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An investigation on the international tourists’ expenditures in Thailand: a modelling approach
15-18Views:138As a result of the increase in both the international tourists’ expenditures and tourist arrivals to Thailand, there is a growing interest in determining the trend of international tourists’ expenditures based on time-series modelling. In our article secondary data were used to produce forecasts of the international tourists’ expenditures in Thailand between 2009 and 2010. The forecasting method is based on the ARFIMAX (0, 0.197, 0, 0.033) model. Furthermore, this method predicted that international tourists’ expenditures in Thailand between 2009 and 2010 will have to contract and slow down. This paper seeks to determine whether the international tourists’ expenditures are affected by other circumstances. The results of this study revealed that the international tourist arrivals to Thailand will also have to slow down. However, from the results, there is solid evidence to support such a claim.
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Forecasting with X-12-ARIMA: International tourist arrivals to India and Thailand
43-61Views:173Forecasting is an essential analytical tool in tourism policy and planning. This paper focuses on forecasting methods based on X-12-ARIMA seasonal adjustment and this method was developed by the Census Bureau in the United States. It has been continually improved since the 1960s, and it is used by many statistics agencies and central banks. The secondary data were used to produce forecasts of international tourist arrivals to India for 2007-2010 and also these data were used to produce forecasts of international tourist arrivals to Thailand for 2006-2010. From these period the results confirm that the best forecasting method based on the X-12-ARIMA seasonal adjustment is X-12-ARIMA(0,1,2)(0,1,1), X-12-ARIMA(0,1,1)(0,1,1) and X-12-ARIMA(2,1,0)(0,1,1) for India and the best forecasting method based on this method is X-12-ARIMA(0,1,1)(0,1,1) and X-12-ARIMA(2,1,0)(0,1,1) for Thailand. Furthermore this method predict that international tourism arrivals to India for 2007–2010 will growth at a positive rate as same as in this during period the number of international tourists arrival to India will be 5,079,651 million, 5,652,180 million, 6,224,480 million and 6,796,890 million, respectively. Also this method predict that international tourism arrivals to Thailand for 2006-2010 will growth at a positive rate as same as in this during period the number of international tourists arrival to Thailand will be 12,211,033 million, 12,699,532 million, 13,187,591 million, 13,674,669 million and 14,161,998 million, respectively. If these results can be generalized for future year, then it suggests that both the India government sector and the Thailand government sector also the private tourism industry sector of these country should prepare to receive increasing numbers of international tourist arrivals both to India and Thailand in this period.
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A structural equation model: Greece’s tourism demand for tourist destination
75-83Views:323Structural equation model (LISREL 8) was applied to test the causal relationships between tourist travel motivations and tourist destination.A survey containing Likert scale questions was conducted to collect data from 100 tourists who had travelled to Greece’s tourist destination. With the help of factor analysis, four dimensions were identified for scales used in the study: travel cost satisfaction, tourism product, tourism product attributes, and tourism product management. Results indicated that the travel cost satisfaction of tourists has a positive influence on tourism product, tourism product attributes and tourism product management. Moreover, our results suggested that the tourist demographics has a positive influence on tourism product and tourism product attributes and has an insignificant relationship with tourism product management. Based on our findings the tourist demographics has not influence on tourism product management. However, these findings suggest that both the private tourism and the governmental tourism sector should develop a better management of tourist destinations so as to develop a stronger attraction of tourism, better amenities, a better accessibility, an appropriate image, to make tourism competitive and to keep tourism product prices at a reasonable level. The implications of the tourism demand model can be used for the public environmental policy-making process based mainly on reasons of interest, ideology or understanding.
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On tests for long-term dependence: India’s international tourism market
77-81Views:117There have been growing interest in studying behavior of long memory process in tourism market. In this research examine the behavior of India’s international tourism market based on long-memory analysis. The international tourism market of India combined with nine countries: USA, UK, Canada, Germany, France, Japan, Malaysia, Australia and Sri Lanka. Moreover, three statistical tests for longmemory process such as R/S test, Modified R/S test and GPH-test are employed to test in these market. The empirical findings in general provide more support for no long memory process or no long-term dependence in international tourism market of India.
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On tests for long-term dependence: India ’s international tourism market
109-113Views:136There have been growing interest in studying behavior of long memory process in tourism market. In this research examine the behavior of India’s international tourism market based on long-memory analysis. The international tourism market of India combined with nine countries: USA, UK, Canada, Germany, France, Japan, Malaysia, Australia and Sri Lanka. Moreover, three statistical tests for longmemory process such as R/S test, Modified R/S test and GPH-test are employed to test in these market. The empirical findings in general provide more support for no long memory process or no long-term dependence in international tourism market of India.
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On tests for long memory process behavior of international tourism market: Thailand and India
95-99Views:144In our research we examine the behaviour of both Thailand’s and India’s international tourism market by using long-memory analysis. The international tourism market of Thailand combined with seven groups such as East Asia, Europe, The Americas, South Asia, Oceania, Middle East and Africa. Similarly, the international tourism market of India combined with nine countries: USA, UK, Canada, Germany, France, Japan, Malaysia, Australia and Sri Lanka. Moreover, three statistical tests for long-memory process such as R/S test, Modified R/S test and GPH-test are employed to study these markets. The empirical findings in general provide more support for long memory process in international tourism market of Thailand and evidence for short-term dependence in international tourism market of India. Therefore, the policy makers of each country should understand the behaviour of long memory process in international tourism market before launching any stimulating campaign to this industry.
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Impact of economic globalization on the human trafficking in the Greater Mekong Sub-region countries
123-130Views:411This study examines the impact of economic globalization on the human trafficking inflows into the Greater Mekong Sub-region (GMS) countries. The paper empirically tests for a cross-section of six countries, including Cambodia, the Yunnan Province of the People’s Republic of China (PRC), Lao People’s Democratic Republic (Lao PRD), Myanmar, Thailand, and Vietnam. Employing the Pooled OLS estimator, as the theory predicts, the economic globalization increases trafficking inflow into the GMS. However, only foreign direct investment (FDI) affects the degree of trafficking of persons, while the effect of trade is insignificant. Moreover, Exchange rate, Migration, Population and Democracy induce higher rates of trafficked persons, whereas Gross Domestic Product (GDP) and other factors, such as education, vocational training and micro-finance through village development funds decrease this problem in the region. Gross National Income per capita (GNI per capita) and rule of law do not have any significant effect on human trafficking.
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