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2023 | OriginalPaper | Chapter

How Would the Kyushu Super-Express Railway Opening Change the Flow of Tourists from the Kansai Region within the Kyushu Wide Area, Japan?: A Micro Behavior Analysis of the Destination’s Hub Function

Authors : Saburo Saito, Kosuke Yamashiro, Masakuni Iwami

Published in: Recent Advances in Modeling and Forecasting Kaiyu

Publisher: Springer Nature Singapore

Abstract

This study predicts whether residents in the Kansai region, the area around Osaka, Kyoto, and Kobe, will increase their sightseeing trips to Fukuoka, Kumamoto, and Kagoshima in the Kyushu region, the southernmost island among four major islands of Japan due to the Opening of the whole Kyushu Shinkansen line, super-express railway line, in March 2011, in terms of the number of people. We also predict how people’s flow among three regions, Fukuoka, Kumamoto, and Kagoshima, will change before and after the Opening of the Kyushu Shinkansen.
The Kyusyu Shinkansen Line partially opened in 2004 between Shin-Yatsushiro and Kagoshima, the south terminal, which composes almost half the southern end of the entire route. This time, the Kyushu Shinkansen line will open in its entire path from Fukuoka through Kumamoto down south to Kagoshima. We note that the location of the Kansai region is 600 km west of Kyushu island. Thus, if the Kansai region residents take the railway to Kyushu, they must take the existing super-express railway up to Fukuoka and then go through Kumamoto down south to Kagoshima using the new Kyushu Shinkansen line. Therefore, for the Kansai residents, since the change will take place beyond Fukuoka, nothing will change to Fukuoka by Opening the Kyushu Shinkansen so that their travel time and cost are the same as before. In this case, the prediction of the increase in the number of visitors to Fukuoka by the traditional models should be zero since Fukuoka’s travel time and cost are the same before and after the Opening of the Kyushu Shinkansen.
In contrast to the traditional models that assume Fukuoka’s attractiveness or value would not change before and after the Opening of Kyushu Shinkansen, this study thinks Fukuoka’s attractiveness or value would increase after the Opening of Kyushu Shinkansen. The reason why we think this is so is the following. Suppose that Fukuoka, Kumamoto, and Kagoshima constitute the composite sightseeing services and that the sightseeing resources are the same before and after the Opening of the Kyushu Shinkansen. Also, assume that visitors must pay the generalized travel cost or the price to consume the composite sightseeing travel services. The Opening of the Kyushu Shinkansen drastically reduces the generalized travel cost in terms of travel time. Thus the visitors can enjoy the same composite sightseeing services at lower prices. Hence, this study considers the Opening of the Kyushu Shinkansen to increase sightseeing visitors’ visit value to Kyushu.
This study aims to formulate this idea as the hub functions of three cities and construct a Poisson model to forecast the frequency of sightseeing trips incorporating the hub functions. Further, we show that the number of sightseeing visitors from the Kansai region to Fukuoka will also change due to the Opening of the whole Kyushu Shinkansen line and to predict how much the number of tourists for Kumamoto and Kagoshima will increase.
This study also applies the same framework to predict the change in people’s sightseeing flows among three regions, Fukuoka, Kumamoto, and Kagoshima, within the wide Kyushu area before and after the Opening of the Kyushu Shinkansen.

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Footnotes
1
Shinkansen refers to the high-speed bullet train network in Japan. For the Shinkansen network, see Ref. [1]. With the full opening of the Kyushu Shinkansen line, the Shinkansen network will be connected from Tokyo to Kagoshima, and JR West and JR Kyushu plan to jointly operate the direct bullet trains between Osaka and Kagoshima using Sanyo Shinkansen and Kyushu Shinkansen tracks.
 
2
Hakata Station is located at the city center of Fukuoka City.
 
3
Also refer to Saito and Yamashiro [7], which includes their studies based on this approach [812].
 
4
Our discussion is closely related to the competing destinations model by Fotheringham [13], in which he demonstrated that a simple gravity model produces biased estimates of the distance-decay parameters if ignoring the destinations’ accessibility measures which reflect the competition between destinations in a given spatial system under the aggregate framework of spatial interaction data. At the disaggregate level, he suggested an explanation that these biases are caused by misspecifying the individual two-stage decision-making behavior as one stage. However, the estimation was based on the aggregate spatial interaction data. In contrast, while we share the concerns with introducing the spatial transactions among destinations, our approach is the micro-behavioral approach, in which modeling and estimation are based on the disaggregate micro-behavior data. Also, we treat the distance decay as the generalized travel cost. Our issue in this study is how the transactions among destinations enhance the unique destination’s attractiveness, that is, not the competitive effect of other destinations on decreasing inflow to a particular destination but the hub effect of other destinations on increasing inflow to a particular destination. As for the aggregate modeling, the competing destinations model and Stouffer’s intervening opportunities model [14] have been combined and evolved into the radiation model due to Simini et al. [15]. For recent developments in the radiation model, refer to Kostubo and Nakaya [16].
 
5
This distance is the actual physical distance.
 
6
Actually, we collected the samples from the Kansai region residents, and the residents in three prefectures, Fukuoka, Kumamoto, and Kagoshima. However, as for the estimation and prediction of the number of sightseeing visitors from the Kansai region, we only use the samples from the Kansai region residents.
 
7
In cooperation with Mainichi Shimbun, the Mainichi, questionnaires are distributed and collected through their channel.
 
8
For predicting the number of visitors after the opening of Kyushu Shinkansen, we used only responses to the question items concerning the past travel behaviors to the Kyushu region. We did not use responses to the question items to ask about the intention of visits after the opening.
 
9
Usually the Kansai region is defined as composed of six prefectures including Wakayama Prefecture. Since there were no respondents from the residents of Wakayama Prefecture in the survey sample, Wakayama Prefecture was excluded from the analysis.
 
10
As of 2021, the shortest travel time from Hakata to Kumamoto is 32 min, and that to Kagoshima is 1 h 12 min.
 
11
As of 2021, the fare from Hakata to Kumamoto is 4700 yen and that to Kagoshima 10,110 yen.
 
12
The title of Table 10th in Report by Characteristics of Location in the Census of Commerce is “The number of shopping streets, the number of business establishments, the number of large stores, the number of business establishments in large stores, the number of employees, annual merchandise sales, and the sales floor space by commercial districts (shopping streets) by prefecture and city.”
 
13
For details including on-site Poisson models, refer to Saito et al. [26, 27].
 
14
The prediction results about the changes in tourists from the Kansai region were reported in the following newspapers. Refer to The Asahi [28], Kumamoto Nichinichi Shimbun [29], Nishi Nippon Shimbun [30], and The Mainichi [3134].
 
15
Cities and towns other than Fukuoka City comprising the Fukuoka metropolitan area as of 2010 are as follows; Cities (Shi): Ogori, Chikushino, Kasuga, Onojo, Munakata, Dazaifu, Koga, Fukutsu, Itoshima; Towns (Machi or Cho): Nakagawa, Umi, Sasaguri, Shime, Sue, Shingu, Hisayama, Kasuya. As of 2021, Nakagawa-Machi is promoted to a city.
 
16
Cities and towns other than Kumamoto City comprising the Kumamoto metropolitan area are as of 2010 as follows; Cities (Shi): Uto, Uki, Aso, Koshi; Towns (Machi or Cho): Misato, Gyokuto, Ootsu, Kikuyo, Mifune, Kashima, Mashiki, Kosa; Villages (Mura): Nishihara. Here, while we use the population as of 2005, we employ the administrative divisions as of 2010 due to the following. As for the Kumamoto metropolitan area, from 2005 to 2010, several municipalities at the level of Machi and Mura merged, and they were promoted to cities. For example, Kumamoto City incorporated neighboring towns (Machi) from 2005 to 2010 and became an ordinance-designated city.
 
17
Cities other than Kagoshima City comprising the Kagoshima metropolitan area are as of 2010 as follows; Cities (Shi): Ibusuki, Tarumizu, Hioki, IchikiKushikino, Aira. As for the Kagoshima metropolitan area, Kagoshima City, Ibusuki City, Hioki City, IchikiKushikino City, and Aira City have experienced mergers or incorporations of neighboring municipalities from 2004 to 2010 so that we employed the administrative divisions and populations as of 2010 to avoid complexity and confusion.
 
18
We have experienced difficulty getting the estimates of the coefficients that have signs that accord with our hypothesis. Therefore, we first deleted the variable, travel cost. Then, we set the hub function for the destination, Kumamoto, to zero. Further, we divided distances between the subject destination and its neighboring destination by the time distance from the sample i’s residence to the subject destination to give the variation to the hub function variable. Finally, we obtained an estimate consistent with our hypothesis.
 
19
The forecasting results about the changes in people movements among three prefectures, Fukuoka, Kumamoto, and Kagoshima, were reported in the newspaper, The Mainichi [35, 36].
 
20
The original version of this chapter appeared in Saito and Yamashiro [37].
 
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Metadata
Title
How Would the Kyushu Super-Express Railway Opening Change the Flow of Tourists from the Kansai Region within the Kyushu Wide Area, Japan?: A Micro Behavior Analysis of the Destination’s Hub Function
Authors
Saburo Saito
Kosuke Yamashiro
Masakuni Iwami
Copyright Year
2023
Publisher
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-99-1241-4_8