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한국정보시스템학회> 정보시스템연구> 레그테크 기반의 자본시장 규제 해석 온톨로지 및 딥러닝 기술 개발을 위한 제언

KCI등재

레그테크 기반의 자본시장 규제 해석 온톨로지 및 딥러닝 기술 개발을 위한 제언

Suggestions for the Development of RegTech Based Ontology and Deep Learning Technology to Interpret Capital Market Regulations

최승욱 ( Choi Seung Uk ) , 권오병 ( Kwon Oh Byung )
  • : 한국정보시스템학회
  • : 정보시스템연구 30권1호
  • : 연속간행물
  • : 2021년 03월
  • : 65-84(20pages)
정보시스템연구

DOI


목차

Ⅰ. 서론
Ⅱ. 이론적 배경
Ⅲ. 레그테크 기반의 온톨로지 및 딥러닝 기술 개발을 위한 사례
Ⅳ. 토의 및 결론
참고문헌

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초록 보기

Purpose
Based on the development of artificial intelligence and big data technologies, the RegTech has been emerged to reduce regulatory costs and to enable efficient supervision by regulatory bodies. The word RegTech is a combination of regulation and technology, which means using the technological methods to facilitate the implementation of regulations and to make efficient surveillance and supervision of regulations. The purpose of this study is to describe the recent adoption of RegTech and to provide basic examples of applying RegTech to capital market regulations.
Design/methodology/approach
English-based ontology and deep learning technologies are quite developed in practice, and it will not be difficult to expand it to European or Latin American languages that are grammatically similar to English. However, it is not easy to use it in most Asian languages such as Korean, which have different grammatical rules. In addition, in the early stages of adoption, companies, financial institutions and regulators will not be familiar with this machine-based reporting system. There is a need to establish an ecosystem which facilitates the adoption of RegTech by consulting and supporting the stakeholders. In this paper, we provide a simple example that shows a procedure of applying RegTech to recognize and interpret Korean language-based capital market regulations. Specifically, we present the process of converting sentences in regulations into a meta-language through the morpheme analyses. We next conduct deep learning analyses to determine whether a regulatory sentence exists in each regulatory paragraph.
Findings
This study illustrates the applicability of RegTech-based ontology and deep learning technologies in Korean-based capital market regulations.

UCI(KEPA)

간행물정보

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


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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)

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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.

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1간편결제 서비스의 지속사용의도에 영향을 미치는 요인에 관한 연구: 플로우, 신뢰 및 혁신저항을 중심으로

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Purpose
The purpose of this study is to deduct the motivative factors such as perceived value, trust, innovative resistance and flow from the pervious studies and to examine the effect of the motivative factors in the continued use of convenient payment service.
Design/methodology/approach
This study made a design of the research model by integrating the factors deducted from the Value-based Adoption Model and the Innovative Resistance Model with the factors deducted from the Flow Theory.
Findings
Results showed that perceived value had a significant effect on trust and innovative resistance. Moreover, trust had a significant effect on flow and continued use. Finally, innovative resistance and flow had a significant effect on continued use. However, the research model in this study was derived from a behavioral point of view, therefore, this model needs to combine the various factors of related fields.

KCI등재

2저자동시인용분석에 의한 Business Analytics 분야의 지적 구조 분석: 2002 ~ 2020

저자 : 임혜정 ( Lim Hyae Jung ) , 서창교 ( Suh Chang Kyo )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 1호 발행 연도 : 2021 페이지 : pp. 21-44 (24 pages)

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Purpose
The opportunities and approaches to big data have grown in various ways in the digital era. Business analytics is nowadays an inevitable strategy for organizations to earn a competitive advantage in order to survive in the challenged environments. The purpose of this study is to analyze the intellectual structure of business analytics literature to have a better insight for the organizations to the field.
Design/methodology/approach
This research analyzed with the data extracted from the database Web of Science. Total of 427 documents and 23,760 references are inserted into the analysis program CiteSpace. Author co-citation analysis is used to analyze the intellectual structure of the business analytics. We performed clustering analysis, burst detection and timeline analysis with the data.
Findings
We identified seven sub- areas of business analytics field. The top four sub-areas are “Big Data Analytics Infrastructure”, “Performance Management System”, “Interactive Exploration”, and “Supply Chain Management”. We also identified the top 5 references with the strongest citation bursts including Trkman et al.(2010) and Davenport(2006). Through timeline analysis we interpret the clusters that are expected to be the trend subjects in the future. Lastly, limitation and further research suggestion are discussed as concluding remarks.

KCI등재

3Word2Vec를 이용한 토픽모델링의 확장 및 분석사례

저자 : 윤상훈 ( Yoon Sang Hun ) , 김근형 ( Kim Keun Hyung )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 1호 발행 연도 : 2021 페이지 : pp. 45-64 (20 pages)

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Purpose
The traditional topic modeling technique makes it difficult to distinguish the semantic of topics because the key words assigned to each topic would be also assigned to other topics. This problem could become severe when the number of online reviews are small. In this paper, the extended model of topic modeling technique that can be used for analyzing a small amount of online reviews is proposed.
Design/methodology/approach
The extended model of being proposed in this paper is a form that combines the traditional topic modeling technique and the Word2Vec technique. The extended model only allocates main words to the extracted topics, but also generates discriminatory words between topics. In particular, Word2vec technique is applied in the process of extracting related words semantically for each discriminatory word. In the extended model, main words and discriminatory words with similar words semantically are used in the process of semantic classification and naming of extracted topics, so that the semantic classification and naming of topics can be more clearly performed. For case study, online reviews related with Udo in Tripadvisor web site were analyzed by applying the traditional topic modeling and the proposed extension model. In the process of semantic classification and naming of the extracted topics, the traditional topic modeling technique and the extended model were compared.
Findings
Since the extended model is a concept that utilizes additional information in the existing topic modeling information, it can be confirmed that it is more effective than the existing topic modeling in semantic division between topics and the process of assigning topic names.

KCI등재

4레그테크 기반의 자본시장 규제 해석 온톨로지 및 딥러닝 기술 개발을 위한 제언

저자 : 최승욱 ( Choi Seung Uk ) , 권오병 ( Kwon Oh Byung )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 1호 발행 연도 : 2021 페이지 : pp. 65-84 (20 pages)

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Purpose
Based on the development of artificial intelligence and big data technologies, the RegTech has been emerged to reduce regulatory costs and to enable efficient supervision by regulatory bodies. The word RegTech is a combination of regulation and technology, which means using the technological methods to facilitate the implementation of regulations and to make efficient surveillance and supervision of regulations. The purpose of this study is to describe the recent adoption of RegTech and to provide basic examples of applying RegTech to capital market regulations.
Design/methodology/approach
English-based ontology and deep learning technologies are quite developed in practice, and it will not be difficult to expand it to European or Latin American languages that are grammatically similar to English. However, it is not easy to use it in most Asian languages such as Korean, which have different grammatical rules. In addition, in the early stages of adoption, companies, financial institutions and regulators will not be familiar with this machine-based reporting system. There is a need to establish an ecosystem which facilitates the adoption of RegTech by consulting and supporting the stakeholders. In this paper, we provide a simple example that shows a procedure of applying RegTech to recognize and interpret Korean language-based capital market regulations. Specifically, we present the process of converting sentences in regulations into a meta-language through the morpheme analyses. We next conduct deep learning analyses to determine whether a regulatory sentence exists in each regulatory paragraph.
Findings
This study illustrates the applicability of RegTech-based ontology and deep learning technologies in Korean-based capital market regulations.

KCI등재

5장노년층의 디지털기기 이용태도가 삶의 만족도에 미치는 영향 : 디지털기기 이용성과의 매개효과

저자 : 김수경 ( Kim Su Kyoung ) , 신혜리 ( Shin Hye Ri ) , 김영선 ( Kim Young Sun )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 1호 발행 연도 : 2021 페이지 : pp. 85-104 (20 pages)

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(기관인증 필요)

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Purpose
This study aims to verify the mediating effect of the utilization performance of digital device on the relationship between user attitude and life satisfaction.
Design/methodology/approach
Using the data of 2018 Digital Divide Survey conducted by the National Information Society Agency(NIA), the mediating effect was verified by Baron & Kenny (1986) 's 3 step process, targeting 1,662 adults older than 55.
Findings
The result is as follows: first, the user attitude of middle and older aged people has a positive effect on their life satisfaction. Second, the effect of user Attitude towards Digital Device of middle and older citizens is partially mediated by the utilization performance of digital device. The results of this study indicate that when providing informatization education in the local community to promote the use of digital devices for the elderly, efforts should be made to grasp the level and inclination of informatization individually, and furthermore present improvements for wireless devices that the elderly can easily access in their daily lives. This study is expected to be a groundwork for a practical intervention to boost positive attitude towards using digital device to enhance the utilization performance of digital device and the life satisfaction of middle and older aged people.

KCI등재

6디지털그림자노동의 분류와 동태성 및 연구 방향

저자 : 이웅규 ( Lee Woong Kyu )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 1호 발행 연도 : 2021 페이지 : pp. 105-121 (17 pages)

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Purpose
Today, through digital services, many people enjoy a conveient and comfortable life. Nevertheless, it is easy to find people in our daily lives who are buried in work without any payment that we did not do before digital services. Such un-payed works under digital environment are called digital shadow works. The purpose of this study is to classification and dynamics of digital shadow works and to suggest research direction.
Design/methodology/approach
Based on two dimension, voluntary participation ('should' type and 'want' type) and work orientation (management-operation), digital shadow works were classified into four categories - chore, makeup, routine, and quest.
Findings
In digital shadow work there are four types of dynamics - routine and quest, makeup and chore, makeup and quest, and quest and actions in offline. According to the classification and analysis of dynamics, three research directions in digital shadow work are suggested and discussed- digital shadow works operation mechanism considering dynamics, expansion of existing user theories based on survey method by digital shadow works and social influences by digital shadow works.

KCI등재

7연관규칙 분석을 통한 ESG 우려사안 키워드 도출에 관한 연구

저자 : 안태욱 ( Ahn Tae Wook ) , 이희승 ( Lee Hee Seung ) , 이준서 ( Yi June Suh )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 1호 발행 연도 : 2021 페이지 : pp. 123-149 (27 pages)

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Purpose
The purpose of this study is to define the anti-ESG activities of companies recognized by media by reflecting ESG recently attracted attention. This study extracts keywords for ESG controversies through association rule mining.
Design/methodology/approach
A research framework is designed to extract keywords for ESG controversies as follows: 1) From DeepSearch DB, we collect 23,837 articles on anti-ESG activities exposed to 130 media from 2013 to 2018 of 294 listed companies with ESG ratings 2) We set keywords related to environment, social, and governance, and delete or merge them with other keywords based on the support, confidence, and lift derived from association rule mining. 3) We illustrate the importance of keywords and the relevance between keywords through density, degree centrality, and closeness centrality on network analysis.
Findings
We identify a total of 26 keywords for ESG controversies. 'Gapjil' records the highest frequency, followed by 'corruption', 'bribery', and 'collusion'. Out of the 26 keywords, 16 are related to governance, 8 to social, and 2 to environment. The keywords ranked high are mostly related to the responsibility of shareholders within corporate governance. ESG controversies associated with social issues are often related to unfair trade. As a result of confidence analysis, the keywords related to social and governance are clustered and the probability of mutual occurrence between keywords is high within each group. In particular, in the case of “owner's arrest”, it is caused by “bribery” and “misappropriation” with an 80% confidence level. The result of network analysis shows that 'corruption' is located in the center, which is the most likely to occur alone, and is highly related to 'breach of duty', 'embezzlement', and 'bribery'.

KCI등재

8항공기 제조업에서 생산계획 동기화를 통한 데이터기반 구매조달 및 재고관리 방안 연구

저자 : 유경열 ( Yu Kyoung Yul ) , 최홍석 ( Choi Hong Suk ) , 정대율 ( Jeong Dae Yul )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 1호 발행 연도 : 2021 페이지 : pp. 151-177 (27 pages)

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Purpose
This paper aims to improve management performance by effectively responding to production needs and reducing inventory through synchronizing production planning and procurement in the aviation industry. In this study, the differences in production planning and execution were first analyzed in terms of demand, supply, inventory, and process using the big data collected from a domestic aircraft manufacturers. This paper analyzed the problems in procurement and inventory management using legacy big data from ERP system in the company. Based on the analysis, we performed a simulation to derive an efficient procurement and inventory management plan. Through analysis and simulation of operational data, we were able to discover procurement and inventory policies to effectively respond to production needs.
Design/methodology/approach
This is an empirical study to analyze the cause of decrease in inventory turnover and increase in inventory cost due to dis-synchronize between production requirements and procurement. The actual operation data, a total of 21,306,611 transaction data which are 18 months data from January 2019 to June 2020, were extracted from the ERP system. All them are such as basic information on materials, material consumption and movement history, inventory/receipt/shipment status, and production orders. To perform data analysis, it went through three steps. At first, we identified the current states and problems of production process to grasp the situation of what happened, and secondly, analyzed the data to identify expected problems through cross-link analysis between transactions, and finally, defined what to do. Many analysis techniques such as correlation analysis, moving average analysis, and linear regression analysis were applied to predict the status of inventory. A simulation was performed to analyze the appropriate inventory level according to the control of fluctuations in the production planing. In the simulation, we tested four alternatives how to coordinate the synchronization between the procurement plan and the production plan. All the alternatives give us more plausible results than actual operation in the past.
Findings
Based on the big data extracted from the ERP system, the relationship between the level of delivery and the distribution of fluctuations was analyzed in terms of demand, supply, inventory, and process. As a result of analyzing the inventory turnover rate, the root cause of the inventory increase were identified. In addition, based on the data on delivery and receipt performance, it was possible to accurately analyze how much gap occurs between supply and demand, and to figure out how much this affects the inventory level. Moreover, we were able to obtain the more predictable and insightful results through simulation that organizational performance such as inventory cost and lead time can be improved by synchronizing the production planning and purchase procurement with supply and demand information. The results of big data analysis and simulation gave us more insights in production planning, procurement, and inventory management for smart manufacturing and performance improvement.

KCI등재

9인플루언서 속성이 유튜브 정보수용과 구매의도에 미치는 영향

저자 : 박소진 ( Park So Jin ) , 오창규 ( Oh Chang Gyu )

발행기관 : 한국정보시스템학회 간행물 : 정보시스템연구 30권 1호 발행 연도 : 2021 페이지 : pp. 179-204 (26 pages)

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Purpose
The purpose of this study is to suggest a research model that shows how Youtube influencers affect consumers' Youtube information adoption and purchase intention. Generally, a communicator's character has a significant effect on the persuasiveness of the message. This study segments influencer characteristics into five dimensions and explores the effect of five characteristics on perceived usefulness of information, perceived enjoyment, information adoption, and purchase intention.
Design/methodology/approach
This study suggests a structural equation model that explains the casual relationship between the five dimensions of Youtuber characteristics and perceived usefulness of information, perceived enjoyment, information adoption, and purchase intention.
Findings
There are little research on what and how the characteristics of a Youtube influencer can affect consumers' information adoption and purchase intention of the product. This study is significant in that it provides a research model that examines the effect of Youtuber characteristics on consumers' information adoption and purchase intention. This research discovered that the dimensions of trustworthiness and attractiveness of influencer affect information adoption and purchase intention through the mediate variables.

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