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한국정보시스템학회> 정보시스템연구> 혼합 임베딩을 통한 전문 용어 의미 학습 방안

KCI등재

혼합 임베딩을 통한 전문 용어 의미 학습 방안

A Method for Learning the Specialized Meaning of Terminology through Mixed Word Embedding

김병태 ( Kim Byung Tae ) , 김남규 ( Kim Nam Gyu )
  • : 한국정보시스템학회
  • : 정보시스템연구 30권2호
  • : 연속간행물
  • : 2021년 06월
  • : 57-78(22pages)
정보시스템연구

DOI


목차

Ⅰ. 서론
Ⅱ. 선행 연구
Ⅲ. 제안 방법론 및 실험 설계
Ⅳ. 실험 결과
Ⅴ. 결론
참고문헌
< Abstract >

키워드 보기


초록 보기

Purpose
In this study, first, we try to make embedding results that reflect the characteristics of both professional and general documents. In addition, when disparate documents are put together as learning materials for natural language processing, we try to propose a method that can measure the degree of reflection of the characteristics of individual domains in a quantitative way.
Approach
For this study, the Korean Supreme Court Precedent documents and Korean Wikipedia are selected as specialized documents and general documents respectively. After extracting the most similar word pairs and similarities of unique words observed only in the specialized documents, we observed how those values were changed in the process of embedding with general documents.
Findings
According to the measurement methods proposed in this study, it was confirmed that the degree of specificity of specialized documents was relaxed in the process of combining with general documents, and that the degree of dissolution could have a positive correlation with the size of general documents.

UCI(KEPA)

간행물정보

  • : 사회과학분야  > 경영학
  • : KCI등재
  • :
  • : 계간
  • : 1229-8476
  • : 2733-8770
  • : 학술지
  • : 연속간행물
  • : 1992-2021
  • : 883


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30권2호(2021년 06월) 수록논문
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KCI등재

1크라우드펀딩 참여와 구전의도에 대한 실증적 분석 : 플랫폼 신뢰를 중심으로

저자 : 김보라 ( Kim Bo Ra ) , 박현선 ( Park Hyun Sun ) , 김상현 ( Kim Sang Hyun )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 1-27 (27 pages)

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Purpose
Even if many startups firms have developed innovative items and a potential for success, they often have a limited financial resources, which makes them difficult to do business. To overcome this financial difficulty, startups have used one of fintech services, called crowdfunding that can be a good alternative to solving the difficulty of financing. The purpose of this study is to empirically validate the proposed research model that investigates the reasons of trusting crowdfunding platform, which positively leads to two outcomes - intention to participate and word-of-mouth for reward-based crowdfunding project.
Design/methodology/approach
We proposed several factors categorized as trust, information quality, and platform traits that have a positive impact on trust of crowdfunding platform, which positively leads to intention to participate and word-of-mouth of crowdfunding. The collected(n=285) from individuals who have participated in crowdfunding project was analyzed with SmartPLS 3.0 to test proposed hypotheses.
Findings
The results showed that all proposed variables (website reputation, crowdfunding familiarity, digital storytelling, information quality, and interaction) had a significant impact on crowfunding platform trust with exception of product differentiation. In addition, crowfunding platform trust was positively associated with participating intention and word-of-mouth. Based on findings, we discussed the research results and implication alone with a direction for future studies.

KCI등재

2사이버비행 요인 파악 및 예측모델 개발: 혼합방법론 접근

저자 : 손새아 ( Shon Sae Ah ) , 신우식 ( Shin Woo Sik ) , 김희웅 ( Kim Hee Woong )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 29-56 (28 pages)

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Purpose
Cyber deviance of adolescents has become a serious social problem. With a widespread use of smartphones, incidents of cyber deviance have increased in Korea and both quantitative and qualitative damages such as suicide and depression are increasing. Research has been conducted to understand diverse factors that explain adolescents' delinquency in cyber space. However, most previous studies have focused on a single theory or perspective. Therefore, this study aims to comprehensively analyze motivations of juvenile cyber deviance and to develop a predictive model for delinquent adolescents by integrating four different theories on cyber deviance.
Design/methodology/approach
By using data from Korean Children & Youth Panel Survey 2010, this study extracts 27 potential factors for cyber deivance based on four background theories including general strain, social learning, social bonding, and routine activity theories. Then this study employs econometric analysis to empirically assess the impact of potential factors and utilizes a machine learning approach to predict the likelihood of cyber deviance by adolescents.
Findings
This study found that general strain factors as well as social learning factors have positive effects on cyber deviance. Routine activity-related factors such as real-life delinquent behaviors and online activities also positively influence the likelihood of cyber diviance. On the other hand, social bonding factors such as community commitment and attachment to community lessen the likelihood of cyber deviance while social factors related to school activities are found to have positive impacts on cyber deviance. This study also found a predictive model using a deep learning algorithm indicates the highest prediction performance. This study contributes to the prevention of cyber deviance of teenagers in practice by understanding motivations for adolescents' delinquency and predicting potential cyber deviants.

KCI등재

3혼합 임베딩을 통한 전문 용어 의미 학습 방안

저자 : 김병태 ( Kim Byung Tae ) , 김남규 ( Kim Nam Gyu )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 57-78 (22 pages)

다운로드

(기관인증 필요)

초록보기

Purpose
In this study, first, we try to make embedding results that reflect the characteristics of both professional and general documents. In addition, when disparate documents are put together as learning materials for natural language processing, we try to propose a method that can measure the degree of reflection of the characteristics of individual domains in a quantitative way.
Approach
For this study, the Korean Supreme Court Precedent documents and Korean Wikipedia are selected as specialized documents and general documents respectively. After extracting the most similar word pairs and similarities of unique words observed only in the specialized documents, we observed how those values were changed in the process of embedding with general documents.
Findings
According to the measurement methods proposed in this study, it was confirmed that the degree of specificity of specialized documents was relaxed in the process of combining with general documents, and that the degree of dissolution could have a positive correlation with the size of general documents.

KCI등재

4혜택/비용, 그림자 노동에 대한 부정적 태도, 반응행동 간 구조적 관계

저자 : Liu Ting Ting , 고준 ( Koh Joon )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 79-103 (25 pages)

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Purpose
Based on consumers' economic, psychological, self-development and conversion costs, this study discusses the relationship between consumers' negative attitude to their shadow work during the course of using self-service in unmanned supermarkets and their behavior.
Design/methodology/approach
Along with the Hirschman(1970)'s EVLN(Exit, Voice, Loyalty, and Neglect) reviewed, the proposed model of this study is based on the S-O-R model(Mehrabian and Russel, 1974) and mental accounting theory(Thaler, 1999), having empirical validation.
Findings
In the process of visits and consumption in unmanned supermarkets, increasing economic and psychological benefits can effectively reduce consumers' negative attitudes towards shadow work. In addition, the increase in switching costs will also effectively reduce consumers' negative attitudes towards shadow work. When shadow work holds a negative attitude, all the three kinds of actions will occur. Unmanned supermarket operators use consumers to create value while giving a certain return to them, which is conducive to the sustainable development of unmanned supermarket enterprises.

KCI등재

5머신러닝을 이용한 국내 수입 자동차 구매 해약 예측 모델 연구: H 수입차 딜러사 대상으로

저자 : 정동균 ( Jung Dong Kun ) , 이종화 ( Lee Jong Hwa ) , 이현규 ( Lee Hyun Kyu )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 105-126 (22 pages)

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Purpose
The purpose of this study is to implement a optimal machine learning model about the cancellation prediction performance in car sales business. It is to apply the data set of accumulated contract, cancellation, and sales information in sales support system(SFA) which is commonly used for sales, customers and inventory management by imported car dealers, to several machine learning models and predict performance of cancellation.
Design/methodology/approach
This study extracts 29,073 contracts, cancellations, and sales data from 2015 to 2020 accumulated in the sales support system(SFA) for imported car dealers and uses the analysis program Python Jupiter notebook in order to perform data pre-processing, verification, and modeling that is applying and learning to Machine learning model after then the final result was predicted using new data.
Findings
This study confirmed that cancellation prediction is possible by applying car purchase contract information to machine learning models. It proved the possibility of developing and utilizing a generalized predictive model by using data of imported car sales system with machine learning technology. It can reduce and prevent the sales failure as caring the potential lost customer intensively and it lead to increase sales revenue by predicting the cancellation possibility of individual customers.

KCI등재

6Digital Immigrants' Goal Structures in Online Learning

저자 : Lee Jung Hoon , Nam Jin Young , Jung Yoon Hyuk

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 127-146 (20 pages)

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Research Purpose
Advances in digital technology have facilitated the widespread adoption of online learning, which has become a substantial way of learning. Although digital immigrants have become a main group of users of learning online, there is a lack of understanding of their online learning. This study aims to explore digital immigrants' adoption of online learning from the goal-pursuit perspective to gain insight into how they use online learning.
Research Method
A laddering interview was conducted with 22 Korean adults to elicit their goals in online learning. Then, a means-end chain analysis was used to derive their hierarchical goal structure.
Findings
The results reveal digital immigrants' goal structure of online learning, consisting of four attributes of online learning (e.g., accessibility, diversity, up-to-dateness, and repeatability) and six goals (e.g., self-esteem, enjoyment, recognition, productivity, gaining insights, and positive relations). This study contributes to the literature by providing a rich picture of their use of online learning.

KCI등재

7SOM과 LSTM을 활용한 지역기반의 부동산 가격 예측

저자 : 신은경 ( Shin Eun Kyung ) , 김은미 ( Kim Eun Mi ) , 홍태호 ( Hong Tae Ho )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 147-163 (17 pages)

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Purpose
The study aims to predict real estate prices by utilizing regional characteristics. Since real estate has the characteristic of immobility, the characteristics of a region have a great influence on the price of real estate. In addition, real estate prices are closely related to economic development and are a major concern for policy makers and investors. Accurate house price forecasting is necessary to prepare for the impact of house price fluctuations. To improve the performance of our predictive models, we applied LSTM, a widely used deep learning technique for predicting time series data.
Design/methodology/approach
This study used time series data on real estate prices provided by the Ministry of Land, Infrastructure and Transport. For time series data preprocessing, HP filters were applied to decompose trends and SOM was used to cluster regions with similar price directions. To build a real estate price prediction model, SVR and LSTM were applied, and the prices of regions classified into similar clusters by SOM were used as input variables.
Findings
The clustering results showed that the region of the same cluster was geographically close, and it was possible to confirm the characteristics of being classified as the same cluster even if there was a price level and a similar industry group. As a result of predicting real estate prices in 1, 2, and 3 months, LSTM showed better predictive performance than SVR, and LSTM showed better predictive performance in long-term forecasting 3 months later than in 1-month short-term forecasting.

KCI등재

8온라인 마켓플레이스의 신뢰 형성과 다차원적 제도적 메커니즘의 역할

저자 : 노윤호 ( Roh Yoon Ho ) , 옥석재 ( Ok Seok Jae )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 165-188 (24 pages)

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Purpose
This study was conducted to identify the multidimensional role of institutional mechanisms in the linear relationship of satisfaction, trust and repurchase intention, which are used as an important concept in the research of e-commerce. To this end, a research model was proposed by combining concepts which are the concept of perceived effectiveness of institutional mechanisms for overall e-commerce environment(e.g., PEEIM) and the concep of perceived effectiveness of institutional structures(e.g., PEIS) of a specific marketplace based on the social cognitive theory.
Design/methodology/approach
This study was conducted by dividing the data into two groups to identify institutional mechanisms and trust-building relationships according to the institutional contexts inherent in e-commerce. The institutional contexts were set up for the top two online companies and the bottom two online companies according to the results of the open market brand assessment from 2018 to 2019 in South Korea.
Findings
The result of this study found that PEIS had a direct impact on trust in both high and low groups respectively whereas PEEIM presented different paradoxical results in high and low groups. In the relationship between the satisfaction and the trust in the vendor of the high group, PEEIM showed negative moderating effects but in the relationship between the trust and the repurchase intention of the low group PEEIM showed positive moderating effects.

KCI등재

9소비자 리뷰 텍스트마이닝을 이용한 신생 산업 시장 구조 분석: 국내 수제 맥주 시장의 경쟁 관계 및 시장 구조를 중심으로

저자 : 이연수 ( Lee Yeon Soo ) , 김혜진 ( Kim Hye Jin )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 189-214 (26 pages)

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Purpose
This paper aims to effectively utilize user-generated content (UGC) and analyze the market structure of a relatively new market which lacks rich user review information. Specifically, we propose a domain-specific text mining tool for the domestic craft beer market and visualize the market structure by incorporating how individual beer products are positioned in the perceptual map of consumers.
Design/methodology/approach
We collect user review information from Naver blogs, and extract words that describe beers. We identify semantic relationships between beer products through text mining, and then depending on these semantic relationships, construct a graph representing the market structure of the domestic craft beer market based on the consumer's perceptual map.
Findings
First, beer products produced in the same brewery are perceived as very similar to consumers. Second, only two products, 'Heukdang Milky Stout' and 'Gompyo', was noticeably distinguishable from other products. Third, even though 'Gyeongbokgung' is from a different brewery, it is located very close to the products of 'Jeju Beer' brewery such as 'Jeju Baeknokdam Ale' and 'Seongsan Ilchulbong Ale', which suggests the influence of 'landmark series.' We successfully show that our methodology effectively describes the market structure of the craft beer market.

KCI등재

10외식업 점주의 배달앱 서비스 이용에 대한 지각된 혜택 및 희생이 지속이용의도에 미치는 영향: 가치기반수용모델을 중심으로

저자 : 이영석 ( Lee Young Seok ) , 송재민 ( Song Jae Min ) , 양성병 ( Yang Sung Byung )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 215-241 (27 pages)

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Purpose
The purpose of this study is to analyze the impact of perceived value on the intention of continuous use of food delivery app services form the perspective of restaurant owners. We adopt the value-based acceptance model (VAM) in order to derive influential factors (i.e., perceived benefits and perceived sacrifices) that affect perceived value, which in turn leads to the continuous use of food delivery app services. In addition, the moderating role of restaurant type in the relationship between perceived benefits/sacrifices and perceived value.
Design/methodology/approach
An online survey was conducted on restaurant owners who are using domestic food delivery app services. Samples were collected using the quota sampling method in accordance with the current market share of food delivery app services. A total of 235 participants (restaurant owners) were identified as a valid sample and used for the final analysis.
Findings
Research findings of the study are as follows. First, sales increase and operational effort decrease among perceived benefits had a significant positive impact on perceived value. Second, perceived cost among perceived sacrifices had a significant negative impact on perceived value. Third, perceived value had a significant positive effect on the intention of continuous use. Finally, the moderating role of restaurant type was found only in the effect of operational effort decrease on perceived value.

12
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KCI등재

1크라우드펀딩 참여와 구전의도에 대한 실증적 분석 : 플랫폼 신뢰를 중심으로

저자 : 김보라 ( Kim Bo Ra ) , 박현선 ( Park Hyun Sun ) , 김상현 ( Kim Sang Hyun )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 1-27 (27 pages)

다운로드

(기관인증 필요)

초록보기

Purpose
Even if many startups firms have developed innovative items and a potential for success, they often have a limited financial resources, which makes them difficult to do business. To overcome this financial difficulty, startups have used one of fintech services, called crowdfunding that can be a good alternative to solving the difficulty of financing. The purpose of this study is to empirically validate the proposed research model that investigates the reasons of trusting crowdfunding platform, which positively leads to two outcomes - intention to participate and word-of-mouth for reward-based crowdfunding project.
Design/methodology/approach
We proposed several factors categorized as trust, information quality, and platform traits that have a positive impact on trust of crowdfunding platform, which positively leads to intention to participate and word-of-mouth of crowdfunding. The collected(n=285) from individuals who have participated in crowdfunding project was analyzed with SmartPLS 3.0 to test proposed hypotheses.
Findings
The results showed that all proposed variables (website reputation, crowdfunding familiarity, digital storytelling, information quality, and interaction) had a significant impact on crowfunding platform trust with exception of product differentiation. In addition, crowfunding platform trust was positively associated with participating intention and word-of-mouth. Based on findings, we discussed the research results and implication alone with a direction for future studies.

KCI등재

2사이버비행 요인 파악 및 예측모델 개발: 혼합방법론 접근

저자 : 손새아 ( Shon Sae Ah ) , 신우식 ( Shin Woo Sik ) , 김희웅 ( Kim Hee Woong )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 29-56 (28 pages)

다운로드

(기관인증 필요)

초록보기

Purpose
Cyber deviance of adolescents has become a serious social problem. With a widespread use of smartphones, incidents of cyber deviance have increased in Korea and both quantitative and qualitative damages such as suicide and depression are increasing. Research has been conducted to understand diverse factors that explain adolescents' delinquency in cyber space. However, most previous studies have focused on a single theory or perspective. Therefore, this study aims to comprehensively analyze motivations of juvenile cyber deviance and to develop a predictive model for delinquent adolescents by integrating four different theories on cyber deviance.
Design/methodology/approach
By using data from Korean Children & Youth Panel Survey 2010, this study extracts 27 potential factors for cyber deivance based on four background theories including general strain, social learning, social bonding, and routine activity theories. Then this study employs econometric analysis to empirically assess the impact of potential factors and utilizes a machine learning approach to predict the likelihood of cyber deviance by adolescents.
Findings
This study found that general strain factors as well as social learning factors have positive effects on cyber deviance. Routine activity-related factors such as real-life delinquent behaviors and online activities also positively influence the likelihood of cyber diviance. On the other hand, social bonding factors such as community commitment and attachment to community lessen the likelihood of cyber deviance while social factors related to school activities are found to have positive impacts on cyber deviance. This study also found a predictive model using a deep learning algorithm indicates the highest prediction performance. This study contributes to the prevention of cyber deviance of teenagers in practice by understanding motivations for adolescents' delinquency and predicting potential cyber deviants.

KCI등재

3혼합 임베딩을 통한 전문 용어 의미 학습 방안

저자 : 김병태 ( Kim Byung Tae ) , 김남규 ( Kim Nam Gyu )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 57-78 (22 pages)

다운로드

(기관인증 필요)

초록보기

Purpose
In this study, first, we try to make embedding results that reflect the characteristics of both professional and general documents. In addition, when disparate documents are put together as learning materials for natural language processing, we try to propose a method that can measure the degree of reflection of the characteristics of individual domains in a quantitative way.
Approach
For this study, the Korean Supreme Court Precedent documents and Korean Wikipedia are selected as specialized documents and general documents respectively. After extracting the most similar word pairs and similarities of unique words observed only in the specialized documents, we observed how those values were changed in the process of embedding with general documents.
Findings
According to the measurement methods proposed in this study, it was confirmed that the degree of specificity of specialized documents was relaxed in the process of combining with general documents, and that the degree of dissolution could have a positive correlation with the size of general documents.

KCI등재

4혜택/비용, 그림자 노동에 대한 부정적 태도, 반응행동 간 구조적 관계

저자 : Liu Ting Ting , 고준 ( Koh Joon )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 79-103 (25 pages)

다운로드

(기관인증 필요)

초록보기

Purpose
Based on consumers' economic, psychological, self-development and conversion costs, this study discusses the relationship between consumers' negative attitude to their shadow work during the course of using self-service in unmanned supermarkets and their behavior.
Design/methodology/approach
Along with the Hirschman(1970)'s EVLN(Exit, Voice, Loyalty, and Neglect) reviewed, the proposed model of this study is based on the S-O-R model(Mehrabian and Russel, 1974) and mental accounting theory(Thaler, 1999), having empirical validation.
Findings
In the process of visits and consumption in unmanned supermarkets, increasing economic and psychological benefits can effectively reduce consumers' negative attitudes towards shadow work. In addition, the increase in switching costs will also effectively reduce consumers' negative attitudes towards shadow work. When shadow work holds a negative attitude, all the three kinds of actions will occur. Unmanned supermarket operators use consumers to create value while giving a certain return to them, which is conducive to the sustainable development of unmanned supermarket enterprises.

KCI등재

5머신러닝을 이용한 국내 수입 자동차 구매 해약 예측 모델 연구: H 수입차 딜러사 대상으로

저자 : 정동균 ( Jung Dong Kun ) , 이종화 ( Lee Jong Hwa ) , 이현규 ( Lee Hyun Kyu )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 105-126 (22 pages)

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Purpose
The purpose of this study is to implement a optimal machine learning model about the cancellation prediction performance in car sales business. It is to apply the data set of accumulated contract, cancellation, and sales information in sales support system(SFA) which is commonly used for sales, customers and inventory management by imported car dealers, to several machine learning models and predict performance of cancellation.
Design/methodology/approach
This study extracts 29,073 contracts, cancellations, and sales data from 2015 to 2020 accumulated in the sales support system(SFA) for imported car dealers and uses the analysis program Python Jupiter notebook in order to perform data pre-processing, verification, and modeling that is applying and learning to Machine learning model after then the final result was predicted using new data.
Findings
This study confirmed that cancellation prediction is possible by applying car purchase contract information to machine learning models. It proved the possibility of developing and utilizing a generalized predictive model by using data of imported car sales system with machine learning technology. It can reduce and prevent the sales failure as caring the potential lost customer intensively and it lead to increase sales revenue by predicting the cancellation possibility of individual customers.

KCI등재

6Digital Immigrants' Goal Structures in Online Learning

저자 : Lee Jung Hoon , Nam Jin Young , Jung Yoon Hyuk

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 127-146 (20 pages)

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Research Purpose
Advances in digital technology have facilitated the widespread adoption of online learning, which has become a substantial way of learning. Although digital immigrants have become a main group of users of learning online, there is a lack of understanding of their online learning. This study aims to explore digital immigrants' adoption of online learning from the goal-pursuit perspective to gain insight into how they use online learning.
Research Method
A laddering interview was conducted with 22 Korean adults to elicit their goals in online learning. Then, a means-end chain analysis was used to derive their hierarchical goal structure.
Findings
The results reveal digital immigrants' goal structure of online learning, consisting of four attributes of online learning (e.g., accessibility, diversity, up-to-dateness, and repeatability) and six goals (e.g., self-esteem, enjoyment, recognition, productivity, gaining insights, and positive relations). This study contributes to the literature by providing a rich picture of their use of online learning.

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7SOM과 LSTM을 활용한 지역기반의 부동산 가격 예측

저자 : 신은경 ( Shin Eun Kyung ) , 김은미 ( Kim Eun Mi ) , 홍태호 ( Hong Tae Ho )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 147-163 (17 pages)

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Purpose
The study aims to predict real estate prices by utilizing regional characteristics. Since real estate has the characteristic of immobility, the characteristics of a region have a great influence on the price of real estate. In addition, real estate prices are closely related to economic development and are a major concern for policy makers and investors. Accurate house price forecasting is necessary to prepare for the impact of house price fluctuations. To improve the performance of our predictive models, we applied LSTM, a widely used deep learning technique for predicting time series data.
Design/methodology/approach
This study used time series data on real estate prices provided by the Ministry of Land, Infrastructure and Transport. For time series data preprocessing, HP filters were applied to decompose trends and SOM was used to cluster regions with similar price directions. To build a real estate price prediction model, SVR and LSTM were applied, and the prices of regions classified into similar clusters by SOM were used as input variables.
Findings
The clustering results showed that the region of the same cluster was geographically close, and it was possible to confirm the characteristics of being classified as the same cluster even if there was a price level and a similar industry group. As a result of predicting real estate prices in 1, 2, and 3 months, LSTM showed better predictive performance than SVR, and LSTM showed better predictive performance in long-term forecasting 3 months later than in 1-month short-term forecasting.

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8온라인 마켓플레이스의 신뢰 형성과 다차원적 제도적 메커니즘의 역할

저자 : 노윤호 ( Roh Yoon Ho ) , 옥석재 ( Ok Seok Jae )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 165-188 (24 pages)

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Purpose
This study was conducted to identify the multidimensional role of institutional mechanisms in the linear relationship of satisfaction, trust and repurchase intention, which are used as an important concept in the research of e-commerce. To this end, a research model was proposed by combining concepts which are the concept of perceived effectiveness of institutional mechanisms for overall e-commerce environment(e.g., PEEIM) and the concep of perceived effectiveness of institutional structures(e.g., PEIS) of a specific marketplace based on the social cognitive theory.
Design/methodology/approach
This study was conducted by dividing the data into two groups to identify institutional mechanisms and trust-building relationships according to the institutional contexts inherent in e-commerce. The institutional contexts were set up for the top two online companies and the bottom two online companies according to the results of the open market brand assessment from 2018 to 2019 in South Korea.
Findings
The result of this study found that PEIS had a direct impact on trust in both high and low groups respectively whereas PEEIM presented different paradoxical results in high and low groups. In the relationship between the satisfaction and the trust in the vendor of the high group, PEEIM showed negative moderating effects but in the relationship between the trust and the repurchase intention of the low group PEEIM showed positive moderating effects.

KCI등재

9소비자 리뷰 텍스트마이닝을 이용한 신생 산업 시장 구조 분석: 국내 수제 맥주 시장의 경쟁 관계 및 시장 구조를 중심으로

저자 : 이연수 ( Lee Yeon Soo ) , 김혜진 ( Kim Hye Jin )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 189-214 (26 pages)

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Purpose
This paper aims to effectively utilize user-generated content (UGC) and analyze the market structure of a relatively new market which lacks rich user review information. Specifically, we propose a domain-specific text mining tool for the domestic craft beer market and visualize the market structure by incorporating how individual beer products are positioned in the perceptual map of consumers.
Design/methodology/approach
We collect user review information from Naver blogs, and extract words that describe beers. We identify semantic relationships between beer products through text mining, and then depending on these semantic relationships, construct a graph representing the market structure of the domestic craft beer market based on the consumer's perceptual map.
Findings
First, beer products produced in the same brewery are perceived as very similar to consumers. Second, only two products, 'Heukdang Milky Stout' and 'Gompyo', was noticeably distinguishable from other products. Third, even though 'Gyeongbokgung' is from a different brewery, it is located very close to the products of 'Jeju Beer' brewery such as 'Jeju Baeknokdam Ale' and 'Seongsan Ilchulbong Ale', which suggests the influence of 'landmark series.' We successfully show that our methodology effectively describes the market structure of the craft beer market.

KCI등재

10외식업 점주의 배달앱 서비스 이용에 대한 지각된 혜택 및 희생이 지속이용의도에 미치는 영향: 가치기반수용모델을 중심으로

저자 : 이영석 ( Lee Young Seok ) , 송재민 ( Song Jae Min ) , 양성병 ( Yang Sung Byung )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 2호 발행 연도 : 2021 페이지 : pp. 215-241 (27 pages)

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Purpose
The purpose of this study is to analyze the impact of perceived value on the intention of continuous use of food delivery app services form the perspective of restaurant owners. We adopt the value-based acceptance model (VAM) in order to derive influential factors (i.e., perceived benefits and perceived sacrifices) that affect perceived value, which in turn leads to the continuous use of food delivery app services. In addition, the moderating role of restaurant type in the relationship between perceived benefits/sacrifices and perceived value.
Design/methodology/approach
An online survey was conducted on restaurant owners who are using domestic food delivery app services. Samples were collected using the quota sampling method in accordance with the current market share of food delivery app services. A total of 235 participants (restaurant owners) were identified as a valid sample and used for the final analysis.
Findings
Research findings of the study are as follows. First, sales increase and operational effort decrease among perceived benefits had a significant positive impact on perceived value. Second, perceived cost among perceived sacrifices had a significant negative impact on perceived value. Third, perceived value had a significant positive effect on the intention of continuous use. Finally, the moderating role of restaurant type was found only in the effect of operational effort decrease on perceived value.

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