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Article

Population Decline and Urban Transformation by Tourism Gentrification in Kyoto City

by
Riku Tanaka
,
Haruka Kato
* and
Daisuke Matsushita
Department of Housing and Environmental Design, Graduate School of Human Life and Ecology, Osaka Metropolitan University, Osaka 558-8585, Japan
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(3), 2247; https://doi.org/10.3390/su15032247
Submission received: 8 January 2023 / Revised: 16 January 2023 / Accepted: 23 January 2023 / Published: 25 January 2023
(This article belongs to the Special Issue Frontier Progress in Sustainable Tourism: Stakeholder, Society, and Environment Perspectives)
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Abstract

:
In recent years, tourist cities worldwide have experienced rapid tourism gentrification, which was caused by the spread of P2P accommodation-matching digital platforms. The research problem is set as follows: whether tourism gentrification caused a population decline in the historical center area of tourist cities. Therefore, this study aims to clarify the causal statistical relationship between population decline and tourism gentrification, focusing on urban transformation by accommodation. As a case, this study analyzes Kyoto City, a world-class tourist city. In summary, we conclude that tourism gentrification caused population decline through displacement in the historical center of Kyoto City. On the other hand, it was found that population decline occurred from factors other than tourism gentrification in the outside area of Kyoto City. The academic contribution is to clarify the effect of population decline on the cause of urban transformation through time precedence with statistical correlation. For tourist cities where the population is declining, the distinction between cause and effect is critical for policymaking toward sustainable tourism where the population is declining. The practical implication is the need for urban planning against tourism gentrification toward sustainability tourism in the historical center of Kyoto City.

1. Introduction

In recent years, tourist cities worldwide have experienced rapid tourism gentrification, which was caused by the spread of P2P accommodation-matching digital platforms. Tourism gentrification is a social problem that needs to be solved toward sustainable tourism. Tourism gentrification is defined as the reinvestment of capital in the urban center to produce space for a more affluent class of people than currently occupying that space [1]. Regarding tourism gentrification, Sigler et al. [2] advised that the driver of recent tourism gentrification is not simply the global rent gap due to the middle-class settlement but rather the new forms of tourism due to the spread of P2P accommodation-matching digital platforms, such as Airbnb. Regarding the effect of recent tourism gentrification, González-Pérez [3] analyzed the case of Parma and found three effects: financial effects, such as real estate speculation and rising property prices; social effects, such as eviction; and functional and scenic effects, such as symbolic and commercial transformations. For example, the disadvantages of tourism gentrification were reported as the change in retail supplies [4] and landscapes [5]. That means the recent spread of P2P accommodation-matching digital platforms has caused a paradox of tourism gentrification as a new urban phenomenon [6].
Among the effects of tourism gentrification, many researchers have discussed the specific social effects of displacement [7]. The severe problem of tourism gentrification unexpectedly results in the displacement of socioeconomically vulnerable local communities [8]. The displacement leads communities to experience disruptions to their mental health, feelings of dispossession, anger, and frustration [9]. Therefore, Cocola-Gant et al. [10] negatively evaluated the P2P accommodation-matching digital platforms as an example of buy-to-let gentrification that residents experience as a process of social injustice. In general, ordinary gentrification also causes middle-class settlement in renovated or redeveloped properties that were formerly occupied by local communities [11]. This inflow of middle-class settlement thus entails the former locals moving out of their local communities [12]. In addition, it was reported that the exclusive process in which local communities are absent from decision making results in inequality [13]. However, it was reported, in some cases, that gentrification affected specific local communities on a local basis but not on a city-wide basis [14]. Sometimes, gentrification is discussed emotionally [15]. Therefore, it is important for urban planning to elucidate statistically whether the population has declined locally or city-wide regarding tourism gentrification.
The research question of this paper is set as follows: whether tourism gentrification caused a population decline in the historical center area of tourist cities. For the research question, this study investigates the statistically causal relationship between population decline and tourism gentrification by distinguishing cause and effect. Regarding the relationship, López et al. [16] elucidated a process of population change was correlated with a decrease in the residents of traditional local communities. Parralejo et al. [17] also clarified the relationship between the increase in tourist accommodations and the population decline in historical center areas. In addition, Urquiaga et al. [18] clarified that the process of population change was related to accommodation supply. However, those previous studies have found correlations but have not clarified clear causal relationships. The causal relationship should be examined through correlation and time precedence of cause and effect [19]. That time precedence means the cause preceded the effect, based on John Stuart Mills’s theory [19]. Regarding the causal relationship, Kato et al. [20] analyzed Kyoto City using a geographic nature experiment and found that the accommodation location was related to population decline. However, a clear causal relationship has not yet been determined as to whether the accommodation location caused the population decline or whether the population decline caused urban transformation by accommodation. That means that there are research gaps in which correlations have been elucidated, but causal relationships have not. For policymaking, correlation alone is insufficient; causal relationships must be elucidated.
Therefore, this study aims to clarify the causal statistical relationship between population decline and tourism gentrification, focusing on urban transformation by accommodation. Urban transformation is defined as the urban systems that are complex, long-term, uncertain, and contested processes of radical change, which result from the interaction and feedback of diverse driving forces across sectors, scales, and time [21]. Therefore, urban transformations cannot be managed by traditional urban policymaking and planning approaches that aim to sustain and optimize existing urban regimes [22]. As a case, this study analyzes Kyoto City, a world-class tourist city. Japan, including Kyoto City, has declined in population due to a low birth rate and an aging population [23]. Therefore, it makes a practical implication to elucidate whether the cause of the population decline is tourism gentrification in Kyoto City. As a critical concept of this study, this study focuses on urban transformation by cities, which analyzes the process of change at the local scale [24]. Previous studies also found that tourism gentrification was attributed to urban transformation via the spread of P2P accommodations [25]. In detail, this study analyzed the urban transformation by accommodation, which is land use before the accommodation operated.
According to the concept of urban transformation, this study hypothesizes the following: If the land use of houses was urban transformation by accommodation correlated with population decline, we thus assume that this displacement caused population decline. On the other hand, if there were no urban transformations by accommodation correlated with population decline, then we assume that population decline was a result of factors other than displacement. The hypothesis is summarized in Figure 1. That hypothesis allows us to examine the effect of population decline on the cause of urban transformation through time precedence with statistical correlation. The distinction between cause and effect is critical for policymaking in Japan, where the population is declining by an aging society. The results would contribute to achieving the academic implication of the causal statistical relationship regarding population decline caused by tourism gentrification.
The originality of this study is to analyze Kyoto City in the historical center area and the outside area separately. The urban transformation was experienced as gentrification in inner areas [26]. It was also found that urban transformation by tourism gentrification is strongly influenced by the historical center area of tourist cities [27]. It was also found that the influence of tourism gentrification affects residents of traditional local communities in the historical center area [28]. These results suggest that the coexistence of traditional local communities and tourism gentrification is difficult socially and economically [28]. That is because the urban transformation by tourism gentrification transformed from rental houses to accommodations [29]. It was also elucidated that the tourism gentrification’s influence affected the historical center area to the outside area [30]. Therefore, this study separately analyzes Kyoto City in the historical center and outside areas. The results provide practical implications in determining the area of policy against tourism gentrification.

2. Materials and Methods

2.1. Case Study: Kyoto City

This study analyzed Kyoto City, a world-class tourist city, as a case study. Specifically, two areas in Kyoto City were analyzed: the historical center area and the outside area, shown in Figure 2 (as an aside, it must be noted that the satellite photo shown in Figure 2 complies with the copyright [31]). The historical center area contains three administrative wards: Kamigyo-ward, Shimogyo-ward, and Nakagyo-ward. This historical center area was also the capital of Japan for 1200 years [32]. Additionally, in the historical center area, many temples and shrines are registered as world heritage by the World Heritage Committee [33]. Therefore, tourists worldwide visit the area.
The analysis period was set as April 2015 to March 2020. During this period, the Japanese government actively attracted foreign tourists through visa relaxation and other measures [34]. Connected to this, rapid touristification became a social issue in Kyoto City. On the other hand, since April 2020, the COVID-19 pandemic has suppressed the inflow of domestic and foreign tourists [35]. During the period, Kato [36] analyzed the questionnaire regarding the resident evaluation of tourism gentrification in Kyoto City and clarified that residents negatively evaluated a decline in the population. Therefore, like other tourist cities worldwide, Kyoto City experienced tourism gentrification during the analysis period [20,36].
This study analyzed the building and neighborhood association (NA) scales separately. Further, land use was analyzed at the building scale. On the other hand, population change was analyzed at the NA scale, as this aggregates the building scale data. That is because Japan’s most miniature scale of population data is the NA scale. In addition, the NA scale is the same as the zip code scale. In Kyoto, NA is the basis for local communities, welfare, childcare, and disaster prevision [37]. Therefore, in Japan, NA plays an essential role in institutional decision making regarding urban planning [38,39,40]. For example, certain NAs have developed building agreements to regulate the zoning of SA [41]. Therefore, NA scale results would factor in the development of urban planning regarding tourism gentrification.

2.2. Analysis Flow

Figure 3 shows the methodology of this study, which consists of six steps. The satellite photo in Figure 3 complies with the copyright [31].
The first step identified the location of the accommodations in 2020. Specifically, this study plotted the location point data of accommodations, which began operation between April 2015 and March 2020. This study categorized accommodations as hotels and SAs. Then, the building polygon data in 2020 was drawn on the map. From the location point data and the building polygon data, the building polygon data of the accommodations were identified by dividing them into hotels and SAs.
The second step identified the location of land use in 2015. Specifically, building polygon data of land use in 2015 was drawn on the map using the land use data in 2020. This land use was categorized into ten types: accommodations, commercial facilities, schools, leisure facilities, high-rise buildings, public facilities, medical facilities, traffic facilities, others, and houses.
The third step clarified the land use in 2015, where accommodations were located in 2020. Precisely, the building polygon data of the accommodations in 2020 in the first step and land use in 2015 in the second step were superimposed on the map. Then the data from the overlapping areas would then clarify the urban transformation from 2015 to 2020.
Fourth, this study clarified the NA-scale population. Specifically, population change from 2015 to 2020 was plotted on the map. The map displayed the population change in seven levels: −100, −20, −5, ±0, +5, +20, and +100.
The fifth step produced NA-scale data on urban transformation and population data. In detail, this study aggregated the building scale urban transformation data in the third step by the NA scale. The urban transformation and population data were combined for each NA.
Finally, the sixth step elucidated the statistical relationship between urban transformation and population data. Multiple regression analysis was performed with population change as the objective variable and urban transformation as the explanatory variable. The multiple regression analysis used the ordinary least squares (OLS). The analysis was conducted separately for the historical center area and the outside area. The results would clarify the urban transformation statistically related to population decline in the historical and outside center areas.

2.3. Accommodation List

This study used the data from the “List of Permitted Facilities Based on the Accommodation Business Law” published by the Kyoto City Information Center [42]. This data includes attributes such as accommodation type, address, applicant name, and business application date. The types of accommodations are classified into hotels and SA. Based on the date of business application, this study identified accommodations that began operations between April 2015 and March 2020.
Accommodation, in this study, is analyzed further by dividing it into hotels and simple accommodations (SA). This classification follows the Ryokan business law in Japan [43]. Ryokan is translated as a Japanese-style hotel in Japanese. Under the Ryokan business law, “ryokan business” is defined as “the business of running a facility, receiving lodging fees, and allowing people to lodge there” [43]. In the eyes of the law, there are four types of accommodation businesses: hotel, SA, inn, and boarding house [43]. SA is mainly used in P2P accommodation services, such as Airbnb in Japan [44]. Among the four types, two types of businesses were analyzed: the hotel and SA. That is because the total amount of the two types within Japan is enormous. Moreover, there are studies on these types of accommodations as significant factors in the process of tourism gentrification in Kyoto City [20,36].

2.4. Census Data

This study uses data from the Japanese census to analyze the number of population changes from 2015 to 2020 [45,46]. The Japanese census is one of Japan’s most critical statistical surveys. Therefore, the government required all citizens to submit the survey. The survey is conducted every five years. Many urban planners use the data for policy making.

2.5. Land Use Data

This study uses data on land use in 2015 and 2020, which Zenrin, Inc sells publicly [47]. In Japan, the government owns land use data. However, it is not available to use the government land use data due to privacy protection. Therefore, the land use data sold by Zenrin, Inc. is Japan’s most accurate land use data. In the data, land use is categorized into accommodations, commercial facilities, schools, leisure facilities, high-rise buildings, public facilities, medical facilities, traffic facilities, others, and houses. Regarding the accommodation, it does not distinguish between the hotel and SA. Houses include detached houses and traditional townhouses. High-rise buildings include condominiums and offices.

3. Results

3.1. Urban Transformation by Accommodation

Section 3.1 analyzed the urban transformation by accommodation in Kyoto City. Figure 4 shows the location of accommodations. The satellite photo in Figure 4 complies with the copyright [31]. Figure 4 categorizes hotels and SAs.
As a result, Figure 4 shows more SAs than hotels. In addition, Figure 4 shows that many SAs are located inside the blocks. SA locations are different from those of hotels, which tend to be located outside of blocks facing the main streets.
Figure 5 shows the location of land use in 2015. The satellite photo in Figure 5 is in compliance with the copyright [31].
As a result, Figure 5 shows that houses are located in the most urban area of Kyoto City. It is the same trend not only in the outside area but also in the historical center area. Even in the historical center area, there are a large number of houses located in the blocks. It was also found that in the historical center area, there are some areas where houses are transformed into high-rise buildings.

3.2. Population Change

Section 3.2 analyzed the population change in the NA scale in Kyoto City. The satellite photo in Figure 6 complies with the copyright [31].
As a result, Figure 6 shows that the population decreased in the outside area. However, in the historical center area, it was found randomly adjacent to decreasing population areas and increasing population areas. This result suggests that the urban transformation by accommodation might be related to population decline in the historical center area.

3.3. Accommodation and Urban Transformation

Section 3.3 clarified the land use in 2015, where accommodations were located in 2020. Figure 7 shows the urban transformation by each land use. In Figure 7, the blue line is the urban transformation by SAs; the red line is that of hotels. Error bars in Figure 7 indicate 95% confidence intervals.
As a result, Figure 7 shows a large amount of urban transformation from houses to accommodations. Among the accommodations, it was also found that there were many urban transformations from houses to SAs. In particular, it was found that SAs had the urban transformation of two houses on average. That result suggests that displacement might have occurred due to urban transformation by SAs.

3.4. Urban Transformation and Population Change

Section 3.4 elucidated the statistical relationship between urban transformation and population change by multiple regression analysis (OLS). Table 1 shows the results of multiple regression analysis with population change as the objective variable and urban transformation as the explanatory variable. The analysis was done separately for the historical center area and the outside area. In Table 1, land uses that did not transform into accommodations are not listed, such as education facilities in the historical center area and medical facilities in the outside area.
As a result, Table 1 shows that the urban transformation that had a statistically significant relationship with population decline were houses in the historical center area. The result indicated a statistical relationship between urban transformation by accommodations and population decline. The results indicated that the urban transformation from houses into accommodations reduced the population by approximately five residents.
On the other hand, it was found that urban transformation other than houses is not associated with population change in the historical center area. In addition, in the outside area, all urban transformations, including houses, were found to be unrelated to population change. These results suggest that population decline was affected by the urban transformation by tourism gentrification as displacement in the historical center of Kyoto City.

4. Discussion

This study clarified that the urban transformation by accommodation caused a population decline in the historical center area of Kyoto City. That means that this study clarified the effect of population decline on the cause of urban transformation through time precedence with statistical correlation using multiple regression analysis. The results also indicated that the urban transformation from houses into accommodations reduced the population by approximately five residents. This result is reasonable because it implies that the urban transformation displaced about one family. That population decline is different from the population decline due to Japan’s low birthrate and aging population. That is because there is no urban transformation from housing to lodging if the aging population is the only cause of population decline.
In previous studies, it has been reported that there is a correlation between tourism gentrification and population decline [16,17,18]. However, the results of these previous studies did not elucidate the statistical causal relationship because those studies did not analyze the time precedence of cause and effect with statistical correlation [19]. Compared to those previous studies, this study’s result has significant academic implications because it leads to a conclusion to the research question regarding a causal statistical relationship: whether tourism gentrification caused a population decline. The reason why this study could clarify the causality is that this study analyzed time precedence with a focus on urban transformation.
On the other hand, no relationship was found between urban transformation and population decline in the outside area of Kyoto City. The result suggests that factors other than tourism gentrification might cause the population decline. That is because no urban accommodation transformation was statistically related to population change. In other words, the results suggest that the urban transformation by accommodation did not reduce the population, but rather that the accommodation might have been transformed on vacant lots caused by the population decline due to the aging population. Previous studies have pointed out that gentrification occurs in the center [23,24,25] and is derived from the center to the outside [27]. Regarding the research gap, this study clarified that gentrification occurs at the center of Kyoto City. In the outside area of Kyoto City, if the aging population is a problem, developing zoning regulations for SAs would be a mistake. Other than the zoning regulation, urban transformation by SA might contribute to revitalizing the outside area of Kyoto City by growing the tourist industry.
Furthermore, SAs caused the typical urban transformation from houses. That means that SAs caused more displacement than hotels. This result was reasonable because it was consistent with the conclusion of Kato et al. [20]. The spread of P2P accommodation- matching digital platforms transformed from houses to SAs. The result indicates the regulations for SAs.
Regarding the discussion about tourism gentrification, it is necessary to note the confounding factors of urban transformation and population decline. For example, urban transformation might link with the trends in land rents and housing prices in the discussion of ordinary gentrification [48]. It was reported that Kyoto City experienced ordinary gentrification in the 1980s [49]. Therefore, Kyoto City has experienced urban transformation through repeated urban decline and revitalization cycles. However, in the 1980s, the population did not decline because of resettlement in the central city [49]. Therefore, the finding that the population has declined despite urban transformation is remarkable. In the future, it is necessary to elucidate further the causal relationship by considering confounding factors over a more extended analysis period. For example, the COVID-19 pandemic would cause new tourism problems [50].
The results of this study suggest that tourism gentrification might cause displacement in the historical center of Kyoto City. In previous studies, it was reported that tourism gentrification caused displacement [3,18,25]. In the historical center of Kyoto City, Kato [36] clarified that residents negatively evaluated a decline in the population. However, they could not deny the possibility that the population declined locally, which Sumika [14] pointed out. This study clarified that the historical center area of Kyoto City experienced the same displacement issues as the historical center area of tourist cities worldwide.

5. Conclusions

In summary, we conclude that tourism gentrification caused population decline through the displacement in the historical center of Kyoto City. On the other hand, it was found that population decline occurred from factors other than tourism gentrification in the outside area of Kyoto City. Figure 8 summarizes the conclusions of this study in response to the hypotheses in Figure 1. In Figure 8, we could assume that this displacement caused a population decline in the historical center of Kyoto City because the land use of houses is an urban transformation caused by accommodation correlated with population decline. On the other hand, we could assume that population decline was a result of factors other than displacement outside of Kyoto City because there were no urban transformations due to accommodation correlated to population decline. The other factors might include the aging of the population.
The academic implication of this study is to clarify the causal statistical relationship regarding population decline caused by gentrification. In previous studies, there were research gaps in which correlations have been elucidated but causal relationships have not. In the field of urban planning, analyzing causal relationships using the randomized controlled trial method is difficult as a prospective study. The novelty of this study is to clarify the statistical causal relationship by focusing on urban transformation. It is expected that many tourist cities, not only in Japan, will experience a population decline in the future. For tourist cities where the population is declining, it is an important topic to determine whether the urban transformation caused the population decline or the population decline caused the urban transformation. The distinction between cause and effect is critical for policymaking toward sustainable tourism in Japan, where the population is declining.
The practical implication is the need for urban planning against tourism gentrification toward sustainability tourism in the historical center of Kyoto City. Urban planning for tourism gentrification needs to compare economic advantages and social disadvantages [19] thoroughly. Regarding the economic advantage as a collective benefit, touristification fostered the tourism industry as a private-sector-led urban revitalization, which created many jobs [51]. Touristification was also the urban strategy that was adopted in the role of a private-sector-led urban revitalization approach [52]. Regarding touristification, a more detailed cost–benefit analysis might move the gentrification issue to a second position. Therefore, urban planners should not ignore that touristification has made some contribution in Kyoto City, where the decline of traditional industries was a severe social problem. However, this study elucidated that excessive touristification caused displacement through tourism gentrification as severe collective costs. That means that tourism gentrification was an inconsistent consequence of the long endeavor of local government to foster neighborhood change in coalition with tourism and commercial development planning [53]. It is a social problem that urban planners cannot ignore because the accommodation location caused a population decline in the historical center area. In the historical center area, the government needs to prevent population decline while continuing to reap the economic benefits of sustainable tourism.
Toward the progress of sustainable tourism, urban planning plays a significant role. For example, urban planners could develop land use zoning and regulation of the total amount of accommodations in the historical center area, as in Spanish tourist cities [54]. One good practice was reported that the traditional local community developed its guidelines for tourism gentrification in the Shutoku District in the historical center area of Kyoto City [55]. The results of this study, analyzed at the NA scale, make it possible to develop urban plans to prevent population decline, taking into account the characteristics of the local communities [41]. In Kyoto City, population decline has recently been a social issue [56]. Therefore, the Kyoto City government has begun to revise the urban planning to solve the population decline due to the aging problem in the outside area [57]. This study’s result suggests that urban planners now need to consider new urban planning for tourism gentrification in the historical center area of Kyoto City.
A limitation of this study is that it does not elucidate the reason why displacement occurred in Kyoto City. Generally, it was found that the reason for displacement is the rising rent prices [3,29]. In Japan, however, rapid rent rises seldom occur because laws protect residents’ rights. On the other hand, rising land prices might directly impact inheritance taxes and property taxes in Japan. For the analysis of the reason for the displacement, it is necessary to investigate the residents who migrated from houses transformed to accommodations in the historical center area. That means it needs to research opinions among people who have decided to leave the historical center area and live elsewhere. Future research should analyze why the displacement occurred by addressing the issue of privacy protection.

Author Contributions

Conceptualization, R.T. and H.K.; methodology, R.T.; software, R.T.; validation, H.K.; formal analysis, R.T.; investigation, R.T.; resources, H.K.; data curation, R.T.; writing—original draft preparation, R.T.; writing—review and editing, R.T., H.K. and D.M.; visualization, R.T.; supervision, H.K.; project administration, R.T.; funding acquisition, H.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the JSPS KAKENHI (grant number 21K14318).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data of accommodation list and census data were available from references [37,38,39,40]. The data presented in this study are available on request from the corresponding author, H.K.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Hypothesis of this study. Regarding the cause of population decline, hypothesis (a) indicates the displacement, and hypothesis (b) indicates the other factors.
Figure 1. Hypothesis of this study. Regarding the cause of population decline, hypothesis (a) indicates the displacement, and hypothesis (b) indicates the other factors.
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Figure 2. Location of Kyoto City. (Author R.T. photographed the right-side pictures).
Figure 2. Location of Kyoto City. (Author R.T. photographed the right-side pictures).
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Figure 3. Analysis Flow.
Figure 3. Analysis Flow.
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Figure 4. Accommodation Location in 2020.
Figure 4. Accommodation Location in 2020.
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Figure 5. Land use in 2015.
Figure 5. Land use in 2015.
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Figure 6. Population Change from 2015 to 2020.
Figure 6. Population Change from 2015 to 2020.
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Figure 7. Average Land use Change from 2015 to 2020.
Figure 7. Average Land use Change from 2015 to 2020.
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Figure 8. Conclusion of this study. In response to the research hypotheses of Figure 1, (a) indicates that population decline was caused by displacement in the historical center of Kyoto City, and (b) indicates that population decline was caused by other factors in the outside of Kyoto City.
Figure 8. Conclusion of this study. In response to the research hypotheses of Figure 1, (a) indicates that population decline was caused by displacement in the historical center of Kyoto City, and (b) indicates that population decline was caused by other factors in the outside of Kyoto City.
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Table
Table 1. Urban Transformation and Population Change.
Table 1. Urban Transformation and Population Change.
BSEtpVIF
Historical center area(Constant)1.7782.7460.6500.517.
Accommodation Facility9.1829.4170.9800.3301.004
Commercial facility−11.95618.338−0.6500.5151.000
Leisure facility8.46720.5100.4100.6801.001
High-rise building1.0944.6840.2300.8151.015
Public facility17.73341.0200.4300.6661.001
Houses−5.0251.490−3.3700.001 *1.019
Outside area (Constant)−1.6143.516−0.4600.646.
Accommodation Facility−8.386118.078−0.0700.9431.000
Commercial facility−45.386204.456−0.2200.8241.000
High-rise building0.14023.8320.0100.9951.001
Public facility17.614144.5940.1200.9031.000
Others−10.43291.446-0.1100.9091.000
Houses−4.7093.946−1.1900.2331.001
Note: *: p < 0.01.
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Tanaka, R.; Kato, H.; Matsushita, D. Population Decline and Urban Transformation by Tourism Gentrification in Kyoto City. Sustainability 2023, 15, 2247. https://doi.org/10.3390/su15032247

AMA Style

Tanaka R, Kato H, Matsushita D. Population Decline and Urban Transformation by Tourism Gentrification in Kyoto City. Sustainability. 2023; 15(3):2247. https://doi.org/10.3390/su15032247

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Tanaka, Riku, Haruka Kato, and Daisuke Matsushita. 2023. "Population Decline and Urban Transformation by Tourism Gentrification in Kyoto City" Sustainability 15, no. 3: 2247. https://doi.org/10.3390/su15032247

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