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In South Korea, elderly population aged 65 or above took up 16.5% of the total population as of 2021 and is expected to increase to 20.3% by 2025, thus leading the nation to enter the stage of a super-aged society (Statistics Korea, 2021). Due to continued decreases in both birth rates and mortality rates, aging, together with low birth rates, has come to be considered the most serious social problem. With an increase in the percentage of the aged population in the total population due to aging, attention has been directed at plans to enhance senior citizens’ quality of and satisfaction with life (Hong and Kim, 2016). Out of such plans, the importance of the elders’ good use of leisure has been stressed, and, in order to achieve this, the need to secure spaces for hobbies and leisure activities has emerged. At present, from among senior citizen welfare facility operation projects implemented by the state and local governments, senior citizen centers play the roles of such leisure welfare facilities (Jeon et al., 2014).

Because short-distance activities increase in old age due to health and physical constraints, it is important to create a physical environment where exchange with neighbors and community activities in the local community are possible (Kim and Koo, 2016). In order to prepare a basis that will provide senior citizens with opportunities for social participation and enable them to enjoy active lifestyles, an age-friendly walking environment must be taken into consideration without fail (Oh et al., 2021). In addition, siting that meets senior citizens’ demands must be performed in consideration of the local characteristics (Cho et al., 2010). In fact, one Fact-finding Survey on the Status of Senior Citizens (FSSSC; 2017) has confirmed great differences between urban and non-urban areas in the rates of using senior citizen centers. However, it is unclear as to how a walking environment taking the physical characteristics of the aged into consideration and differences in spatial demands affect the revitalization of senior citizen centers so that this study will analyze this problem through the case of Goyang-si (Goyang Special Case City) in Gyeonggi-do (Gyeonggi Province).

With the emergence of the problem of aging as a global demographic change, the World Health Organization (WHO) announced in 2007 the Global Age-friendly Cities Guide. A measure against the increase in aged population, they sought to create cities that, by providing diverse policies and services, would enable the aged to take part actively in the local community without inconvenience due to environmental changes. Accordingly, Gyeonggi-do legislated a related ordinance for active old age and joined the WHO’s Global Network of Age-Friendly Cities & Communities (GNAFCC) in 2018, thus pursuing an age-friendly city so that not only the aged but also people in all age groups may live comfortably.

Out of municipalities in Gyeonggi-do, as for Goyang-si, the number of senior citizens aged 65 or above amounted to 160,146 as of the end of August 2022, thus taking up 14.9% of the total population. The aging rate is expected to reach 20.6% by 2028, and the number of senior citizens is expected to reach 300,000 (305,687; 26.7%) by 2035, respectively, so that the city is faced with its entry into the stage of a super-aged society. In addition, though the number of senior citizen centers per 1,000 senior citizens in Gyeonggi-do was 4.81 (Gyeonggi Data Dream, 2022; and Gyeonggi Provincial Government, 2022), the number of senior citizen centers per 1,000 senior citizens in Goyang-si was merely 3.65 (Gyeonggi Data Dream, 2022; and Gyeonggi Provincial Government, 2022). Consequently, the city urgently needs to prepare for both an aged society and a super-aged society and must expand support for the creation of an environment for the aged (Moon et al., 2020).

Consequently, this study will select Goyang-si as the object of a case study and explore plans to revitalize the use of senior citizen centers in terms of walking accessibility and the characteristics of both spatial demands for and users of senior citizen centers. In order to achieve this, this study will perform multiple regression analysis of the number of registered members of senior citizen centers, walking environments surrounding senior citizen centers, spatial differences in the number of users of senior citizen centers, and sociodemographic statistical values, all of which are senior citizen center revitalization indices.

With a continued increase in senior citizens’ needs for leisure and social activities in a super-aged society, the preference for senior citizen welfare facilities has become stronger. South Korea’s baby boom generation (born in 1955-1963) is equipped with high educational levels and a wealth of social experiences. Consequently, discussion is urgently needed on the roles of senior citizen leisure welfare facilities meeting current senior citizens’ needs, which have become complex in contrast to those of senior citizens in the past (Lee and Yoon, 2018). According to Article 31 of the Welfare of Senior Citizens Act, senior citizen welfare facilities are divided into senior citizen residential welfare facilities, senior citizen medical welfare facilities, senior citizen leisure welfare facilities, and senior citizen protection agencies, and senior citizen leisure welfare facilities include the facilities of senior citizen welfare centers, senior citizen centers, and senior citizen education courses. As of 2021, out of 68,823 senior citizen leisure welfare facilities nationwide, senior citizen centers amounted to 67,211, thus taking up the bulk of senior citizen leisure welfare facilities. When the Ministry of Health and Welfare’s 2020 Fact-finding Survey on the Status of Senior Citizens (Ministry of Health and Welfare, 2020) is examined, 28.1% of the total senior citizens used senior citizen centers, which shows that senior citizen centers are representative senior citizen leisure welfare facilities used by senior citizens. In addition, through multiple regression analysis of factors affecting the quality of life of senior citizens aged 65 or above who used senior citizen centers in 25 gu (districts) in Seoul, Kang and Lee (2018) elucidated that satisfaction with life increased as satisfaction in the use of senior citizen centers increased. Interest in facilities for the good use of leisure in old age has thus increased with South Korea’s entry into a super-aged society, and, as such spaces for the good use of leisure, senior citizen centers have the positive effects of providing senior citizens with opportunities for leisure activities and promoting social relationships within this population group so that their importance has increased day by day (Lee, 2019).

While senior citizen centers are highly important, as has been mentioned above, most earlier research was conducted with a focus on senior citizen welfare centers out of senior citizen leisure facilities, which are far lower in the frequency of facility siting than are senior citizen centers. Based on data from the Korean Social Life, Health and Aging Project (KSHAP), Park and Park (2021) analyzed factors affecting the use of senior citizen welfare centers by senior citizens aged 65 or above living in K gu of 25 administrative gu (25 districts) in Seoul in 2018, confirming that the use of such welfare centers was affected by gender, age, educational level, and income level. Lee and Yoon (2018) conducted a survey and logistic regression analysis of senior citizens living in five eup (towns), myeon (townships), and dong (neighborhoods) near senior citizen welfare centers in N si (city) in Gyeonggi-do, discovering that variables including gender, educational level, current housing (home ownership, jeonse (returnable key money-based rental), monthly rental, etc.), and income were influencing factors of the use of these facilities. In addition, Park and Choi (2017) conducted a study in order to present architectural planning guidelines reflecting both users’ needs and geographical characteristics so as to revitalize senior citizen welfare centers in Chungcheongbuk-do (North Chungcheong Province), categorizing current status investigations and spatial compositions of senior citizen welfare centers.

In addition, as for senior citizen centers, research was conducted limited to satisfaction in using these facilities according to users’ characteristics rather than the surrounding physical environments or to sociodemographic factors. Ko and Lee (2017) conducted a survey of senior citizens using senior citizen centers in K gu of 25 administrative gu (25 districts) in Seoul and, through the methods of t-test, correlation analysis, and multiple regression analysis, discovered that the quality of senior citizen centers’ services, users’ ages, and users’ monthly incomes significantly affected satisfaction in using senior citizen centers in this order.

The walking environment for senior citizens is very important for movement to destinations. The means of transportation most often used by senior citizens who are mobile in daily life are in the order of foot (74.0%), subway (17.0%), and bicycle (7.0%) (Noh and Yang, 2011). Most activities in old age thus rely much on foot, and a comfortable, safe, and pleasant environment is very important for senior citizens. A study by Park et al. (2017) positivistically analyzed senior citizens’ walking behavior and elucidated that senior citizens’ walking activities occurred mostly within neighborhoods and that streets with high walking frequency in age-friendly neighborhood environments were places where facilities and walking safety conducive to senior citizens’ social activities had been secured. Consequently, because neighborhood living areas equipped with service facilities within walking distances play key roles in enhancing senior citizens’ living standards and letting them break out of a state of social isolation, it is necessary to grasp both the types of major facilities needed by senior citizens and walking distances from neighborhood living facilities (Choi and Park, 2017).

Most existing research on senior citizens’ walking environments consists of subjective surveys. Through multiple linear regression analysis based on surveys of senior citizens in Seongnam-si (Seongnam City) aged 60 or above, Lee (2011) confirmed that physical environmental factors affecting walking satisfaction included the continuity of sidewalks, presence/absence of street lights, speed reduction facilities, and benches. A study by Oh et al. (2021) conducted a survey of senior citizens aged 65 or above in Busan-si (Busan Metropolitan City) on age-friendly walking environments in reference to the WHO’s Checklist of Essential Features of Age-Friendly Cities. According to the results of analysis, satisfaction was high with pedestrian roads, pedestrian crosswalks, street shelters, and public toilets. Through a survey of senior citizens in areas in Daegu-si (Daegu Metropolitan City) with high concentrations of aged population on senior citizens’ awareness of walking environments, Park and Lee (2022) confirmed high awareness of the state of pavement, continuity, and slope out of physical walking environments were high. Based on the 2017 Survey on Residential Conditions, Kwon and Choi (2021) elucidated that, for senior citizens and people with disabilities nationwide, who are mobility-disadvantaged, age, gender, urban parks and green fields, and public transportation accessibility were factors affecting walking satisfaction. Establishing as the independent variables sociodemographic factors collected through a survey and variables including walking environments, neighborhood facility accessibility, and use of senior citizen centers, Kim (2019) conducted research to verify the mediating effects of satisfaction with senior citizen centers on senior citizens’ residential satisfaction. According to the results of the study, out of independent variables significantly affecting satisfaction with senior citizen centers, derived were the sociodemographic factors of gender, age, and family form and the walking environments and neighborhood facilities of sidewalk widths, safety evacuation facilities, traffic volume, pedestrian crosswalks, benches, parks, hospitals, and banks.

Article 55(2) of the Regulations on Housing Construction Standards, etc., stipulates that, when residents’ communal facilities are installed in a housing complex of 100 or more households, they must include senior citizen centers and children’s playgrounds in the case of a housing complex of 150 or more households. From this, it is apparent that the installation of senior citizen centers focuses on population density rather than demands. If the supply of public facilities to cities centered on population density in the past, nowadays, a consideration of residents’ actual activities is becoming important (Kim, 2021). Because an unequal distribution of public facilities among areas is linked to differences in the quality of life of service users, solutions must be prepared (Seoung, 2019). Consequently, in order to stop quantitative supply and to be able to supply public facilities appropriately to areas needing them, investigations of local demands and local characteristics are prerequisites (Jo and Nam, 2019).

Most existing studies on demands for senior citizen welfare facilities assume that these facilities must be sited in areas with high concentrations of senior citizens on the basis of the housing construction standards mentioned above. Establishing aging rates and proportions of super-aged senior citizens as senior citizen welfare demand variables and limiting the senior citizens welfare supply variable to the number of such facilities, Choi and Cho (2020) used the Coulter coefficient of inequality, location quotient (LQ), and Relative Concentration Index to analyze regional equity in the supply of senior citizen welfare facilities. A study by Jeon et al. (2019) derived areas concentrated with populations aged 65 or above in Cheongju-si (Cheongju City) on the level of aggregated gu and, through network analysis per city-based facility including senior citizen welfare facilities and convenience facilities, examined equity in services. In addition, in order to analyze the balanced arrangement of senior citizen centers in Buk-gu in Gwangju-si (Gwangju Metropolitan City) that took into consideration the scope of senior citizens’ movements, Song et al. (2017) established a radius of 150 m as senior citizens’ pedestrian space in areas concentrated with senior citizen centers in Buk-gu and elucidated that overlapping senior citizen centers must be relocated or combined. In order to explore spatial disagreement between the spatial distribution of facilities demanded by senior citizens in Seoul and senior citizens’ actual residential distribution, Cho and Lee (2017) examined such spatial disagreement through both the spatial distribution of the six types of facilities of hospitals, traditional Korean medicine (TKM) hospitals, parks, senior citizen centers, senior citizen welfare centers, and traditional markets and the distribution of senior citizens’ residential areas by using Moran’s I technique.

The uniqueness of this study is as follows. First, factors affecting the revitalization of the use of senior citizen centers will be analyzed by adding physical and spatial characteristics to sociodemographic characteristics. Sociodemographic characteristics such as users’ genders and ages are major factors affecting the use of such facilities and were analyzed in earlier research as well, but the effects of physical environments surrounding the facilities failed to be sufficiently taken into consideration. This study will simultaneously examine the effects of both physical environments around senior citizen centers and differences in spatial needs, which were not examined in existing research.

Second, physical walking environments near senior citizen centers that make it possible to enhance senior citizens’ access to these facilities will be measured to find out their effects. Existing studies (Lee, 2011; Oh et al., 2021; Park and Lee, 2022; Kwon and Choi, 2021; and Kim, 2019) showed that pedestrians’ sociodemographic characteristics and physical environments subjectively perceived by pedestrians were important factors of walking activities. However, existing research based on surveys rely on pedestrians’ perception. Evaluations through surveys can differ in satisfaction according to pedestrians’ tendencies even in the same walking environment. In contrast, this study will explore differences in the number of senior citizen centers according to differences in physical walking environments objectified on the basis of digitized data.

Third, establishing the number of registered members of senior citizen centers as a measure of actual demands, this study will analyze spatial differences in demands for senior citizen centers and present a plan for revitalizing senior citizen centers. Research on senior citizen welfare facilities, which currently are installed according to the criterion of population density, mostly relies on the number of facilities installed, which is limited in failing to reflect actual demands. Indeed, though senior citizen centers so far have been supplied more in urban areas according to the criterion of population density, according to the Ministry of Health and Welfare’s 2017 Fact-finding Survey on the Status of Senior Citizens, the rate of using senior citizen centers was higher in non-urban areas than in urban areas (Ministry of Health and Welfare, 2017). Consequently, finding out regional and spatial differences in demands for the use of senior citizen centers is important for the appropriate siting and revitalization of these facilities.

As in <Figure 1>, the temporal and spatial scopes of this study were senior citizen centers in Goyang-si in 2018. Data on the zone boundaries of administrative dong and senior citizen centers in the city were acquired from both the Open Market on the Korea National Spatial Data Infrastructure Portal and the Gyeonggi Data Dream. In the case of senior citizen centers, data on addresses were converted into spatial data through Geocoding in/of ArcGIS Pro, as shown in <Figure 1>. While there were 560 senior citizen centers in Goyang-si as of 2018, 555 were constructed for this study, with the exclusion of five facilities with missing data. Senior citizen centers in the city were concentrated near Ilsan New Town and the Hwajeong housing site development district, both areas with relatively high population density.

Figure 1. 
The study area in Goyang-si, South Korea and spatial distribution of senior citizen centers

<Figure 2> shows the results of the spatial clustering of the number of registered members of senior citizen centers derived through Getis-Ord Gi*, and the clusters thus formed exhibit spatial slanting. When the spatial clusters derived are interpreted with respect to the boundaries of administrative dong in Goyang-si, coldspots are Ilsan New Town, Hwajeong district, and Haengsin district including Juyeop-dong, Daehwa-dong, Madu-dong, Jeongbalsan-dong, Janghang-dong, and Haengsin-dong, all of which are housing site development districts where urbanization has proceeded. Areas where hotspots are located correspond to those with high percentages of non-urban areas such as Gobong-dong and Gwansan-dong. This is interpreted to signify that because there are many other leisure spaces that can be chosen according to one’s tastes and preferences, senior citizens in urban areas use senior citizen centers relatively less. As for senior citizens living in non-urban areas, because leisure spaces are limited to senior citizen centers, spatial slanting seems to arise in the rate of utilization. This is supported by the 2017 Fact-finding Survey on the Status of Senior Citizens announced by the Ministry of Health and Welfare, according to which, the percentage of senior citizens using senior citizen centers was 11.5% in urban areas and 48.5% in non-urban areas, respectively (Ministry of Health and Welfare, 2017). Indeed, when the sites of senior citizen leisure welfare facilities were analyzed on the basis of data on senior citizen leisure welfare facilities as of 2018 provided by the Goyang City Government, urban areas in the city had many leisure facilities besides senior citizen centers including seven educational courses for senior citizens (two in Daehwa-dong, one in Janghang-dong, two in Hwajeong-dong, and two in Haengsin-dong), three senior citizen welfare centers (one in Daehwa-dong, one in Janghang-dong, and one in Hwajeong-dong). In contrast, non-urban areas had one educational course for senior citizens (one in Gobong-dong) and no senior citizen welfare centers, thus showing relative and regional differences in the number of leisure facilities.

Figure 2. 
Spatial distribution of Hotspot/Coldspot in the number of Registered member

Before explaining the results of regression analysis, this study diagnosed the homoscedasticity of the residuals of the regression analysis models. If and when the homoscedasticity hypothesis, a basic hypothesis of regression analysis that variances of the residuals are identical, is violated, the results of the regression models can no longer be trusted (Breusch and Pagan, 1979). Consequently, in order to verify whether or not the regression analysis models in this study satisfied homoscedasticity, the White test was performed. According to the results of White test, significance levels were equal to or greater than 5% for two of the models (p-value=0.121 (Model 2), 0.12 (Model 3)). However, because the significance level was equal to or less than 5% (p-value=0.016) for Model 1, heteroscedasticity was shown to exist. In order to resolve problems due to heteroscedasticity, the values of robust standard errors, which adjust standard errors in the results of regression analysis, were derived and a multiple regression analysis model was constructed.

As shown in <Table 3>, out of the results of multiple regression analysis, value R² was 0.207 for Model 1, 0.158 for Model 2, and 0.205 for Model 3, respectively. This indicates the explanatory power of independent variables of each model with respect to the number of registered members of senior citizen centers, which is a dependent variable. In other words, it means that the explanatory power is 20.7% for Model 1, 15.8% for Model 2, and 20.5% for Model 3, respectively. Next, multicollinearity (i. e., variance inflation factors (VIFs)) in multiple regression analysis of the three models above with respect to independent variables was reviewed, the results of which derived VIF values of 5 or less for all variables so that there was no problem with multicollinearity.

When Model 3, which, out of the three models, includes all variables, is examined first, the number of CCTVs, mean slope, areas of major roads, and hotspots and coldspots with concentrated numbers of registered members of senior citizen centers were derived as significant variables from among independent variables at significance levels within 95%. Identically to results derived in earlier research that used surveys on senior citizens’ walking environments (Lee, 2011; and Park and Lee, 2022), the slope and the areas of major roads (continuity of sidewalks) were derived as significant variables. In addition, hotspots and coldspots, which involve the degree of concentration of the number of registered members of senior citizen centers and were used to find out spatial differences in demands for these facilities, were statistically significant factors in this study. When, out of physical walking environment variables, CCTVs in pedestrian space around senior citizen centers (400 m) increased by one, the number of registered members of senior citizen centers decreased by 0.113. When the mean slope increased by 1°, the number of registered members decreased by 0.706. When the area of major roads increased by 1 km², the number of registered members decreased by 71.437. In addition, as for senior citizen centers’ spatial bias variables, hotspots had 8.333 more annually registered members of senior citizen centers than did other areas, and coldspots had 4.798 fewer annually registered members of these facilities than did other areas.

However, in Model 3 in this study, all sociodemographic variables were statistically insignificant, unlike in earlier research. This is clear (Table 3) from the results of Model 2, with the exception of the spatial clustering variable. With the spatial clustering variable excluded, Model 2 derived areas of pedestrian roads, percentage of males, and percentage of single-person households as significant variables. In Model 3, which included spatial clusters, significance was revealed not in the variables above but in the spatial clustering variable. Because spatial clusters may have influencing relationships with the variables of areas of pedestrian roads, percentage of males, and percentage of single-person households, sociodemographic variables in this model seem to have lost significance. As for areas of pedestrian roads, the mean value (3.1 km²) in urban centers (coldspots) was higher than the mean value (0.3 km²) in non-urban areas (hotspots). As for the percentage of single-person (aged) households, the man value was 37.7% in urban centers and 34.6% in non-urban areas, respectively, with the former surpassing the latter in the percentage of single-person households. Consequently, areas of pedestrian roads and the percentage of single-person households can be interpreted as variables indicating urban centers. As for the percentage of males, the mean value in non-urban areas (43.0%) was greater than that in urban centers (40.7%). Because variables that were thus significant in Model 2 exhibited patterns similar to those of the spatial clustering variable, when they are taken into consideration together with the latter variable, significance levels can be low. In order to explore such differences more clearly, however, additional positivistic research is necessary. In addition, such differences in data can be the causes of distorted results because this study was constructed in terms not of pedestrian space but of units of administrative dong due to limitations in collecting data in the construction of sociodemographic variables. In other words, such results must be taken into consideration as variables that are important for revitalizing senior citizen centers even though walking environment variables including areas of pedestrian roads and sociodemographic variables including the percentages of males and single-person households were statistically insignificant in Model 3. This point agrees with the results of earlier research as well.

According to the results of analysis in this study, in consideration of physical walking environments, senior citizen centers’ spatial characteristics, and sociodemographic characteristics, the number of CCTVs within a radius of 400 m from senior citizen centers had a negative (−) relationship with the number of registered members of senior citizen centers, thus exhibiting results differing from the hypothesis established in this study. As for CCTVs, this study failed to take into consideration the time gap between the time frame of installation and the time frame of the perception of pedestrian safety after installation. For these reasons, the following interpretation is possible. Crime prevention effects did not arise because many CCTVs were installed. Rather, the places where these devices were installed originally were environments with poor crime prevention so that the number of CCTVs was increased, without changes in pedestrians’ perceptions such as subjectively felt safety and the mitigation of fear. According to Baek et al. (2018), residents tend to perceive areas installed with CCTVs as crime-ridden areas. Pedestrian safety can increase when, after the installation of CCTVs, residents perceive the installation these devices and feel safe. Consequently, it can be interpreted that the relationship was derived as a negative (−) one due to the occurrence of a time gap between the time frame of installing CCTVs and the time frame of perceiving pedestrian safety. As for other interpretations of the relationship between the number of CCTVs and the number of registered members, the matter can be examined in terms of places where CCTVs are installed. In order reasonably to install CCTVs in places where pedestrians’ safety can be guaranteed, local governments have established the goal of installing public CCTVs at points with high crime rates. However, there is no clear standard on CCTV installation so that, with police cooperation regarding criminal data difficult to expect, local residents’ opinions must be relied on to a considerable extent (Han et al., 2018). For this reason, even when there are many CCTVs around senior citizen centers, positive effects on pedestrians’ safety may be difficult to expect.

Next, the mean slope has a negative (−) relationship with the number of registered members of senior citizen centers. As for Goyang-si, though the mean slope is approximately 2° so that relatively level land is formed, it shows that differences in slopes affect walking environments even in such a level region. Even in a level topographic environment, the steeper slopes are, the more difficult it becomes for senior citizens to maintain a balance due to reduced physical functions, thus increasing the risk of accidents such as slipping and injuries from falls (Roh and Park, 2018). Consequently, increases in the mean slope cannot create walking environments that are conducive to senior citizens’ access to facilities. The areas of major roads likewise have a negative (−) relationship with the number of registered members of senior citizen centers. It seems to be because when the area of major roads increases, the number of severed pedestrian roads increases, and when traffic volume in and widths of major roads increase, the frequency of accidents increases (Park and Lee, 2016), thus creating a walking environment that is vulnerable in terms of traffic safety and poor in terms of safety and negatively affecting the use of senior citizen centers sited in the area. In addition, according to the results of this study, hotspots, which are concentrated areas with a large number of registered members of senior citizen centers, have a positive (+) relationship while coldspots, which are concentrated areas with a small number of registered members of senior citizen centers, have a negative (−) relationship. Such results statistically show that, in a situation with other walking environments controlled, there are absolute spatial differences in the number of users of senior citizen centers. As shown in <Figure 2>, senior citizen centers in Goyang-si that were concentrated in urban areas such as new towns and housing site development districts but exhibiting low rates of utilization were coldspots. Distributed on the outskirts was a relatively small number of senior citizen centers, which exhibited high rates of utilizations so that they were derived as hotspots. In other words, the results agreed with the hypothesis established in this study: demands for senior citizen centers are greater in urban outskirts and non-urban areas, which are not equipped with diverse cultural infrastructures, than in urban centers, which are equipped with such infrastructures. This shows the need for installation criteria that take into consideration differences in geographical and spatial demands together with installation according to population density, or the existing senior citizen center installation criterion.

Some variables out of the physical walking environment variables established in this study were statistically insignificant. As for major roads in pedestrian space, increases in their areas alone increased the number of vehicles and therefore were directly linked to ruptures in walking so that qualitative levels may not have had significant effects. In contrast, because green fields and urban parks, which can significantly affect pedestrians in walking environments on qualitative levels, were taken into consideration in terms only of the areas of housing complexes, statistically insignificant results were derived. For senior citizens, sidewalk pavement materials, shades of street trees, degree of cleanliness, and benches providing rest during walks can affect the qualitative levels of the walking environment rather than areas. In addition, insignificant results may be characteristics only of Goyang-si, the object of this study. In the results of a survey of residents of the city by Yoon and Lee (2021), the factor most strongly affecting the walking environment was illegal parking/stopping of vehicles. In addition, reflecting the necessity to take into consideration not only hardware aspects but also software factors such as sidewalk pavement materials, degree of cleanliness, cooperation in land use, and citizen-centeredness (community spaces), it is possible to present the interpretation that factors other than the physical walking environment can be significant to pedestrians in Goyang-si.