• Title/Summary/Keyword: Shopping Pattern

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Evaluation on Development Performances of E-Commerce for 50 Major Cities in China (중국 주요 50개 도시의 전자상거래 발전성과에 대한 평가)

  • Jeong, Dong-Bin;Wang, Qiang
    • Journal of Distribution Science
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    • v.14 no.1
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    • pp.67-74
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    • 2016
  • Purpose - In this paper, the degree of similarity and dissimilarity between pairs of 50 major cities in China can be shown on the basis of three evaluation variables(internet businessman index, internet shopping index and e-commerce development index). Dissimilarity distance matrix is used to analyze both similarity and dissimilarity between each fifty city in China by calculating dissimilarity as distance. Higher value signifies higher degree of dissimilarity between two cities. Cluster analysis is exploited to classify 50 cities into a number of different groups such that similar cities are placed in the same group. In addition, multidimensional scaling(MDS) technique can obtain visual representation for exploring the pattern of proximities among 50 major cities in China based on three development performance attributes. Research design, data, and methodology - This research is performed by the 2013 report provided with AliResearch in China(1/1/2013~11/30/2013) and utilized multivariate methods such as dissimilarity distance matrix, cluster analysis and MDS by using CLUSTER, KMEANS, PROXIMITIES and ALSCAL procedures in SPSS 21.0. Results - This research applies two types of cluster analysis and MDS on three development performances based on the 2013 report of Aliresearch. As a result, it is confirmed that grouping is possible by categorizing the types into four clusters which share similar characteristics. MDS is exploited to carry out positioning of both grouped locations of cluster and 50 major cities belonging to each cluster. Since all the values corresponding to Shenzhen, Guangzhou and Hangzhou(which belong to cluster 1 among 50 major cities) are very large, these cities are superior to other cities in all three evaluation attributes. Twelve cities(Beijing, ShangHai, Jinghua, ZhuHai, XiaMen, SuZhou, NanJing, DongWan, ZhangShan, JiaXing, NingBo and FoShan), which belong to cluster 3, are inferior to those of cluster 1 in terms of all three attributes, but they can be expected to be the next e-commerce revolution. The rest of major cities, in particular, which belong to cluster 4 are relatively inferior in all three attributes, so that this automatically evokes creative innovation, which leads to e-commerce development as a whole in China. In terms of internet businessman index, on the other hand, Tainan, Taizhong, and Gaoxiong(which belong to cluster 2) are situated superior to others. However, these three cities are inferior to others in an internet shopping index sense. The rest of major cities, in particular, which belong to cluster 4 are relatively inferior in all three evaluation attributes, so that this automatically evokes innovation and entrepreneurship, which leads to e-commerce development as a whole in China. Conclusions - This study suggests the implications to help e-governmental officers and companies make strategies in both Korea and China. This is expected to give some useful information in understanding the recent situation of e-commerce in China, by looking over development performances of 50 major cities. Therefore, we should develop marketing, branding and communication relevant to online Chinese consumers. One of these efforts will be incentives like loyalty points and coupons that can encourage consumers and building in-house logistics networks.

Utilizing the Effect of Market Basket Size for Improving the Practicality of Association Rule Measures (연관규칙 흥미성 척도의 실용성 향상을 위한 장바구니 크기 효과 반영 방안)

  • Kim, Won-Seo;Jeong, Seung-Ryul;Kim, Nam-Gyu
    • The KIPS Transactions:PartD
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    • v.17D no.1
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    • pp.1-8
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    • 2010
  • Association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from voluminous transactional data. Certainly, one of the major purposes of association rule mining is utilizing the acquired knowledge to provide marketing strategies such as catalogue design, cross-selling and shop allocation. However, this requires too much time and high cost to only extract the actionable and profitable knowledge from tremendous numbers of discovered patterns. In currently available literature, a number of interest measures have been devised to accelerate and systematize the process of pattern evaluation. Unfortunately, most of such measures, including support and confidence, are prone to yielding impractical results because they are calculated only from the sales frequencies of items. For instance, traditional measures cannot differentiate between the purchases in a small basket and those in a large shopping cart. Therefore, some adjustment should be made to the size of market baskets because there is a strong possibility that mutually irrelevant items could appear together in a large shopping cart. Contrary to the previous approaches, we attempted to consider market basket's size in calculating interest measures. Because the devised measure assigns different weights to individual purchases according to their basket sizes, we expect that the measure can minimize distortion of results caused by accidental patterns. Additionally, we performed intensive computer simulations under various environments, and we performed real case analyses to analyze the correctness and consistency of the devised measure.

Implementation of CNN-based Classification Training Model for Unstructured Fashion Image Retrieval using Preprocessing with MASK R-CNN (비정형 패션 이미지 검색을 위한 MASK R-CNN 선형처리 기반 CNN 분류 학습모델 구현)

  • Seunga, Cho;Hayoung, Lee;Hyelim, Jang;Kyuri, Kim;Hyeon-Ji, Lee;Bong-Ki, Son;Jaeho, Lee
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.6
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    • pp.13-23
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    • 2022
  • In this paper, we propose a detailed component image classification algorithm by fashion item for unstructured data retrieval in the fashion field. Due to the COVID-19 environment, AI-based online shopping malls are increasing recently. However, there is a limit to accurate unstructured data search with existing keyword search and personalized style recommendations based on user surfing behavior. In this study, pre-processing using Mask R-CNN was conducted using images crawled from online shopping sites and then classified components for each fashion item through CNN. We obtain the accuaracy for collar of the shirt's as 93.28%, the pattern of the shirt as 98.10%, the 3 classese fit of the jeans as 91.73%, And, we further obtained one for the 4 classes fit of jeans as 81.59% and the color of the jeans as 93.91%. At the results for the decorated items, we also obtained the accuract of the washing of the jeans as 91.20% and the demage of jeans accuaracy as 92.96%.

A Study on Increasing the Efficiency of Image Search Using Image Attribute in the area of content-Based Image Retrieval (내용기반 이미지 검색에 있어 이미지 속성정보를 활용한 검색 효율성 향상)

  • Mo, Yeong-Il;Lee, Cheol-Gyu
    • Journal of the Korea Society for Simulation
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    • v.18 no.2
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    • pp.39-48
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    • 2009
  • This study reviews the limit of image search by considering on the image search methods related to content-based image retrieval and suggests a user interface for more efficient content-based image retrieval and the ways to utilize image properties. For now, most studies on image search are being performed focusing on content-based image retrieval; they try to search based on the image's colors, texture, shapes, and the overall form of the image. However, the results are not satisfactory because there are various technological limits. Accordingly, this study suggests a new retrieval system which adapts content-based image retrieval and the conventional keyword search method. This is about a way to attribute properties to images using texts and a fast way to search images by expressing the attribute of images as keywords and utilizing them to search images. Also, the study focuses on a simulation for a user interface to make query language on the Internet and a search for clothes in an online shopping mall as an application of the retrieval system based on image attribute. This study will contribute to adding a new purchase pattern in online shopping malls and to the development of the area of similar image search.

A Case Study on the Smart Tourism City Using Big Data: Focusing on Tourists Visiting Jeju Province (빅 데이터를 활용한 스마트 관광 도시 사례 분석 연구: 제주특별자치도 관광객 데이터를 중심으로)

  • Junhwan Moon;Sunghyun Kim;Hesub Rho;Chulmo Koo
    • Information Systems Review
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    • v.21 no.2
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    • pp.1-27
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    • 2019
  • It is possible to provide Smart Tourism Service through the development of information technology. It is necessary for the tourism industry to understand and utilize Big Data that has tourists' consumption patterns and service usage patterns in order to continuously create a new business model by converging with other industries. This study suggests to activate Jeju Smart Tourism by analyzing Big Data based on credit card usage records and location of tourists in Jeju. The results of the study show that First, the percentage of Chinese tourists visiting Jeju has decreased because of the effect of THAAD. Second, Consumption pattern of Chinese tourists is mostly occurring in the northern areas where airports and duty-free shops are located, while one in other regions is very low. The regional economy of Jeju City and Seogwipo City shows a overall stagnation, without changes in policy, existing consumption trends and growth rates will continue in line with regional characteristics. Third, we need a policy that young people flow into by building Jeju Multi-complex Mall where they can eat, drink, and go shopping at once because the number of young tourists and the price they spend are increasing. Furthermore, it is necessary to provide services for life-support related to weather, shopping, traffic, and facilities etc. through analyzing Wi-Fi usage location. Based on the results, we suggests the marketing strategies and public policies for understanding Jeju tourists' patterns and stimulating Jeju tourism industry.

Survey on the Brand of Online Custom Dress Shirts and Analysis of the Sizing System (온라인 맞춤 드레스셔츠 업체 현황조사 및 치수체계 분석)

  • An, Dong-joo;Lee, Jeong-yim
    • Fashion & Textile Research Journal
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    • v.20 no.5
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    • pp.556-568
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    • 2018
  • In this study, we surveyed the current status and sizing system of the custom dress shirts sold through online shopping, compared with the sizing system of the ready-made dress shirts. We tried to collect the information needed to make the well fitted dress shirts for middle-aged men from this study. The 17 online custom dress shirt brands were selected and the sales type, sales price, design options and size options of each brand were analyzed. The sizing systems of online custom dress shirt brands were compared with the sizing system of the 10 ready made dress shirt brands. The result showed that online custom dress shirts brands offered a variety of design options and size options to meet the consumers' individuality, taste and demand for good fit. In the ready-made brands, all 10 brands were using the same size notation system. In the same size designation, the difference in product size among the ready-made brands showed a tendency to be smaller than the online custom brands. The online custom brands had the different size notation system among brands. The size notation, the number of size designation and the size interval were different for each brand. Also, in the online custom brands, the product size among brands differed from each other in the same size designation. Therefore, the standardized size information and sizing system for middle-aged men that could be used as criteria when making the product size and pattern design in online custom brands were needed.

Retail Fashion Buyers' Utilization of Information Source in Dongdaemum Market (동대문 시장을 이용하는 리테일 바이어의 경력 및 소속업체 연매출에 따른 정보원 활용)

  • Kim, Jihye;Chung, Sung-Jee
    • Journal of the Korea Fashion and Costume Design Association
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    • v.16 no.1
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    • pp.41-52
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    • 2014
  • The purposes of this study were to explore differences in utilization of information sources depending on the length of buyers' career and annual sales volume of stores where buyers work for. The questionnaire was prepared by the researcher and was answered by 200 buyers who purchase their items from Dondaemun market. The researcher analyzed the data using both ANOVA and Tukey's test as a post-hoc test. The conclusion of this study is summarized below. First, there were significant differences in utilization of information sources among buyer groups depending on the length of buyers' career. The buyers with more than 10 years career showed more effective utilization of information source such as resident buying offices, manufacturers, trade publications, trade associations, fashion reports, celebrities, window shopping, professional magazines, and advice from others. Second, there were significant differences in utilization of information sources among buyer groups depending on annual sales volume of the stores where the buyers work for. The buyer who work for the store with its annual sales volume in excess of 2 billion won showed more effective utilization of information source such as trade association, professional magazines, sales record, want slips, advertising results, sales trends, customer surveys, sales meetings, customer advisory panel, in-store merchandising bureau and advice from other experienced buyers. However, buyers of the store with its annual sales volume lower than 100 million won showed different pattern utilization of information sources such as vendors, trade publication, celebrities and advice from others.

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The Development of Users' Interesting Points Analyses Method and POI Recommendation System for Indoor Location Based Services (실내 위치기반 서비스를 위한 사용자 관심지점 탐사 기법과 POI추천 시스템의 구현)

  • Kim, Beoum-Su;Lee, Yeon;Kim, Gyeong-Bae;Bae, Hae-Young
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.5
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    • pp.81-91
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    • 2012
  • Recently, as location-determination of indoor users is available with the development of variety of localization techniques for indoor location-based service, diverse indoor location based services are proposed. Accordingly, it is necessary to develop individualized POI recommendation service for recommending most interested points of large-scale commercial spaces such as shopping malls and departments. For POI recommendation, it is necessary to study the method for exploring location which users are interested in location with considering user's mobility in large-scale commercial spaces. In this paper, we proposed POI recommendation system with the definition of users' as 'Stay point' in order to consider users' various interest locations. By using the proposed algorithm, we analysis users' Stay points, then mining the users' visiting pattern to finished the proposed. POI Recommendation System. The proposed system decreased data more dramatically than that of using user's entire mobility data and usage of memory.

Comparison Between Actual and 3D Virtual Skirts of Different Front and Back Silhouette with Regard to the Evaluation of Subjective Appearance and Shape Characteristics (앞과 뒤 실루엣이 다른 스커트의 가상착의와 실제 착의에 대한 주관적 외관평가와 형태특성 비교)

  • Lee, Heeran;Hong, Kyunghi
    • Journal of Fashion Business
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    • v.21 no.5
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    • pp.91-108
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    • 2017
  • Interests in 3D virtual clothing technology and its application in online shopping malls are increasing with the advent of the Fourth Industrial Revolution. Most studies on 3D virtual clothing, however, are focused on observing drapes or ease of virtual clothing depending on fabric properties of representative clothing items. Therefore, the purpose of this study is: first, to determine if current input of typical material characteristics in 3D CLO are sufficient to formulate virtual skirts with different front and back silhouettes; second, to determine if subjective appearance evaluation matched physical shape characteristics of those skirts. In this study, appearances of typical cotton, wool, silk, rayon, and polyester skirts with different front and back pattern were compared between actual and virtual clothing depending on fabric materials. Subjective appearance evaluation was conducted by 7 experts regarding similarity between actual and virtual clothing with a 5-point scale. For objective evaluation of the both types of skirt shape, degree of roundness at the cross section, displacement of side seam, position of back waistline, and the number of folds at the skirt back were observed. In the case of cotton and wool, not the subjective appearance evaluation as well as shape characteristics of virtual skirts were well matched to the actual shape of skirts with a few material inputs. However, current material inputs for silk, rayon and polyester were insufficient to cover material differences in formation of virtual skirts with different front and back silhouettes.

Comparison on Fashion Information Sources, Clothing Benefits Sought & Purchase Criteria according to Consumers' Time Pressure Level (소비자의 시간압박 수준에 따른 패션정보원, 추구혜택, 구매기준 비교연구)

  • Kim, Chil-Soon;Lee, Jin-Hwa
    • Journal of the Korean Society of Clothing and Textiles
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    • v.30 no.1 s.149
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    • pp.20-30
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    • 2006
  • The purposes of this study were to investigate demographic profiles between the consumer group under high time pressure(HTP) and the group under low time pressure(LTP) during the shopping, to examine the level of association between the fashion information sources and time pressure variable, to determine the difference in clothing benefits sought between HTP and LTP, and to determine the difference in purchase criteria. We distributed questionnaires to 600 women aged in 20-65. The reliable 562 questionnaires were used for a statistical analysis. Data analyses were conducted with SPSS program on t-test, cluster analysis, factor analysis, and Chi square test. We obtained the following results: There was a significant association between demographic variables such as age, occupation, education, residence area, & family cycle and time pressure variable. Fashion information sources were classified into 4 factors. HTP searched information on fashion products using more various sources than LTP did. There was also a significant difference between HTP and LTP in clothing benefit sought. Four clothing benefit factors such as trendy/social position, economic value, protection/comfort, and makeup of body shape were sought more by HTP than by LTP. In addition, HTP considered significantly more purchase criteria such as color/pattern, comfort, quality, suitability, material, sewing finishing, coordination, price, brand, easy care, and country of origin than LTP.