efficiencies, but underestimate the scale efficiency of international tourist hotels so that the necessity of considering the existence of the quasi-fixed input is justified. The second stage uses the SFA model to purge the effects from exogenous variables and statistical noise. The SFA results show that the exogenous variables have significant influences on input slacks and pure technical efficiency. The degree of market concentration has positive impacts on labor, F&B expense and operating expense input slacks and has a negative impact on pure technical efficiency because international tourist hotels with the lower degree of market concentration may reduce wasted resources under the competitive pressure. A hotel size has positive effects on all input slacks and has a negative effect on pure technical efficiency because the losses from the complexity of allocating resources dominates the gains from sharing or joint utilization. An international tourist hotel in the resort area has negative relationships with all input slacks and a positive relationship with pure technical efficiency because popular visiting spots can help international tourist hotels to attract more visitors, or managers of resort hotels may adopt superior managerial strategies to improve their efficiency.
An international tourist hotel participating in the international and/or domestic hotel chain has positive relationships with labor and F&B expense input slacks, but has a negative relationship with other expense. Because marketing chain and technology transfers can help international tourist hotels to attract visitors and obtain the managerial experience, but requiring standard services and facilities can cause them to increase more labors and F&B expenses. SARS has positive effects on labor and F&B expense input slacks and has a negative effect on pure technical efficiency because avoiding SARS infection can cause a decrease in demands for accommodation and F&B in international tourist hotels. The financial tsunami has positive effects on labor and other expense input slacks and has a negative effect on pure technical efficiency because the uncertainty of economic environment can lead to a decrease the unnecessary tourism expenditure.
After adjusting the variable input data from the SFA results in the second stage, the efficiency-evaluation results in the third stage show that international tourist hotels in Taiwan
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could reduce inputs by 45.9%, on average, and still produce the same level of outputs. The mean pure technical efficiency measure is 0.990 and the mean scale efficiency measure is 0.546, implying that the technical inefficiency mainly results from the inappropriate production scale. In addition, international tourist hotels have an ample space to improve their technical and scale efficiencies. The efficiency-evaluation results also show that the conventional DEA models overestimate the technical and scale efficiencies, but underestimate the pure technical efficiency of international tourist hotels so that the usage of the three-stage approach is justified. Finally, international tourist hotels which mainly receive group visitors have the worst performance because the better bargaining power of travel agencies can cause international tourist hotels to increase the usage of inputs.
In chapter 3, the empirical results show that, in the first stage, the Malmquist productivity index without quasi-fixed and adjusted inputs underestimates the productivity change so as to justify the necessity of considering the existence of quasi-fixed input. After adjusting the variable input data from the SFA results in the second stage, the productivity index in the third stage shows that the initial increase in productivity has been compensated by a decrease.
The productivity growth or deterioration mainly results from the technological progress or regress and the scale efficiency improvement or deterioration during the period of 2003-2009.
The results also show that the Malmquist productivity index with the quasi-fixed input and without adjusted inputs underestimates the productivity change. The key factors of the productivity changes estimated by the Malmquist productivity index with the quasi-fixed input and without adjusted inputs as well as those estimated by the Malmquist productivity index with quasi-fixed and adjusted inputs are different so as to justify the usage of the three-stage approach. Finally, international tourist hotels with mainly receiving group visitors have the better improvement of productivity than those with receiving simultaneously group and individual visitors as well as mainly receiving individual visitors, because international tourist hotels have an ample space to improve their productivity or pay more attention to decreasing the productivity deterioration. The sources of the productivity changes among three types of visitors are different, but the scale efficiency change plays an important role in all types.
In chapter 4, the empirical results indicate that the scale efficiency hypothesis is supported in Taiwan’s international tourist hotel industry. An international tourist hotel that mainly receives individual visitors and an international tourist hotel that simultaneously receives group and individual visitors have negative impacts on profitability because mainly serving
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group visitors can help international tourist hotels to obtain more visitors once and increase their profitability. SARS has a negative effect on profitability because avoiding SARS infection can lead to a decrease in demands for accommodation and F&B in international tourist hotels. The financial tsunami has a negative effect on profitability because the uncertainty of economic environment can lead to a decrease in demands for accommodation and F&B in international tourist hotels. In addition, the effect of SARS dummy on the profitability is larger than financial tsunami dummy because the effect of financial tsunami is weakened by allowing mainland tourists to visit Taiwan.
The tourism industry has gradually played an important role in the economic growth in Taiwan. International tourist hotels are the most critical part of the tourism industry.
Therefore, studying the efficiency and productivity change and investigating the determinants of profitability in the international tourist hotel industry become more and more important.
Some important lessons may emerge directly from the empirical results. First of all, for studies of efficiency and productivity change to be more informative to decision and policy
Some important lessons may emerge directly from the empirical results. First of all, for studies of efficiency and productivity change to be more informative to decision and policy