Data

The empirical data comes from the monthly operation report and tourist numbers of Taiwan international hotel published by Taiwan Tourism Bureau from 1999 January to 2013 October. To understand the relationship between operation variable and tourist variant during the whole period, the dataset used in this study with complete information contains 60 different international hotels across 178 months and 10680 observations were formulated a panel dataset.

Figure 6, 7, and 8 show that hotel performance as revenue, occupancy rate, and room rate present uptrend except the year 2003 of SARs event during the sample periods. However, we also find that hotel locations difference seemly lead to different hotel performance pattern during the sample periods.

Table 2 reports the sample firm-year mean and standard deviation of hotel important operation variables for the whole sample periods in the seven regions. The Hotel Classification system of Taiwan Tourism Bureau base on the geographical location is classified into Taipei, Kaohsiung, Taichung, TaoChuMiao, Eastern, Scenic, other regions.

Table 2 shows that the mean and STDV values of the hotel operation variables in different regions. The highest mean value of rooms is about 360 in Kaohsiung and 3 times more than lowest mean value (102) in others location. The mean of occupancy rate is highest (71%) in Taipei and lowest (45%) in others. The mean of average rate is higher in Taipei (3122) and scenic (3181) regions. The hotels in location of Taipei and Kaohsiung have obviously higher average revenue (23832632, 15915359) than other geographical regions. Finally, the mean of employee numbers are 344 and 342 in Taipei and Kaohsiung than other geographical location.

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Figure 9, 10, 11, 12, 13, 14, and 15 illustrate the trends of domestic tourists and foreigners tourists with different country in different hotel locations. According to these figures, we can understand that the tourist behaviors with different nationality are very different in hotel location difference. More domestic tourists have accommodated in Scenery and Others, but foreigners have consumed more in main city areas. And Chinese tourist arrival numbers significantly increased after year 2005.

International tourist arrived numbers can be treated as travel demand then directly affect the hotel operation. The foreigner and domestic travel demand drivers and creates opportunities for profitability in hotel business model. Table 3 reports the mean and standard deviation of the international hotel visitor arrival in different geographical regions. For domestic tourists, highest mean of the arrival number is 5990 in the Scenic region, which imply that domestic tourist prefer to travel the eastern areas. For Chinese tourists, they mostly arrive hotel is in the eastern with mean value of 2820. Taipei region is most attractive location to stay a night, because the tourists from the North America, Japan, Asia, and Europe have their highest mean values in Taipei from the result of Table 3.

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CHAPTER IV

EMPIRICAL RESULTS

In this sub-section, there are two main issued are discussed base on the empirical model. This second section considers the relationship between tourist arrivals and hotel operation with different disaggregated analysis in two categories. The first category consists of the investigation between domestic and foreigner tourist arrivals and hotel operations in section 4.1. The second category consists of the investigation between the Chinese tourist arrival and hotel operations in section 4.2.

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4.1 Nationality effect on the hotel operation

From Table 4 to Table 6, the empirical results show that the impact of different tourist nationality effects on the international operation variables with different locations. The time series include 178 monthly observations from 1999 January to 2013 October. The cross section data is collected by different areas which are defined by Taiwan Tourism Bureau. The dependent variables are classified into four categories: Revenue, Rate, Occupancy, and Employee. The interpretations of the empirical results are as follows:

Revenue. Table 4 illustrates the empirical results of nationality effects on the hotel revenue with difference location in Taiwan. Table 4 shows the estimated coefficients of different nationality tourists on the room sector revenue. Most explanatory variable coefficients are significant positive at the 10% level. The positive value for coefficients indicates that foreigner visitors significantly increase the hotel revenues.

From Table 4, we can observe that the relationship between the nationality and the hotel revenue would vary by different hotel location. In Taipei area, the coefficient of European tourists is significantly largest (2976.1630) than other coefficients of tourist origins. It implies that European tourist arrivals could increase more hotel revenue than other foreigner and domestic tourists in Taipei location. This empirical result is also shown in the hotel location of Kaohsiung, TaoChuMiao, Scenery and Others area. However, the domestic tourists have little impact on the hotel revenue in Taipei. In Kaohsiung area, the highest coefficient is the variable of U.S. tourist arrivals with 1610.3390. The Asian tourist arrivals would bring highest impact on the hotel revenue in Taichung.

For domestic tourists, the coefficient (1466.1100) in scenic area shows the most

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significant economic impact. The Japanese customers with second highest coefficient value have positive influence on the hotel revenue in the Eastern location.

Therefore, the positive relationships between the hotel revenue and numbers of international customers are significantly influenced by location difference. Compare to the difference of the location, the Australian tourists has most little influence coefficient on the hotel revenue such as in Kaohsiung, Taichung, Eastern, Eastern, Scenery, and Others. For the comparison of nationality, the most insignificant coefficients is in Eastern, which only domestic, USA and Japanese tourist have positive impact on the hotel revenue. The hotel revenues are most sensitive to the European tourists in most locations.

Rate. The average room rate level would dependent on the hotel location according to Table 2. We can realize that Taiwan tourism present expansion in recently years and good and service price level have increased until now. Table 5 reports the results for the tourist nationality effect on the room rate level in different hotel locations. The significant positive coefficients present the positive relationship between the customer numbers and the room daily rate.

The coefficients of different nationality only in the location of TaoChuMiao are all significantly positive. It implied that the foreigner and domestic tourists push the hotel room price in over past 13 years in TaoChuMiao. Thus, the coefficients of Japanese and American tourists are significant positive with room rate in Taipei.

However, in Kaohsiung, different foreigner tourist arrivals such as Japanese, Asian, and European have significant positive relationship with hotel room rate. Meanwhile, in the scenic area, the coefficient of domestic tourists (0.0870), American tourists (0.1389), Asian tourists (0.5528), and Austrian tourists (0.4483) are higher than other areas. There are only the domestic tourists and European tourists with positive impact

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on the hotel price. Therefore, hotels with different location have different room rate growth pattern which have been affected by different foreigner and domestic tourists in our sample period. The hotel room rates are most sensitive to the European tourists in most locations.

Occupancy. Hotel performance has positive relationship with occupancy (Corgel et al., 2013). Table 6 illustrates the relationship between the room occupancy and tourist arrival numbers. The positive coefficient indicates the positive relationship between tourist arrivals and the hotel occupancy rate.

The numbers of domestic customers have significantly positive relationship with room occupancy in some locations, and have significantly negative relationship with room occupancy in other locations. The coefficients of European tourists presents negative coefficient in Taipei, Taichung, Taiwan eastern areas, the location of TaoChuMiao, and others areas. Which imply the European tourists decrease as the the hotel occupancy rate increase in these regions. Domestic tourists and foreigner tourists such as American, Japanese, and Asian have more strong positive impacts on the hotel occupancy rates than other locations. For European tourists and Australian tourists, they have more storing positive impacts on the hotel occupancy rates in each Scenery, and Others regions.

The hotel occupancy is most sensitive to the Asian tourists in most locations such as Taichung, TaoChuMiao, and Others. The result of Table 6 demonstrates that individual hotel employee increase only has significant positive relationship with specific tourist nationality. This relationship would change with different hotel locations. The hotel managers in different location should project the service quality planning on their target tourist market based on our result.

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4.2 China effect on the hotel operation

According to the report of UNWTO Tourism Highlights, 2014, China ranked the first-large in international tourism expenditure in 2012 from the ranked 7th in 2000.

The spending by outbound Chinese tourists extended its lead further, which increased expenditure in 2013 by a massive US$ 27 billion to a record US$ 129 billion. This oversee spending amount is almost ten time rather than the amount in 2000. It is boosted by disposable incomes surge, foreign travel permission and currency appreciation.

The Taiwan authority has released the regulation of Chinese people traveling to Taiwan in 2002, January. But until 2009, the obviously increasing numbers of China tourists have shown in international tourism hospital report of Taiwan Tourism Bureau.

Therefore, the increasing China tourists should have significant impact on the hotel operation performance.

From Table 7 to Table 9, we use China arrival number as independent variable to test the impact of china tourist numbers on each international hotel operation variables of different location in Taiwan by the pool regression with time series and cross section data. The time series include 58 monthly observations from 2009 January to 2013 October. The cross section data is collected by different areas which are defined by Taiwan Tourism Bureau. The dependent variables are classified into four categories: Revenue, Rate, Occupancy, and Employee. The interpretations of the empirical results are as follows:

Revenue. Table 7 illustrates the relationship between the Chinese tourist arrivals and the hotel revenue by difference hotel location in Taiwan. The estimated coefficients in Table 7 are significant positive at the 10% level but only in Kaohsiung presents insignificant on the room department revenue. The positive value for

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coefficients indicates that more Chinese visitors would significantly increases the hotel revenues. The highest coefficient is 2203 of the hotel in other area. The second high coefficient number is 1488 in Taipei. The results illustrate that Chinese tourists have higher contributed spending in the hotels of other area and Taipei. But the hotels in Kaohsiung have little economy benefit from the Chinese tourist arrivals. Compare to Table 5, Chinese tourist as European travelers have significant impact on the hotel revenue located inOther area.

Rate. Table 8 reports the relationship between the Chinese tourist arrivals and the hotel room rates in different areas. The coefficients are only significant negative in Taipei, Kaohsiung, and TaoChuMiao. The room rate coefficient in Kaohsiung is negative 0.0934 and larger than others. It implies the relationship between Chinese arrivals and room rate is different to the previous section result of other foreigner tourists and presents the Chinese tourists choose the hotels with lower room price especially in Kaohsiung. This result shows that more and more Chinese tourists stay at normal hotel than international tourism hotels as the hotel room rate has increased continually.

Occupancy. Table 9 illustrates the relationship between the room occupancy and Chinese tourist arrivals. The positive coefficient of different areas all indicates that Chinese tourist arrivals have positive relationship with the occupancy of hotels. The occupancy of hotels in Others location which include Tainan, Keelung, Penghu, and Yilan counties are highly sensitive to Chinese tourist arrivals due the largest coefficient 0.0074% in Table 11 as the Asian tourist arrival results in Table 7. This result implies that Chinese tourists could increase room occupancy of hotels in all locations.

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CHAPTER V

CONCLUSION

This paper incorporates the disaggregation analysis into panel regression model to investigate the relationship between the tourist arrivals from different country and hotel operation in different location.

The results of past research focus on the aggregated data of tourist arrivals and hotel operation variables but neglect the difference of the hotel location and arrival nationality. It only offer less information for hotel managers to understand that which country tourist is import target market to their business operation variables with different hotel locations. Meanwhile, the sample sizes in this paper are more and broader than previous researches which only consider the listing firms (the firms trading in the stock exchange).

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5.1. Foreigner and domestic tourist arrivals

On the second part of our results, we explore how the references of international consumers from different distinct cultures might differ concerning the hotel room services and products. Cultural difference will influence customer’s perceptions of hotel pricing policies. Wang and Mattila (2011) stated that “customer’s cultural background is an important factor because culture shapes how people think and perceive and event.” In the hospitality industry it is reasonable to believe differences between Western and Chinese customers in their reactions to hotel pricing policies.

Kimes and Wirtz (2003) demonstrate that Asian customer experience revenue management practices to be less reasonable than consumer from Europe and North America in the restaurant industry. Choi and Mattila (2006) tested the perception of fairness of hotel room rate between US and Korean guests and believe that US guests recognize the hotel pricing to be fairer than Korean guests. Mattila and Choi (2006) indicate that offering information on a hotel’s room rate policy had a relatively more storing positive effect on Korean than on their US consumers.

Rate restrictions as one of hotel pricing policies are the methods that hotels rule to segment customers and to rationalize why different customers have different prices to pay (Mauri, 2007). Rate restrictions is connected to revenue management to help hotel guests to self-segment into different rate classes for the purposes of controlling the demand between peak and off-peak periods, and rewarding loyal guests, and arranging the highest-margin business benefits (Kimes and Singh, 2009)

The disaggregation analysis models between the relationship between the relationship between the tourist arrival numbers and the hotel operation variables in helpful in assisting hotel managers’ assessment of various tourist segments in making hotel pricing policies, human resource, marketing and competition decision.

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The positive relationships between the hotel revenue and international customers are significantly influenced by location and nationality difference. Therefore the hotel performance should be measured by different hotel location for employee performance assessment. The hotel customers from different countries with culture difference present different consumer behavior. In Taiwan, European guests have mostly impact on the hotel revenue and hotel managers should pay more attention on rate restriction and pricing policy to European segments in order to stabilize hotel revenue management. Meanwhile, the hotel managers in Scenery location also suffer higher revenue volatility and should control the demand between peak and off-peak periods for profit maximum.

The previous empirical results by (Pan, 2007) support market demand variations significantly affect the difference between high season and low season optimal room rates with the data of tourist hotels in Taipei. This paper further supports the positive relationship between the customer numbers and the room daily rate and evidence that different international guests affect the hotel room rate with location difference. Our results indicate that hotel room rate is strong positive sensitive to European tourists in most locations and the most domestic guests and foreigner guests would increase the hotel room rate in Scenery location. The significant positive relationship between hotel price and European tourist arrivals could be explained by the culture difference that west consumers perceive the hotel room pricing to be fairer than Eastern consumers (Kimes and Wirtz, 2003; Choi and Mattila, 2006) as a cost increase period.

The explanation to why most hotel room rate is more sensitive to guests in Scenery could be due to the location factor of destination’s attractiveness which may include the tourism welcomeness, Tourism infrastructure, and crime rate (Assaf, Josiassen, and Agbola, 2015).

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Our results also show that the relationship between tourist coming and the hotel occupancy rate presents significant positive or negative. The US, Asian, Australian, and European have different degree negative relationship with the hotel occupancy rate. The negative relationship is more important in European tourist with negative coefficients except in Taichung and Scenery and is very different to other foreigner guests and domestic guests. This empirical result could be due to the demand between peak and off-peak period, and offer more customer behavior information to design the hotel rate restrictions to attract more customers.

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5.2. Chinese tourist effect

Furthermore, we also examine the relationship between Chinese tourist arrivals and the hotel operation variable. Chinese tourists have strong positive relationship in the hotels location of Others area and Taipei area. The positive coefficient of all areas indicates that Chinese tourist arrivals have positive relationship with the occupancy of hotels. The occupancy of hotels in other location which include Tainan, Keelung, Penghu, and Yilan counties are highly sensitive to Chinese tourist arrivals. Chinese tourists prefer choosing the hotels with lower room price especially in Kaohsiung.

Finally, the relationship between employee numbers and Chinese tourist arrivals is positive only statistically significant positive in Taichung, Kaohsiung, Scenery, and others locations. The result also shows that Chinese tourist arrivals have little impact on the hotel employee numbers in Taipei.

The Chinese tourists have more influence on Taiwan tourism market due to the progress of a peaceful Taiwan Strait tie. From these results of that Chinese tourist arrivals have different degree impacts on hotel revenue income and occupancy by different locations. The hotels in Taipei with priority location strategy can benefit more economic rewards from Chinese tourists. And the hotels in Others area with higher accessible such as attractions (Jiufen, Yehliu), Night markets (Keelung Miaokou, Tainan Flowers) can attract more Chinese tourists than other locations.

Moreover, the hotels in Kaohsiung following by the demand law could use price discount to increase the Chinese tourist accommodations.

Based on our empirical results, manager can acknowledge that the customers origin culture difference and location factor are vital sensitive to revenue management, pricing policies, and employee human resource development, and performance management.

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5.3. Limitation and opportunities of future research

The paper suffers from vital limitations that could be investigated in future research. First, future studies can be conducted on the additional control variables such as economic conditions in the country of destination or origin. Second, future studies could be expanded to examine the location factors, to test whether the findings of this study can be explained by the location factors such as infrastructure, tourism welcomeness, and crime rate so on. Finally, future studies might consider extending the sample of this study. For example the more detail hotel information might have influenced the findings in this paper and affected the results that were drawn from the data used. We believe that adding more listing hotel to the sample would be important in order to validate and provide further evidence to the meaningful of the present findings and practice application.

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Balaguer, L. and Cantavella-Jorda, M. (2002). Tourism as a long-run economic

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