• Science of Emotion and Sensibility
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• v.5 no.4
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• pp.1-10
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• 2002

A web based virtual try-on provides customers a more enjoyable shopping experience that visualize clothes on personal mannequin. The researchers compared virtual fitting models which were developed in 2000 at Korea and in 2000 and 2002 at U.S. The results of this study as follows: The information about user's body size was required to input for selection of a virtual fitting model. 7 to 19 different body size, shape, and face features including weight and height were needed for visualizing virtual fitting model. The body type of the U.S virtual fitting model(My virtual model) was selected by front view silhouette for women, and by shoulder width and midriff silhouette for men. The more detailed information was required for developing Korean virtual fitting model. The additional body size information required in the site were leg and arm lengths, waist length, and thigh and ankle circumferences. The body proportion of Korean cyber personal mannequin was longer and narrower than the U.S cyber personal mannequin. It was recommended that standardized body length, width, and depth proportions calculated from national anthropometric data must be applied for developing Korean virtual fitting model. With application of more detailed information on face feature and advanced graphic image technology the 'My virtual model in 2002 resembled the human body shape of various race.

• Smart Media Journal
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• v.13 no.1
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• pp.67-75
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• 2024

The purpose of this research is to investigate consumer responses to production recommendations by AI. In order to test hypotheses of this study, we conducted experimental study that was a 2(Brand reputation: high vs. low) X 2(Social comparison: high vs. low). The results of this study showed the interaction effects of brand reputation and social comparison on brand attitude. Based on the results, we provide theoretical implications to extent the existing research regarding product recommendations. Moreover, the results of this study provide some practical implications and a new aspect about AI recommendations.

• Journal of Intelligence and Information Systems
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• v.10 no.1
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• pp.13-25
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• 2004

In the online shopping environment, consumers suffer from the process of selecting an optimal supplier. Although comparison shopping agent-based web sites and consumers' online community sites support the selection process, they have limitations when considering diverse and dynamic purchase conditions as a whole, which is the cause of additional consumer effort for optimal supplier selection. This study provides a decision support model with a sensitivity analysis for selecting an optimal supplier considering purchase conditions as a whole. It screens suppliers with filtering factors and provides optimal suppliers through a sensitivity analysis from a Quadratic Programming model. We implemented a prototype system and showed that it could be an effective decision support system for selecting the optimal supplier in the online shopping environment.

• Archives of design research
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• v.16 no.1
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• pp.261-270
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• 2003

This paper focuses on the navigation methods which users select in different websites or for different tasks. Identifying the preferred navigation methods used for each case would help developers to construct the structure of website more effectively and confidently. To achieve the goal, this paper presents a framework on the classification of links as S_link and C_link. Then experiment is designed in order to evaluate the type of preferred link in each case. For the experiment, two different types of prototype websites such as news sites and shopping sites were constructed for which two different types of tasks such as goal-centered tasks and process-centered tasks were given to users. Particularly, to minimize the effects of visual elements and technical difference, prototype websites were produced with only HTML, not JavaScript nor Shockwave Flash. The result showed dearly that type of tasks had more significant effects on users navigation patterns than type of website. And users are more dependent on the S_link in the goal-centered task and on the C_link in the process-centered task. These findings were more apparent at the Qualitative test which was conducted for the comparative analysis between prototype site and real site.

• Information Systems Review
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• v.25 no.4
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• pp.233-248
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• 2023

The increasing integration of intelligent information technologies within organizational systems has amplified the risk to personal information security. This escalation, in turn, has fueled growing apprehension about an organization's capabilities in safeguarding user data. While Internet users adopt a multifaceted approach in assessing a company's information security, existing research on the multiple dimensions of information security is decidedly sparse. Moreover, there is a conspicuous gap in investigations exploring whether users' evaluations of organizational information security differ across industry types. With an aim to bridge these gaps, our study strives to identify which information security attributes users perceive as most critical and to delve deeper into potential variations in these attributes across different industry sectors. To this end, we conducted a structured survey involving 498 users and utilized the analytic hierarchy process (AHP) to determine the relative significance of various information security attributes. Our results indicate that users place the greatest importance on the technological dimension of information security, followed closely by transparency. In the technological arena, banks and domestic portal providers earned high ratings, while for transparency, banks and governmental agencies stood out. Contrarily, social media providers received the lowest evaluations in both domains. By introducing a multidimensional model of information security attributes and highlighting the relative importance of each in the realm of information security research, this study provides a significant theoretical contribution. Moreover, the practical implications are noteworthy: our findings serve as a foundational resource for Internet service companies to discern the security attributes that demand their attention, thereby facilitating an enhancement of their information security measures.

• Journal of Families and Better Life
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• v.26 no.1
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• pp.15-29
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• 2008

The study examined the characteristics of internet shopping mall sites including on-line market places and integrated internet stores from a perspective of consumer protection. Specifically, the study investigated 1) whether sufficient information is provided on the internet shopping mall sites, 2) whether shopping mall sites abide by internet advertising principles, and 3) specific examples of consumer misleading potentialities from internet shopping sites. Further, on-line market places and integrated internet stores were compared based on their informativeness and potential consumer misleading factors. Total 50 shopping mall sites were analyzed for examining the types of information provided and consumer misleading factors. To verify study questions, descriptive statistics were used. For comparison between on-line market places and integrated internet stores, Chi-square test and independent-sample t-test were employed. The results of this study were as the following: First, not a few of the internet shopping mall sites did not provided important information such as safety and warrantees. Second, important disclosures were not noticeable on the web pages and distracting factors were frequently used. Third, integrated internet stores were desirable compared to on-line marketplaces based on informativeness and consumer misleading potentialities. As the result of this study, internet shopping malls need to advised to provide sufficient information and reduce potential misleading factors.

• Journal of the Korean Society for information Management
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• v.34 no.3
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• pp.89-107
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• 2017

This study aims to compare information seeking behavior of 1300K users on PC and mobile phone. Transaction logs of 1300K, a major Korean shopping search engine, were analyzed. These transaction logs were collected over 1 month period, from April 1 to April 31, 2016. The results of this study show that there are a little more mobile sessions than PC sessions. Users conducted slightly more browsing on PCs than mobile phones, whereas users submitted queries more than two times on mobile phones than on PCs. Users clicked more search results on PCs than mobile phones, whereas users made important decision makings such as product purchases more on mobile phones than PCs. Top queries and categories were similar between PCs and mobile phones. Queries and categories on mobile phones were more focused than queries on PCs. Overall, mobile search behavior is more simple, passive, and focused than PC search behavior. The results of this study can be implemented to the effective improvement and development of search services for different devices.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.147-163
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• 2004

For the purchase of a cheaper product on the Internet, many customers have been trying to search online shopping mall sites and visit comparison-pricing shops that compare prices and other criteria of the product. Others have been participating into online auction markets or group-buying markets. However, a lot of online shopping malls, auction markets, and group-buying markets provide the same product with different prices. Since these marketplaces have different price settlement mechanism, it is very difficult for the customers to determine marketplace to purchase, considering different kinds of marketplaces at the same time. To overcome such limitations, decision rules and solution procedures for purchase decision making are necessary, which can cover multiple marketplaces simultaneously. For this purpose, purchase decision making in each market must be conducted to maximize customer's utility, and conflicts with other marketplaces must be resolved. Therefore, we have developed the rules and methods that can negotiate cooperatively the purchase decision making in several marketplaces, and designed an architecture of Intelligent Buyer Agent and a message structure to support the idea.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.1109-1113
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• 2009

Exchange of data between users and system is made by users' inputting their information into HTML input forms like when signing up in websites or buying in online shopping malls. If users make a mistake of inputting their information, the system gives an error message in order for users to correct their mistakes. Although ISO recommends immediate feedback, Bargas et al. gave a report that feedback in all after filling forms out is more usable than feedback one by one when inputting data online. We made a comparative experiment on usability under each case of feedback one by one and feedback in all. The result is immediate feedback is more usable and satisfactory. The analysis of data resulted that immediate feedback produced fewer error and gets higher subjective ratings.

• 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%.