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논문검색은 역시 페이퍼서치

정보시스템연구검색

The Journal of Information Systems


  • - 주제 : 사회과학분야 > 경영학
  • - 성격 : 학술지
  • - 간기: 계간
  • - 국내 등재 : KCI 등재
  • - 해외 등재 : -
  • - ISSN : 1229-8476
  • - 간행물명 변경 사항 :
논문제목
수록 범위 : 30권 1호 (2021)
6,000
초록보기
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.

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

임혜정 ( Lim Hyae Jung ) , 서창교 ( Suh Chang Kyo )
6,400
초록보기
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.

Word2Vec를 이용한 토픽모델링의 확장 및 분석사례

윤상훈 ( Yoon Sang Hun ) , 김근형 ( Kim Keun Hyung )
6,000
초록보기
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.

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

최승욱 ( Choi Seung Uk ) , 권오병 ( Kwon Oh Byung )
6,000
초록보기
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.

장노년층의 디지털기기 이용태도가 삶의 만족도에 미치는 영향 : 디지털기기 이용성과의 매개효과

김수경 ( Kim Su Kyoung ) , 신혜리 ( Shin Hye Ri ) , 김영선 ( Kim Young Sun )
6,000
초록보기
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.

디지털그림자노동의 분류와 동태성 및 연구 방향

이웅규 ( Lee Woong Kyu )
5,700
초록보기
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.

연관규칙 분석을 통한 ESG 우려사안 키워드 도출에 관한 연구

안태욱 ( Ahn Tae Wook ) , 이희승 ( Lee Hee Seung ) , 이준서 ( Yi June Suh )
6,700
초록보기
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’.

항공기 제조업에서 생산계획 동기화를 통한 데이터기반 구매조달 및 재고관리 방안 연구

유경열 ( Yu Kyoung Yul ) , 최홍석 ( Choi Hong Suk ) , 정대율 ( Jeong Dae Yul )
6,700
초록보기
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.

인플루언서 속성이 유튜브 정보수용과 구매의도에 미치는 영향

박소진 ( Park So Jin ) , 오창규 ( Oh Chang Gyu )
6,600
초록보기
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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