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Having emerged as an issue in contemporary society, the occurrence of vacant houses has established itself as a chronic and difficult problem in not only large cities but also rural areas and small and medium provincial cities. Vacant houses threaten the socioeconomic stability of cities and accelerate urban decay, thus bringing about a vicious cycle where they lead, once more, to an increase in vacant houses.

With the Population and Housing Census by Statistics Korea as the standard, the number of vacant houses across South Korea amounted to approximately 1.5 million 18 thousand in 2019, an increase by approximately 980 thousand houses in comparison with the previous year, which took up approximately 8.4% of the total number of houses. In addition, according to data from the Ministry of Land, Infrastructure and Transport (MOLIT), it is possible to observe a phenomenon where vacant houses continuously emerge, with a focus on old downtown areas. In a situation where such a trend is predicted to continue, the estimated ratio of vacant houses in South Korea is expected to amount to approximately 13% in 2025 (Park, 2018).

The fact that vacant house increase rates are high in small and medium provincial cities other than the Seoul metropolitan area and large cities must be understood from a perspective identical to that on issues such as the extinction of provincial communities due to underpopulation or depopulation (Jang and Kwon, 2021). With the exception of the Seoul metropolitan area, Gyeongsangnam-do (South Gyeongsang Province) is the region with the second largest number of vacant houses. When the current status of old and poor detached houses in Gyeongsangnam-do other than houses for transactions including unsold houses is examined, the following areas have the largest numbers of vacant houses, in this order: 1,394 houses in Goseong-gun (Goseong County); 1,278 houses in Tongyeong-si (Tongyeong City); 1,250 houses in Changwon-si (Changwon City); and 1,180 houses in Jinju-si (Jinju City).

Because the causes of vacant houses are so diverse that they cannot be conclusively attributed to one particular characteristic, they must grasped with a focus on the characteristics of the area in question. The study by Silverman et al. (2013) cites as a cause of vacant houses socioeconomic or housing market deterioration such as a rise in the poverty rate or areas with businesses that exhibit high long-term absence rates. A study by Molly (2014) points out an oversupply of housing and a low housing demand as causes of vacant houses. Unlike in the present, in the past, there was no interest in the problem of vacant houses itself because their occurrence was seen as one of the physical phenomena arising due to problems such as urban decay (Accordino and Johnson, 2000).

To this day, many cities worldwide have failed to break the vicious cycle of urban decay due to a method of presuming development and growth and experienced difficulties resolving diverse ensuing problems (Kabisch et al., 2006). Decline due to continued urban congestion gives rises to a population decrease along with a long-term economic recession in the area in question and to changes in the physical environment of urban spaces (Olsen, 2013; Pallagst, 2010).

A broader understanding of the problem of vacant houses becomes possible only when the occurrence of vacant houses is grasped in a complex manner together with demographic, economic, and social circumstances instead of being viewed through a single cause (Glock and Hartmut, 2004). At present, vacant houses occur in nearly all areas in South Korea regardless of population increase or decrease. Consequently, continuously under way is research to determine the causes of vacant houses and to devise responses to the problem (Lee and Lee, 2017).

Due to an increase in vacant houses, efforts have been made to improve policies and systems for managing vacant houses on the levels of both the central government and local governments. Though support was provided to the use and management of vacant houses in farming and fishing villages through the Agricultural and Fishing Villages Improvement Act legislated in 1994 and the Act on the Promotion of Amelioration of Housing in Agricultural and Fishing Villages legislated in 1995, the relevant law was amended as the Building Act in 2016 due to the spread of vacant houses into urban areas. Subsequently, the Act on Special Cases Concerning Unoccupied House or Small-scale Housing Improvement was legislated in 2017, leading to local governments’ legislation of ordinances related to vacant houses. In particular, the Act on Special Cases Concerning Unoccupied House or Small-scale Housing Improvement is the first law created to construct a vacant house management system systematically and has the policy significance of perceiving vacant houses as an urban problem and seeking to maintain or repair them efficiently. According to elucidation by Kim et al. (2020), however, this law focuses on resolving the problem of vacant houses through demolition in implementing small-scale housing maintenance/repair projects and therefore is limited in fundamentally resolving the problem of vacant houses. Consequently, ex post and passive policy responses and a situation that makes a planned management of vacant house-dense areas difficult have been pointed out as problems.

Against such a backdrop, this study seeks to grasp the current status of the occurrence of vacant houses on the regional level and to compare the characteristics of the occurrence of vacant houses according to special-purpose areas. In accordance with these, it seeks to explore the characteristics of vacant house concentrations in residential and commercial areas and to analyze the influencing factors of vacant houses, thus proposing the direction for effective vacant house management. In other words, the goal of this study is to present ex ante planned activities necessary for managing vacant houses per special-purpose area positivistically.

The spatial scope of this study was Jinju-si in Gyeongsangnam-do. Currently, Jinju-si exhibits the doughnut effect and the decline of its old downtown area due to the large-scale development of its outskirts such as Innovation Cities and station catchment areas. As of 2020, a total of 11,436 vacant houses existed in Gyeongsangnam-do, out of which 1,180 (approx. 10.3%) were possessed by Jinju-si, thus ranking fourth in areas with high occurrences of vacant houses in the province after Goseong-gun (approx. 12.2%), Tongyeong-si (approx. 11.2%), and Changwon-si (approx. 11%). As can be seen in <Figure 1>, according to investigations, there were a total of 580 vacant houses in the urban area, or center, of Jinju-si and a total of 600 vacant houses in the non-urban area, or outskirts, of the city, respectively:

Figure 1. 
Status of vacant houses in Jinju-si

In order to establish the scope of this study, the degree of the density of vacant houses in Jinju-si was analyzed. According to the results, as in <Figure 2>, there was a concentration of 45 to over 134 vacant houses even in the urban area of Jinju-si, with a focus on the old downtown area. Consequently, out of the city’s old downtown area, which matches the definition of a vacant house-dense area that this study seeks to grasp, the Cheonjeon-dong (Cheonjeon Neighborhood), Seongbuk-dong (Seongbuk Neighborhood), Jungang-dong (Jungang Neighborhood), and Sangbong-dong (Sangbong Neighborhood) areas were selected as the target areas, and their characteristics were analyzed:

Figure 2. 
Density of vacant houses in Jinju-si

The temporal scope of this study was 2019-2021. Based on data on vacant houses in Jinju-si investigated in 2019, field surveys were conducted on a total of three occasions. The actual circumstances were investigated during May 8-23, 2020 on the first occasion and during September 3-27, 2020 on the second occasion, respectively. The third investigation was conducted during July 8-21, 2021, thus concluding the investigations of the reality of vacant houses.

The scope of the contents of this study was to classify special-purpose areas in the target areas into residential and commercial areas, to extract the number of vacant houses, to analyze factors influencing the occurrence of vacant houses, and to prepare plans for vacant houses per area. As for the data on vacant houses used in this study, basic analysis was conducted by using data on vacant houses investigated by civil servants of Jinju-si.

Before field surveys, <Figure 3> shows the derivation of a vacant house-dense area, with a part of Cheonjeon-dong in the old downtown area of Jinju-si as an example. Vacant houses were considered to be concentrated when 2-3 or more of them existed on a single parcel. When vacant houses were outside parcels or existed independently, they were considered not to be concentrated. Subsequently, based on the second field survey, physical characteristics, individual structure characteristics, demographic characteristics, geographical characteristics, and environmental characteristics were added to concretize the data.

Figure 3. 
Examples of density discrimination

This study proceeded in this process: first, the identification of the distribution of vacant houses in the target areas and current status surveys; second, the construction of analysis methods and variables; and third, the analysis of the occurrence of vacant houses in the target areas and of the characteristics of these areas. To achieve this, literature review, field surveys, geographic information system (GIS) analysis, and vacant house occurrence influencing factor analysis through SPSS (v. 28) and Process Macro for SPSS (4.0) were performed. The detailed process of this study was as in <Figure 4>.

Figure 4. 
Description of the research flow

At stage 1, GIS was used to confirm the general current status of and the vacant house distribution in Jinju-si. In addition, through field surveys of the four dong (neighborhoods) in the old downtown area of Jinju-si, the general characteristics of vacant houses in residential and commercial areas were derived. At stage 2, through a review of earlier research, the causes of the occurrence of vacant houses were constructed as the variables, and analysis methods were established. At stage 3, the characteristics of the occurrence of vacant houses in residential and commercial areas were analyzed, and a conclusion was derived. At stage 4, based on the causes of the occurrence of vacant houses derived, plans for using vacant houses per type were derived.

In relation to the occurrence and formation of vacant houses, research grasping the causes of the occurrence of vacant houses has been conducted in multifaceted ways: housing market characteristics (Park and Oh, 2018; Kim and Kim, 2019); sociodemographic characteristics (Basset et al., 2006; Molly, 2016; Lim and Na, 2020; Park and Lim, 2020); physical characteristics (Mallach, 2006; Lee, 2020); and spatio-structural characteristics (Wilson et al., 1994; Morckel, 2013; Kim et al., 2020; Lee and Kim, 2021).

Examining the causes of the occurrence of vacant houses in terms of the housing market, Park and Oh (2018) used data on individual structures to analyze the factors behind the occurrence of vacant houses in Daegu-gwangyeoksi (Daegu Metropolitan City). Unique physical characteristics of individual structures having significant influence on the occurrence of vacant houses were the structures’ areas, numbers of stories, and degree of deterioration. The smaller the areas, the fewer the numbers of stories, and the further in the past the years of the construction of houses were, the higher was the likelihood of the occurrence of vacant houses. In terms of the regional characteristics, the number of adjacent vacant houses, the presence or absence of maintenance areas, and the population growth rate and the aged population ratio in the last five years were grasped as important variables, and the greater the number of adjacent vacant houses, the more within maintenance areas houses were located, the lower the areas’ population growth rates were, and the lower the aged population ratios were, the higher was the likelihood of the occurrence of vacant houses. In conclusion, the occurrence of vacant houses implies that the additional occurrence of vacant houses in adjacent areas can be brought about. With Gwangju-gwangyeoksi (Gwangju Metropolitan City) as the target area, Kim and Kim (2019) analyzed vacant houses per housing type. Using data provided by Statistics Korea, analysis was conducted after classification into houses that were vacant due to other reasons and vacant houses that had not been used or inhabited for one year or more. Derived from the results was the fact that vacant houses occurred the most with detached houses and apartments. Subsequently, regression analysis was conducted to elucidate that vacant house ratios increased due to population migration to adjacent areas, an increase in the aged population, and a decrease in the economically active population. In addition, the decline of local industries and infrastructures rather than urban decay were pointed out as causes of an increase in vacant house ratios.

As for research from the sociodemographic perspective, a study by Basset et al. (2006) is representative. In the study by Basset et al. (2006), the causes of the occurrence of vacant houses in Flint were analyzed on a macroscopic level. According to the results, factors such as race, school closures, process of changes in neighborhoods, and large-scale debts were derived to cause vacant houses. In relation to this, a study by Molly (2016), too, demonstrated positivistically that an increase in unemployment rates, an increase in impoverished household ratios, and an increase in seized house ratios were related to the occurrence of vacant houses, thus confirming that changes in population structures and lifestyles increased the number of vacant houses in an area. In a study by Lim and Na (2020), with Incheon-gwangyeoksi (Incheon Metropolitan City) as the target, the types and influencing factors of the occurrence of vacant houses were analyzed. When the area was analyzed after being classified into the inner city type, mixed type, insular type, and expandable type, the density of vacant houses was high, in this order: inner city type; mixed type; expandable type; and insular type. In the inner city type, the degree of the deterioration of vacant houses was the highest due to lots with low accessibility to the Seoul metropolitan area and a failure to guarantee economic feasibility in reconstructions and redevelopments, and the correlation between population decrease and the occurrence of vacant houses was the highest. In the mixed type, the ratio of vacant houses with a comparatively low degree of deterioration was high. The insular type had this characterized: though the proportion of vacant houses was small, the risk of vacant houses was very high due to the natural occurrence of vacant houses brought about by the departure of young people and the deaths of senior citizens. The expandable type had this characteristic: Incheon-gwangyeoksi expanded because of aspects such as innovative industries so that the quality of housing was fair and vacant house density and deterioration were low but vacant houses occurred in the old downtown area inside the city due to population migration to new cities. In the study by Park and Lim (2020), data on vacant houses in Jeonju-si (Jeonju City) were used to analyze the characteristics of the distribution of vacant houses. In order to analyze the characteristics of hot spots where vacant houses were concentrated, the following were used: as regional characteristic variables, housing benefit beneficiaries, population increase rates, aged population ratios, aged house ratios, and average actual transaction prices; as physical characteristic variables, the numbers of years elapsed since the construction of houses, structures’ gross floor areas (GFAs), and widths of the closest roads; and, as land use planning variables, the National Land Planning and Utilization Act and other laws. The results of analysis presented as an implication a close relationship between the excessive regulation of land use, an absence of physical changes to de facto houses, housing prices, and aged population ratio and the occurrence of vacant houses.

As for research from the physical and environmental perspectives, in the study by Mallach (2006), environmental defects such as small areas for use and outdated infrastructures, too, were causes of the occurrence of vacant houses in addition to the fact that the physical aging and structural risks of houses impeded the use of the houses so that the owners stopped managing the houses and neglected them as a result. Lee’s study (2020) analyzed the major influencing factors of the occurrence of vacancy among detached houses, with the old downtown area in Incheon-gwangyeoksi as the target area. The influencing factors of the occurrence of vacant houses were the sites’ scales, shapes, and contact with adjoining roads on the level of houses and the slopes and designation as maintenance areas on the neighborhood level, respectively. The ratio of solitary aged households influenced the occurrence of vacant houses on the regional level, thus demonstrating that the residents’ socioeconomic vulnerability acted as a cause of the occurrence of vacant houses. In conclusion, the implication was that, under a condition where the housing demand did not increase, the supply of new housing could act as a triggering factor for the occurrence of vacant houses.

Also reviewed were studies examining the occurrence of vacant houses from the spatio-structural and geographical perspectives. Kim et al. (2020) analyzed the influence of regional characteristics on the occurrence of vacant houses. According to the results of the study, vacant houses tended to occur with an increase in distances to neighborhood living facilities such as primary schools and amenities. Lee and Kim (2021) elucidated site characteristics according to the characteristics of the spatial distribution of vacant houses and accessibility to major life social overhead capital (SOC) facilities in small provincial cities. The results of analysis yielded the fact that: the greater accessibility to medical, welfare, and cultural life SOC facilities was, the lower was the distribution of vacant houses; and, on the contrary, accessibility to administrative and educational life SOC facilities did not much influence the distribution of vacant houses. The study by Wilson et al. (1994) on Cleveland analyzed patterns in spatial changes to the ratio of neglected houses over ten years, positivistically analyzing that the phenomenon of the neglect of houses spread outside the central area. As for similar results, Morckel’s study (2013), which analyzed the relationship between the causes of the occurrence of vacant houses and gentrification in Columbus and Youngstown, likewise confirmed that geographical characteristics and gentrification characteristics influenced the neglect of houses.

According to the results of such reviews of earlier studies, it is apparent that vacant houses occur not from a single cause but from complex causes and through diverse channels in multifaceted ways.

Studies on the external effects of the occurrence of vacant houses have mainly analyzed vacant houses’ relationships with social problems such as crimes and housing prices.

First, a representative accomplishment in the study of the relationship between vacant houses and criminal and socially deviant acts is the broken windows theory announced in 1982 by criminologists James Q. Wilson and George L. Kelling. According to this theory, when broken windows are left alone, crime begins to spread, with a focus on places where broken windows are neglected.

As for related studies, Immergluck (2016) confirmed a positive relationship between seized vacant houses and the crime rate in the area, with Chicago as the target area. As for similar research conducted in South Korea, Yeom (2019) positivistically demonstrated the relationship between vacant houses and theft/violent crimes. In the results of analysis, it was estimated that the crime of theft per 1,000 people increased by 0.128 case when the degree of the concentration of vacant houses increased by 1%.

Next, Seo and Lim (2022) conducted a study estimating the value decline rates of vacant houses in Gunsan-si (Gunsan City) in Jeollabuk-do (North Jeolla Province) through expert investigations. The results of estimations of value decline rates due to internal and external depreciation positivistically demonstrated that the more vacant houses’ grades rose or the poorer were the states of vacant houses, the greater were gaps in value decline rates, and the greater the degree of the concentration of vacant houses was, the more the value of vacant houses dropped. From this, it was apparent that, in terms of external effects of the occurrence of vacant houses, emphasized were connections according to houses’ physical characteristics, regional characteristics, and owners’ characteristics. Likewise, the study by Cho et al. (2020) confirmed that the owners’ actions could influence vacant houses such as cases in urban areas where the owners purchased houses for investment purposes and left them vacant even when rental demands existed. In addition, when vacant houses were neglected, surrounding houses could turn into vacant houses and the entire area could turn into a slum in the end, thus raising the need for active measures to mitigate vacant houses that had already occurred.

According to the results of reviews of earlier studies, it was important to understand the causes of the occurrence of vacant houses and spatial characteristics on the regional level. However, it was confirmed that existing studies mostly analyzed vacant houses from a macroscopic perspective and that studies analyzing the causes of the occurrence of vacant houses in relation to spatial characteristics were insufficient. Consequently, this study is differentiated in that: first, it added environmental characteristic variables in the areas in question, which were not reflected in earlier research; and, second, it elucidated the causes of the occurrence of vacant houses on the basis of field surveys of individual vacant houses and presented measures for using vacant houses. In relation to special-purpose areas, the study by Choi et al. (2013) used the areas of special-purpose areas as independent variables, and the study by Cho et al. (2022) grasped the floating population change ratio per special-purpose area. The study by Jang and Kwon (2021) used special-purpose areas as regional environmental variables influencing the occurrence of vacant houses. Most studies included special-purpose areas among variables for analysis. Consequently, this study is differentiated in analyzing vacant house concentration factors per special-purpose area. Related earlier studies described above implied differences per special-purpose area, and this study, likewise assuming differences in special-purpose areas would influence the occurrence of vacant houses, conducted research after distinguishing between residential and commercial areas. Analyzing the characteristics of vacant houses on the basis of distinction between residential and commercial areas from such a perspective, this study will be able to contribute to the construction of a vacant house management system per special-purpose area that takes into consideration the characteristics of the lots.

<Table 2> shows the basic statistics of variables used to derive factors behind the concentration of vacant houses in the old downtown area in Jinju-si, which consist of the average, standard variation, minimal value, and maximal value of or for each variable. As for whether or not a vacant house was concentrated, a dependent variable of this study, the figure was 24.8% when the vacant house was one in an area concentrated with vacant houses and 75.2% when the vacant house was one outside an area concentrated with vacant houses, respectively. Because vacant houses located in dispersion instead of being concentrated were far more numerous, it will be possible to find the causes of the concentration of vacant houses.

When the basic statistics of the independent variables were examined, the average of individual official land prices amounted to 12.9 won/m², thus being higher than 10.8 won/m², the average official land price fluctuation rate. Cases of parcels in the old downtown area of Jinju-si with poor contact with adjoining roads or small scales were fewer than parcels that were otherwise, in a ratio of approximately 4:6. However, irregularly shaped parcels were distributed more than were regularly shaped parcels, in a ratio of approximately 7:3. The average economically active population ratio was 11.1%, smaller than the average aged population ratio of 19.7%. This showed that the aged population in the old downtown area of Jinju-si was relatively larger than the economically active population. The average slope of parcels in the old downtown area of Jinju-si where vacant houses were located was approximately 10˚, and, as for individual parcels, there were cases of vacant houses located on parcels with gentle slopes measuring approximately 5˚ at a minimum and those of vacant houses located on parcels with steep slopes measuring approximately 42˚ at a maximum, thus confirming deviation among vacant houses per parcel. In the case of the structures, wooden and brick/concrete structures amounted to a ratio of approximately 2:8, thus confirming that vacant houses in the old downtown area of Jinju-si consisted mainly of brick/concrete structures. The average aged house ratio was 13.7%, and buildings constructed before and after 1970 amounted to a ratio of approximately 6:4, thus confirming that buildings constructed before 1970 were more numerous. In the case of slate roofs, they and cases of non-slate roofs amounted to a ratio of approximately 3:7, thus being smaller in number than the latter. The average fluctuation rate of the number of businesses decreased by –0.4%, and, in the case of the time of the occurrence of vacant houses, vacant houses occurring before 2010 were more numerous than those occurring after 2010, in a ratio of approximately 6:4. In the cases of vacant houses within 400 m from administrative district boundaries and river boundaries and vacant houses within 4,000 m from environmental pollutant emission sites, they were derived to be smaller in number than those not thus located, in a ratio of approximately 4:6.

Next, after distinguishing among the characteristics through a process of exploratory factor analysis (EFA), the reliability of each variable was verified. In order to measure the appropriateness of the selected variables, Kaiser-Meyer-Olkin (KMO) normed fit and the Bartlett value were used. When the results of EFA in <Table 3> are examined, the KMO value, which indicates the degree to which correlation among variables is explained by (an)other variable( s), amounted to 0.812, thus showing that the selection of vacant house occurrence factor variables was appropriate. The χ² value, which indicates the appropriateness of the model, was 2089.637, and the significance probability value of Bartlett’s rectangularity test was 0.000 (P<0.001), thus showing the existence of a common factor. The Eigen value, which signifies the degree of variance that can be explained by a factor, amounted to 1 or above for all factors, thus showing that a factor could explain the variance of at least one variable.

In addition, the cumulative variance explanatory power, which examined how valid it was to classify the 17 indices selected in this study into five characteristics, amounted to 77.082%. While factor loading for the observed variables per index mostly amounted to 0.4 or above, the factor loading for the presence or absence of slate roofs was yielded to be less than 0.4 and therefore excluded from the independent variables. According to the results of reliability analysis of the five factors derived, the Cronbach’s were yielded to be 0.858, 0.771, 0.826, 0,819, and 0.843, respectively. Consequently, with them exceeding the general baseline of 0.6, internal consistency was judged to exist.

While the dependent variables of this research model were discrete variables divided according to whether or not a vacant house was in an area concentrated with vacant houses in the special-purpose area in question, they constituted cases where the probability of the occurrence of events was extremely low. Because linear models could not be used for such a model, a rare event logistic regression model based on the random utility theory was used to make estimations. The results of the estimation of intercepts and regression coefficients of the rare event logistic model are interpreted by recalculating log odds values with exponential functions. In other words, in accordance with the characteristics of the occurrence of vacant houses reviewed in earlier research, an odds ratio of the occurrence of a vacant house in a space not concentrated with vacant houses against the possibility of the occurrence of a vacant house in a space concentrated with vacant houses in the special-purpose area in question is obtained and interpreted. The odds ratio is obtained by taking the reciprocal of the logarithmic function for each coefficient value. When that value amounts to 1 or above, then, with other conditions being equal, this can be interpreted as: by how many times the influence of a vacant house in an area concentrated with vacant houses will increase to cause the concentration of vacant houses in an area not concentrated with vacant houses because of a change to a single factor.

According to the results of model estimation in <Table 4>, the aged housing ratio, economically active population ratio, and aged population ratio out of demographic industrial factors yielded significant results in terms of the concentration of vacant houses in residential and commercial areas alike. In the case of the fluctuation rate of the number of businesses, it yielded significant results only in commercial areas and did not do so in residential areas. It was yielded that the probability of the concentration of vacant houses increased by 1.21 times when the aged house ratio in residential areas increased by 1%, decreased by 1.92 times when the economically active population increased by 1%, and increased by 1.27 times when the aged population ratio increased by 1%, respectively. In the case of commercial areas, the probability of the concentration of vacant houses decreased by 2.98 when the aged house ratio increased by 1%, increased by 1.32 times when the economically active population ratio increased by 1%, and decreased by 1.08 times when the aged population ratio increased by 1%, respectively. As for the fluctuation rate of the number of businesses, it was derived to be a significant variable only in commercial areas. When the fluctuation rate of the number of businesses increased by 1%, the probability of the concentration of vacant houses decreased by 1.2 times.

In the case of official land prices out of socioeconomic factors, it was a variable yielding significant results in terms of concentration after the occurrence of vacant houses in residential and commercial areas alike, and the land price fluctuation rate yielded significant results only in commercial areas. It was derived that the probability of the concentration of vacant houses increased by 3.37 times when official land prices increased by 1 in residential areas and decreased by 2.21 times when official land prices increased by 1 in commercial areas, respectively. In addition, in the case of the land price fluctuation rate, when it increased by 1%, the probability of the concentration of vacant houses in commercial areas increased by 1.12 times.

Out of lots and physical factors, undersized parcels and slopes were derived to be variables having influence only on residential areas; and, as for the case of poor contact with adjoining roads, it yielded significant results in terms of the concentration of vacant houses in residential and commercial areas alike. In residential areas, the probability of the concentration of vacant houses increased by 2.20 times on when parcels were small rather than otherwise, increased by 1.12 times when contact with adjoining roads was poor rather than otherwise, and increased by 1.04 times when the slope increased by 1˚, respectively. Likewise, in commercial areas, the probability of the concentration of vacant houses increased by 2.92 times when contact with adjoining roads was poor rather than otherwise.

Out of individual housing factors, the structures of buildings and the time of the occurrence of vacant houses had no significant influence on concentration after the occurrence of vacant houses in residential and commercial areas alike, and the years of construction had significant influence on the concentration of vacant houses only in residential areas. In residential areas, the probability of the concentration of vacant houses increased by 1.07 times for detached houses built before 1970 rather than those built after the year.

In the case of the regional environmental factor, in residential areas, the presence or absence of vacant houses near environmental pollutant emission sites alone yielded significant results in terms of concentration after the occurrence of vacant houses, and the probability of the concentration of vacant houses increase by 2.88 times when there were vacant houses within 400 m from environmental pollutant emission sites in residential areas. In commercial areas, the presence or absence of vacant houses on the boundaries of administrative districts alone yielded significant results in terms of the concentration of vacant houses, and it could be confirmed that the probability of the concentration of vacant houses increased by 3.04 times when there were vacant houses within 400 m from administrative districts. The presence or absence of vacant houses near river boundaries yielded significant results in terms of concentration after the occurrence of vacant houses in residential and commercial areas alike. When there were vacant houses within 400 m from river boundaries, the probability of the concentration of vacant houses decreased by 3.76 times in residential areas but increased by 3.50 times in commercial areas.