• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.366-377
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• 2010

As internet and mobile technology brings rapid transformation to this society of information, how relations are conducted between customers have become a critical factor influencing companies. Companies are creating Internet communities based on their brands, encouraging customers to actively form and develop brand communities. Thus, this report proposes a plan to analyze the effectiveness of community activities based on the customers active involvement and how to effectively manage and utilize it. The purpose of this research is to understand the effects on-line brand communities and their characters have on customer behavior. Also, it will study the effects community attitudes have on brand decisions and oral transmission communication when on-line brand communities choose a brand. This report was conducted to survey on-line university students to understand how communities' attitude affects the decision of on-line university brand and oral transmissions when students choose to study at a on-line university. According to research, those factors brought positive responses to character of the brand communities(confidentiality of information, interactivity, convenience, intimacy) and by doing so, on the customer's attitude side, positive results on intention of purchase and oral transmissions can be expected. In addition, the character of the brand communities affects intention of purchase and oral transmission communication. Based on this research, it is possible to propose a marketing strategy that revitalizes brand communities' activities.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.85-105
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• 2012

In recent years, IT advancement has brought out the new Internet communication environment such as online social network services, where people are connected in global network without temporal and spatial limitation. The popular use of online social network helps people share their experience and preference for specific products and services, thus holding large potential to significantly affect firms' business performance through Word-of-Mouth (WOM). This study examines the role of online social network in raising WOM effect on the movie industry by comparing with the similar role of Internet portal, another major online communication channel. Analyzing 109 movies and data from both Twitter and Naver movie, we found that significant WOM effect exists simultaneously in both Twitter and Naver movie. However, we also found that different figures of online viral effects exist depending on the popularity of movies. In the hit movie group, before the movie release, the WOM effect occurs only in Twitter while the WOM effect arises in both Twitter and Naver movie at the same time after the movie release. In the less-popular (or niche) movie group, the WOM effect occurs in both Twitter and Naver movie only before the movie release. Our findings not only deepen theoretical insights into different roles of the two online communication channels in provoking the WOM effect on entertainment products but also provide practitioners with incentive to utilize SNS as strategic marketing platform to enhance their brand reputations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.9-15
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• 2019

Large global online shopping malls, such as Amazon, offer services in English or in the language of a country when their products are sold. Since many customers purchase products based on the product reviews, the shopping malls actively utilize the sentimental analysis technique in judging preference of each product using the large amount of review data that the customer has written. And the result of such analysis can be used for the marketing to look the potential shoppers. However, it is difficult to apply this English-based semantic analysis system to different languages used around the world. In this study, more than 500,000 data from Amazon fine food reviews was used for training a deep learning based system. First, sentiment analysis evaluation experiments were carried out with three models of English test data. Secondly, the same data was translated into seven languages (Korean, Japanese, Chinese, Vietnamese, French, German and English) and then the similar experiments were done. The result suggests that although the accuracy of the sentimental analysis was 2.77% lower than the average of the seven countries (91.59%) compared to the English (94.35%), it is believed that the results of the experiment can be used for practical applications.

• Smart Media Journal
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• v.8 no.1
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• pp.74-81
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• 2019

Recently, machine learning technology has had a significant impact on society, particularly in the medical, manufacturing, marketing, finance, broadcasting, and agricultural aspects of human lives. In this paper, we study how to apply machine learning techniques to foods, which have the greatest influence on the human survival. In the field of Smart Farm, which integrates the Internet of Things (IoT) technology into agriculture, we focus on optimizing the crop growth environment by monitoring the growth environment in real time. KT Smart Farm Solution 2.0 has adopted machine learning to optimize temperature and humidity in the greenhouse. Most existing smart farm businesses mainly focus on controlling the growth environment and improving productivity. On the other hand, in this study, we are studying how to apply machine learning with respect to harvest time so that we will be able to harvest fruits of the highest quality and ship them at an excellent cost. In order to apply machine learning techniques to the field of smart farms, it is important to acquire abundant voluminous data. Therefore, to apply accurate machine learning technology, it is necessary to continuously collect large data. Therefore, the color, value, internal temperature, and moisture of greenhouse-grown fruits are collected and secured in real time using color, weight, and temperature/humidity sensors. The proposed FPSML provides an architecture that can be used repeatedly for a similar fruit crop. It allows for a more accurate harvest time as massive data is accumulated continuously.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.71-86
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• 2023

The purpose of this exploratory study is to compare the differences in public perceptual characteristics of Korean and Chinese societies regarding the metaverse using big data analysis. Due to the environmental impact of the COVID-19 pandemic, technological progress, and the expansion of new consumer bases such as generation Z and Alpha, the world's interest in the metaverse is drawing attention, and related academic studies have been also in full swing from 2021. In particular, Korea and China have emerged as major leading countries in the metaverse industry. It is a timely research question to discover the difference in social awareness using big data accumulated in both countries at a time when the amount of mentions on the metaverse has skyrocketed. The analysis technique identifies the importance of key words by analyzing word frequency, N-gram, and TF-IDF of clean data through text mining analysis, and analyzes the density and centrality of semantic networks to determine the strength of connection between words and their semantic relevance. Python 3.9 Anaconda data science platform 3 and Textom 6 versions were used, and UCINET 6.759 analysis and visualization were performed for semantic network analysis and structural CONCOR analysis. As a result, four blocks, each of which are similar word groups, were driven. These blocks represent different perspectives that reflect the types of social perceptions of the metaverse in both countries. Studies on the metaverse are increasing, but studies on comparative research approaches between countries from a cross-cultural aspect have not yet been conducted. At this point, as a preceding study, this study will be able to provide theoretical grounds and meaningful insights to future studies.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.61-69
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• 2023

In recent years, due to heightened environmental awareness, Electric Power Steering (EPS) has been increasingly adopted as the steering control unit in manufactured vehicles. This has had numerous benefits, such as improved steering power, elimination of hydraulic hose leaks and reduced fuel consumption. However, for EPS systems to respond to actions, sensors must be employed; this means that the consistency of the sensor's linear variation is integral to the stability of the steering response. To ensure quality control, a reliable method for detecting defects and assessing linearity is required to assess the sensitivity of the EPS sensor to changes in the internal design characters. This paper proposes a data-driven defect and linearity assessment monitoring system, which can be used to analyze EPS component defects and linearity based on vehicle speed interval division. The approach is validated experimentally using data collected from an EPS test jig and is further enhanced by the inclusion of a Graphical User Interface (GUI). Based on the design, the developed system effectively performs defect detection with an accuracy of 0.99 percent and obtains a linearity assessment score at varying vehicle speeds.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.159-166
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• 2023

This study analyzed what consumer characteristics affect the experience of using overseas direct purchase at a time when the overseas direct purchase market is rapidly increasing and consumers' interest in overseas direct purchase is increasing accordingly. For the study, personal data from the 2022 Korea Media Panel Survey were used, and data from 6,734 people who responded "yes" or "no" to whether or not to use overseas direct purchase among 9,941 total respondents were used for analysis. In addition, three variables (demographic, media utilization status, values and lifestyle) were selected among the items of the Korea Media Panel Survey. First, general characteristics were analyzed fo 6,734 people, then, Chi-square test and t-test were performed for comparative analysis between each variable according to the use of overseas direct purchase. Finally, logistic regression analysis was performed to identify the factors affecting overseas direct purchase. As a result of the analysis, 4 out of 5 demographic variables, 2 out of 3 media utilization variables, and 3 out of 7 values and lifestyle variables were derived as decisive factors for using overseas direct purchase. These results can be used to establish marketing strategies that can increase the use of consumers through domestic shopping malls, such as providing differentiated services for the sale of overseas direct shopping products on domestic shopping sites.

• Information Systems Review
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• v.23 no.3
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• pp.177-200
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• 2021

Recently, the use of prepaid electronic payments such as electronic wallets, digital currency and prepaid points is gradually increasing. Prepaid electronic payments has the characteristic of being used after charging first. This study empirically investigated the factors affecting the intention to use online charging in order to help improve the service that require prepaid recharge by applying transformed TAM. Since there are not many previous studies for the intention to use online charging, we extract factors through preceding researches for electronic cash and mobile easy payment. Also we analyze the intention to use online charging for transportation card users, focusing on the moderating effects. As a result of the study, it was found that 'convenience', 'ubiquity', and 'self-efficacy' among the independent variables had a positive (+) effect on mediation variable 'perceived usefulness'. 'Perceived usefulness' was analyzed to have a significant influence on the dependent variable 'usage intention'. According to users' gender, internet usage time, internet shopping frequency, online charging frequency and transportation card usage type, the moderating effect was significant on 'perceived usefulness' and 'usage intention'. As an implication, it was suggested that service improvement and differentiated marketing are needed in direction of increasing the usefulness of services. Additional research directions were proposed for services such as e-wallets, prepaid points and digital currencies by adding other factors and moderate variables.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.2
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• pp.589-600
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• 2015

The purpose of this study was to verify the analysis of differences between importance and satisfaction of destination attractiveness for the national marine sports games using IPA method. By doing so, this study aimed to utilize the result of study for a practical marketing strategy in operating and establishing Korean marine sports market circumstances. The participants of this study consisted of 328 who were participated in marine sport event (yacht, fin-swimming, canoe, triathlon and so on) of 9th national marine sports games. Samples were extracted by convenient sampling method. A total 328 questionnaires were collected in this study except data which did not respond or trustless responded. In data processing, Cronbach's ${\alpha}$, frequency analysis, paired t-test and Importance-Performance Analysis were performed through SPSS 20.0. The results were as follows. First, I quadrant included Programs Multiplicity, Pamphlet, Stand preparations, Food Cleanliness, Effective Progress, Guide Know-How, Food taste. Third, II quadrant included Pre-Publicity, Internet Information, Proper Food Price, Shade Facilities, Convenient Parking, Restroom Cleanliness, Number of Restroom, Safety Facilities. Fourth, III quadrant included Entertaining Program, Number of Guide, Local Culture, Game Progress, Directional Sign. Fifth, IV quadrant included Performance Program, Well-Matched Event, View Distance, Various Food.

• Korean Business Review
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• v.20 no.2
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• pp.105-118
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• 2007

Recommender system is the tool for E-commerce company based on the internet for increasing their sales ratio in the market. Recommender system suggests the list of items which night be wanted by customers. This list generated by the result of customers' preference prediction through the prediction algorithm automatically. Recommender system will be able to offer not only the important information for marketing strategy but also reduce the cost of customers' information retrieval trough the analysis of customers' purchase patterns and features. But there are several problems like as the extension of the users and items scales and if the recommendation to customers generated by unreliable recommender system makes the customer royalty to the system to weaken. In this study, we propose the criterion for pre-evaluation on the prediction performance only using the preference ratings on the items which are rated by customers before prediction process and we study the features of customers who are classified through this classification criterion.