The process of identifying the characteristics of the trading area to be analyzed and analyzing the difference from the competitive trading area is an essential prior task in establishing marketing strategies to revitalize a trading area. However, most trading area studies, so far, have relied heavily on quantitative descriptive statistics of a trading area itself or the empirical insight of researchers. As a result, objective and valid research methodologies for analyzing the characteristics of trading area were very deficient and there were few research attempts to analyze differences from competing trading areas based on the perception differences of visitors. To achieve the objectives of this study, the following procedures were carried out. First, a questionnaire survey was conducted for consumers who frequently or accustomed to visiting the trading areas of Konkuk University Station (K TA), Hongik University Station (H TA), and Gangnam Station (G TA), which were selected as the target trading areas. Next, through using the chi-square test, it was verified whether there were significant differences between the three trading areas and the eight categories, such as the origin of the visit and the type of visiting companion. The differences in the association of visitors between trading areas and categories were plotted in diagrams. And by using the Multiple Correspondence Analysis (MCA), which is an extension of CA, the perception differences of visitors were visualized on the positioning map with respect to the relationship between the three trading areas and gender/type of visit companion, and gender/age group. In addition, by using the Multidimensional Preference Analysis (MDPREF), one of the types of Multidimensional Scale Methods (MDS), the difference in perception of visitors is analyzed through a positioning map on the relationship between three trading areas, the purpose of the visit, major use business types, and information sources. A procedural methodology for the creation of a trading area positioning map was presented. The results are as follows. First, there were significant differences in the categories of the origin of visit, type of visiting companion, average spending amount, visiting transportation, and return transportation in the three trading areas. Second, the MCA results verified that the K TA is is favored by the female and the 20s, the H TA by the male and the 30s, and the G TA by the 40s. Finally, the results of the MDPREF analysis are as follows. First, in terms of the perception of visitors, the H TA was recognized as a mixed trading area with multi-dimensional purposes, not specific factors, unlike the other two trading areas. Second, in the relationship between the three trading areas and the major business type used, the three trading areas were not differentiated and were found to be in fierce competition. Third, in terms of information sources, there was no difference in the information sources used by visitors to the three trading areas, and it was found that visitors preferred to obtain informations through Internet search, neighborhood recommendation, and SNS. The results provide trading area marketers with a theoretical methodology to build effective trading area marketing strategies including market segmentation and customer targeting through the objective identification of visit characteristics and analysis of perceptual differences of trading area visitors. In addition, the results suggest a theoretical and procedural methodology for arranging the trading area positioning map that is differentiated as a competitive strategy and repositioning the specific trading area by improving the visitor
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