The Tourism Studies

There are few preceding studies to verify whether the environmental load of tourism is serious or not. In this paper, the load of Okinawa is verified from the state of its embodied carbon dioxide emissions. This CO_2 emissions is estimated by its embodied intensity obtained by Input-Output analysis. By using this analysis, the intensity can include both direct and indirect CO_2 emissions. Indirect emissions means those of its intermediate inputs from other industries. As a result of this paper, its embodied intensity is 0.61 (t-c/ million yen) and its emissions is 346,552 (t-c). Comparing to other industries, they are large. Therefore, the environmental load of tourism in Okinawa is considerable.

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The purpose of this paper is to examine the determinants of tourism budgets of prefectures of Japan by using time-series data and cross-sectional data. Firstly, based on the financial statistics analyzed in time series, the tourism budgets, particularly investment expenses, have been in the long-term decrease since 1995. Two aspects can be considered to be the factors of the decrease of investment expenses; the reduction of subsidies from the Japanese government and the slowdown in growth of the tourism market. Secondly, the analysis of the data of 2009 shows the amount of tourism budgets is influenced on the tourism demand and the source of revenue for tourism. Although the tourism budgets of the prefectures depend on the subsidies, it is essential to establish the independent funding source.

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A bicycle is useful because of its flexibility and mobility for tourists to move around in large-scale regions including in rural areas. This study investigates tourists' behavior in the context of rental bicycle use in Azumino, Nagano, Japan. A GPS and GIS are used for tracking tourists on bicycles and their movement is logged and analyzed. The average utilization time is two and a half hours and the average travel distance is 11 kilometers. The time spent walking, at under 5 km/h on GPS logs, is longer than the time spent cycling, at above 5 km/h. Dual kernel density estimation is applied to visualize the intensities of tourists' space use, considering the differences between walking and cycling. Moreover, tourists' behavior is classified into three patterns by the sequence of their movement on GPS tracks. The sequence, time, and distance are compared in each pattern. Based on the results of these analyses, the determined factors of tourists' movement patterns are discussed.

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