• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.139-157
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• 2002

The rapid growth of e-commerce has made both companies and customers face a new situation. Whereas companies have become to be harder to survive due to more and more competitions, the opportunity for customers to choose among more and more products has increased. So, the recommender systems that recommend suitable products to the customer have an important position in E-commerce. This research introduces collaborative filtering based recommender system which helps customers find the products they would like to purchase by producing a list of top-N recommended products. The suggested methodology is based on decision tree, product taxonomy, and association rule mining. Decision tree is used to select target customers, who have high possibility of purchasing recommended products. We applied the recommender system to a Korean department store. The methodology is evaluated with the analysis of a real department store case and is compared with other methodologies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2073-2080
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• 2015

Even though users choose goods they want to buy in on-line shopping malls, real purchase is often performed in off-line shopping malls. It is called reverse showrooming. It means that users' analysis of goods based on images and description of internet shopping malls has limitation. Thus, large-scale online shopping malls provide a customized shopping information. However, in that case, the provided information is a simple list of goods users bought or retrieved. Thus, a system to analyze various needs of users and apply the result into on-line shopping mall is necessary. In this paper, an analysis system is proposed. The system contains a module to analyze user defined preference and a module to analyze users' reviews. The former designates two goods and collects preferences of individual users. the latter analyzes reviews about purchased goods based on database dictionary stored in advance for analyzing reviews. The system implemented shows that it is possible to recommend some goods that meet each users's needs

• Journal of the Korea Society of Computer and Information
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• v.7 no.1
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• pp.161-173
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• 2002

The increasing disposable time through advancing information has come to make the tourism industry as well as the information communication industry glow in the 21st century We cannot make rational decision without proper guide information. It is impossible to anticipate tourism Products which are invisible products consisting of a variety of basic combinations of products. Tourists are getting dissatisfied with tourism experts' distorted guidance every year. A recent survey shows that the current tourism information system can't meet the need of tourists who are informative and individualized. This paper presents tourism information system that offers the most appropriate tour courses depending on the tastes of tourists by utilizing expert system, artificial intelligent applied technology. This paper is the first attempt to maximize comsumer satisfaction by developing the intelligent agent system that is able to reflect the traits of individualized customers' in the tourism industry The establishment of this system will contribute to activating the tourism industry, ultimately, by decreasing inconveniencies and tour schedules appropriate to the purpose of individual tours.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.49-62
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• 2022

Online customer review data can be easily collected on the Internet and also they describe sentimental evaluation of a product in different aspects. Previous sentiment analysis studies evaluate the degree of sentiment with review data, which may have multiple sentences describing different product aspects. Since different aspects of a product can be described in a sentence, the proposed method suggested analyzing a sentence to build a pair of a product aspect terms and sentimental terms. Bidirectional LSTM and CRF algorithms were used in this paper. A pair of aspect terms and sentimental terms are evaluated by pre-defined evaluation rules. The paper suggested using the result of evaulation as inputs of QFD, so that the quantified customer voices effect on the requirements of a new product. Online reviews for a hair dryer were used as an example showing that the proposed approach can derive reasonable sentiment analysis results.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.75-100
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• 2022

Untact mobile commerce shows a rapid growth due to the prolonged COVID-19 pandemic. And companies have a lot of tough competition in this trend. However, the detail pages of products which play an important role in purchase decision have been provided mostly for consumers in a form of stereotyped information composition. This study has found that the form of (image-centered vs. text-centered) information composition of detailed descriptions of products in the detail pages of mobile products has an effect on product attitude and purchase intention as consumers' information appeal methods vary depending on product types (search goods vs. experience goods). That is, search goods whose information search is easy and whose quality is predictable could be found that product attitude and purchase intention have a more positive effect on the form of image-centered information composition. And experience goods whose quality is unpredictable could be found that product attitude and purchase intention have a more positive effect on the form of text-centered information composition. And effects of congruence between product types based on Higgins' regulatory focus theory and the form of information composition have found to vary depending on consumers' chronic regulatory focus. Promotion focus seeking consumers showed effects of congruence between product types and the form of information composition and prevention focus seeking consumers did not show effects of congruence between them. That is, promotion focus seeking consumers have found to have more positive product attitude and purchase intention in the form of image-centered information composition of experience goods and text-centered information composition of search goods. And prevention focus seeking consumers have found to be unable to have an effect on product attitude and purchase intention even though the form of image or text-centered information composition of search and experience goods is presented. The study implies that the form of information composition should be designed, produced, and provided for consumers by considering product types and consumer propensity when designing it in the detail pages of mobile products.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.1-17
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• 2012

Personalized smart devices such as smartphones and smart pads are widely used. Unlike traditional feature phones, theses smart devices allow users to choose a variety of functions, which support not only daily experiences but also business operations. Actually, there exist a huge number of applications accessible by smart device users in online and mobile application markets. Users can choose apps that fit their own tastes and needs, which is impossible for conventional phone users. With the increase in app demand, the tastes and needs of app users are becoming more diverse. To meet these requirements, numerous apps with diverse functions are being released on the market, which leads to fierce competition. Unlike offline markets, online markets have a limitation in that purchasing decisions should be made without experiencing the items. Therefore, online customers rely more on item-related information that can be seen on the item page in which online markets commonly provide details about each item. Customers can feel confident about the quality of an item through the online information and decide whether to purchase it. The same is true of online app markets. To win the sales competition against other apps that perform similar functions, app developers need to focus on writing app descriptions to attract the attention of customers. If we can measure the effect of app descriptions on sales without regard to the app's price and quality, app descriptions that facilitate the sale of apps can be identified. This study intends to provide such a quantitative result for app developers who want to promote the sales of their apps. For this purpose, we collected app details including the descriptions written in Korean from one of the largest app markets in Korea, and then extracted keywords from the descriptions. Next, the impact of the keywords on sales performance was measured through our econometric model. Through this analysis, we were able to analyze the impact of each keyword itself, apart from that of the design or quality. The keywords, comprised of the attribute and evaluation of each app, are extracted by a morpheme analyzer. Our model with the keywords as its input variables was established to analyze their impact on sales performance. A regression analysis was conducted for each category in which apps are included. This analysis was required because we found the keywords, which are emphasized in app descriptions, different category-by-category. The analysis conducted not only for free apps but also for paid apps showed which keywords have more impact on sales performance for each type of app. In the analysis of paid apps in the education category, keywords such as 'search+easy' and 'words+abundant' showed higher effectiveness. In the same category, free apps whose keywords emphasize the quality of apps showed higher sales performance. One interesting fact is that keywords describing not only the app but also the need for the app have asignificant impact. Language learning apps, regardless of whether they are sold free or paid, showed higher sales performance by including the keywords 'foreign language study+important'. This result shows that motivation for the purchase affected sales. While item reviews are widely researched in online markets, item descriptions are not very actively studied. In the case of the mobile app markets, newly introduced apps may not have many item reviews because of the low quantity sold. In such cases, item descriptions can be regarded more important when customers make a decision about purchasing items. This study is the first trial to quantitatively analyze the relationship between an item description and its impact on sales performance. The results show that our research framework successfully provides a list of the most effective sales key terms with the estimates of their effectiveness. Although this study is performed for a specified type of item (i.e., mobile apps), our model can be applied to almost all of the items traded in online markets.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.292-304
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• 2009

This paper is to identify how merchandise quality, store environment, personnel service, sales promotion, store amenities and supporting service which is considered to store image components influence on satisfaction and loyalty and examine the role of satisfaction in explaining relationships between store image and loyalty. The results of the study are as follows: (1) each components of store image influence on cognitive satisfaction or emotionally based satisfaction or loyalty. (2) merchandise quality and store amenities have influence on cognitive satisfaction and emotionally based satisfaction is affected by personnel service and supporting service, but store environment has directly influence on loyalty. (3) store image components that is concerned with service in the store e.g. personnel service, supporting service build customer loyalty by mediating emotionally based satisfaction. In order to build strong customer loyalty, marketer have to formed through store image components that is much stronger on loyalty.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.366-381
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• 2013

This paper is to identify how variety of products, product quality, guarantees, employee services and physical environment of store which is considered to store image components influence on satisfaction and loyalty, which in turn effects on loyalty in grocery retailing stores. A survey was conducted to collect the data with consumers who had the actual purchase experience within 1 years in grocery retailing stores. Analysis of structural equation modeling with SPSS 19.0 and AMOS 16.0 were performed to test the research hypothesis. The result of the study as follows: First, product quality and employee services influence on both satisfaction and trust, but physical environment of store are effects on satisfaction only. Second, no store image components influence on loyalty. Finally, satisfaction was effect on both trust and loyalty, whereas trust was not effect on loyalty. In order to build strong customer loyalty, marketer have to strengthen the relationship quality such as satisfaction and trust, and formed through store image components that is much stronger on loyalty.

• The Journal of Society for e-Business Studies
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• v.23 no.3
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• pp.145-157
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• 2018

The social curation service that selectively provides information generated by individuals or groups with the same interests can have a synergistic effect when combined with the recently used SNS-based chatting function. If these kinds of chatting-based curation technologies are applied to the Internet shopping malls, particularly, buyers can obtain more reliable information in real time basis, and sellers can provide them with more differentiated and rich information in a continuous manner. This research suggests a chatting-based commerce platform that provides the social curation service based on chats among sellers, existing buyers, and potential buyers. The proposed commerce platform can organize a chat channel for each store and product not only to immediately respond to new and existing customer inquiries about stores, brands, and detailed products, but also to continuously activate differentiated sales strategies to customers subscribed to the channel. In particular, MongoDB is used to permanently save and archive the information and chatting history of each channel, so that the buyer can search and refer to them recorded in the corresponding channel at any time.

• Journal of Korean Society of Transportation
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• v.19 no.1
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• pp.17-28
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• 2001

The purpose of this study is to analyze logistics cost of transportation systems on EC(electronic commerce) between company and consumer. Transportation system in logistics is classified by three types on EC. The first type is the direct delivery from supply factory to consumers(type I). The second type is the delivery through distribution center in each area by owner logistics company (type II). The third type is the commission of delivery to the third party logistics company(type III). The logistics of EC has various service characteristics such as dealing with small quantity, various goods, and high frequency. This study assumes that all day's order is delivered on a next day. The logistics cost function is calculated according to the number of orders, delivery distance, transport quantify. and allocated freight trucks for daily order of the subject zone. The logistics cost changes according to the daily order characteristics. Therefore it is simulated to analyze the logistics cost change that considers the type of transportation's order characteristics. As a result of analysis, if the number of order is less than 10 and the quantify of each order is less than 10kg, type III has an advantage over the others And if the number of order is more than 10 and the quantity of each order is more than 10kg, type I has an advantage in the same zone and type II has an advantage in the other zones. This study is limited on the actual application because this study doesn't consider logistics infra of supply company and transport service time. If further study that considers these factors is implemented, it can estimate more accurate logistics cost on EC and propose an efficient freight transport alternatives to the company. This study attributes to estimate the logistics cost change over the frequency of daily order, the quantify of supply goods, and the transport distance on EC.