FORECASTING THE INTERNATIONAL TOURISM DEMAND FROM EAST ASIA TO JAPAN

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1 FORECASTING THE INTERNATIONAL TOURISM DEMAND FROM EAST ASIA TO JAPAN Naohisa OKAMOTO Associate Professor University of Tsukuba Graduate School of Systems and Information Engineering 1-1-1, Tennodai, Tsukuba, Ibaraki Japan Fax: Takeshi KURIHARA Graduate Student University of Tsukuba Graduate School of Systems and Information Engineering 1-1-1, Tennodai, Tsukuba, Ibaraki Japan Fax: Haruo ISHIDA Professor University of Tsukuba Graduate School of Systems and Information Engineering 1-1-1, Tennodai, Tsukuba, Ibaraki Japan Fax: Abstract: This paper suggests a method in forecasting international tourism demand. The forecasting model has two stages of estimation. First stage is the International Trip Generation. We explained this by using a logistic curve. Second, we proceed to find out the travel destination by using the aggregate logit model. Results for the forecast of tourists coming to Japan led to two main conclusions. 1) The number of tourists from every Asian country shows a growing tendency until ) Moreover, the rate of tourist visiting Japan will decrease gradually compared to other regions such as North America where the rate is steadily increasing. Key Words: International tourism, International trip generation, Travel destination 1. INTRODUCTION The 2004 is the first year for Japan to accommodate more the 6 million foreign tourists. (Tourism Report, 2005). Then in year 2005, 6.72 million foreign tourists visited Japan, while Japanese tourists traveling overseas accounted for million. This situation continues to be a serious problem because the international balance of payments of tourism in Japan is at a deficit stage. However, Tourism Report (2005) showed that the problem has improved. The main reasons are 1) various kinds of campaigns to promote and increase the number of foreign tourists coming to Japan like the Visit Japan Campaign since 2003 and 2) increasing number of international tourist from Asian countries according to their economic growth. On the other hand, the rate of tourist visiting Japan from Asian countries decreases, especially Korea (69.41%, 1987 to 28.91%, 1995) (Watanabe, 1997). Generally, although the number of foreign tourist is increasing, it is not clear how many tourists will totally visit Japan in the future. The main aim of this paper is to suggest a method in forecasting international tourism demand. In this paper, the forecasting model takes two stages of estimation. First stage is the International Trip Generation. As Morichi (2001) tackled the international trip generation in 1389

2 Japan. We applied his method for estimating tourism flow from Asian countries. It is explained by using a logistic curve, which is often used as a growth function in economics. The second stage is to find out the travel destination by using the aggregate logit model. 2. EXISTING RESEARCH A series of study established the way for forecasting the international trip generation and travel destination (Morichi, 2001; Nakamura, 2005; Lemire, 1989). There are few studies for international tourism. Like the World Tourism Organization s (WTO) study which forecasted the number of tourists for each country by using the Delphi method. The WTO estimated the international tourism demand for 2020, where in it accounted 140 million in Japan, 21.7 million in Korea and 100 million in China. However, this figure seems to be overestimated. One possible could be population decrease brought by the aging society in every country. The reason for the limited study on international tourism is the lack of statistical data. Given this situation, we tried to forecasting the international tourism from Asian countries by using the data from national governments, private sectors and so on. 3. DATA The data on international tourism is not yet fully collected and also has not been updated for a long period. The analysis of Japanese international tourist uses The Ministry of Justice Annual report on Immigration. The data from Korea National Tourism Organization is used for the analysis of Korean tourism. Hong Kong Tourism Board is used for the analysis of Hong Kong tourism while Thailand National Statistical Office is applied for the analysis of Thailand. Asia-Pacific Tourism Exchange Center World Tourism Statistics is used for the analysis of the other Asian countries not mentioned above. Determination of GDP and other variables uses UN Statistical Yearbook and other materials from official government and private sector. Table 1 shows the data source for the number of tourists in Asian countries. It also presents the data period available for analysis and whether or not it includes the travel destination. More detailed data information for analysis is shown in Appendix. Table 1 Data source of the number of tourist country source year destination Japan Annual Report on Immigration Korea Tour 2 Korea web site Hong Kong A Statistical Review of Hong Kong Tourism Thailand Thailand in figures Singapore Yearbook of Statistics Singapore China Taiwan World Tourism Statistics Malaysia Indonesia

3 4. ANALYSIS ON INTERNATIONAL TRIP GENERATION Morichi (2001) explained about international trip generation in Japan as follows, International trip generation is growing little by little because there is little information about travel abroad or so for first stage. Second stage will face radical increasing number of tourists as the international travel spreading for Japanese residents. However, international trip generation does not increase permanently because international tourism takes a lot of costs including flight time, flight fee, hotel charge and so on. Eventually international trip generation will approach some saturation point in the future. This paper analyzed the international trip generation from Asian countries. It could be possible to apply the above mentioned theory of the process of Japanese international trip generation. Hence, this analysis is explained by using a logistic function. The logistic function is calculated based on the following formula: K y = 1+ exp( ax + b) (1) y :number of travel per year per person K :saturated number of travel x :variables a, b :parameter K presents a saturated number of international travel. Figure 1 shows that international trip generation is growing and approaching to the saturated point K. K number of travel/person/year year Figure 1 S shaped logistic curve and saturation point 4.1 The Analysis Targets and Explanatory Variables The selected countries for this analysis are Japan, Korea, Hong Kong, Thailand and China. Although it doesn t have enough data for analysis, China is also included the analysis because China is now watched with keen interest among international tourism market. Explanatory variables are GDP/capita, exchange rate and Gini coefficients. GDP/capita is included since it exhibits its own economic power as it takes a lot of money to travel abroad. Exchange rate (nominal exchange rate) is also significant explanatory variable. If exchange rate 1391

4 falls (e.g. 1$ = 150 yen changes to 1$ = 100 yen), then tourists can take advantage for international travel. Gini coefficient is a zero to one value showing income differential. Income differential may disturb international tourism especially in developing countries. Priori expectation of sign of explanatory variable is; GDP/capita (+), Exchange rate (-) and Gini coefficient (-). 4.2 Parameter Estimation Table 2 shows the results of parameter estimation for each country. R-square is high enough to say that this model was well estimated. Our priority of estimating the forecasting model is to make a simple model. Japan, Korea, Hong Kong and China include GDP and Exchange rate in the model. However, the model wasn t estimated well without Gini Coefficient variable. Parameter sign of exchange rate variable is different from each country. Usually it seems that the number of international tourist increases as the exchange rate depreciates. So the expected parameter sign is negative. China and Hong Kong shows the negative parameter as we expected. On the other hand, the parameter estimation resulted positive for Korea and Thailand. It thought to be caused by the Asian financial crisis occurred in Asian financial crisis adversely affected Korea and Thailand their currency collapsed and it affected the result of estimation. Table 2 Parameter estimation (International Trip Generation) Japan Korea Hong Kong Thailand China saturated number of tourist (number/person/year) (1.96) (2.15) (2.27) (2.07) (4.63) GDP/capita (US$/person) (6.22) (7.93) (2.53) (2.02) (2.96) exchange rate (each currency/us$) (6.79) (-0.10) (1.87) (-1.89) gini coefficient constant (-0.34) (13.67) (17.14) (1.44) (1.72) (0.077) R-squared number of observation ( ) T value 4.3 Forecasting the Number of International Tourist We forecasted the number of international tourist in the future by using the parameter estimated in the last section (4.2) and the future value of each variable estimated by some organizations. Future population data uses the middle estimation of National institute of Population and Social Security Research in Japan, and the middle estimation of UN in other Asian countries (see Table 3). Future GDP data uses Ministry of Land, Infrastructure and Transport, Socio-Economic Research Center and Japan Center for Economic Research in Japan, and International Energy Agency in other Asian countries (see Table 4). It is difficult to forecast the future exchange rate and Gini coefficient, so we substituted the forecasting value to average value of latest 10 years (see Table 5 for future exchange rate). This paper uses for future Gini coefficient in Thailand. 1392

5 Table 3 Future population (thousand people) Japan 127, , , , , ,580 Hong Kong 7,182 7,537 7,871 8,187 8,490 8,764 Thailand 64,081 66,951 69,568 71,894 73,857 75,421 Korea 48,182 49,080 49,672 50,020 50,171 50,045 China 1,322,273 1,364,875 1,402,321 1,429,473 1,445,100 1,450,521 Table 4 Future GDP average growing rate (%) data 2005~ 2010~ 2015~ 2020~ 2025~ Socio-Economic high Research Center mid low Japan Japan Center of high Economic Research mid low Ministry of land, Infrastructure and Transport Hong Kong Thailand International Energy Agency Korea China Table 5 Future exchange rate Hong Kong Thailand Korea China exchange rate currency HK$/US$ Baht/US$ Won/US$ RMB/US$ Forecasting the number of international tourist in Japan is shown in figure 2. The graph draws real value and estimated value until Real value and estimated value present a similar tendency. The rest is estimated value after The biggest forecast of this paper is 29.4 million Japanese international tourists from Ministry of Land, Infrastructure and Transport in On the other hand, the smallest forecast accounts for 14.5 million from Japan Center for Economic Research. The various forecasts used various GDP forecasting by each organization. The number of international tourist from Japan will range between 20 million to 30 million. Morichi (2001) forecasted the number of Japanese international tourist by airports in Japan. They estimated that the number of international tourist will be double at the Narita international airport in 2020 compared to While in this paper, we estimated that the number of future international tourist would be mostly doubled. Hence, the forecasting value in this analysis estimated with a high accuracy to some extent. Figure 3 shows the number of future international tourist from Asian countries. The number of international tourist from every Asian country shows the growing tendency until We estimated each amount like 16.1 million in China, 10.9 million in Korea, 7.7 million in Hong Kong and 3.5 million in Thailand. The number of Chinese international tourist does not grow constantly after It is possible to undervalue for Chinese tourists because there are not enough data for estimation. 1393

6 million people 50 WTO Ministry of Land, Infrastructure and Transport Estimated value Real value Japan Center for Economic Research; Lower estimate year Figure 2 Forecasting future international tourists in Japan million people China 12 8 Korea Hong Kong 4 Thailan year Figure 3 Forecasting future international tourists in Asian 5. ANALYSIS ON TRAVEL DEMAND DISTRIBUTION We estimated the number of international tourist in Asian countries as shown in the last chapter. Then, we proceeded to find out the travel destination by using the aggregate logit model. 1394

7 5.1 The Target Area In this model, nine countries (i.e. Japan, Korea, Hong Kong, Thailand, China, Taiwan, Singapore, Malaysia and Indonesia) and two regions (i.e. North America and Oceania) were considered as alternatives of travel destinations. Europe does not include in the model due to unavailability of detail data. 5.2 Explanatory Variables and Parameter Estimation Explanatory variables are made up of attractiveness and resistance of the travel and some dummy variables. For attractiveness, the variables World heritage, GDP and Hotel were used. World heritage is one of the most attractive places for tourist to visit. Such world heritages are comprised of natural, cultural and mixed-type places. All types of world heritage are included in this model. GDP - is a variable perceived to contribute high attractiveness in the model. Moreover the analysis of international trip generation uses international GDP. On the other hand, the analysis of travel destination ratio uses GDP of alternative travel destinations. Hotel generally, tourists stay in the hotels during their tour. The quality of the hotels is thought to influence attractiveness to the tourists. Thus, the score of each hotel is computed using the formula below. Score i = 1 n i Rank j j ln( Price j ) Price: stay fee per night of j hotel i : country n i (2) Hotel rank is usually determined by the number of stars. The website hotels.com was utilized to compare the star rank of the hotels all over the world. Consequently, price is calculated in US dollar. Then, average hotel quality in the country is calculated by the summation of the scores of all the hotels in the target area. Finally it is divided by the number of hotels. The target cities are Tokyo (Japan), Seoul (Korea), Beijing (China), Taipei (Taiwan), Hong Kong, Bangkok (Thailand), Singapore, Kuala Lumpur (Malaysia), Jakarta (Indonesia), Sydney (Oceania), New York (North America) which are mostly capitals of the country or mega cities. The number of hotels and price were taken from the Japanese travel guidebook published by Diamond Big Co. Ltd Globe-Trotter Travel Guidebook and Ota Publications Japan Hotel Almanac for Tokyo. The quality of hotel at 2001 is shown in Table 6. Bangkok, Singapore and Jakarta got the highest quality rank. Main reason for this is that 1) star rank is high (Singapore) and 2) price is comparatively cheap (Bangkok and Jakarta). Table 6 Quality index of hotel at 2001 City Quality City Quality Tokyo Hong Kong New York Bangkok 1.02 Sydney Singapore 1.06 Seoul Kuala Lumpur Beijing Jakarta 1.06 Taipei

8 For resistance variables we use Flight time / number of travel, Big Mac Index and Visa. Flight time / number of travel - can be treated as a resistant to individual s travel. Usually it becomes an obstacle for people if the flight time to the destination is longer than normal. In the determination of flight time, we used ABC world airways guide Blue book / Red ABC Travel Guides from 1990 to 1995 and OAG world airways guide The complete guide to air travel from 1996 to The target airports are shown in Table 7 while the minimum flight time for the routes is used for the analysis. North America has four airports, so their average flight time is calculated for the analysis. Flight time changes greatly in the case that whether the route is direct or connecting flight. For example, Seoul Beijing flight had taken 8 hours 45 minutes till Then it has improved to 1 hour 50 minutes since 1995 when the direct flight started. Number of travel was estimated in the last chapter. It represents how the international travel is spread for that country. At first, number of travel is small because the international travel has not yet popularized. Eventually, flight time / number of travel will show a higher tendency. However, flight time / number of travel became smaller and smaller as the international travel is spread widely. Figure 4 shows the future flight time / number of travel in Japan. In the year 2005, North America has the biggest flight time / number of travel and Korea has the smallest. The disparity between North America and Korea turns to be small as the number of Japanese tourist grows. Table 7 Target airport North America Asia New York ( J. F. K airport ) Tokyo ( Narita airport ) San Francisco airport Seoul ( Kimpo airport ) Los Angels airport Beijing airport Chicago ( Ohea airport ) Taipei ( C. K. S airport ) Oceania Hong Kong ( Chek Lap Kok airport Sydney ( Kingsford Smith airport ) Bangkok ( Don Muang airport ) Singapore ( Changi airport ) Kuala Lumpur international airport Jakarta ( Soekarno-Hatta airport ) flight time / number of travel in Japan 6000 North America Korea year Figure 4 Future flight time / number of travel in Japan Big Mac Index - is an annual report published by London Economist Newspaper Ltd. We used it as a consumer price index, since McDonald establishments are widely distributed all over the world. 1396

9 Visa - needed to enter some countries even if the travel is shorter than a week. Visa obligation will also be a resistant of individual s travel because it takes time and cost to acquire it. The following variables are used as a dummy variable in this model. Asia - is a one-zero dummy variable. It takes the value of one if they are Asian countries, and zero other regions. English - is a one-zero dummy variable. It takes the value of one if their mother tongue is English, and zero otherwise. We estimated the parameter with these variables. The result of the estimation is shown in Table 8 below. R-square resulted to be over 0.70, these models can present the travel destination with high accuracy. The T value of each variable is mostly significant. Although not all T value of each variable are not significant, we chose model 2 for our estimation because R-square is resulted to be high. Figure 5 and 6 show the Japanese travel destination ratio in 2001 with model 2.These two graphs are similar in the point; 1) North America presents the highest rate, and 2) the ratio amounts over 70 % with higher 4 countries (North America, Oceania, Korea and China). There is a differential between real ratio and estimated one in Oceania and Korea. This is a future task that could improve the model. Singapore 4% Thailand 6% Hong Kong 6% Taiwan 6% China 11% Table 8 Parameter estimation (travel destination) model 1 model 2 coefficience t value coefficience t value World heritage (5.42) (3.17) GDP(US $/population) (2.16) (2.69) Hotel 2.17 (2.32) 2.37 (2.25) Flight time / number of travel ( LOG ) (-6.94) (-6.80) (hour/number of travel/year/population) Big Mac Index (-1.85) (-2.71) Asia (-1.76) English (-2.05) Visa (-1.47) R-squared Number of observation Malaysia 2% Indonesia 3% North America 39% Malaysia 2% Singapore 4% Thailand 7% Hong Kong 6% Taiwan 4% China 11% Oceania Korea 6% 17% Figure 5 Japanese travel destination ratio in 2001 (real rate) (exclude Europe and other region) Korea 6% Indonesia 6% Oceania 14% Figure 6 Estimated rate North America 40% 1397

10 5.3 Forecasting the Future Travel Destination We proceeded to forecasting the future travel destination by using parameters and future estimated value of variables. Future GDP data uses the same value of international trip generation analysis. Future travel time uses the time in 2001, assumed to be constant after Future number of travel uses the value estimated in the last chapter. Future World heritage, Hotel and Big Mac Index is used the value of 2001 as constant since it is difficult to forecast. Asia and English dummy were also held constant. Figure 7 and 8 show the future travel destination in Korea and China. It can be seen that North America became popular destination for both countries. This suggests that future flight time / number of travel becomes small as the number of travel per person grows. That is to say, the time resistance to North America coming far from Asian countries turns to be small according to the spread of international tourism. These figures also show that many Asian counties diminish its rate including Japan. For example, travel destination rate to Japan by Korean tourist decreases from 11.6 % in 1990 to 10.8% in 2030 and by Chinese tourist decreases from 12.6 % to 11.4 %. 100% 80% 60% Indonesia Malaysia Singapore Thailand Hong Kong Taiwan China Oceania 40% 20% 0% 100% 80% 60% North America Japan year Figure 7 Future travel destination in Korea Indonesia Malaysia Singapore Thailand Hong Kong Taiwan Korea Oceania 40% 20% 0% North America Japan year Figure 8 Future travel destination in China 1398

11 6. FORECASTING THE FUTURE INBOUND TOURISTS IN JAPAN Finally we estimate how many foreign tourists will visit Japan. The forecasting was held only with Korea, Hong Kong, Thailand and China because of the data restriction. Figure 9 shows the number of tourist and the rate (share of total traffic) of tourist visiting Japan from Korea. The number of Korean tourists to visit Japan will increase according to the growth of international tourist (from 0.60 million in 2007 to 1.12 million in 2030). The rate of tourist visiting Japan from Korea will decrease gradually from Figure 10 shows the number of tourist visiting Japan and the rate of tourist visiting Japan from China. The number of Chinese tourists to visit Japan will decrease after The main reason for this is the decrease of rate to visit Japan from Another reason would be the forecast says that the number of Chinese international tourist will not increase so much. The graph presents that the number of tourist to visit Japan will reach 1.73 million in That will increase to a peak value of 1.92 million in 2020 and then will decrease to 1.85 million in thousand people 1600 the number of tourist visiting Japan the rate of tourist visiting Japan % year Figure 9 The number of tourist and the rate of tourist visiting Japan from Korea thousand people 2000 the number of tourist visiting Japan the rate of tourist visiting Japan % year Figure 10 The number of tourist and the rate of tourist visiting Japan from China 1399

12 7. CONCLUSION In this study, the model for forecasting international tourism demand was developed. This model is consisted of two steps 1) demand generation and 2) demand distribution. From modeling analysis, we got two main conclusions from the two estimations. 1) The number of tourist from every Asian country shows the growing tendency until ) The rate of tourist visiting North America showed growing tendency in the future. On the other hand, the rate of tourist visiting Asian countries including Japan will decrease. Eventually, it is possible that Japanese inbound would decline in the future. Japan started inbound campaign since After that, Japanese inbound demand is dramatically increasing now. However, there would be declining number of tourist arrivals from Asian countries going to Japan. So in addition to the promotion of Japanese tourism, it will be needed to consolidate the support policy for foreign visitors such as the equipment of tourist information center. And easing the entry visa for foreign visitors would be required for getting more tourists visit Japan. This model included only external factors and not policy factors. It means that this model is the trend model. Japanese government has started inbound campaign since To understand the effect of these promotions, political variable should be included for further improvement. REFERENCES ABC world airways guide, Blue book / Red ABC Travel Guides, China National Economy Publishing House, Almanac of China s Economy, Directorate General Budget, Accounting and Statistics, Japan External Trade Organization website [GDP Taiwan] ( Globe-Trotter Travel Guidebook, Diamond Big Co. Ltd, [Hotel] Hara Y, (1999), Asia Economic Theory, NTT Publishing Co, Ltd, pp [Gini Coefficients] Hong Kong Tourism Board, A Statistical Review Of Hong Kong Tourism Hotels.com website ( International Energy Agency, (2004), World Energy Outlook 2004 [Future GDP] Japan Center for Economic Research, website [Future GDP] ( Japan Hotel Almanac, Ota Publications, Korea National Tourism Organization, Tour 2 Korea website, ( London Economist Newspaper Ltd, Economist, [Big Mac Index] Ministry of Internal Affairs and Communication, Japan Statistical Yearbook, Ministry of Justice, Annual Report on Immigration, Ministry of Land, Infrastructure and Transport, (2005), Tourism Report 2005 Ministry of Land, Infrastructure and Transport, website [Future GDP estimation] ( Ministry of the Interior, Taiwan Population Statistics, Morichi S. and Todoroki T, (2001), Analysis on Structure and Future Trend of Regional Disparity for Overseas Tourist Demand of Japan, Transport Policy Studies Review, 1400

13 Vol.4, No.1, 8-18 Nakamura Y. Takebayashi M et al, (2005), An Empirical Analysis of the International Tourism Demand, The 32nd Conference of Infrastructure Planning CD-Rom No.239 National Institute of Population and Social Security Research website [Future population] ( Nicole L. and Tae H. O, (1989), Modeling Destination Choice Of International Tourists With An Application To Japanese Tourists, Proceedings of the 5th World Conference on Transport Research, OAG world airways guide, The complete guide to air travel, OAG, Okamoto N. Morichi. S et al, (1995), A study on Regional Difference of Recreational Destination Choice Behavior, Journal of the Eastern Asia Society for Transportation Studies, Vol.1, No.1, Singapore Department of Statistics, Yearbook of Statistics Singapore Socio-Economic Research Center, website [Future GDP estimation] ( Thailand National Statistical Office, (2004), Thailand in Figures 2003, Alpha Research Co, Ltd UNESCO website [Number of world heritage] ( United Nations Statistics Division, Demographic Yearbook, United Nations Statistical Division, Statistical Yearbook, United Nations Statistics Division, (2005), World Population Prospects University of British Colombia, PACIFIC Exchange Rate Service website [Exchange rate] ( Watanabe T. and Unuma T, (1997), A Study on Inbound Tourism Policies for Regional Development in Japan, Institute for Transport Policy Studies 2nd research report, World Tourism Organization, (1997), Tourism 2020 Vision Vol.3 East Asia and the Pacific Yai T. Yamada H and Okamoto N, (1995), Nationwide Recreation Travel Survey in Japan: Outline and Modeling Applicability, Transportation Research Record, No.1493,

14 Data source APPENDIX data country source publisher Japan Annual Report on Immigration Ministry of Justice Korea website Korea National Tourism Organization Hong Kong A Statistical Review of Hong Kong Tourism Hong Kong Tourism Board number Thailand Thailand in figures Alpha Research of Singapore Yearbook of Statistics Singapore Singapore Department of Statistics tourist China Taiwan Malaysia Indonesia Japan World Tourism Statistics Japan Statistical Yearbook Asia-Pacific Tourism Exchange Center Ministry of Internal Affairs and Communication population China Almanac of China's Economy China National Economy Publishing House Taiwan Taiwan Population Statistics Ministry of the Interior others Demographic Yearbook United Nations Statistics Division Japan Japan Statistical Yearbook Ministry of Internal Affairs and Communication GDP Taiwan Japan External Trade Organization website Directorate General of Budget, Accounting and Statistics others Statistical Yearbook United Nations Statistics Division exchange rate Statistical Yearbook United Nations Statistics Division all countries PACIFIC Exchange Rate Service University of British Colombia Gini coefficience Thailand Asia Economic Theory NTT Publishing Co. Ltd world heritage all countries website UNESCO hotel flight time Blue book / Red ABC Travel Guides ABC world airways guide all countries The complete guide to air travel OAG world airways guide Japan Japan Hotel Almanac Ota Publications others Globe-Trotter Travel Guidebook Diamond Big Co. Ltd visa all countries OAG Flight Guide Supplement OAG Big Mac Index all countries Economist London Economist Newspaper Ltd National Institute of Population Japan website future population and Social Security Research others World Population Prospects United Nations Statistics Division website Ministry of Land. Infrastructure and Transport future GDP Japan website Socio-Economic Research Center website Japan Center for Economic Research others World Energy Outlook 2004 International Energy Agency 1402

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