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Abstract 6

I. 서론 18

1. 연구 배경 및 목적 18

1.1. 연구의 배경 18

1.2. 연구의 목적 19

2. 연구의 범위 및 방법 21

3. 연구의 구성 26

II. 이론적 고찰 28

1. 상업공간에 관한 이론적 고찰 28

1.1. 상권의 개념과 유형 28

1.2. 도시 상업 활동과 공간구조 31

1.3. 서비스 업태와 상점(점포)의 종류 35

1.4. 서비스업의 입지이론 38

1.5. 선행연구의 검토 41

III. 연구지역의 상점 현황조사 및 데이터베이스 구축 49

1. 연구지역의 고찰 49

2. 조사의 개요와 연구지역 업체의 일반현황 53

2.1. 업체의 조사 53

2.2. 분석 대상 업종의 분류 54

3. 상업공간 데이터베이스 구축 59

3.1. 상점의 공간자료 및 공간분석자료 59

3.2. 연구지역의 업종별 현황 63

IV. 근린생활권의 상업공간 특성분석 66

1. 상업공간 지역특성분석 66

1.1. 중심권역 및 중심지분석 66

1.2. 중심권역별 상권분석 및 상권지도작성 76

2. 근린생활권의 상업공간 업종특성분석 83

2.1. 업종간 상관분석 83

2.2. 업종별 공간자기상관분석 89

2.3. 업종의 인구동태적 공간입지분석 96

2.4. 업종의 사회생태적 공간입지분석 122

V. 상업입지선정을 위한 모형 139

1. 입지선정을 위한 상업입지확률모형 구축 139

1.1. 변수의 구성 140

1.2. 식료품관련소매업의 입지확률모형 구축 142

1.3. 교육관련서비스업의 입지확률모형 구축 146

1.4. 가정용품관련소매업의 입지확률모형 구축 150

1.5. 음식관련업의 입지확률모형 구축 154

2. 상업입지확률모형 결과 요약 158

VI. 결론 160

1. 연구의 요약 160

2. 향후 과제 162

참고문헌 164

감사의 글 174

List of Tables

Table 1. Spatial base database used to analysis of the study 25

Table 2. Main characteristics of urban commercial districts 32

Table 3. Location type stores by principle of equality 37

Table 4. Analysis of consideration of the pre-study on the commercial space 48

Table 5. Land use in the subject area 51

Table 6. Residential status of subject area 52

Table 7. Current status by the business types according to the Korean standard industrial classification 53

Table 8. Comparison between Korea standard industrial classification and commercial space analysis business types classification 55

Table 9. Commercial space analysis business types classification table 57

Table 10. Spacial database list for building commercial space characteristics analysis and commercial location model 61

Table 11. Result of status analysis per business types within the subject area 63

Table 12. Results of analysis on average distance and expected adjacent distance between the stores by the business type 68

Table 13. Results of analysis on NNI by the commercial district density grade and the status of the commercial district 72

Table 14. Comparison between the trade area analysis methods 79

Table 15. Results of correlation analysis between the business types 86

Table 16. Types of spatial correlations according to significant level of LISA 92

Table 17. Results of analysis of Moran's I coefficient and Getis-Ord General G indicator 94

Table 18. Results from the analysis of the average population density by business types in subject area 97

Table 19. Results from the analysis of the average size of the adjacent roads by business types in subject area 100

Table 20. Results from the analysis of the function of adjacent roads by business types in subject area 103

Table 21. Results from the analysis of the distance from the crossroads by business types in subject area 106

Table 22. Results from the analysis of the distance from the crosswalks by business types in subject area 109

Table 23. Results from the analysis of the distance from the public organizations by business types in subject area 112

Table 24. Results from the analysis of the location floors by business types in subject area 115

Table 25. Results from the analysis of the business types by location floors in subject area 118

Table 26. Results from the analysis of the distance from the central place by business types in subject area 120

Table 27. Results from the analysis of the store size in the malls by business types in subject area 124

Table 28. Results from the analysis of the size of business land by business types In subject area 127

Table 29. Results from the analysis of the business types depended on land usage plans in subject area 130

Table 30. Results from the analysis of the business types depended on the building-to-land ratio in subject area 133

Table 31. Results from the analysis of the price of the business land by the business types in subject area 136

Table 32. Variables of Logistic regression analysis 141

Table 33. Spatial distribution status of foodstuff related service business 143

Table 34. Commercial location probability model per phase -2LL value of foodstuff related retail business and Hosmer - Lemeshow verification statistical quantity result 144

Table 35. Logistic regression model of foodstuff related retail business 144

Table 36. Spatial distribution status of education related service business 146

Table 37. Commercial location probability model per phases -2LL value of education related service business and Hosmer - Lemeshow verification statistical quantity result 147

Table 38. Logistic regression model of education related service business 148

Table 39. Spatial distribution status of home appliance related retail business 150

Table 40. Commercial location probability model -2LL value of home appliance related retail business and Hosmer - Lemeshow verification statistical quantity result 151

Table 41. Logistic regression model of home appliance related retail business 152

Table 42. Spatial distribution status of food related business 154

Table 43. Commercial location probability model per phases -2LL value of food related business and Hosmer - Lemeshow verification statistical quantity result 155

Table 44. Logistic regression model of food related business 156

Table 45. Result summary of Commercial location probability model per business types 158

Table 46. Selection independent variable of Logistic regression analysis per business types 159

List of Figures

Fig. 1. Flow chart of the study 24

Fig. 2. Framework of study 27

Fig. 3. Berry's model for classifying commercial districts 33

Fig. 4. Location per business types by the price product in classifying the retail 35

Fig. 5. Relation between minimum requirements, maximum reaching range and backyard area in the central place 40

Fig. 6. Subject area of this study 49

Fig. 7. Changing trends of population in Bokdae-Dong area 50

Fig. 8. Scatter plot chart showing land use status of the subject area 51

fig. 9. Scatter plot chart showing residential status of the subject area 52

Fig. 10. Industry status based on the Korean standard industrial classification 54

Fig. 11. Spatial database for commercial space characteristics analysis and commercial location model 59

Fig. 12. Flow chart showing the setup of stores distribution map 60

Fig. 13. Thematic map used for geographical space patterns 62

Fig. 14. Results on analysis of the distribution status by business types in subject area 64

Fig. 15. Store distribution map of the large scale classification of business types in subject Area 65

Fig. 16. Flow chart of study showing how to set central area and central place 67

Fig. 17. Result of store density analysis 70

Fig. 18. Result of NNI analysis per the commercial district density grade 72

Fig. 19. The number of the commercial district and the store distribution ratio per the density grad 73

fig. 20. The number of the store compared to the number of the commercial district per the density grade 73

Fig. 21. Result of setting up the central area analysis 74

Fig. 22. Process of analysis on the central spot 75

Fig. 23. Outcomes of setting up the central places by the central areas 76

Fig. 24. Flow chart using Huff's probability model 77

Fig. 25. Isoprobability contour map using Huff's model 81

Fig. 26. Isoprobability contour map by the central places 82

Fig. 27. Flow chart of correlated analysis among business types 84

Fig. 28. Scatter plot chart showing density scatter among commercial business types 85

Fig. 29. Outcomes of hot spot of Getis-Ord Gi* Indicator 95

Fig. 30. Results from the analysis of the average population density by business types in subject area 98

Fig. 31. The average population density distribution map by large scale classification of the types of business in subject area 99

Fig. 32. Results from the analysis of the average size of adjacent roads by business types in subject area 101

Fig. 33. The distribution map of the size of adjacent roads by large scale classification of the types of business in subject area 102

Fig. 34. Results from the analysis of the function of adjacent roads by business types in subject area 104

Fig. 35. The functional distribution map of the adjacent roads by large scale classification of the types of business in subject area 105

fig. 36. Results from the analysis of the distance from the crossroads by business types in subject area 107

Fig. 37. The distance distribution map between crossroads by business types in subject area 108

Fig. 38. Results from the analysis of the distance from the crosswalks by business types in subject area 110

Fig. 39. The distance distribution map of the crosswalks by large scale classification of the business types in subject area 111

Fig. 40. Results from the analysis of the distance from the public organizations by business types in subject area 113

Fig. 41. The distance distribution map from the public organizations by business types in subject area 114

Fig. 42. Results from the analysis of the location floors by business types in subject area 116

Fig. 43. The distribution map of the location grades of the stores by large scale classification of the business types in subject area 117

Fig. 44. Results from the analysis of the business types by location floors in subject area 119

Fig. 45. Results from the analysis of the distance from the central place by business types in subject area 121

Fig. 46. The distribution map of the distance from the central place by large scale classification of the business types in subject area 122

Fig. 47. Results from the analysis of the store size in the malls by business types in subject area 125

Fig. 48. The distribution map of the total size of the stores in the mall by large scale classification of the business types 126

Fig. 49. Results from the analysis of the size of business land by business types in subject area 128

Fig. 50. The distribution map of the business land size by large scale classification of the business types in subject area 129

Fig. 51. Results from the analysis of the business types depended on land usage plan in subject area 131

Fig. 52. The distribution map of the land usage plan by large scale classification of the business types 132

Fig. 53. Results from the analysis of the business types depended on the building-to-land ratio in subject area 134

Fig. 54. The distribution map of the large scale classification of business types depended on the building-to-land ratio in subject area 135

Fig. 55. Results from the analysis of the price of the business land by the business types in subject area 137

Fig. 56. The distribution map of the business land price by large scale classification of the business types in subject area 138

Fig. 57. ROC graph verification result of foodstuff related retail business 145

Fig. 58. ROC graph verification result of education related service business 149

Fig. 59. ROC graph verification result of home appliance related retail business 153

Fig. 60. ROC graph verification result of food related business 157

초록보기

In this study, characteristics of commercial space of neighborhood unit was analyzed utilizing spatial data and GIS analysis tools and it was intent to provide help in decision-making for accurate and efficient location selection using commercial location model. For this end, characteristics of commercial space was analyzed by conducting analysis of regional characteristics and analysis of characteristics of business types and commercial location probability model, which is a commercial location model, was built by carrying out Logistic regression analysis and the result was summarized.

Summarizing the study, first, for analysis of regional characteristics of commercial space, central area and central place was analyzed using density overlapping analysis, that methods of GIS's spatial pattern analysis, nearest nearby index (NNI), commercial quarters concentration index, and Mean Center method and as the result, subject area was analyzed in four central areas and central places. Based on central places of four central areas established using Huff's probability model, analysis of trade area was carried out and it was prepared in isoprobability contour.

Second, for characteristics analysis of commercial space business types, correlation analysis between business types, spatial autocorrelation analysis of business types, demographic dynamics spatial location analysis of business types, and social ecological spatial location analysis of business types were conducted. Correlation between business types was analyzed using GRID model Sample function and statistical correlation analysis.

Moran's I coefficient per business types and Getis-Ord General G Index, which is local indicators of spatial association (LISA), were calculated and they were expressed using Getis-Ord Gi* Index. Through this, spatial autocorrelation analysis was carried out for finding out dependency of space, autocorrelation, and heterogeneity on space.

Spatial operate was implemented using GIS analysis tools and location characteristics per business types were analyzed by conducting demographic dynamics spatial location analysis using dispersion analysis and social ecological spatial location analysis.

Third, probability values of stores at many locations were calculated through Logistic regression analysis and model research for decision-making of commercial locations, commercial location probability model for selecting final location of stores was built and its result was summarized.

Accomplishments are as the follows. First, store the first thing to consider is selection of locations when starting a new store. Selection of location became possible by finding out central place and trade area formation by conducting analysis of regions. Second, store or business type could be selected by finding out location characteristics per business types. Third, final location of store could be selected by comparing many locations of stores one wants to be located in probability values by building location probability model per business types.

By making decision-making of location selection possible systematically when starting a new store through this study, it is judged that this can provide and become a guideline to founders of new business for selecting location of stores as well as business types when starting new stores. It is believed that this will become helpful for researchers studying commercial space structures and for finding out characteristics of commercial space in neighborhood unit.

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