• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.3
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• pp.175-187
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• 2011

People could be effected by other's recommendations when they are in making decision to buy something. This phenomenon was called as 'word of mouth effect' and proved to be very significant to change consumer's attitude because of a lack of information about products or services what they needed. And also there are two kinds of views about Brand communication. One is that Brand communication would be weakening due to less cost to search information. the other is that Brand communication would be strengthen because of a lack of sensibility to product. Therefore, the purpose of this study is to examine the function of online word of month and the effect of brand communication by adopting a concept of BRQ. As The results, First, Online word of mouth have significantly effected on consumer's attitude even though those information are all texts and have been suspicious if it is true or not. Second, consumer brand relationship quality have a influence on consumer's attitude. In conclusion, This study would give implications for companies to build marketing strategies.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.2
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• pp.107-115
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• 2018

US Retailers consider two major holiday shopping days as their most profitable-the Friday after Thanksgiving, Black Friday, and the Monday after Thanksgiving, CyberMonday. Online shopping discount events have boosted up the shopping markets resulting in pumping up National economy. For such reasons, Korea also has launched online shopping discount event, which is called 'Cyber hot days'. The primary purpose of this paper is to understand consumer behavior on Cyber hot days and suggest how retailers can harness those consumer behaviors and how government agency can support both retailers and consumers to boost up shopping markets. The results of empirical test shows that economic value, emotional value, and product variety were found to be significantly related to consumers' attitude on Cyber hot days, but convenience value, social value, and product uniqueness were not. Consumers' attitude was also found to be significantly related to the repurchase intention. It implicates that price, enjoyment, and product variety are important aspects to Korean consumers when they purchase during online shopping discount event.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.345-346
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• 2023

본 연구는 한국 거주 외국인을 대상으로 한국 의류의 착용실태 및 착용 시 불편사항, 선호도 등을 알아보고자 하였다. 이를 통해 그 수요가 증가하고 있는 외국인 소비자를 흡수할 수 있는 의류개발에 필요한 기초자료를 얻고자 하였다. 본 연구는 설문지법으로 진행되었으며, 분석에는 SPSS 26.0 프로그램을 사용하였다. 의류 구매장소는 온라인 쇼핑이 가장 많았고, 구매 아이템은 티셔츠, 재킷이 많았다. 가격대는 3만원에서 5만원 사이가 가장 많았다. 구매 이유는 심미적 요인이 높았다. 한국 의류는 어깨부위, 다리길이가 가장 불편하였고, 바지가 가장 맞지 않는 것으로 나타났다. 선호스타일은 캐주얼과 모던 스타일이 많았고, 심플하고 편안한 이미지의 의복을 선호하며, 천연소재를 선호하였다. 조금 여유있는 실루엣의 의복을 선호하고 재킷, 티셔츠 등의 아이템을 선호하였다. 향후 국적, 체형 등에 따른 착의실태 및 선호도에 대한 연구가 진행되어야 할 것으로 생각된다.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.321-331
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• 2020

The purpose of this study is to explore the impact of home stay platform on guests' willingness to comment online under the Shared home stay business model. Shared platform of home stay facility in addition to providing a variety of support services, help the landlord to the tenant do offline accommodation services, implementation, trading, will need to take some measures to actively promote the tenant groups to the landlord, the evaluation is objective, effective and sufficient number in order to better promote the sharing credit ecological establishment of home stay facility. In this study, consumers who have used the Shared home stay platform are taken as the research objects. The survey method adopts network questionnaire survey and Likert seven subscales. The statistical software SPSS24.0 program is used to process the data. Firstly, descriptive statistical analysis was conducted, followed by validity analysis and reliability analysis. After the reliability and validity of the questionnaire were determined, correlation analysis and regression analysis were used to verify the proposed hypothesis. The research results of this study are summarized as follows :(1) the usability of platform comment function, guest satisfaction and platform reward have a positive impact on the guest online comment willingness; (2) The credit mechanism of the platform has a positive regulating effect on the process of tenant satisfaction influencing tenant comment intention.

• Management & Information Systems Review
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• v.38 no.4
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• pp.41-60
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• 2019

The purpose of this study is to investigate the effect of salesperson's adaptive selling tactics on consumers who purchase Small and Medium Enterprises' product with the help of salespeople in the store. Specifically, we examine whether salesperson's adaptive selling tactics affect consumers hedonic shopping value and utilitarian shopping value. Furthermore, we try to figure out the effect of shopping value on the salesperson relationship commitment and consumer product satisfaction. The subjects of this study have surveyed the consumers with experience in purchasing SME's products through salespeople in the Gyeongnam area. As data process, SPSS 21.0 was used as the analysis tool and AMOS 21.0 was used to analyze the structural equation model. The implications of these findings are as follows. First, the salesperson's role has a positive effect on the consumer's product satisfaction. Second, it can be suggested that the salesperson's adaptive selling tactics are an important variable affecting the consumer's shopping value. Third, the results on the consumers who have hedonic shopping value have a strong positive influence rather than the consumers who have the utilitarian shopping value. The adaptive selling tactics of the salesperson should be encouraged to increase sales performance. In order to generate more performance in a competitive market environment, it is necessary to continuously strive to increase contact between the salesperson and the consumer in order to improve the quality of the relationship.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.217-233
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• 2011

In this study, we have examined how the potential users of IT convergence product use the external information sources for purchasing decision focusing on a case of smartphone. Although the specifications and price of IT convergence products, such as smartphone, tablet pc, and smart TV, are considered as major criteria for purchasing decision, the competitiveness of these factors have disappeared as many companies launch similar products in the market. External information sources play a significant role to differentiate the alternatives by offering value-added experience information. The effect of external information sources becomes stronger for experience and high-involvement product whose performance can be evaluated through only users' direct experience. In this study, we categorized the external information sources for smartphone into five; company ads, personal network, expert group, consumers, and media. Through an empirical study with potential smartphone users, we verified how these external information sources affect users' purchasing decision in the perspective of the perceived attributes of information source, quality of information, and individual's characteristics based on self-regulatory theory.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.259-271
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• 2010

It is inevitable that personal privacy will be one of the most significant pressure points for most of the 2000s. Information privacy has been called one of the most important ethical issues in information age. It has become apparent that organizational practices, individuals' perceptions of these practices, and societal responses are very closely related in many ways. However, unfortunately, researches attempting to develop and validate an instrument that identifies and measures the primary dimensions of individuals' concerns about organizational information privacy practices were scarce. Based on a number of preliminary studies, this study tried to develop and validate an Korean organization oriented measurement instrument. This instrument is expected to be used as useful guide lines for the managers who are responsible for IT/IS ethical issues.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6133-6145
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• 2013

With the increasing number of online wine stores, customers are increasingly seeking to purchase wine online. On the other hand, purchasing wine online is prohibited by law or regulation in Korea. Therefore, customers mainly search for wine information, inquire about wine products, and make a pre-purchase at an online wine store. Online wine stores play important roles in customer's purchase decision-making, and are likely to be a useful wine distribution channel in the near future. Therefore, the aim of this study was to identify the determinants of the online wine purchase intention, and examine the structural relationships between the determinants and online wine purchase intention. The site quality of online wine stores (information quality, system quality, service quality), and perceived value (quality value, price value, emotional value, social value) were selected as the determinants of online wine purchase intention based on literature review. The data was collected from those who had experience using an online wine store to purchase wine, and the data was used to test the proposed research model. The findings showed that the information quality was not related to the perceived value (quality value, price value, emotional value, social value). The system quality was proven to be positively and significantly related to the quality value, price value, and emotional value, whereas it had no impact on the social value. In addition, the service quality was found to affect the perceived value (quality value, price value, emotional and social value). Finally, the results showed that the quality value, emotional value, and social value have a positive impact on the online wine purchase intention, whereas the price quality is not related to the online wine purchase intention. These results are expected to make a contribution to a better understanding of how the quality of online wine stores and the customer's perceived value affect the online wine purchasing intention.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1689-1697
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• 2018

This paper explored how to design amobile application for Korea's traditional markets based on O2O service and data science technologies. In order to cover a broader scope of customers, diversify the ways to sell products, and increase the profits of Korea's traditional markets, the application bridges online customers with offline stores at traditional markets and augments both convenience and accessibility. Beyond the typical face-to-face interactions between customers and sellers at traditional markets, this application offers mobile payments and personalized recommendations of nearby stores and preferable products using Beacon and datascience technologies. Moreover, it offers multi-language support for foreign customers who are not familiar with Korea's traditional markets and the products sold there. In conclusion, using O2O service, which is a rising trend among prevalent platform technologies, this study proposed a new e-commerce model for Korea's traditional markets to promote market expansion.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.