• Spatial Information Research
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• v.18 no.2
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• pp.67-75
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• 2010

When people are shopping at a large shopping mall, they usually become to go around many stores for looking for better products and comparing them. In this paper, we design and implement a purchasing activity support system based on an Ambient Service Model that provides relevant stores information on map interface hierarchically through user contexts based search, to support such user's purchasing activities with the help of relevant information. In this system, users can search for relevant stores information through the system by Ambient Query which is created by their location and stores information with a mobile device. Then, users obtain relevant stores information provided in the form of hierarchy of keywords as a highly condensed summary and easily figure out the locations of the stores on a map interface. Moreover, users search additional other kinds of relevant stores information over the hierarchy of keywords. Eventually, users can obtain relevant stores information intuitively and conveniently without complex search processes. We implemented this system by integrating the subordinate technologies such as RFID, map-based, location-based and ontology technology. We also performed experiments on a well-known shopping region (Ilsan Lapesta shopping mall, Goyang-city Gyeonggi-do, Korea). Finally, we also confirmed that users' shopping activities were significantly improved by utility the present system.

• Journal of Korean Society for Quality Management
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• v.33 no.4
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• pp.21-41
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• 2005

This study analyzes the Internet utilization pattern of customer by comprehensively investigating the previous studies on the behavior pattern of customer in terms of Internet business. Based on the analysis, this study develops research framework that supports strategic decision-making for resource allocation in Internet business. Such research framework would be helpful for providing the typology of Internet business model that can be specialized by each industry. As a result of the simulation analysis, it was found that the optimal resource allocation portfolio providing maximum profits to the Internet bookstore involves large-scale investment on delivery service and customer support service which are the key factors for post-purchase customer satisfaction, regardless of the growth pattern or size of Internet bookstore market. Consequently, from the above analysis, the investment ratio of resources for the profit maximization of Internet bookstore was drawn. Conclusively, based on the comprehensive examination of the results, this study provided a framework for dynamic resource allocation decision-making, and proposed a management strategy which allows consumers to shop under more favorable environment, and simultaneously enables the Internet bookstore to accomplish management objectives such as continuous growth and profit maximization.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.118-126
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• 2003

In data mining, having access to large amount of data sets for the purpose of predictive data does not guarantee good method, even where the size of Real data is Mobile commerce unlimited. In addition to searching expected Goods objects for Users, it becomes necessary to develop a recommendation service based on XML. In this paper, we design the optimized XML Recommender product data. Efficient XML data preprocessing is required, include of formatting, structural, and attribute representation with dependent on User Profile Information. Our goal is to find a relationship among user interested products from E-Commerce and M-Commerce to XDB. Firstly, analyzing user profiles information. In the result creating clusters with analyzed user profile such as with set of sex, age, job. Secondly, it is clustering XML data which are associative products classify from user profile in shopping mall. Thirdly, after composing categories and goods data in which associative objects exist from the first clustering, it represent categories and goods in shopping mall and optimized clustering XML data which are personalized products. The proposed personalized user profile clustering method has been designed and simulated to demonstrate it's efficient.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1231-1238
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• 2021

Recently, large online shopping malls are providing image search services as well as text or category searches. However, in the case of an image search service, there is a problem in that the search service cannot be used in the absence of an image. This paper describes the development of a system that allows users to find the clothes they want through hand-drawn images of the style of clothes when they search for clothes in an online clothing shopping mall. The hand-drawing data drawn by the user increases the accuracy of matching through neural network learning, and enables matching of clothes using various object detection algorithms. This is expected to increase customer satisfaction with online shopping by allowing users to quickly search for clothing they are looking for.

• Korean Security Journal
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• no.23
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• pp.41-63
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• 2010

This study aimed to asses the relationship between shoppers' security need sufficiency and customer satisfaction on the quality of security services in Shopping Mall. This study gathered data from 485 citizen in five shopping centres at KyungKi areas. Collected data was analysed by factor analysis, reliability analysis, path analysis and multiple regression analysis with SPSS WIN 16.0. The results of the study yielded the following four perspectives. First, secure equipment and the service quality of security officers in the shopping malls have a decisive effect on customers psychological stability and crime prevention. Second, they are a strong influence upon customer satisfaction and operational security. Especially, the professionalism of the staff has a marked effect. Third, the service quality of security officers and secure equipment in the malls have an effect on operational security services and efficiency of secure services. Finally, this dissertation showed that the quality of secure equipment services and officers' mild In summary, the conclusion of this study is that secure equipment service, officers' mild manner and professionalism of the security officers affect the customer satisfaction measurement directly. They also affect customer satisfaction through psychological stability and the prevention of crime indirectly. In other words, the good quality of security in the shopping centres affects the using of facilities definitely.

• Korean small business review
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• v.41 no.1
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• pp.53-73
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• 2019

Recently, as the number of shopping facilities has increased, such as complex shopping malls, warehouse type superstores, large fashion outlets, and so on, the conflicts over the opening of large stores between neighboring municipalities are increasing. However, current regulations on the opening of large-scale stores, such as the impact analysis on commercial area, do not adequately reflect the characteristics of new type shopping facilities. In this study, we tried to suggest a rational policy alternative with more realistic suitability by analyzing the characteristics of 'regional shopping facilities' beyond the scope of the municipalities, and analyzing the impact on the regional merchants. The main results of the study are summarized as follows. First, unlike previous researches, which are limited to small business sector, this study presents the results of comprehensively comparing and analyzing the impact on the detailed sectors of the whole distribution market, including the large distribution sector and online distribution sector. Second, in this study, we calculated the total (average) amount of market penetration rate of existing shopping facilities by the entire regional shopping facilities in the Seoul metropolitan area, and this is considered to be of great value in relation to the recognition of problems at the whole level of the metropolitan area and the search for alternative solutions.

• Fire Science and Engineering
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• v.18 no.3
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• pp.108-113
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• 2004

Emergency response of fire prevention manager has an effect on decisive emergency exit behavior of customer who is not accustomed to emergency response in a large-scale shopping department on fire. Especially enclosed stairways in a large scale store are usually located in back space where is impossible for customer to access. Therefore, speedy emergency exit inducement by fire prevention manager is needed for the customer's safe egress. The object of study is to analyse the factors affecting egress behavior and emergency response of fire prevention manager in respect of fire prevention management.

• Journal of the Korean Home Economics Association
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• v.45 no.6
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• pp.1-9
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• 2007

Even though self-confidence is a personal factor of a people, it works as behavioristic factor in consumer behavior. In this study, the influence of consumer self-confidence on clothing purchase behavior was investigated. A total of 284 data sets were analyzed after collecting questionnaires from college students in Seoul using convenient sampling method. For data analysis, chi-square test, analysis of variance, reliability test and factor analysis were performed by SPSSWIN program. The results were as followed. First, the clothing purchase places were affected by the consumers' level of self-confidence. The more confident consumers preferred internet shopping and Dongdaemun market to large-scale shops. The discount stores were selected by the less confident consumers. Second, information search was one of the main reasons to visit internet shopping mall by the more confident consumers. Third, the more confident consumers showed the higher level of clothing involvement than the less confident consumers. Finally, unplanned purchases, such as pure impulse buying and reminder buying were more likely to occur by the more confident consumers with less purchase conflicts.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.23-38
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• 2012

There is a large difference between purchasing patterns in an online shopping mall and in an offline market. This difference may be caused mainly by the difference in accessibility of online and offline markets. It means that an interval between the initial purchasing decision and its realization appears to be relatively short in an online shopping mall, because a customer can make an order immediately. Because of the short interval between a purchasing decision and its realization, an online shopping mall transaction usually contains fewer items than that of an offline market. In an offline market, customers usually keep some items in mind and buy them all at once a few days after deciding to buy them, instead of buying each item individually and immediately. On the contrary, more than 70% of online shopping mall transactions contain only one item. This statistic implies that traditional data mining techniques cannot be directly applied to online market analysis, because hardly any association rules can survive with an acceptable level of Support because of too many Null Transactions. Most market basket analyses on online shopping mall transactions, therefore, have been performed by expanding the co-occurrence criteria of traditional association rule mining. While the traditional co-occurrence criteria defines items purchased in one transaction as concurrently purchased items, the expanded co-occurrence criteria regards items purchased by a customer during some predefined period (e.g., a day) as concurrently purchased items. In studies using expanded co-occurrence criteria, however, the criteria has been defined arbitrarily by researchers without any theoretical grounds or agreement. The lack of clear grounds of adopting a certain co-occurrence criteria degrades the reliability of the analytical results. Moreover, it is hard to derive new meaningful findings by combining the outcomes of previous individual studies. In this paper, we attempt to compare expanded co-occurrence criteria and propose a guideline for selecting an appropriate one. First of all, we compare the accuracy of association rules discovered according to various co-occurrence criteria. By doing this experiment we expect that we can provide a guideline for selecting appropriate co-occurrence criteria that corresponds to the purpose of the analysis. Additionally, we will perform similar experiments with several groups of customers that are segmented by each customer's average duration between orders. By this experiment, we attempt to discover the relationship between the optimal co-occurrence criteria and the customer's average duration between orders. Finally, by a series of experiments, we expect that we can provide basic guidelines for developing customized recommendation systems. Our experiments use a real dataset acquired from one of the largest internet shopping malls in Korea. We use 66,278 transactions of 3,847 customers conducted during the last two years. Overall results show that the accuracy of association rules of frequent shoppers (whose average duration between orders is relatively short) is higher than that of causal shoppers. In addition we discover that with frequent shoppers, the accuracy of association rules appears very high when the co-occurrence criteria of the training set corresponds to the validation set (i.e., target set). It implies that the co-occurrence criteria of frequent shoppers should be set according to the application purpose period. For example, an analyzer should use a day as a co-occurrence criterion if he/she wants to offer a coupon valid only for a day to potential customers who will use the coupon. On the contrary, an analyzer should use a month as a co-occurrence criterion if he/she wants to publish a coupon book that can be used for a month. In the case of causal shoppers, the accuracy of association rules appears to not be affected by the period of the application purposes. The accuracy of the causal shoppers' association rules becomes higher when the longer co-occurrence criterion has been adopted. It implies that an analyzer has to set the co-occurrence criterion for as long as possible, regardless of the application purpose period.

• Korean Institute of Interior Design Journal
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• no.41
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• pp.137-145
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• 2003

This research analyzed the space scheme in connection with complexity, one of the new changes in the discount stores, and has a goal of predicting the direction of space scheme in the upcoming complexity era. The research was conducted in the following way. Firstly, this researcher tried to grasp what kinds of changes were required in the overall distribution industry socially and economically. Secondly, the characteristic and situation of discount stores were scrutinized. Thirdly, the domestic stores' complexity status was classified and types of those were elicited. Fourthly, the time-series change and use were analyzed. The result of this analysis reveals that the types of complexity can be divided by location and adjustment to environmental changes. The time-series analysis shows that total operating area, the number of parked cars and the tenant ratio have increased dramatically in 2000 and 2003. And, according to the correlation analysis between factors, the tenant ratio has, a strong correlation with other two factors. Self-complexity takes the basic form of living facilities and complexity with other facilities is combined with other cultural, sales, educational and administrative ones. Mass-complexity is merged with the stadiums, parks or station sites. As you've seen, the concept of complex shopping mall for the realization of one stop shopping and convenience will continue in the days to come. It is desirable that the study on the large-scale shopping spaces will be conducted continually for the preparedness of future life style.