• The Korean Journal of Franchise Management
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• v.10 no.1
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• pp.43-52
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• 2019

Purpose - Many companies use the Internet to conduct their business to maintain and acquire their customers. SNS is used as a site where users can create profiles, build personal networks, and then share and exchange information with others. Not only do people use SNS for their self-promotion, but they also promote their services by creating SNS pages. SNS is recognized as a medium for implementing effective advertising strategies and is being used as an important means of promoting the company. Therefore, in this study, we investigate the effect of SNS marketing characteristics of restaurant franchise firms on utilitarian value and hedonic value and examine their effects on purchase intention. Research design, data, and methodology - The data were collected from 20s-60s respondents who have used SNS for restaurant visit using Google survey. A total of 159 responses were collected and used for final analysis. Smart PLS 3.0 was used for the hypothesis test. Results - As a result of an analysis, it was shown that the influence of the playfulness and affordability of information on the utilitarian value had a significant positive effect. Interaction and up-to-date did not have a positive effect on utilitarian value. Interaction, affordability, and up-to-date have no significant positive effects on hedonic value. The playfulness of information has a positive effect on the hedonic value. Both utilitarian value and hedonic value had positive effects on purchase intention. Conclusions - The findings of this study suggest that the SNS marketers of restaurant franchisors should focus on the playfulness, affordability, and up-to-date rather than the interactivity of SNS. In marketing through SNS, the act of presenting the basis of information and enhancing the provision of information through objective criteria makes it possible to experience the practical value of information. It is necessary to develop differentiated contents which cause customers interest and fun and to induce many customers' purchase intent by providing objective and realistic information. In order to increase the customers' repurchase intentions toward the food service business, customers should maximize the hedonic value and practical value felt through information. It should also focus on providing information that customers are receptive to, rather than providing prompt information.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.343-348
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• 2022

This study aims to analyze the user experience of unmanned checkout counters perceived by consumers using SNS big data. For this study, blogs, news, intellectuals, cafes, intellectuals (tips), and web documents were analyzed on Naver and Daum, and 'unmanned checkpoints' were used as keywords for data search. The data analysis period was selected as two years from January 1, 2020 to December 31, 2021. For data collection and analysis, frequency and matrix data were extracted through Textom, and network analysis and visualization analysis were conducted using the NetDraw function of the UCINET 6 program. As a result, the perception of the checkout counter was clustered into accessibility, usability, continuous use intention, and others according to the definition of consumers' experience factors. From a supplier's point of view, if unmanned checkpoints spread indiscriminately to solve the problem of raising the minimum wage and shortening working hours, a bigger employment problem will arise from a social point of view. In addition, institutionalization is needed to supply easy and convenient unmanned checkout counters for the elderly and younger generations, children, and foreigners who are not familiar with unmanned calculation.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.199-219
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• 2018

With the everyday use of the Internet and the spread of various smart devices, users have been able to communicate in real time and the existing communication style has changed. Due to the change of the information subject by the Internet, data became more massive and caused the very large information called big data. These Big Data are seen as a new opportunity to understand social issues. In particular, text mining explores patterns using unstructured text data to find meaningful information. Since text data exists in various places such as newspaper, book, and web, the amount of data is very diverse and large, so it is suitable for understanding social reality. In recent years, there has been an increasing number of attempts to analyze texts from web such as SNS and blogs where the public can communicate freely. It is recognized as a useful method to grasp public opinion immediately so it can be used for political, social and cultural issue research. Text mining has received much attention in order to investigate the public's reputation for candidates, and to predict the voting rate instead of the polling. This is because many people question the credibility of the survey. Also, People tend to refuse or reveal their real intention when they are asked to respond to the poll. This study collected comments from the largest Internet portal site in Korea and conducted research on the 19th Korean presidential election in 2017. We collected 226,447 comments from April 29, 2017 to May 7, 2017, which includes the prohibition period of public opinion polls just prior to the presidential election day. We analyzed frequencies, associative emotional words, topic emotions, and candidate voting rates. By frequency analysis, we identified the words that are the most important issues per day. Particularly, according to the result of the presidential debate, it was seen that the candidate who became an issue was located at the top of the frequency analysis. By the analysis of associative emotional words, we were able to identify issues most relevant to each candidate. The topic emotion analysis was used to identify each candidate's topic and to express the emotions of the public on the topics. Finally, we estimated the voting rate by combining the volume of comments and sentiment score. By doing above, we explored the issues for each candidate and predicted the voting rate. The analysis showed that news comments is an effective tool for tracking the issue of presidential candidates and for predicting the voting rate. Particularly, this study showed issues per day and quantitative index for sentiment. Also it predicted voting rate for each candidate and precisely matched the ranking of the top five candidates. Each candidate will be able to objectively grasp public opinion and reflect it to the election strategy. Candidates can use positive issues more actively on election strategies, and try to correct negative issues. Particularly, candidates should be aware that they can get severe damage to their reputation if they face a moral problem. Voters can objectively look at issues and public opinion about each candidate and make more informed decisions when voting. If they refer to the results of this study before voting, they will be able to see the opinions of the public from the Big Data, and vote for a candidate with a more objective perspective. If the candidates have a campaign with reference to Big Data Analysis, the public will be more active on the web, recognizing that their wants are being reflected. The way of expressing their political views can be done in various web places. This can contribute to the act of political participation by the people.

• The Journal of Information Systems
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• v.23 no.1
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• pp.225-246
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• 2014

With the recent establishment of a ubiquitous environment and the paradigm shift to a smart society, the use of mobile devices, such as smart phones and tablet PCs, has become widespread. Thus, the trend is gradually shifting from using Web-based Instant Messenger to using Mobile-based Instant Messenger. Mobile Instant Messenger refers to a service that allows instant messaging as well as data sending and receiving between individuals with exclusive application programs(mobile Apps), which can be used in portable devices-such as smart phones-with wireless Internet access. Korea's portal sites, telecommunication companies, and even big companies have all rushed into the MIM market to join the competition. The reason so many companies are showing interest in the MIM business is because it is rising as a core platform to substitute portal sites in the mobile society, and MIM is perceived as the best means to attract and secure users. The intention to reuse or use continually was considered an important factor in maintaining a dominant position amidst such fierce competition, and consequently, most research thus far has reflected such thought. However, the frequent or long-term use of a system alone cannot indicate the definite success of the system, nor guarantee its dominant position in the market. On the contrary, MIM dependence, which goes beyond simple repetitive use and indicates a state where users actually or emotionally depend on a specific system, can better explain the user action. However, not much research has been conducted on dependence. The research results showed that lively message, concise message, message responsiveness, and social belonging significantly affected perceived usefulness. Message responsiveness, Link, and social belonging significantly affected flow. Flow significantly affected MIM dependence, and perceived usefulness did not affect MIM dependence. This study has proven that lively message, concise message, message responsiveness, Link, social belonging and perceived usefulness are important antecedents and mediating factors of MIM dependence. Moreover, this study is significant in that it explains the overall process of MIM dependence, and expands on the variety and scope of research that can be applied to MIM-related studies.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.349-353
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• 2021

This study is a review study attempted to analyze the current situation of surgical robots based on previous research on surgical robots in the era of the 4th revolution, and to forecast the future direction of surgical robots. Surgical robots have made full progress since the launch of the da Vinci and the surgical robot is playing a role of supporting the surgeries of the surgeons or the master-slave method reflecting the intention of the surgeons. Recently, technologies are being developed to combine artificial intelligence and big data with surgical robots, and to commercialize a universal platform rather than a platform dedicated to surgery. Moreover, technologies for automating surgical robots are being developed by generating 3D image data based on diagnostic image data, providing real-time images, and integrating image data into one system. For the development of surgical robots, cooperation with clinicians and engineers, safety management of surgical robot, and institutional support for the use of surgical robots will be required.

• Management & Information Systems Review
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• v.37 no.1
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• pp.139-154
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• 2018

R programming is free and open source system associated with a rich and ever-growing set of libraries of functions developed and submitted by independent end-users. It is recognized as a popular tool for handling big data sets and analyzing them. Reflecting these characteristics, R has been gaining popularity from data analysts. However, the antecedents of R technology acceptance has not been studied yet. In this study we identify and investigates cognitive factors contributing to build user acceptance toward R in education environment. We extend the existing technology acceptance model by incorporating social norms and software capability. It was found that the factors of subjective norm, perceived usefulness, ease of use affect positively on the intention of acceptance R programming. In addition, perceived usefulness is related to subjective norms, perceived ease of use, and software capability. The main difference of this research from the previous ones is that the target system is not a stand-alone. In addition, the system is not static in the sense that the system is not a final version. Instead, R system is evolving and open source system. We applied the Technology Acceptance Model (TAM) to the target system which is a platform where diverse applications such as statistical, big data analyses, and visual rendering can be performed. The model presented in this work can be useful for both colleges that plan to invest in new statistical software and for companies that need to pursue future installations of new technologies. In addition, we identified a modified version of the TAM model which is extended by the constructs such as subjective norm and software capability to the original TAM model. However one of the weak aspects that might inhibit the reliability and validity of the model is that small number of sample size.

• Journal of Distribution Science
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• v.12 no.8
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• pp.17-29
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• 2014

Purpose - The use of corporate social activities to implement the concept of corporate social responsibility enhances brand equity and attitude, and strengthens economic competitiveness. In areas such as mobile communications, companies take the responsibility of protecting customers and enhance the quality of the mobile communication service, helping to make an effort to obey the regulations of the public trade order and fair trade agreement, enabling a healthy society through communication with elderly living alone or youths without parents, and enhancing marketing strategies. Research design, data, and methodology - To test the hypothesis, a survey was conducted. The surveyed population includes people who use the big three mobile communication services. The survey was conducted from October 4th to October 14th, 2013. A total of 500 survey questionnaires were circulated and 483 were collected; out of these, 32 were excluded due to missing or incomprehensible information. The data was analyzed with SPSS 18.0 via frequency analysis, trust analysis, search factor analysis, relationship analysis, confirmation factor analysis using AMOS 18.0, and structural equation model analysis. Results - Research on corporate social responsibility has been frequently conducted recently. Companies are perceived as social constituents satisfying the social desires of people in addition to customer needs. Further, companies are returning profits to society to satisfy community needs, because there is greater emphasis on the social responsibilities of companies. Companies' social responsibilities should include marketing strategies and the identification of customer needs. This study shows that social service activities influence brand value, which influences customer attitudes; therefore, social service activities indirectly influence customer attitudes. In order to increase customers' purchasing intention, it is essential to improve brand image via social services and provide a distinctive quality of service. Conclusions - This research has used the purposive selection method in the empirical analysis to identify the effect of social services on brand value and customer attitude. Therefore, this study revealed that businesses, whose ultimate objective is to improve customers' purchasing intention, should promote their brand equity through corporate social responsibility activities and offer a distinct service quality. Limitations in the progress of research were found and future indications to overcome these limitations are suggested as follows. First, survey responders had a limited understanding of social responsibilities; therefore, this concept needs to be explained to people first. Second, the research was done on people who live in Daejeon; thus, it is not representative of the entire country. The research has to be repeated with people in other cities. Third, there is a limitation in the study because the purposive selection method was used on Daejeon customers. In the future, a more precise selection of the population is needed. Fourth, Daejeon has unique geographical and size characteristics. Thus, customers in Seoul and other areas may display different characteristics and research on them may reveal different findings. Therefore, again, this study has to be repeated in other areas.

• The Research Journal of the Costume Culture
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• v.31 no.1
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• pp.34-52
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• 2023

In this study, text mining was conducted on the product names of skirts, pants, shirts/blouses, and dresses to analyze the characteristics of keywords appearing in online shopping product names. As a result of frequency analysis, the number of keywords that appeared 0.5% or more for each item was around 30, and the number of keywords that appeared 0.1% or more was around 150. The cumulative distribution rate of 150 terms was around 80%. Accordingly, information on 150 key terms was analyzed, from which item, clothing composition, and material information were the found to be the most important types of information (ranking in the top five of all items). In addition, fit and style information for skirts and pants and length information for skirts and dresses were also considered important information. Keywords representing clothing composition information were: banding, high waist, and split for skirts and pants; and V-neck, tie, long sleeves, and puff for shirts/blouses and dresses. It was possible to identify the current design characteristics preferred by consumers from this information. However, there were also problems with terminology that hindered the connection between sellers and consumers. The most common problems were the use of various terms with the same meaning and irregular use of Korean and English terms. However, as a result of using co-appearance frequency analysis, it can be interpreted that there is little intention for product exposure, so it is recommended to avoid it.

• Smart Media Journal
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• v.12 no.8
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• pp.60-68
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• 2023

After COVID-19, hotel industry is rapidly experiencing changes in the business environment, and under the influence of the Fourth Industrial Revolution, hotel industry is striving to secure competitive advantages through differentiation, including the use of big data and the IoT in service provision, as well as the introduction of artificial intelligence(AI) robot services. This study analyzed the perceived value of AI robot services and their impact on usage attitudes and behavioral intentions of customers who have used hotels that have introduced AI robot services. The results of the study showed that the value of robot services perceived by customers who have used robot services in hotels is categorized into three dimensions: social, experiential, and functional, and all of them have a positive effect on usage attitudes, with social, functional, and experiential values having a positive effect on usage attitudes in that order. Attitude toward use was also analyzed to have a positive effect on behavioral intention, which is consistent with the value-attitude-behavior model. Therefore, it is necessary for hotels to improve the satisfaction of hotel guests through diversified services of AI robot service.

• Information Systems Review
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• v.22 no.3
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• pp.15-30
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• 2020

In the real estate industry, the latest changes in the Fourth Industrial Revolution, such as big data analytics, machine learning, and VR (virtual reality), combine to bring about industry change. Proptech is a new term combining properties and technology. This study aims to derive and analyze from a comprehensive perspective the quality factors (systems, services, interfaces, information) for mobile real estate brokerage services that are well known and used in the domestic market. The surveys in this study were conducted online and offline and a total of 161 samples were used for statistical analysis. As a result, all hypotheses were approved to except system quality and service quality. The results show that the domestic proptech companies who are mostly focused on real estate brokerage services, peer-to-peer lending, advertising platforms and apartments need to grow in various fields of proptech business of other countries including Europe, USA and China.