Japanese Tourist Arrivals Research Articles

Forecasting International Tourist Flows to a Small Island: The Case of Saipan

Sustainable tourism, unlike conventional tourism, explicitly strives to maintain economic, environmental, and social sustainability in tourist destinations. Saipan, the capital and the largest island of the chain of Pacific islands known as the Commonwealth of the Northern Mariana Islands (CNMI), is a tropical destination that heavily relies on the tourist industry as a source of income. When analyzing the trends of tourist arrivals from the top three countries that account for the majority of tourist arrivals in Saipan-China, Japan, and Korea-the necessity to implement sustainable tourism in Saipan becomes clear. This article forecasts tourism demand, which is one of the main factors in determining sustainable tourism on a small island. Analyzing both long-term and cyclical trends in tourist arrivals assists budget-constrained policymakers and related organizations in implementing sustainable tourism. Therefore, forecasting accuracy is essential in tourism policy and planning. The tourist arrival data obtained from Marianas Visitors Authority’s official Japanese website are made into a time series for Chinese, Japanese, and Korean visitor data from 2006 to 2016. Given the various time-series forecasting models, we employ simple but powerful forecasting techniques, such as ARIMA and ETS to control for the possible seasonality and trend in our tourism data. Using these forecast methods, the tourist arrival data is used to predict the future trends of tourist arrivals in Saipan for the next twelve months. The performance of our forecasting model in this study is evaluated based on the five measures of accuracy, as measured by comparison with actual tourism flows: mean error, mean absolute scaled error, mean percentage error, mean absolute error, and mean absolute percentage error. A comparison of the two popular forecast techniques in this study shows that the ETS model statistically outperforms the ARIMA model in terms of various measures of accuracy. A practical implication of this finding is that the ETS approach should be used when forecasting tourism demand for small islands. We predict the visitor arrivals from China, Japan, and Korea to Saipan by using the better model. The estimated 80% and 95% intervals for the number of tourist arrivals by the ETS model are presented in this study. The upper (lower) bound is the maximum (minimum) value of the estimated tourist arrivals. We find strong evidence that the tourist arrival trend for Korean visitors to Saipan will increase in the short run; although, the Chinese and Japanese tourist arrival trends seems to be stable, except for Japanese tourist arrivals in August. Nonetheless, with such an intense demand for Saipan’s natural resources, sustainable island tourism becomes necessary. Our estimated result is useful to practitioners in the sense that they are able to prepare for carrying capacities and the means of destination management on Saipan. Proper management for maintaining the island environmentally, economically, and socially requires the preservation of indigenous culture, local quality of life, natural resources, and economic stability while accommodating the demands of arriving tourists. It is crucial to preserve the assets of Saipan in order to maintain and improve its economy. Thus, our time series modeling for forecasting the number of visitors becomes necessary to develop overall economic, environmental, and social sustainability in the island. An interesting addition to implementing sustainable tourism in Saipan is the idea of maintaining a “cap” on the number of incoming tourists visiting the island. Perhaps, with more research on Saipan’s environment, specifically an estimate of how much of the island’s resources tourists exhaust and how much the island can withstand the aforementioned, this “cap” could be practical to prevent perpetual damage to Saipan’s biodiversity, resources, culture, and economy. Along with this idea, knowing the minimum number of tourists needed to sustain Saipan’s necessities is valuable.

Forecasting model for the number of long stay Japanese tourist arrivals in Chiang Mai

Aim: The aging phenomenon of the elderly occurs worldwide, especially in Japan, which is the highest average age. Therefore, long-stay tourism is alternative tourism for the elderly Japanese tourists. This research aimed to construct the appropriate forecasting model for the number of long stays Japanese tourist arrivals in Chiang Mai, Thailand.Method: The data in this study gathered from the Chiang Mai Immigration Office was recorded monthly from January 2014 to July 2017, a total of 43 months. Then the data were classified into two sets. The first data set from January 2014 to December 2016 for 36 months was used to build the forecasting model using Classical decomposition, Seasonal, simple exponential smoothing, Box-Jenkins, and Combining. The second data set from January 2017 to July 2017, a total of 7 months, was used to compare the earlier three forecasting accuracy model methods via the criteria of RMSE.Findings: Research results indicated that combining forecasts was the most suitable for forecasting the number of long-term Japanese tourist arrivals in Chiang Mai.Implications/Novel Contribution: It can be noticed that there has been no published study in academic journals concerning the forecasting long stay Japanese tourist arrivals in Chiang Mai, Thailand. So this research contributes to the literature by adding significant knowledge.

Tourism demand analysis: The impact of the economic policy uncertainty on the arrival of Japanese tourists to the USA

AbstractThis paper aims to investigate the effects of economic uncertainty on the Japanese tourists who travelled to the United States (USA) over the period 1996Q1–2015Q1. To achieve this aim, for the first time the Economic Policy Uncertainty index has been used as an independent variable in international tourism demand analysis models. The unit root and the cointegration tests have been applied to account for unknown structural breaks. Empirical findings indicate that one standard deviation increase in the Economic Policy Uncertainty index leads to a 4.7% decrease in the number of Japanese tourist arrivals to the USA in the long run.

AGGREGATION, HETEROGENEOUS AUTOREGRESSION AND VOLATILITY OF DAILY INTERNATIONAL TOURIST ARRIVALS AND EXCHANGE RATES*

Tourism is a major source of service receipts for many countries, including Taiwan. The two leading tourism countries for Taiwan are Japan and USA, which are sources of short and long haul tourism, respectively. As a strong domestic currency can have adverse effects on international tourist arrivals through the price effect, daily data from 1 January 1990 to 31 December 2008 are used to model the world price, exchange rates, and tourist arrivals from the world, USA and Japan to Taiwan, and their associated volatility. Inclusion of the exchange rate and its volatility captures approximate daily and weekly price and price volatility effects on world, US and Japanese tourist arrivals to Taiwan. The Heterogeneous Autoregressive (HAR) model is used to approximate the slowly decaying correlations associated with the long memory properties in daily and weekly exchange rates and international tourist arrivals, to test whether alternative short and long run estimates of conditional volatility are sensitive to the long memory in the conditional mean, to examine asymmetry and leverage in volatility, and to examine the effects of temporal and spatial aggregation. The approximate price and price volatility effects tend to be different, with the exchange rate typically having the expected negative impact on tourist arrivals to Taiwan, whereas exchange rate volatility can have positive or negative effects on tourist arrivals to Taiwan. For policy purposes, the empirical results suggest that an arbitrary choice of data frequency or spatial aggregation will not lead to robust findings as they are generally not independent of the level of aggregation used.

Modeling the Volatility in Short and Long Haul Japanese Tourist Arrivals to New Zealand and Taiwan

Long haul international travel is more expensive than short haul international travel. This paper estimates the effects of short and long haul volatility (or risk) in monthly Japanese tourist arrivals to Taiwan and New Zealand, respectively. The primary purpose in attracting international tourists is to encourage international tourist spending. Variations in international tourist arrivals are equivalent to variations in international tourism expenditures if the rate of growth in tourism spending is constant, as is likely. In this sense, international tourist arrivals are equivalent to the prices of financial assets in that changes in both lead to positive or negative financial returns. We use symmetric and asymmetric conditional volatility models that are commonly used in financial econometrics, namely the GARCH (1,1), GJR (1,1) and EGARCH (1,1) models. The data series are for the period January 1997 to December 2007. The volatility estimates for the monthly growth in Japanese long haul tourists to New Zealand and short haul tourists to Taiwan indicate that the former has an asymmetric, as well as a leverage, effect on risk, whereby negative shocks increase volatility but positive shocks of similar magnitude decrease volatility, while the latter has a symmetric effect. These empirical results seem to be similar to a wide range of financial stock market returns, so that the models used in financial econometrics are also applicable to international tourist arrivals. The empirical results may be used to recommend whether long haul or short haul international tourists should be encouraged for Taiwan and New Zealand.

Aggregation, Heterogeneous Autoregression and Volatility of Daily International Tourist Arrivals and Exchange Rates

Tourism is a major source of service receipts for many countries, including Taiwan. The two leading tourism countries for Taiwan, comprising a high proportion of world tourist arrivals to Taiwan, are Japan and USA, which are sources of short and long haul tourism, respectively. As it is well known that a strong domestic currency can have adverse effects on international tourist arrivals, daily data from 1 January 1990 to 31 December 2008 are used to model the world price and US$ - New Taiwan $ and Yen - New Taiwan $ exchange rates, and tourist arrivals from the world, USA and Japan to Taiwan, as well as their associated volatility. The sample period includes the Asian economic and financial crises in 1997, and part of the global financial crisis of 2008-09. Inclusion of the exchange rate allows approximate daily price effects on world, US and Japanese tourist arrivals to Taiwan to be captured. The Heterogeneous Autoregressive (HAR) model does not reproduce the theoretical hyperbolic decay rates associated with fractionally integrated (or long memory) time series models, but it can nevertheless approximate quite accurately and parsimoniously the slowly decaying correlations associated with such models. The HAR model is used to approximate long memory properties in daily exchange rates and international tourist arrivals, to test whether alternative short and long run estimates of conditional volatility are sensitive to the approximate long memory in the conditional mean, to examine asymmetry and leverage in volatility, and to examine the effects of temporal and spatial aggregation. The empirical results show that the conditional volatility estimates are not sensitive to the approximate long memory nature of the conditional mean specifications. The QMLE for the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for world, US and Japanese tourist arrivals to Taiwan, and the world price and US$ / New Taiwan $ and Yen/ New Taiwan $ exchange rates, are statistically adequate and have sensible interpretations. Asymmetry (though not leverage) is found for several alternative HAR models for the world, US and Japanese tourist arrivals to Taiwan. For policy purposes, these empirical results suggest that an arbitrary choice of data frequency or spatial aggregation will not lead to robust findings as they are generally not independent of the level of aggregation used.

Modelling Short and Long Haul Volatility in Japanese Tourist Arrivals to New Zealand and Taiwan

This paper estimates the effects of short and long haul volatility (or risk) in monthly Japanese tourist arrivals to Taiwan and New Zealand, respectively. In order to model appropriately the volatilities of international tourist arrivals, we use symmetric and asymmetric conditional volatility models that are commonly used in financial econometrics, namely the GARCH (1,1), GJR (1,1) and EGARCH (1,1) models. The data series are for the period January 1997 to December 2007. The volatility estimates for the monthly growth in Japanese tourists to New Zealand and Taiwan are different, and indicate that the former has an asymmetric effect on risk from positive and negative shocks of equal magnitude, while the latter has no asymmetric effect. Moreover, there is a leverage effect in the monthly growth rate of Japanese tourists to New Zealand, whereby negative shocks increase volatility but positive shocks of very similar magnitude decrease volatility. These empirical results seem to be similar to a wide range of financial stock market prices, so that the models used in financial economics, and hence also the issues related to risk and leverage effects, are also applicable to international tourism flows.

Analyzing the Behavioral Trends in Tourist Arrivals from Japan to Australia

As tourism forecasts are obtained based on past observations, an historical analysis of Japan’s postwar economic success, social factors, and the national government’s institutional policies and reforms can help to provide a better understanding of the growth in Japanese outbound travel and the trending patterns in Japanese tourist arrivals to Australia. To achieve these aims, a statistical analysis of the time series behavior of tourism demand, specifically quarterly tourist arrivals from Japan to Australia from 1976 to 2000, are examined. In addition to analyzing the full sample, the authors also consider three subsamples, namely quarter 1 of 1976 to quarter 2 of 1987, quarter 3 of 1987 to quarter 2 of 1997, and quarter 3 of 1997 to quarter 2 of 2000, to evaluate the sensitivity of the estimates to changes in trends arising from the 1987 stock market crash and the Asian economic and financial crises in 1997. Autoregressive moving average time series models are estimated to analyze alternative patterns of trending behavior within this class of models.

A study in the seasonal variation of Japanese tourist arrivals in Singapore

Among the major overseas tourism markets for Singapore (besides the neighbouring ASEAN countries), Japan is the second largest. The number of Japanese visitors to Singapore had increased from 0.38 million in 1985 to 0.84 million in 1998, an increase of almost 121 per cent. In terms of the share of Japanese tourists in the domestic tourism market, it had only increased from 12.4 to 13.5 per cent. To attract more Japanese visitors, it helps to have a clear understanding of the pattern of Japanese tourist arrivals so that different promotion strategies can be devised and implemented. In this paper, we analyzed the pattern of arrivals by focusing on seasonal indices. The study found that the seasonal indices of Japanese tourist arrivals are stable over time. Policy implications of the finding were also discussed.

The impact of the Asian financial crisis on Japanese demand for travel to Hong Kong: A study of various forecasting techniques

The Asian financial crisis has drawn worldwide attention because of its significant economic impact on local economics, especially on the economy of a tourism‐dependent destination. Unfortunately, there have been very few articles about the relationship of the Asian financial crisis and tourism demand forecasting. This relative lack of prior studies on the Asian financial crisis and tourism demand forecasting is particularly true in the context of Hong Kong. This article reports on a study that utilized officially published data to test the accuracy of forecasts of Japanese demand for travel to Hong Kong, measured in terms of the number of Japanese tourist arrivals. Seven commonly‐used tourism forecasting techniques were used to determine the forecasting accuracy. The quality of forecasting accuracy was measured in five dimensions. Experimental results indicated mixed results in terms of forecasting accuracy. Overall, artificial neural network outperformed other techniques in three of the five dimensions.

A cultural analysis of Japanese tourists: challenges for tourism marketers

Presents the results of an empirical analysis of the cultural differences between Australian and Japanese populations in a tourism context. Argues that the challenge for tourism marketers lies in understanding the cultural make‐up of the Japanese market, and developing culture‐oriented marketing strategies. Identifies the major reasons for the decline in Japanese tourist arrivals to Australia. Compares the Japanese and Western cultural orientation. Describes and interprets the cultural dimensions identified by a principal components analysis. Determines the most critical cultural dimensions and their indicators by a LISREL analysis. The findings show that the key cultural factors influencing Japanese holiday experiences in Australia are culturally determined perceptions of service and interpersonal relations with hosts. Presents the impact of cultural traits on Japanese tourist perceptions of Australian service and interpersonal contact with hosts. Discusses the implications of these findings for tourism marketers.

A neural network model to forecast Japanese demand for travel to Hong Kong

Apart from simple guesswork, time-series and regression techniques have largely dominated forecasting models for international tourism demand. This paper presents a new approach that uses a supervised feed-forward neural network model to forecast Japanese tourist arrivals in Hong Kong. The input layer of the neural network contains six nodes: Service Price, Average Hotel Rate, Foreign Exchange Rate, Population, Marketing Expenses, and Gross Domestic Expenditure. The single node in the output layer of the neural network represents the Japanese demand for travel to Hong Kong. Officially published annual data in the period of 1967 to 1996 were used to build the neural network. Estimated Japanese arrivals were compared with actual published Japanese arrivals. Experimental results showed that using the neural network model to forecast Japanese arrivals outperforms multiple regression, naı̈ve, moving average, and exponent smoothing.

An Econometric Study on Japanese Tourist Arrivals in British Columbia and its Implications

This paper focuses on the marketing of professional services, and on the very specific context of barristers in the British legal professions. We examine the background provided by this sector of professional services, and then present the results of a set of qualitative investigations into the role of marketing as it is perceived by members of this profession, and identify a series of perceived by members of this profession, and identify a series of considering the implications of our findings for how marketing concepts can be productively employed in this area of activity and the needs for conceptual as well as practical extension, but remain largely pessimistic about the current prospects for extending marketing activities into the area of barristers’ marketing.

What is Service Quality When ‘Service’ Equals Regulation?

A econometric model was developed to study Japanese tourist arrivals in British Columbia. Based on quarterly tourist arrival statistics, this study also examined the stability of the parameters of the model over nine holding periods. It was found that the income and habit variables were significant in all the nine holding periods while the exchange rate variable only contributed to the explanation of the dependent variable in two particular periods. The study also found that the number of Japanese tourists has reached full capacity in the summer season, but there is still potential for growth in the winter season. Implications of the findings to the development of the Japanese tourists market in British Columbia were discussed.

The Changing Market Place in Asian Outbound Tourism: Implications for Hospitality Marketing and Management

The last two decades brought dramatic changes to the market place of tourism destinations in the Pacific Rim. Japanese tourist arrivals multiplied, followed by similar developments in arrivals from other Asian countries. This paper focuses on the development of outbound tourism from the four Asian “Tigers” Hong Kong, Singapore, South Korea, and Taiwan. It traces the emergence of these markets and the spatial patterns of development by placing it into the outbound destination life cycle concept.