• Journal of Information Technology Services
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• v.14 no.1
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• pp.251-262
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• 2015

This study checks the conceptual definition of domestic book curation which is still in the beginning stage, the necessity of developing service and business, domestic and overseas case of relevant service. Further, the problem of book recommendation service and the difficulty anticipated in the embodiment of service are investigated together and the business model as new IT service is suggested to supplement them. Specifically, the collection of book information and customer information (interest and purchase pattern) and the procedure of mining the collected information and the process of embodying visualization was presented in the sector of service in the first place. Then, the technical transfer of developed solution and the construction cost and the method to impose commission over contents sales are presented in the sector of business. Diverse social and economic effects are expected to realize by developing and utilizing such services, namely, promoting the distribution of excellent book which were kept in dead storage so far due to lack of marketing support, recommendation readers the proper books which are convenient and necessary.

• Journal of Distribution Science
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• v.15 no.6
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• pp.77-96
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• 2017

Purpose - This study aims to develop correspondence strategies to the environment change in domestic retail store types. Recently, new types of retails have emerged in retail industries. Therefore, trade area platform has developed focusing on the speed of data, no longer trade area from district border. Besides, 'trade area smart' brings about change in retail types with the development of giga internet. Thus, context shopping is changing the way of consumers' purchase pattern through data capture, technology capability, and algorithm development. For these reasons, the sales estimation model has been shown to be flawed using the notion of former scale and time, and it is necessary to construct a new model. Research design, data, and methodology - This study focuses on measuring retail change in large multi-shopping mall for the outlook for retail industry and competition for trade area with the theoretical background understanding of retail store types and overall domestic retail conditions. The competition among retail store types are strong, whereas the borders among them are fading. There is a greater need to analyze on a new model because sales expectation can be hard to get with business area competition. For comprehensive research, therefore, the research method based on the statistical analysis was excluded, and field survey and literature investigation method were used to identify problems and propose an alternative. In research material, research fidelity has improved with complementing research data related with retail specialists' as well as department stores. Results - This study analyzed trade area survival and its pattern through sales estimation and empirical studies on trade areas. The sales estimation, based on Huff model system, counts the number of households shopping absorption expectation from trade areas. Based on the results, this paper estimated sales scale, and then deducted modified probability model. Conclusions - In times of retail store chain destruction and off-line store reorganization, modified Huff model has problems in estimating sales. Transformation probability model, supplemented by the existing problems, was analyzed to be more effective in competitiveness business condition. This study offers a viable alternative to figure out related trade areas' sale estimation by reconstructing new-modified probability model. As a result, the future task is to enlarge the borders from IT infrastructure with data and evidence based business into DT infrastructure.

• Journal of Energy Engineering
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• v.25 no.4
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• pp.198-206
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• 2016

Fuel economy label will be used as a national indicator in energy management, leading to the development of car technology manufacturer and plays a role in providing consumer vehicle purchase information. But the government's fuel economy label is continued consumer complaint is different and diminishing fuel economy were introduced by the government to measure the exact fuel economy label than resetting the 5-cycle test method in the US for the domestic vehicle standards. Originally two test mode in order to reduce the impact of the sharp increase in the resources required but methods of calculating a measured result value by driving all of the five test mode a variety of environmental conditions and the running pattern is reflected to the fuel economy label (city( FTP-75 mode), highway(HWFET mode)) and using 5-cycle correction formula for calculating a fuel consumption value and the equivalent value to calculate the result of the 5-cycle test. The compensation was calculated expression 30s, 5-Cycle Test Method of vehicles in 2011 was considered necessary to review the existing 5-cycle correction formula for the New Type car due to the recent rapid development of automotive technology. In this study, recent technology is targeting 14 units New Type car applied over the same test method and the existing check test mode specific fuel economy properties and, as a result of analyzing the corrected expression differences that have already been developed with the existing test vehicle resulting large did not show the difference was found to correction formula also not getting the existing fuel correction expression significant effect on the improvement of the current automobile technology as a maximum error of less than 1.5%.

• Journal of Global Scholars of Marketing Science
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• v.19 no.2
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• pp.17-26
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• 2009

As the lifestyle of consumers changes and the need for various products increases, new products are being developed in the market. Each household owns various home appliances which are purchased through the choice of a decision maker. These appliances include not only large-sized products such as TV, refrigerator, and washing machine, but also small-sized products such as microwave oven and air cleaner. There exists latent correlation among possession of home appliances, even though they are purchased independently. The purpose of this research is to analyze the effect of demographic factors on the purchase and possession of each home appliances, and to derive some relationships among various appliances. To achieve this purpose, the present status on the possession of each home appliances are investigated through consumer survey data on the electric and energy product. And a multivariate probit(MVP) model is applied for the empirical analysis. From the estimation results, some appliances show a substitutive or complementary pattern as expected, while others which look apparently unrelated have correlation by co-incidence. This research has several advantages compared to previous literatures on home appliances. First, this research focuses on the various products which are purchased by each household, while previous researches such as Matsukawa and Ito(1998) and Yoon(2007) focus just on a particular product. Second, the methodology of this research can consider a choice process of each product and correlation among products simultaneously. Lastly, this research can analyze not only a substitutive or complementary relationship in the same category, but also the correlation among products in the different categories. As the data on the possession of home appliances in each household has a characteristic of multiple choice, not a single choice, a MVP model are used for the empirical analysis. A MVP model is derived from a random utility model, and has an advantage compared to a multinomial logit model in that correlation among error terms can be derive(Manchanda et al., 1999; Edwards and Allenby, 2003). It is assumed that the error term has a normal distribution with zero mean and variance-covariance matrix ${\Omega}$. Hence, the sign and value of correlation coefficients means the relationship between two alternatives(Manchanda et al., 1999). This research uses the data of 'TEMEP Household ICT/Energy Survey (THIES) 2008' which is conducted by Technology Management, Economics and Policy Program in Seoul National University. The empirical analysis of this research is accomplished in two steps. First, a MVP model with demographic variables is estimated to analyze the effect of the characteristics of household on the purchase of each home appliances. In this research, some variables such as education level, region, size of family, average income, type of house are considered. Second, a MVP model excluding demographic variables is estimated to analyze the correlation among each home appliances. According to the estimation results of variance-covariance matrix, each households tend to own some appliances such as washing machine-refrigerator-cleaner-microwave oven, and air conditioner-dish washer-washing machine and so on. On the other hand, several products such as analog braun tube TV-digital braun tube TV and desktop PC-portable PC show a substitutive pattern. Lastly, the correlation map of home appliances are derived using multi-dimensional scaling(MDS) method based on the result of variance-covariance matrix. This research can provide significant implications for the firm's marketing strategies such as bundling, pricing, display and so on. In addition, this research can provide significant information for the development of convergence products and related technologies. A convergence product can decrease its market uncertainty, if two products which consumers tend to purchase together are integrated into it. The results of this research are more meaningful because it is based on the possession status of each household through the survey data.

• Food Science and Preservation
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• v.19 no.1
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• pp.54-61
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• 2012

According to lifestyle changes, the consumers' concern about food also shifts from calories and nutrition to health and convenience. Fresh-cut produce is one of the new turns in the consumption pattern of fruits and vegetables. The increasing demand for it requires processors to make them stable in quality and safe from microorganisms. The results of the evaluation of the production process and hygienic management of fresh-cut lettuce revealed that the facilities used, such as the drainage holes, floors, and door knobs, were severely contaminated with microbes, and that the work equipment, workbenches, landing nets, and centrifuges were highly contaminated. Accordingly, improved production processes and management systems are necessary, as is the implementation of a quality control system from the stage of raw-material purchase to the distribution stage.

• Journal of the Korea Fashion and Costume Design Association
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• v.9 no.3
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• pp.133-149
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• 2007

Amid a wave of informatization, the world is allowing diverse exchanges and cooperations in the global village to be promoted. And, a change in the life environment and the consumption pattern allows the key word in distribution revolution called 'online' and 'emotion' to be recalled. As the emotion is being positioned as the trend of the new era, this study has its significance in that even the fashion industry desperately requires the emotion marketing aiming at the artistic value and practicality in fashion and the creation in value-added, and requires the development and utilization plan for diverse VMD programs on the rational dress shop, like the successful case of the trendy shop such as America's large bookstore 'Barnes & Noble.' Accordingly, the purpose of this study is to design and suggest the virtually trendy dress shop as one plan of utilizing VMD, by examining about the fashion business environment and about 'emotion trend' according to the consumer purchase needs, and through researching into the cases of the trendy dress shops with the emotion marketing. The virtual trendy dress shop 'Muse,' which was proposed as its research result, was designed with having the main concept as urban naturalism, which points to the urban and sophisticated coordination, and to the simple personality and rational value, as one method of utilizing VMD in the differentiated dress shop. And, it is desired to be performed the researches on the development and the utilization plan for diverse VMD programs in the dress shop down the road.

• Journal of Fashion Business
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• v.13 no.4
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• pp.85-98
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• 2009

Advance development of the internet has brought significant changes to the distribution structure of the fashion industry, resulting in decreased sales in Road shops and sudden growth of online fashion specialty shopping malls. As detailed analysis on internet fashion shopping malls is necessary in order to make a future projection on changes in the fashion industry, this thesis aims to study the color, fabric / pattern, silhouette, item / detail, image, etc of 2008 S/S apparel fashion style sold in the top ten shopping malls, selected in terms of sales volume and awareness. The results were further analyzed to characterize each individual shopping malls, upon which the design was compared with the five main trends for the season provided by three fashion research agencies in order to study the level of trend acceptance. Studies showed that 'Romantic Sake' trend was most widely accepted, followed by 'Eco Nature' which most reflected the characteristics of Spring. 'Modern Ethenic' trend was most aggressively accepted at more upscale shopping malls targeting older demographic, while " Play Urban' was highly accepted by shopping malls specializing in young casual. Due to the disadvantage of not being able to try on the items before purchase, styles following the 'City Luxe' trend featuring fitted suits showed the lowest trend acceptance. Amongst the design elements, color was most widely accepted.

• Fashion & Textile Research Journal
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• v.23 no.3
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• pp.370-379
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• 2021

This study investigated the wearing status and design preferences regarding athleisure wear, focusing on young women in their 20s and 30s and middle-aged women in their 40s and 50s participating in yoga and fitness activities. A total of 332 valid samples were used for the survey by setting the same number of samples for each age group. The results showed that young women in their 20s and 30s exhibited weight control, and middle-aged women in their 40s and 50s maintained their health in relation to exercise. Athleisure wear brands were found to prefer foreign brands over domestic brands. When purchasing athleisure wear, the foremost considerations were material functionality, fit according to body shape, and reasonable prices. The preferred athleisure wear leggings design showed that both middle-aged women and young women preferred nine-piece leggings. Women in their 20s to 50s were found to purchase and acquire information on athleisure wear online. Hence, the pattern of life is rapidly transitioning from offline to online, and the market structure of athleisure wear is gradually transitioning toward an omni-channel society with a distribution market structure that combines information technology(IT) and mobile technologies. Therefore, It is required to develop athleisure wear of various functional products that meet the trends according to the global market environment and consumer class.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.1-12
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• 2006

Approaches to spatial analysis differ from the type of spatial objects to be treated. Especially, in here, the case where two spatial data sets coexist is considered. The goal of such case lies on detecting a subset of spatial objects out of a large set that affects the distribution of the other object. However, it is not easy to extract a subset from a large set by visualization just with the help of GIS since huge amount of data are provided nowadays. In this research, therefore, relationship between two different spatial data are analyzed by quantitative measure in the case study of marketing geography. A purchase history data of a small retail store and the location of its competitors are given as source data for the analysis. The goal of analysis from the aspect of this case study is to extract strong competitors of the store that affects the sales amount of the store among many competitors. With the result, therefore, it is expected that market area pattern and competitive power of stores under micro scale retail environment would be understood by quantitative measure.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.