• Journal of Internet Computing and Services
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• v.15 no.2
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• pp.59-71
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• 2014

This study applied customer perspective to find out ways how to protect customers' privacy by themselves. It does so by examining the factors which affect customer privacy protection behaviors. Based on the Privacy Act, this study developed the construct of Privacy Rights awareness and finds the law's effect on privacy awareness and behavioral change. The study finds that there exists a significant difference in privacy protection behavior according to privacy rights awareness. Independent variables are as follows: Five variables (Perceived vulnerability, Perceived severity, Perceived response effectiveness, Perceived barriers, Privacy Rights awareness) were tested as critical variables influencing Behavioral Intention in PMT model. Privacy awareness had a moderating effect on the relationship between perceived severity and privacy protection behavior. This study would contribute on theoretical expansion of Protection Motivation Theory and also provide practical implications for effective ways to promote behavioral changes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.1-6
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• 2019

This study visualized users reaction about movies based on keywords with high frequency. For this work, we collected data of movie reviews on . A total of six movies were selected, and we conducted the work of data gathering and preprocessing. Semantic network analysis was used to understand the relationship among keywords. Also, NetDraw, packaged with UCINET, was used for data visualization. In this study, we identified the differences in characteristics of review contents regarding each movie. The implication of this study is that we visualized movie reviews made by sentence as keywords and explored whether it is possible to construct the interface to check users' reaction at a glance. We suggest that further studies use more diverse movie reviews, and the number of reviews for each movie is used in similar quantities for research.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.426-442
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• 2019

This study identifies possible determinants that may have influences on the switching behavior from the current payment system of credit or check cards to the easy payment service based on push-pulling-mooring model. And this research empirically tests how those determinants affect switching intention to the easy payment service. The moderating effect of policy expectation is also taken into account. The findings show switching intention to the easy payment service is influenced by the followings: dissatisfaction with the current payment system as a pushing factor, perceived easy of use and trust in easy payment service as pulling factors, and affective/cognitive inertia and unfavorable subjective norm as mooring factors. The results also show that moderating effect of policy expectation exists in the relationship between perceived ubiquitousness and switching intention.

• Journal of Nutrition and Health
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• v.54 no.1
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• pp.67-75
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• 2021

Purpose: The theory of planned behavior (TPB) was used to investigate how the psychological constructs of attitude, subjective norms, and perceived behavioral control (PBC) affect the individual intention of behaviors in adults. Social support is also important in enabling the stability of healthy eating. This study examined the relationship between three major constructs of TPB as well as social support and the intention of healthy dietary behaviors in adults residing in Beijing, China using the extended TPB. Methods: The study questionnaire was based on previously validated items and an online survey was conducted from October to November 2020. Using a total of 244 Chinese adults in Beijing, multiple linear regression analysis was used to test the relationships between three major constructs of TPB as well as the social support and intention of healthy eating. Results: Among the three major constructs of TPB, subjective norms (p = 0.044) and PBC (p = 0.000) were significantly related to the behavioral intention of healthy eating (p = 0.000), and the model explained 76.6% of the variance of the behavioral intention from the three constructs of TPB included in the multiple linear regression model. The additional inclusion of social support to the model did not increase the explanatory power of the model to describe the behavioral intention of healthy eating. The subjective norms (p = 0.040) and PBC (p = 0.000) were still significant where social support did not explain the variance of the behavioral intention adequately. Conclusion: The subjective norms and PBC may be potential determinants of the behavioral intention of healthy eating in adults residing in Beijing, China. These study results can be used to promote healthy eating in Chinese adults living in urban areas. Large-scale intervention studies will be needed to determine if social norms and PBC predict the actual behaviors of healthy eating in Chinese adults.

• Journal of The Korean Association of Information Education
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• v.26 no.6
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• pp.533-541
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• 2022

Metaverse have begun to attract attention because it facilitate interaction between learners and teachers in non face- to- face environment. In order to use the metaverse in the educational field such as online class, it is important that pre-service teachers intend to use it. The purpose of this study is to analyze the structural relationship between the pre-service teacher's educational competence and the intention to use the metaverse based on the technology acceptance model. The influence factors of flexibility for new technology, teacher efficacy, and TPACK were examined. It was conducted with 240 pre-service teachers, and the data of 183 pre-service teachers finally collected were used for the analysis. As a result of the study, among the metaverse educational competencies of elementary school pre-service teachers, flexibility and TPACK mediate perceived ease, and the pathways affecting metaverse use intention were significant. In this regard, theoretical and practical implications that can be helpful in the discussion and intention of using the metaverse of pre-service teachers were presented.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.57-79
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• 2016

It is a rising trend that the number of users using one of the social media channels, the Social Network Service, so called the SNS, is getting increased. As per to this social trend, more companies have interest in this networking platform and start to invest their funds in it. It has received much attention as a tool spreading and expanding the message that a company wants to deliver to its customers and has been recognized as an important channel in terms of the relationship marketing with them. The environment of media that is radically changing these days makes possible for companies to approach their customers in various ways. Particularly, the social network service, which has been developed rapidly, provides the environment that customers can freely talk about products. For companies, it also works as a channel that gives customized information to customers. To succeed in the online environment, companies need to not only build the relationship between companies and customers but focus on the relationship between customers as well. In response to the online environment with the continuous development of technology, companies have tirelessly made the novel marketing strategy. Especially, as the one-to-one marketing to customers become available, it is more important for companies to maintain the relationship marketing with their customers. Among many SNS, Facebook, which many companies use as a communication channel, provides a fan page service for each company that supports its business. Facebook fan page is the platform that the event, information and announcement can be shared with customers using texts, videos, and pictures. Companies open their own fan pages in order to inform their companies and businesses. Such page functions as the websites of companies and has a characteristic of their brand communities such as blogs as well. As Facebook has become the major communication medium with customers, companies recognize its importance as the effective marketing channel, but they still need to investigate their business performances by using Facebook. Although there are infinite potentials in Facebook fan page that even has a function as a community between users, which other platforms do not, it is incomplete to regard companies' Facebook fan pages as communities and analyze them. In this study, it explores the relationship among customers through the network of the Facebook fan page users. The previous studies on a company's Facebook fan page were focused on finding out the effective operational direction by analyzing the use state of the company. However, in this study, it draws out the structural variable of the network, which customer committment can be measured by applying the social network analysis methodology and investigates the influence of the structural characteristics of network on the business performance of companies in an empirical way. Through each company's Facebook fan page, the network of users who engaged in the communication with each company is exploited and it is the one-mode undirected binary network that respectively regards users and the relationship of them in terms of their marketing activities as the node and link. In this network, it draws out the structural variable of network that can explain the customer commitment, who pressed "like," made comments and shared the Facebook marketing message, of each company by calculating density, global clustering coefficient, mean geodesic distance, diameter. By exploiting companies' historical performance such as net income and Tobin's Q indicator as the result variables, this study investigates influence on companies' business performances. For this purpose, it collects the network data on the subjects of 54 companies among KOSPI-listed companies, which have posted more than 100 articles on their Facebook fan pages during the data collection period. Then it draws out the network indicator of each company. The indicator related to companies' performances is calculated, based on the posted value on DART website of the Financial Supervisory Service. From the academic perspective, this study suggests a new approach through the social network analysis methodology to researchers who attempt to study the business-purpose utilization of the social media channel. From the practical perspective, this study proposes the more substantive marketing performance measurements to companies performing marketing activities through the social media and it is expected that it will bring a foundation of establishing smart business strategies by using the network indicators.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.43-61
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• 2016

Customer reviews help potential customers make purchasing decisions. However, the prevalence of reviews on websites push the customer to sift through them and change the focus from a mere search to identifying which of the available reviews are valuable and useful for the purchasing decision at hand. To identify useful reviews, websites have developed different mechanisms to give customers options when evaluating existing reviews. Websites allow users to rate the usefulness of a customer review as helpful or not. Amazon.com uses a ratio-type helpfulness, while Yelp.com uses a count-type usefulness index. This usefulness index provides helpful reviews to future potential purchasers. This study investigated the effects of sentiment and readability on useful votes for customer reviews. Similar studies on the relationship between sentiment and readability have focused on the ratio-type usefulness index utilized by websites such as Amazon.com. In this study, Yelp.com's count-type usefulness index for restaurant reviews was used to investigate the relationship between sentiment/readability and usefulness votes. Yelp.com's online customer reviews for stores in the beverage and food categories were used for the analysis. In total, 170,294 reviews containing information on a store's reputation and popularity were used. The control variables were the review length, store reputation, and popularity; the independent variables were the sentiment and readability, while the dependent variable was the number of helpful votes. The review rating is the moderating variable for the review sentiment and readability. The length is the number of characters in a review. The popularity is the number of reviews for a store, and the reputation is the general average rating of all reviews for a store. The readability of a review was calculated with the Coleman-Liau index. The sentiment is a positivity score for the review as calculated by SentiWordNet. The review rating is a preference score selected from 1 to 5 (stars) by the review author. The dependent variable (i.e., usefulness votes) used in this study is a count variable. Therefore, the Poisson regression model, which is commonly used to account for the discrete and nonnegative nature of count data, was applied in the analyses. The increase in helpful votes was assumed to follow a Poisson distribution. Because the Poisson model assumes an equal mean and variance and the data were over-dispersed, a negative binomial distribution model that allows for over-dispersion of the count variable was used for the estimation. Zero-inflated negative binomial regression was used to model count variables with excessive zeros and over-dispersed count outcome variables. With this model, the excess zeros were assumed to be generated through a separate process from the count values and therefore should be modeled as independently as possible. The results showed that positive sentiment had a negative effect on gaining useful votes for positive reviews but no significant effect on negative reviews. Poor readability had a negative effect on gaining useful votes and was not moderated by the review star ratings. These findings yield considerable managerial implications. The results are helpful for online websites when analyzing their review guidelines and identifying useful reviews for their business. Based on this study, positive reviews are not necessarily helpful; therefore, restaurants should consider which type of positive review is helpful for their business. Second, this study is beneficial for businesses and website designers in creating review mechanisms to know which type of reviews to highlight on their websites and which type of reviews can be beneficial to the business. Moreover, this study highlights the review systems employed by websites to allow their customers to post rating reviews.

• The Journal of the Korea Contents Association
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• v.12 no.10
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• pp.453-465
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• 2012

The major purpose of this study is to examine the effects of customers' perceptions toward service quality of mobile music service on customer loyalty and switching intention. For this purpose, this study posited three service quality characteristics including interface, service, price quality as key determinants of customer loyalty and switching intention based on relevant literature reviews. A research model and hypotheses concerning the relationship between these variables were constructed. Moreover, this study explored the moderating effects of attractiveness of alternative and switching costs on the relationship between customer loyalty and switching intention. An online survey was administrated on 433 mobile music service users and a simple, multiple, and hierarchical regression analysis were employed. The results indicated that all of interface, service, price quality have significant positive influences on customer loyalty, and both of service quality and attractiveness of alternatives have influences on the switching intention in a positive way. On the other way, it was shown that switching costs have a negative influence on the switching intention. The moderating effect of attractiveness of alternatives on the relationship between customer loyalty and switching intention was also found. The implications of these results are discussed.

• Information Systems Review
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• v.10 no.2
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• pp.137-158
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• 2008

Rapid development of various information technologies creates new opportunities in online and offline markets. In this changing market environment, customers have various demands on new products and services. Therefore, their power and influence on the markets grow stronger each year. Companies have paid great attention to customer relationship management. Especially, personalized product recommendation systems, which recommend products and services based on customer's private information or purchasing behaviors in stores, is an important asset to most companies. CRM is one of the important business processes where reliable information is mined from customer database. Data mining techniques such as artificial intelligence are popular tools used to extract useful information and knowledge from these customer databases. In this research, we propose a recommendation system that predicts customer's purchase intention. Then, customer's purchasing intention of specific product is predicted by using data mining techniques using receipt data set. The performance of this suggested method is compared with that of other data mining technologies.