Abstract
JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 2019, VOL. 18, NO. 5, 404–420 https://doi.org/10.1080/13467581.2019.1666012 CONSTRUCTION MANAGEMENT Cost effectiveness analysis of the governmental financial support program for traditional market remodeling project a b Chul Jong Yoo and Yea Sang Kim a b Haemilcm Corporation, Gyeonggi-do, Korea; College of Engineering School of Civil, Architectural Engineering & Landscape Architecture, Sungkyunkwan University, Suwon City, Korea ABSTRACT ARTICLE HISTORY Received 11 January 2019 The sales of the traditional markets have declined sharply since the 2000s. Therefore, the Accepted 5 September 2019 government has employed various measures including diverse policy and economic support programs. However, despite the continuing financial support for modernizing the facilities of KEYWORDS the traditional markets, the effectiveness of each support has not been tested. Therefore, it is Traditional market; Facility urgent to establish a clear direction for the support programs. This study analyzed the Modernization Financial effectiveness (i.e., increase in sales) of the support for diverse market types in order to run Support program; market the Traditional Market Financial Support Program efficiently. In order to achieve the study characteristics objective, this study collected annual sales data from 66 markets and statistically analyzed the data by market types and facility support type. The results of this study showed that the support increased the sales of markets and the increase in sales was different between support facility types and market characteristics. The results empirically proved the Traditional Market Facility Modernization Program increased the sales of traditional markets. The results of this study will be useful to manage the Traditional Market Facility Modernization Program efficiently. 1. Introduction it is different from hypermarkets, discount department stores, and large supermarkets with modern faculties. In South Korea, a traditional market is a place where As the national income increases and urbanization tourists can enjoy history, culture, and tourist attrac- accelerates, the traditional markets are losing competi- tions of the area in addition to the exchange of goods tiveness against the modern markets. The sales of and services. It is designated by a mayor, a municipal Korean traditional markets declined steadily from 32.7 governor, or a mayor of the province to develop or trillion KRW in 2005 to 19.9 trillion KRW in 2013 promote it. The traditional market has been considered (Figure 1). Although it slightly increased to 21.8 trillion as a place of representing the life of the ordinary KRW in 2016, the increase was marginal. Therefore, the people as well as trading goods. The people working government operates a financial program to moder- in the traditional market are small business owners and nize the facilities of the traditional markets by investing CONTACT Yea Sang Kim yeakim@skku.edu College of Engineering School of Civil, Architectural Engineering & Landscape Architecture, Sungkyunkwan University, Seobu-Ro Jangan-Gu, Suwon City, Gyeonggi-do, Korea © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the Architectural Institute of Japan, Architectural Institute of Korea and Architectural Society of China. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 405 Figure 1. Total sales amount in traditional markets (Exchange rate: USD 1 = KRW 1,050). Small Enterprise and Market Service (2010, 2014, 2015, 2016). Figure 2. Total financial support amount for remodeling the traditional market (Exchange rate: USD 1 = KRW 1,050). Small Enterprise and Market Service (2010, 2014, 2015, 2016). in public resources. The government hopes that the little effects on actual market promotion although program will enhance the competitiveness of the mar- merchants and customers were highly satisfied with kets and promote the self-sufficiency of them, which it. Song (2015) pointed out that the projects were are mainly run by small business owners. carried out uniformly without considering business The financial program refers to the financial sup- types despite various supports had been made to port of the government to improve user convenience, modernize the facilities. Lee (2016) argued that it revitalize the market, and promote mutual benefits by would be necessary to differentiate the support to modernizing inconvenient old facilities and expand- satisfy the unique needs of each traditional market ing convenience facilities. However, although approxi- instead of uniformed supports. He classified the tradi- mately 2.9 trillion KRW has been invested to the tional market into various types and emphasized the program from the central and local governments for needs for establishing and implementing support the past twelve years (2005–2016) (Figure 2), the sales policies meeting the needs of each market. However, of the traditional markets decreased by 33% during he failed to provide clear conclusions because it was the same period (Ministry of SMEs and Startups 2017). difficult to verify the effectiveness of each support Various studies have been conducted to under- item. Lee and Lee (2015) evaluated the satisfaction stand why the sales of the traditional markets did regarding the facility support. They argued that it not increase even though the huge financial resources would be necessary to support the facility constructed have been invested in the program. These studies according to the market characteristics, but it would have tried to identify the causal factors from the be required to confirm the support type for facility viewpoints of business administration, marketing, modernization and the effects of investment. Kim and and community development. For example, Lee, Chung (2013) examined the effects of facility moder- Kim, and Kim (2015) reported that the program had nization on market revitalization and used the 406 C. J. YOO AND Y. S. KIM Table 1. Previous studies on traditional markets. Author(s) Year Study Title Study Results Kim, Byung-Seon et al. 2006 The Indoor Environment Measurement Analysis of This study derived the indoor environmental Arcade-Type Markets in Korea measurement by design after identifying the design elements of Arcade-Type Markets among the physical improvements of traditional markets Jung, Woo-Gun 2011 A Study on Status of Facilities Modernization at This study analyzed the changes in business Traditional Markets performance according to the market revitalization support and suggested the needs of the actual data analysis. Seo, Jung-Suk 2012 Effects of Perceived Benefits and Costs of Traditional This study identified the opinions of merchants Market Aid on Relationship Quality and Support of regarding the support policies and provided Marketeer implications for the policy direction. Lee, Duk-Hoon and Lee, 2013 A Study on the Effect of Governments’traditional Retail This study conducted a survey on the merchants of four Young-Seok and Periodic Market Policies on Revitalization of major traditional markets and analyzed the factors Market affecting the revitalization by support policy. Park, Cheong-Ho 2013 An analyzing on the factors of affecting physical and This study conducted the service quality and Non-physical improvement strategies for the revitalization awareness survey for consumers and traditional markets merchants to provide implications through influence relationship analysis and interpretations. Park, Cheong-Ho and Koo 2014 An Analysis of the Influential Relationship between This study analyzed the effects of cultural promotion Ja-Hoon Cultural Promotion Activities and Social Capital in the activities sponsored by public supports in the Traditional Market: A Comparative View with Routine traditional markets on the social activities of Merchant Activities merchants and self-government activities. Song, Myeong-Gu 2015 A study on the characteristics by type of the facility This study analyzed the user satisfaction for shopping modernization project for the traditional market amenities, safety facilities, and facilities to promote activation commercial supremacy and support market specialized facilities in order to provide improvement points. Lee, Kyu-Hyun 2016 An empirical research on the improvement plan and This study typified the service quality attributes and problem of government-led traditional market estimated the visitor satisfaction through logit revitalization support programs regression analysis in order to identify the problems of support policies and derive improvement points. Kang, Gye-Soo 2016 A study on the improvement plan of supporting This study pointed out various problems associated with traditional market not determining investment priorities in advance. This study indicated the necessity of applying the benefit principle and establishing customized supporting structure for maintaining the facility modernization project. Lee, Sung-Kyun 2017 A Study on Traditional Market Decline and Revitalization This study analyzed the five successful traditional in Korea markets and the spatial characteristics and the actual use of the buildings of the declining traditional markets in order to provide a market revitalization plan. changes in the number of markets, the number of terms of the Traditional Market Facility Modernization shops, and the number of merchants as the indices Program and project management. of vitalization. He concluded that, although the facility The goals of this study were to derive the theore- modernization program affected the market revitaliza- tical concepts and problems about the concept, pro- tion positively, it was not effective enough compared cedure, and government policies of the traditional to the amount of investment. He also reported that it market facility modernization project financial support was impossible to accurately assess the market revi- program, to verify the effects of the program statisti- talization effects because he could not secure the cally, and to draw the plans to operate and manage sales data. the program efficiently. The detailed methods of each Numerous researchers have studied the same topic step are as follows. (Table 1). Most of them pointed out the problems of First, this study established the evaluation criteria supporting institutions that support indiscriminately and procedures of the facility modernization financing without conducting adequately assessment or testing program in South Korea, evaluated the financial sup- the effects of supports in advance. However, no stu- port cases, and classified the characteristics of the dies evaluated the actual changes in sales according market and the types of support facilities based on to the market characteristics and facility types. It is the findings. believed that the success of the program depends on Second, the study model was set up and hypoth- understanding how the program can be operated eses were developed. Afterward, the necessary data efficiently or identifying what kinds of supports are was collected to test the hypotheses statistically. The effective to increase the sales for each market. The target market was identified and the data of financial objective of this study was to discover the optimal support time, support amount, and changes in sales facility support plan by analyzing support methods, were collected. support size, facility construction types, market char- Third, the effects of financial supports were evalu- acteristics, and support effects (changes in sales) in ated using t-test, ANOVA, and multiple regression JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 407 Table 2. Evaluation item and score criteria for Facility Modernization Project. Management Classification Project Feasibility Project Possibility Activation Add ·Subtract points Total Scores 35 30 35 10 110 Main Contents · Is the project · Ratio of secured · Merchant education · Additional points: Award, feasibility tested in self- payment participation rate Excellence Traditional Market Certification, and advance expense · Card usage rate fire mutual benefit association subscription - Is the project plan is · Stakeholder · Onnuri gift certificate rate sound consent rate subscription rate · Deduction points: Failure to freeze rent, · How urgent is the · Secure · Merchant association improper business management, and non- project? construction membership compliance to audit items · Is the construction site? – yes or subscription rate Examination result non-compliance) cost appropriate? no) · Merchant fee · Is the maintenance · Possibility to payment rate plan sound? perform in the · Achievements of self- · Will the rent remain current year business the same after modernization construction? · Rate of marking the country of origin and price · Degree of maintaining the pathway of customers Ministry of SMEs and Startups Notice No. 2017–20. Summary of Traditional Markets and Shopping Districts Facility Modernization Operation Guideline Article 10–13. Ministry of SMEs and Startups (2018) Announcement of Traditional Markets and Shopping Districts Revitalization Support Project, pp16 ~ 20. reconstructed. shared use facility, electrical, gas and fire fighting analysis. Based on the analysis results, the study drew the plans to efficienate the business management of system, and CCTV. The merchant association of each the Facility Modernization Financial Support program. market decides the facility to be supported when it submits the application for support. An evaluation committee (composed of one member from Ministry 2. Introduction and problems of the of SMEs and Startups, one member from a local gov- traditional market facility modernization ernment, and two external committee members) project financial support program selects the market to be supported by the Facility Modernization Project considering the various items The financial support for the Traditional Market (Table 2). The committee visits the market in person Facility Modernization Program is provided up to and evaluates the actual condition. 8 billion KRW per market (up to 11 billion for the The application procedure of the traditional market market holding more than 700 stores) for each type is basically a bottom-up procedure. A market mer- of facility according to Special Act on the chant organization (e.g., merchant association) sub- Development of Traditional Markets (2017) and mits an application to a local government and an Shopping District. The support amount consists of evaluation committee (composed of the Ministry of national expense (60%), local government expense SMEs and Startups, a local government, and civilian (30%), and self-payment expense (10%). This program experts) decides the market to support at the final can support various facilities including arcade, custo- selection meeting. Afterward, Ministry of SMEs and mer service center, access road, customer facilities, Figure 3. Flowchart of financial support for the Facility Modernization Project. 408 C. J. YOO AND Y. S. KIM Startups submits the budget to the Ministry of Table 4. Classification of facility type. Facility type Contents Strategy and Finance to confirm the budget and exer- Convenience Customer service, restroom, tradition cise it next year (Figure 3). Although the deadline for experience center, culture center, heating application and selection date can vary, the Ministry and cooling facility, merchant training center, and merchant association office of SMEs and Startups always holds a briefing session Walkability Arcade, canopy work, passage pavement, floor to the merchant organizations every year. maintenance, stair construction, escalator In this process, it becomes hard to manage the construction, district management, and elevator construction outcome of financial support, which is a major Accessibility Parking lot construction, parking lot extension, problem. First, the merchant association decides parking lot maintenance, parking lot ramps construction, entrance, entrance rain cover, thetypeoffacilitymodernization construction by awning screen installation, and access road themselves and merchants prefer to conduct construction Visualization Electric sign, LED display, LED lighting expensive constructions. However, they do not construction, sign maintenance, guide signs, consider how this facility improvement affects the and symbolic sculpture Facility maintenance Remodeling (store walls, ceilings, interior, and increase in sales specifically in this decision- entrance), electrical wiring construction, gas making process. Secondly, it is necessary to eval- line maintenance work, broadcasting and uate whether the project is required at the current communication construction, fire prevention works, solar power construction, cooling condition of a facility, whether the project will be tower replacement, logistics and cold cost-effective, and whether the applied project will storage, and CCTV increase the sales of the market. However, these factors are not considered in the application pro- 3. Data acquisition and analysis methodology cess and the evaluation of the committee is also very subjective. Therefore, the effects of this finan- It will be necessary to compare the sales of the market cial support for modernizing the facilities have not received financial support and those of the market been tested through the post-evaluation process. not received financial support in order to identify if In order to maximize the effects of the Traditional the financial support used for modernizing the tradi- Market Facility Modernization Program’s financial sup- tional markets in South Korea led to sales growth. port, it is necessary to reflect the results of the finan- Moreover, it will be required to analyze the market cial support analysis in the policy establishment step characteristic, the support status by facility type, and and the facility evaluation step for selecting a facility the dynamics of sales. to support. Therefore, it is urgent to prioritize facility This study collected data from 66 markets. Fifty- types to support and establish a plan to efficienate two markets among them received in some form of financial support. government support and the other 14 markets did not receive government support. The overall status data could be collected through Statistics Korea (2016). The data related to support funds such as facility type, market characteristics, support timing, Table 3. Classification of market characteristics. and amount of investment were collected from the Classification of Market Characteristics Ministry of SMEs and Startups, Small Enterprise and Classification of Market Type Building type market Market Service, and local governments using the Multipurpose building type (commercial+ residential area) National Information Disclosure System. The sales Underground shopping complex type data (the past 11 years) of the supported and Classification of Market Size Large-sized market (More than 1,000 stores) unsupported markets were collected from each Medium-large-sized market (More than merchant association by visiting each association 500) Medium-sized market (More than 100 in person. stores) It is necessary to classify the targets of remodel- Small-sized market (Less than 100) Classification by the Size of National trading area ing projects and the purposes of the support fund a trading area Metropolitan trading area to know when the support fund was more effec- Local trading area tively used. Therefore, this study identified five Neighboring trading area Classification by Major Clothing goods and necessities categories of markets (i.e., market type, market Goods Agro-fishery products and food size, the size of a trading area, main handling products Restaurants and eateries items, and region) and classified each category Region classification Capital area – metropolitan area into detailed types (Table 3). The usage details of market) Capital area – small and medium city the support fund were analyzed in order to recog- market nize what kinds of facilities were remodeled using Local small and medium city market) the support fund and 38 items could be extracted Small Enterprise and Market Service (2014) Management situation investiga- tion of traditional markets and shopping districts. Summary of p.15 ~ 17. from the analysis. However, since it is hard to draw JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 409 Table 5. Cases of supporting facility remodeling. Year Classification 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Total M1 Facility types □ 2 Amount of Support 2,995,000 403,018 3,398,018 M2 Facility types □ 1 Amount of Support 912,390 912,390 M3 Facility types □ ○ 2 Amount of Support 229,464 490,000 719,464 M4 Facility types ○ △ 2 Amount of Support 349,980 1,286,6523 13,216,503 M5 Facility types △ ○ 3 Amount of Support 7,083,381 73,227 2,922,000 10,078,608 M6 Facility types 1 Amount of Support 155,650 155,650 M52 Facility types □ 3 Amount of Support 1,178,000 15,500 54,780 1,248,280 Total Facility types 4 7 9 1013 10 201922 21 18 153 (unit: case) 지원금액 5,412,464 8,407,700 25,085,565 17,979,081 12,707,133 8,821,642 12,233,209 10,031,195 13,753,941 18,769,354 9,188,357 142,389,641 Support amount (unit: 1,000KRW) *Symbols: ○:Convenience; □: Walkability; Δ: Accessibility; : Visualization; : Facility maintenance; Currency unit: KRW; and Exchange rate: 1 USD = 1,050 KRW 410 C. J. YOO AND Y. S. KIM Table 6. Testable hypotheses and statistical analyses used for each hypothesis. No. Hypothesis Statistical Analysis Method 1H1 : There is no difference in the rate of change in sales between the markets with facility support and those T-test without facility support. H1 : There is a difference in the rate of change in sales between the markets with facility support and those without facility support. 2H2 : In the case of the markets with facility support, there is no difference in the rate of change in sales between T-test the year immediately after receiving the support and the year without receiving the support. H2 : In the case of the markets with facility support, there is a difference in the rate of change in sales between the year immediately after receiving the support and the year without receiving the support. 3H3 : In the case of the markets with facility support, the total amount of support and the number of support Multiple Regression Analysis affect the rate of change in sales differently. H3 : In the case of the markets with facility support, the total amount of support and the number of support do not affect the rate of change in sales differently. 4H4 : The type of remodeled facility does not affect the rate of change in sales of the market. One-way ANOVA H4 : The type of remodeled facility affects the rate of change in sales of the market. Post-hoc analysis: Tukey HSD 5H5 : The characteristics of a market receiving the support do not affect the rate of change in sales of the market. One-way ANOVA H5 : The characteristics of a market receiving the support affect the rate of change in sales of the market. Post-hoc analysis: Tukey HSD 6H6 : There is no interaction effect between facility type and market characteristics on the rate of change in sales. Multivariate ANOVA H6 : There is an interaction effect between facility type and market characteristics on the rate of change in sales. Multiple Regression Analysis Two-way ANOVA Post-hoc analysis: Tukey HSD *H : Null Hypothesis, H : Alternative Hypothesis 0 A meaningful results by analyzing too many items, 4. Analysis results this study grouped them into five facility types (i.e., convenience, walkability, accessibility, visualization, Hypothesis 1: There will be a difference in the rate and facility maintenance) considering the charac- of change in sales between the markets with facility teristics of facilities (Table 4). The effectiveness support and those without facility support. analysis analyzed these five types. The obtained data is summarized as the facility This hypothesis intended to verify whether the support cases (Table 5) and 52 markets among 66 financial support program increased sales or not. This survey target markets were supported by this pro- study collected the annual sales data for the past gram. The data of these 52 markets included the eleven years for all 66 markets. Using the data, this type of facilities supported by this program and the study analyzed the rate of changes in the annual sale amount of support for the past 11 years (2005–2015). for three years for 153 support cases of 52 markets and The rates of changes in sales were estimated based on 14 markets without receiving supports using t-test. The the obtained data for further analysis. results of the analysis revealed that the rate of change Acost-effectiveness analysis was conducted on in sales of the supported markets and that of not the data by establishing various hypotheses (Table supported markets were significantly (p < 0.05) differ- 6) and diverse statistical analyses were used to test ent and H1 was accepted. Specifically, the rate of them. These analyses used received support (i.e., change in sales of not supported 14 markets decreased yes or no), the number of support, and the amount in all the years while that of supported 52 markets of support as independent variables. Dummy vari- increased in all the years. The results clearly indicated able analysis was used because each independent that the financial support for the facility remodeling variable had a different number of data when 153 had positive effects on the rate of change in sales. support facilities were classified by facility type and Particularly, the difference between the mean rate of market type. The rate of change in sales was used change in sales of the market with support and that of as a dependent variable because it was the factor the market without support was the largest (6.98%) at representing the management performance of the 1 year after support. The hypothesis and statistical market. method for this study are as stated in Table 7. Table 7. Descriptive statistics and the results of t-test on the rate of change in sales of markets with support and markets without support. Descriptive Statistic T-test (Equal Variance) Support Rate of Change Received Sample Standard Standard Degree of p-value Mean Standard Error of in Sales (Yes or No) Size Mean Deviation Error t Freedom (two-tail) Difference Difference One year after Yes 153 .0259 .0599 .0048 12.932 305 .000 .0698 .0054 support No 154 −.0439 .0298 .0024 Two years after Yes 153 .0115 .0509 .0041 10.087 305 .000 .0469 .0046 support No 154 −.0353 .0271 .0021 Three years after Yes 153 .0034 .0417 .0033 8.184 305 .000 .0321 .0039 support No 154 −.0287 .0252 .0020 JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 411 Table 8. Descriptive statistics and the results of t-test on the immediate effects of support on the rate of change in annual sales. Descriptive Statistic T-test (Equal Variance) Support Rate of Change Received Sample Standard Standard Degree of p-value Mean Standard Error of in Sales (Yes or No) Size Mean Deviation Error t Freedom (two-tail) Difference Difference One year after Yes 153 .0259 .0600 .0048 11.658 570 .000 .0533 .0045 support No 419 −.0274 .0434 .0021 Table 9. The effects of the total amount of support per Hypothesis 2: In the case of the markets with facility market and the total number of support per market on the support, there is a difference in the rate of change in sum of the rates of changes in sales. sales between the year immediately after receiving the Standardized support and the year without receiving the support. Unstandardized Regression Coefficients Coefficient) Standard It was confirmed from the hypothesis 1 that the Model B Error Beta t p-value support made a difference in the overall changes in Constant .024 .039 .605 .548 sales. However, the increase in sales can be a result of Total amount of .002 .001 .321 2.020 .049* support per selection criteria because one of the selection criteria market is the potential of the market. (Therefore, the increase Total number of .002 .013 .025 .160 .873 support per in sales of the supported market may be an obvious market result.) Therefore, the study compared the yearly rate Dependent variable: Sum of the rates of changes in sales. of change in sales of supported markets. Specifically, the study compared the rate of change The traditional market remodeling project may pro- in sales within a year after receiving a support with vide a different amount of fund per support and markets that of other years without receiving a support in the may receive support for a different number of times. same market. This test was conducted because the Therefore, this hypothesis is to evaluate the effects of increase in sales could be a result of better efforts of the total amount of support and the number of supports merchants instead of the financial support for on the rate of change in sales. A multiple regression remodeling. analysis was conducted with using the total amount of In the case of 52 supported markets, they support (x1) and the number of supports (x2) as inde- received 153 supports during the eleven years. The pendent variables and the sum of the rates of changes rates of annual change in sales immediately after in sales (y) as a dependent variable. The results of the receiving the support were compared with those of analysis showed that the total amount of support (x1) years without receiving the support using t-test. The significantly (p < 0.05) affected the dependent variable analysis results showed that they were significantly while the number of supports did not significantly (p < 0.05) different. In other words, H2 was (p ≥ 0.05) affect the dependent variable (Table 9). The accepted. The result indicated that the facility sup- results implied that, in Facility Modernization Project, port increased the sales regardless of market char- the amount of support was more important than the acteristics and basic conditions. In summary, the number of supports to increase the sales. sales increased by 2.59% on average one year after receiving a support and it decreased by Hypothesis 4: The type of remodeled facility affects 2.74% on average when no support was received the rate of change in sales of the market. (Table 8). The facility support for traditional markets can be cate- Hypothesis 3: In the case of the markets with facility gorized into five types (i.e., convenience walkability, support, the total amount of support and the num- accessibility, visualization, and facility maintenance) ber of support affect the rate of change in sales (Table 10). Therefore, the success of a financial support differently. program depends on how to prioritize the facility types to Table 10. Mean rate of change in sales by facility type. Facility Convenience Walkability Accessibility Visualization Maintenance Support Received Sample Sample Sample Sample Sample Rate of Change in Sales (Yes or No) Size Mean Size Mean Size Mean Size Mean Size Mean One year after support Yes 29 .0245 37 .0361 26 .0487 20 .0301 41 .0012 No 124 .0262 116 .0226 127 .0212 133 .0253 112 .0349 Two years after support Yes 29 .0032 37 .0096 26 .0116 20 .0054 41 .0221 No 124 .0135 116 .0122 127 .0115 133 .0125 112 .0077 Three years after Yes 29 .0065 37 −.0017 26 −.0008 20 .0024 41 .0090 support No 124 .0027 116 .0050 127 .0043 133 .0035 112 .0013 412 C. J. YOO AND Y. S. KIM Table 11. Difference in the rate of change in sales by facility type (ANOVA). Rate of Change in Sales Sum of Squares Degree of Freedom Mean Squares F p-value One year after support Treatment .043 4 .011 3.145 .016* Error .504 148 .003 Total .547 152 Two years after support Treatment .007 4 .002 .717 .582 Error .387 148 .003 Total .394 152 Three years after support Treatment .003 4 .001 .434 .784 Error .262 148 .002 Total .265 152 Hypothesis 5: The characteristics of a market receiv- be supported. This hypothesis aimed to test this aspect ing the support affect the rate of change in sales of and this study conducted one-way ANOVA to evaluate the market. the differences in the rates of changes in sales within three years from receiving a support. Another factor determining the success of The rates of changes in annual sales indicated a financial support program is to identify which mar- the sales increased the most immediately after ket should be supported in advance. Therefore, it is receiving a support and the increment decreased critical to understand the effects of the market char- with time. Moreover, it is noteworthy that the sup- port for accessibility and walkability facility types acteristics on the rate of change in sales. The market characteristics can be categorized into market type, changed the sales noticeably (Table 10). The results market size, the size of a trading area, main handling of the one-way ANOVA test indicated that the sup- port significantly (p <0.05) affected the rate of items, and region (Table 13). Each category has sev- eral sub-categories. To test this hypothesis, ANOVA change in sales only at one year after the support was conducted to test the effects of market character- (Table 11). Moreover, Tukey HSD post-hoc analysis was also conducted for evaluating which facility istics’ sub-categories on the rate of change in sales. The results of ANOVA indicated that the effects of type affected the rate of change in sales more market type, market size, the size of a trading area, (Table 12). The results of this analysis showed that the effect of accessibility was significantly (p < 0.05) main handling items, and region on the rate of larger than that of facility maintenance. The differ- change in sales were significantly different. Moreover, the mean rate of change in sales showed ence between the effects of the two variables was 4.75%. The results clearly indicated that support for that it increased the most in the first year after receiv- accessibility was more effective than that for facility ing a support and decreased afterward, which was a similar pattern with the facility type. At one year maintenance. Table 12. Tukey HSD post-hock analysis for evaluating the rate of change in sales by facility type. Dependent Variable 95% confidence interval Difference in Mean Standard Lower Upper Facility Type (I) Facility Type (J) (I-J) Error p-value Bound Limit Rate of Change in Sales Convenience Walkability −.0116 .0144 .928 −.0516 .0283 One Year After Accessibility −.0241 .0157 .542 −.0677 .0193 Support Visualization −.0056 .0169 .997 −.0524 .0412 Facility .0233 .0141 .471 −.0158 .0624 maintenance Walkability Convenience .0116 .0144 .928 −.0283 .0516 Accessibility −.0125 .0149 .918 −.0537 .0287 Visualization .0060 .0162 .996 −.0386 .0507 Facility .0349 .0132 .068 −.0015 .0715 Maintenance Accessibility Convenience .0241 .0157 .542 −.0193 .0677 Walkability .0125 .0149 .918 −.0287 .0537 Visualization .0185 .0173 .821 −.0293 .0665 Facility .0475* .0146 .012* .0070 .0879 maintenance Visualization Convenience .0056 .0169 .997 −.0412 .0524 Walkability −.0060 .0162 .996 −.0507 .0386 Accessibility −.0185 .0173 .821 −.0665 .0293 Facility .0289 .0159 .368 −.0150 .0728 maintenance Facility Convenience −.0233 .0141 .471 −.0624 .0158 maintenance Walkability −.0349 .0132 .068 −.0715 .0015 Accessibility −.0475* .0146 .012* −.0879 −.0070 Visualization −.02892 .0159 .368 −.0728 .0150 *All statistical significance was determined at p < 0.05. JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 413 Table 13. Mean rate of change in sales by market characteristics. Market Type Market Size Building Type Multipurpose building type Underground shopping complex Large-sized Medium-large-sized Medium-sized Small-sized Rate of Change in Sales Sample Size Mean Sample Size Mean Sample Size Mean Sample Size Mean Sample Size Mean Sample Size Mean Sample Size Mean One year after support 71 .0305 57 .0209 25 .0242 19 .0470 28 .0243 80 .0231 26 .0210 Two years after support 71 .0157 57 .0046 25 .0155 19 .0233 28 .0199 80 .0077 26 .0057 Three years after support 71 .0039 57 -.0045 25 .0200 19 .0089 28 .0105 80 .0019 26 -.0034 Size of a trading area Main Handling Items Region Agro-fishery pro- Capital Area – National Trading Metropolitan Neighboring ducts and food Clothing goods Restaurants and Capital Area – small and medium Local small and Area Trading Area Local Trading Area Trading Area products and necessities eateries metropolitan area cities medium cities Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Rate of Change in Sales Size Mean Size Mean Size Mean Size Mean Size Mean Size Mean Size Mean Size Mean Size Mean Size Mean One year after support 31 .0387 36 .0089 52 .0116 34 .0541 82 .0232 52 .0206 19 .0519 87 .0386 16 .0131 50 .0079 Two years after support 31 .0210 36 .0084 52 -.0011 34 .0258 82 .0088 52 .0087 19 .0313 87 .0180 16 .0089 50 .0011 Three years after 31 .0059 36 .0105 52 -.0015 34 .0012 82 -.0005 52 .0069 19 .0108 87 .0067 16 .0013 50 -.0016 support 414 C. J. YOO AND Y. S. KIM Table 14. Differences in the rate of change in sales by market characteristics (ANOVA). Market Type Market Size Rate of Change in Sales Sum of Squares Degree of Freedom Mean Squares F p-value Sum of Squares Degree of Freedom Mean Squares F p-value One year after support Treatment .003 2 .001 .411 .664 .010 3 .003 .906 .440 Error .544 150 .004 .537 149 .004 Total .547 152 .547 152 Two years after support Treatment .004 2 .002 .847 .431 .007 3 .002 .857 .465 Error .390 150 .003 .387 149 .003 Total .394 152 .394 152 Three years after support Treatment .011 2 .005 3.097 .048* .003 3 .001 .647 .586 Error .254 150 .002 .262 149 .002 Total .265 152 .265 152 Size of a trading area Main Handling Items Region Sum of Degree of Mean p- Sum of Degree of Mean p- Sum of Degree of Mean p- Rate of Change in Sales Squares Freedom Squares F value Squares Freedom Squares F value Squares Freedom Squares F value One year after support Treatment .053 3 .018 5.357 .002** .015 2 .007 2.097 .126 .033 2 .016 4.811 .009** Error .494 149 .003 .532 150 .004 .514 150 .003 Total .547 152 .547 152 .547 152 Two years after Treatment .019 3 .006 2.453 .066 .009 2 .004 1.656 .194 .009 2 .005 1.809 .167 support Error .376 149 .003 .386 150 .003 .385 150 .003 Total .394 152 .394 152 .394 152 Three years after Treatment .003 3 .001 .653 .583 .003 2 .001 .851 .429 .002 2 .001 .673 .512 support Error .262 149 .002 .262 150 .002 .263 150 .002 Total .265 152 .265 152 .265 152 JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 415 Table 15. Post-hoc analysis (Tukey HSD) of the sub-categories of market type. 95% confidence Dependent variable interval Difference in Standard Lower Upper Market Type (I) Market Type (J) Mean (I-J) Error p-value bound limit Rate of Change in Sales Three Years Building Type Multipurpose Building .0085 .0073 .478 −.0088 .0258 after a Support Underground −.0160 .0095 .218 −.0387 .0066 shopping complex Multipurpose Building Building Type −.0085 .0073 .478 −.0258 .0088 Underground −.0245* .0098 .037* −.0479 −.0011 shopping complex Underground Building Type .0160 .0095 .218 −.0066 .0387 shopping complex Multipurpose Building .0245* .0098 .037* .0011 .0479 *All statistical significance was determined at p < 0.05. Table 16. Post-hoc analysis (Tukey HSD) of the sub-categories of the size of a trading area. 95% confidence Dependent Variable interval Size of a Trading Area Size of a Trading Difference in Mean Standard Lower Upper (I) Area (J) (I-J) Error p-value bound limit Rate of Change in Sales One Year after National Metropolitan .0298 .0141 .153 −.0067 .0665 a Support Local .0271 .0130 .165 −.0068 .0610 Neighboring −.0153 .0142 .704 −.0525 .0217 Metropolitan National −.0298 .0141 .153 −.0665 .0067 Local −.0027 .0124 .996 −.0351 .0297 Neighboring −.0452* .0137 .007** −.0810 −.0094 Local National −.0271 .0130 .165 −.061079 .0068 Metropolitan .0027 .0124 .996 −.029713 .0351 Neighboring −.0425* .0126 .006** −.075525 −.0095 Neighboring National .0153 .0142 .704 −.021751 .0525 Metropolitan .0452* .0137 .007** .009479 .0810 Local .0425* .0126 .006** .009540 .0755 *All statistical significance was determined at p < 0.05. after receiving a support, building type (3.05%) in a 2.45% higher sales increase than the multipurpose building type. In the aspect of the trading area size, market size, large (4.70%) in market size, neighbor- hood commercial area (5.41%) in the size of a trading the neighboring trading area had a 4.52% higher area, restaurants and eateries (5.19%) in main hand- increase and a 4.25% higher sales increase than metro- politan and local trading areas, respectively. In terms of ling items, and metropolitan area (3.86%) in region was the major factors affecting the mean rate of region, capital area – metropolitan area market showed increase in sales (Table 13). a 3.07% higher sales increase than local small and med- ium cities market (Tables 15–17). When the sub-categories of the market type were compared, the rate of increase in sales was signifi- cantly different for the size of a trading area after Hypothesis 6: There is an interaction effect between facility type and market characteristics on the rate three years (p = 0.048) and the region after one year (p = 0.002). There was no difference among sub- of change in sales. categories of market size and major handling items (Table 14). Tukey HSD post-hoc analysis was con- 4.1. Interaction effect between facility type and ducted for market type, market size, and region, market characteristics (MANOVA) which showed a significant difference, in order to find out which sub-category affected the rate of Hypotheses 4 and 5 tested if the market type and change in sales more. market characteristics influenced the increase in The results showed that the underground shopping sales. However, it is possible that the effect of market complex type had a higher rate of change in sales at type on the increase in sales depends on the level of three years after receiving a support than multipurpose market characteristics. In other words, market type building type (p = 0.048). Moreover, the neighboring and market characteristics may interact. Since market trading area had a higher rate of change in sales at characteristic variables can regulate the effects of one year after receiving a support than metropolitan a facility support type on the change in sales, their (p = 0.007) and local (p = 0.006) trading areas. At interaction was tested using MANOVA. one year after receiving a support, capital area – metro- The results of the analysis showed that only the politan area showed a higher rate of increase in sales main handling items among market characteristics than local small and medium cities (p = 0.010). In sum- had a regulation effect on the changes in sales of mary, the underground shopping complex type had facility type. Particularly, facility type and main 416 C. J. YOO AND Y. S. KIM Table 17. Post-hoc analysis (Tukey HSD) of the sub-categories of region. 95% Confidence Dependent Variable Interval Difference in Standard Lower Upper Region (I) Region (J) Mean (I-J) Error p-value bound limit Rate of Change in Sales One Year Capital area – Capital area – small and .0255 .0159 .247 −.0121 .0632 after a Support metropolitan area medium cities Local small and medium .0307* .0103 .010* .0061 .0553 cities Capital area – small and Capital area – −.0255 .0159 .247 −.0632 .0121 medium cities metropolitan area Local small and medium .0052 .0168 .949 −.0346 .0450 cities Local small and medium Capital area – −.0307* .0103 .010* −.0553 −.0061 cities metropolitan area Capital area – small and −.0052 .0168 .949 −.0450 .0346 medium cities *All statistical significance was determined at p < 0.05. Table 18. Between-subjects effect test of support facility type and market characteristics (Multivariate ANOVA). Source Sum of Squares of Type III Degree of Mean Variable Rate of Change in Sales error Freedom Squares F p-value Facility type One year after receiving .017 4 .004 1.425 .229 a support Two years after receiving .009 4 .002 .847 .498 a support Three years after receiving .004 4 .001 .596 .666 a support Main handling items One year after receiving .022 2 .011 3.702 .027 a support Two years after receiving .011 2 .006 2.166 .119 a support Three years after receiving .003 2 .001 .748 .475 a support Facility type * Main handling One year after receiving .076 8 .010 3.133 .003** items a support Two years after receiving .011 8 .001 .535 .828 a support Three years after receiving .008 8 .001 .560 .809 a support handling item showed significant interaction on the coefficient (beta) was 0.240, 0.200, and 0.186 for rate of change in sales at one year after receiving walkability, accessibility, and visualization, respec- support (p = 0.003). It means that the item mainly tively, indicating the order of the magnitude of sold in the market can influence the effects of facility impact. The results clearly showed that the sup- type on the sales. Table 18 shows the interaction port to walkability, accessibility, and visualization terms between facility type and the entire market improved the sales, or management performance characteristics. (Table 19). 4.2. Multiple regression analysis of facility type Table 19. Multiple regression analysis of support facility type and the amount of support (Multiple Regression Analysis). Multiple regression analysis was carried out to find Standardized the variables significantly affecting the sales based Unstandardized Regression on theresults of MANOVA (4.6.1). Therateof Coefficients Coefficient change in sales was a dependent variable, and Standard Model B Error Beta t p-value investment (yes/no) and the amount of support Constant −.006 .009 −.633 .528 for each facility type were independent variables. Convenience .023 .014 .148 1.648 .102 The results of the analysis indicated that the Walkability .033 .013 .240 2.606 .010** Accessibility .032 .015 .200 2.115 .036* amount of support (p = 0.010), walkability Visualization .033 .015 .186 2.134 .034* (p = 0.010), accessibility (p = 0.036), and visualiza- Amount of 1.031E-08 .000 .266 3.207 .002** Support tion (p = 0.034) significantly affected the rate of (1,000 change in sales. Facility maintenance was excluded KRW) from the analysis due to multicollinearity issue. Dependent variable: Rate of change in sales one year after receiving a support The beta values of these significant variables *Exchange rate: 1,000 KRW = 1 USD. were allpositiveandthestandardizedregression JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 417 Table 20. Test of interaction terms. Interaction \Sum of Squares of Type III error Degree of Freedom Mean Squares F p-value Market Type * Walkability .020 2 .010 2.781 .065 Market Type * Accessibility .006 2 .003 .856 .427 Market Type * Visualization .009 2 .004 1.206 .302 Market Size * Walkability .004 3 .001 .346 .792 Market Size * Accessibility .004 3 .001 .399 .754 Market Size * Visualization .011 3 .004 .972 .408 Size of a trading area * Walkability .007 3 .002 .742 .528 Size of a trading area * Accessibility .001 3 .000 .129 .943 Size of a trading area * Visualization .011 3 .004 1.112 .346 Main Handling Items * Walkability .028 2 .014 4.108 .018** Main Handling Items * Accessibility .004 2 .002 .512 .601 Main Handling Items * Visualization .015 2 .008 2.150 .120 Region * Walkability .001 2 .000 .111 .895 Region * Accessibility .015 2 .007 2.255 .108 Region * Visualization .000 1 .000 .129 .720 Dependent variable: Rate of change in sales one year after receiving a support Table 21. Tukey HSD post-hoc analysis of main handling items. 95% confidence interval Main handling items (I) Main handling items (J) Mean Difference(I-J) Standard Error p-value Lower Bound Upper Bound Clothing goods and necessities Agro-fishery and food products −.0026 .0103 .963 −.0271 .0217 Restaurants and eateries −.0313 .0156 .114 −.0682 .0056 Agro-fishery and food products Clothing goods and necessities .0026 .0103 .963 −.0217 .0271 Restaurants and eateries −.0286 .0148 .133 −.0637 .0064 Restaurants and eateries Clothing goods and necessities .0313 .0156 .114 −.0056 .0682 Agro-fishery and food products .0286 .0148 .133 −.0064 .0637 Dependent variable: Rate of change in sales one year after receiving a support 4.3. Analyzing the regulation effects of facility It is possible to identify what kinds of item and walk- type (two-way ANOVA) ability have the largest interaction effect using Tukey HSD post-hoc analysis. However, the main handling The regulation effects of walkability, accessibility, items were not significantly (p < 0.05) different. and visualization, which were found significant in “Restaurant and eatery market” had 3.13 and 2.86% the previous multiple regression analysis, were ana- higher sales on average than “clothing goods and lyzed further for each market characteristic. Two- necessities” and “agro-fishery products and food pro- way ANOVA was performed and the results showed ducts”, respectively. The results of the analysis revealed that there was a significant interaction effect that the support to walkability at “restaurants and between the main handling item and walkability eateries market” had the largest effect (Table 21). (Table 20). Table 22. Summary of analysis results. Hypothesis Analysis Results Significant Results or Variable H1 Difference in sales between market with or without Markets with receiving supports had a higher sales increase than those without receiving a support receiving supports H2 Among markets with receiving supports, the difference The year receiving a support had a higher sales increase than the year without in sales between a year with a support and a year receiving a support without a support H3 Effects of support content on sales volume The amount of support affected the changes in sales H4 Change in sales by facility type Support to accessibility was more effective than that to facility maintenance H5 Change in sales by market characteristics Market Type Support to underground shopping complex type had a higher impact on sales than support to multipurpose building type Size of a Trading Area Support to neighboring trading area had a higher impact on sale than that to metropolitan and local trading areas Region Support to capital area-metropolitan area had a higher impact on sales than local small and medium cities H6 Interaction between facility type & market The facility type and main handling item have an interaction effect on the characteristics changes in sales Variables among facility types affecting sales Walkability Accessibility Visualization Regulation effect of facility type and market Walkability Support to restaurants and eateries had a higher characteristics impact on sales than that to agro-fishery products and food products 418 C. J. YOO AND Y. S. KIM the facility support had a higher impact on sales 5. Summary and conclusions increase than those without receiving the facility sup- This study evaluated the support cases of the Facility port. Moreover, when analyzing the markets receiving Modernization Project and analyzed the rates of the facility support, the year receiving the support change in sales depending on the support. This showed a higher increase in sales than the year with- study also analyzed the rates of change in sales by out receiving the support. The results are meaningful the amount of support and the number of support. because the effects of the support on sales were Moreover, the construction type of supported facility proven empirically. H3 intended to test which had was categorized into 5 facility types. Additionally, the a higher impact on sales between the amount of market characteristics were classified into market support and the number of support. The results of type, market size, the size of a trading area, main the analysis indicated that the amount of support handling item, and region. Lastly, it was statistically affected the sales more. Moreover, the results implied evaluated if the rate of change in sales varied by that a large amount of support was more effective facility type and market characteristics. than frequent support. Specifically, this study aimed to identify an efficient H4 analyzed the changes in sales in order to iden- management plan of the financial support program tify the support to which facility type had the highest by examining the effects of the program by facility effect on sales. The analysis confirmed that the sup- type and market characteristics. In terms of facility port for accessibility was more effective than the sup- type, the results showed that accessibility increased port for facility maintenance. sales significantly more than facility maintenance. In H5 analyzed the changes in sales in order to identify terms of market characteristics, the support increased the effects of market characteristics on them. The ana- the sales greatly in underground shopping complex lysis results indicated that the support for the under- type, neighboring trading area, and capital area – ground shopping complex has a higher impact on metropolitan area market. The results of this study sales than that to multipurpose building. Moreover, it also showed that enhanced walkability, accessibility, was found that, in terms of market type, the support to and visualization greatly increased sales. In terms of the neighboring trading area was more effective to the interaction between facility type and market char- increase sales than that to metropolitan and local trad- acteristics, the support to walkability among facility ing areas. In terms of region, the support to the capital types increased the sales in restaurants and eateries area-metropolitan area increased sales more effectively market. Based on the analysis results, proposed ways than that to local small and medium cities. to efficienate the project are summarized in Table 22. H6 intended to find out the interactions among The objective of this study was to propose a way to facility support, facility type, and facility characteristics efficienate the Facility Modernization Financial on the changes in sales in order to identify what kind Support for Traditional Market program by identifying of support to which facility type was the most effec- and analyzing the factors affecting the rate of change tive in which market characteristic. The analysis results in sales according to the facility type and market showed that walkability, accessibility, and visualiza- characteristics. Although the government has contin- tion had positive effects on sales. There was the lar- ued to support the Facility Modernization Financial gest interaction between the support to walkability Support for Traditional Market program, the effects and restaurants and eateries market. No other inter- of it on the sales increase have not been tested. action effect was observed. Moreover, merchant associations have applied for This study analyzed the effects of facility type and construction support for a facility requiring higher market characteristics on the relationship between cost without considering the effects of facility financial support and the changes in sales. This improvement. The applied projects have been evalu- study drew some meaningful analysis results. In ated by the evaluation committee and committee short, Facility Modernization Financial Support had members are required to examine the effectiveness positive effects on the management achievements of of the support objectively. However, the decisions and markets and the support had different effects on sales evaluations mostly rely on subjective criteria. In order depending on the facility type and market to set the clear direction of Facility Modernization characteristics. Financial Support program and maximize the effects The important practical implication of this study is of the support, this study analyzed the data of 66 that the sales of the market can be increased when markets, classified the facility construction type and market characteristics and facility types are consid- market characteristics, and analyzed the changes in ered in selecting markets to support, unlike the cur- sales to draw the following conclusions. rent selection criteria. Since the goal of the program is H1 and H2 tested whether the facility support is to maximize the performance through financial sup- effective in the sales increase. The results of analyses port, we believe that the results of this study have on empirical data showed that markets with receiving made a great contribution to identifying the direction. JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 419 We also believe that the presented analysis method types. In other words, we admit that there may be very will contribute to changing the concept of policy- complex interactions among the amount of govern- makers in establishing and operating similar policies ment support, the purpose of the support, and the and enhancing the effectiveness of policies in the sales trend, but only a few data analysis were possible future. due to limited data availability. We believe that future The followings are the suggestions to improve the studies will need to obtain more various datasets and efficiency of financial support based on the results of analyze them using more sophisticated techniques. this study. Data availability (1) The amount of financial support is a more important determinant of the effects of financial The datasets used and/or analysed during the current study are available in the article. support than the number of financial support. (2) When reviewing the financial support applica- tions, the accessibility type should be priori- Disclosure statement tized over the facility maintenance type. No potential conflict of interest was reported by the (3) It is recommended to support the underground authors. shopping complex type over the multipurpose building type in the aspect of market character- istics. Moreover, the neighboring trading area Funding should be prioritized over the metropolitan trad- No funding was received to conduct the research. ing area and the local trading area. Moreover, capital area-metropolitan area market should be supported first over local small and medium city Notes on contributors market. However, the local government must Chul Jong Yoo finished his Ph.D. at Sungkyunkwan decide which market to support according to University, and is the CEO of Haemil CM Corporation. He the management efficiency along with the pre- has extensive research and practical experience in super- servation and value of the market. vision and construction management. (4) When determining the facility type to be sup- Yea Sang Kim is a professor at the Department of ported without considering the market character- Architectural Engineering and Landscape Architecture, istics, the priority should be given in the order of Sungkyunkwan University, and teaching construction man- walkability, accessibility, and visualization. agement. He majored in architectural engineering and design for his undergraduate and MS and completed them (5) When determining the facility type to be sup- in Yonsei University, Korea. He also earned his MS and Ph.D. ported with considering the market characteris- at the University of Texas at Austin, the U.S.A. in construc- tics, the walkability facility of a restaurants and tion engineering and project management. His main eateries type market should be supported first. research theme is the application of management theories to the construction project and industry. He has rich experi- Therefore, it will be possible to prioritize the facility ence in improving construction laws and regulations in Korea as well. type to be supported by considering the facility type in managing the financial support remodeling program. Moreover, the results of this study can be used as an References objective index to select a target market in considera- Jung, W. G. 2011. “A Study on Status of Facilities tion of the effects of market characteristics. Modernization at Traditional Market” Master’s Thesis, Thisstudyproposedawaytoefficienate the financial Kyungsung University. support of the Traditional Market Facility Modernization Kang, G. S. 2016. “A Study on The Improvement Plan Of Program. It is expected that the sales of markets will Supporting Traditional Market” Master’s Thesis, Pusan increase more if the government considers the market National University Kim, B. S., J. W. Roh, T. Y. Kim, and K. H. Kim. 2006. “The characteristics and facility types, like the analysis results of Indoor Environment Easurement Anslysis of Arcade-Type this study, while selecting markets for financial support Markets in Korea.” Journal of Asian Architecture and according to the financial support policy. Since the objec- Building Engineering 5 (1): 191–198. doi:10.3130/ tive of this policy is to revitalize the market through the jaabe.5.191. financial support of the Facility Modernization Program, it Kim, Y. H., and C. M. Chung. 2013. “A Study on the Effects of is believed that the results of this study will contribute to the Traditional Market Modernization Project on Commercial Supremacy Vitalization.” Journal of the proposing the direction of facility support programs to Korean Society of Housing Environment 11 (3): 277–290. hands-on staffs operating policies and increase actual ISSN: 1738-0316. http://www.reik.or.kr/ benefits for store owners. Lee, D. H., and Y. S. Lee 2013. “A Study on the Effect of Although this study directly collected vast amounts Governments’traditional Retailand Periodic Market of data, there were a limited number of collectible data Policies on Revitalization of Market : Focused on 420 C. J. YOO AND Y. S. KIM Traditional Retail and Periodic Markets in the Urban Areas Support Program. https://www.mss.go.kr/. https://search. of Daegu and Daejeon” Journal of Korean Industrial mss.go.kr/RSA/front_new/Search.jsp. Economic Association 26 (5): 2337–2360. ISSN: 1229- Park, C. 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Traditional Markets and Shopping Districts Revitalization orgId=309&confmNo=309002&kosisYn=Y
Journal
Journal of Asian Architecture and Building Engineering
– Taylor & Francis
Published: Sep 3, 2019
Keywords: Traditional market; Facility Modernization Financial Support program; market characteristics
