• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 추계학술발표대회
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• pp.1114-1115
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• 2023

이 논문은 해양 안전 및 보트 운항 훈련을 위한 소형선박 시뮬레이터의 개발을 다룬다. 시뮬레이터는 자유 운항, 시험 모드 운항, 초급자 훈련 모드 운항 등 다양한 기능을 제공하며, 사용자의 실력과 선호도에 따라 맞춤 교육을 제공한다. 이를 통해 보트 운항의 안전성을 향상시키고, 비용 효율적인 방법으로 많은 사용자들에게 접근 가능한 학습 도구를 제공한다.

• 융합경영연구
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• 제9권1호
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• pp.1-14
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• 2021

Purpose: The article deals with the proposition that consumers' fashion consumption behavior will still follow the consumption behavior of fast fashion, despite recognizing the importance of slow fashion. Research design, data and methodology: The research model to verify this proposition is topic modelling with big data including unstructured textual data. we combined 5,506 news articles posted on Naver news search platform during the 2003-2019 period about fast fashion and slow fashion, high-frequency words have been derived, and topics have been found using LDA model. Based on these, we examined consumers' perception and consumption behavior on slow fashion through the analysis of Topic Network. Results: (1) Looking at the status of annual article collection, consumers' interest in slow fashion mainly began in 2005 and showed a steady increase up to 2019. (2) Term Frequency analysis showed that the keywords for slow fashion are the lowest, with consumers' consumption patterns continuing around 'brand.' (3) Each topic's weight in articles showed that 'social value' - which includes slow fashion - ranked sixth among the 9 topics, low linkage with other topics. (4) Lastly, 'brand' and 'fashion trend' were key topics, and the topic 'social value' accounted for a low proportion. Conclusion: Slow fashion was not a considerable factor of consumption behavior. Consumption patterns in fashion sector are still dominated by general consumption patterns centered on brands and fast fashion.

• 산경연구논집
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• 제11권2호
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• pp.25-31
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• 2020

Purpose: The AEO (Authorized Economic Operator) program, created in 2001 in the United States due to 9.11 terrorist's attack, fundamentally changed the trade environment. Korea, which introduced AEO program in 2009, has become one of the world's top countries in the program by ranking 6th in the number of AEO certified companies and the world's No. 1 in MRA (Mutual Recognition Agreement) conclusions. In this paper, we examined what trade-economic and non-economic effects the AEO program and its MRA have in Korea. Research design, data and methodology: In this study we developed a model to verify the impact between utilization of AEO and trade-economic effects of the AEO and its MRA. After analyzing the validity and reliability of the model through Structural Equation Model we conducted a survey to request AEO companies to respond their experience on the effects of AEO program and MRA. As a result, 196 responses were received from 176 AEO companies and utilized in the analysis. Results: With regard to economic effects, the AEO program and the MRA have not been directly linked to financial performance, such as increased sales, increased export and import volumes, reduced management costs, and increased operating profit margins. However, it was analyzed that the positive effects of supply chain management were evident, such as strengthening self-security, monitoring and evaluating risks regularly, strengthening cooperation with trading companies, enhancing cargo tracking capabilities, and reducing the time required for export and import. Conclusions: When it comes to the trade-economic effects of AEO program and its MRA, AEO companies did not satisfy with direct effects, such as increased sales and volume of imports and exports, reduced logistics costs. However, non-economic effects, such as reduced time in customs clearance, freight tracking capability, enhanced security in supply chain are still appears to be big for them. In a rapidly changing trade environment the AEO and MRA are still useful. Therefore the government needs to encourage non-AEO companies to join the AEO program, expand MRA conclusion with AEO adopted countries especially developing ones and help AEO companies make good use of AEO and MRA.

• 한국IT서비스학회지
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• 제21권5호
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• pp.15-28
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• 2022

Recently, government agencies are actively adopting the platform model as a means of public policy. However, existing studies on the public platform are minimal and have focused on user experiences or the possibility of public usage of the platform model. Now the research concerning building governance structure and utilizing network effects of the platform after adopting the platform model in the public sector is keenly required. This study intended to ignite academic dialogue on the governance of public platforms in the context of digital transformation. This study focused on a case of the 'Special delivery,' a public delivery app established by Gyeonggi-do. In order to analyze the characteristics of the public platform and its governance structure, data were collected from press releases, policy reports, and news articles. Data was analyzed using the frame of Hagui's platform design factors and Ansell & Gash's collaborative governance model. The results of the public platform analyses showed 1) incompleteness in the value trade-off accounting, which was designed for platform business based on general cost-benefit analysis, and 2) a closed governance structure that limits direct participation of diverse user groups(i.e., service provider, customer) in order to enhance providers' utility by preventing customers' excessive online activities. The results of this study provided theoretical and policy implications regarding designing the strategy for accounting for value trade-offs and functioning governance structure for public platforms.

• 유통과학연구
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• 제21권5호
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• pp.113-120
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• 2023

Purpose: The purpose of the study is to examine how payment systems for traditional distribution channels pursue changes and how they collaborate in-depth with fintech companies. This study examines the changing payment system through the strategic partnership between distribution companies and fintech companies. Research Design, Data and Methodology: The study conducted research using a variety of secondary materials and existing literature and also utilized the interview method. More specific and in-depth research is conducted through various literature studies and secondary data. Findings and Results: The findings of the study are as follows. First, distributors have occasionally directly adopted simple payment systems due to changes in payment systems as a result of online advances. Second, distributors were found to collaborate with fintech companies when not directly using simple payment. Conclusions: Such maneuvers by distributors are aimed at first, providing convenience and simplicity for consumers. Second, developing the ability to apply big data for accumulating consumer information and third, producing a customer lock-in effect by reducing the fees charged for existing payment services. The present study will provide many domestic and international distributors with a new perspective and practical implications in terms of the distribution and finance industries.

• 무역학회지
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• 제46권2호
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• pp.263-280
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• 2021

With the advent of the era of the 4th Industrial Revolution, various support policies and programs are being introduced as the promotion of startups related to the 4th industry is promoted as a core policy of the government. Based on major technologies such as Artificial Intelligence(AI), Big Data, Internet of Things(IoT), Blockchain, and Automation leading the 4th industrial revolution, logistics and distribution companies are expanding the range of markets and services provided. The purpose of this study is to examine the current status of startups in the logistics field based on major technologies of the 4th Industrial Revolution, which are rapidly growing at home and abroad, and suggest implications for revitalizing logistics startups through a policy demand survey. As a result of the study, in order to foster domestic logistics startups, we propose policy support for integration of logistics startups, integrated management of information, provision of physical space, network platform, and practical education and mentoring.

• 유통과학연구
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• 제19권4호
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• pp.25-35
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• 2021

Purpose: This study aims to analyze the factors affecting customer satisfaction in the customer reviews of omni-channel, posted on Internet blogs, cafes, and YouTube using text mining analysis. Research, data, and Methodology: In this study, frequency analysis is performed and the LDA (Latent Dirichlet Allocation) is used to analyze social big data to respond to reviewers' reaction to the recently opened omni-channel shopping reviews by L Shopping Company. Additionally, based on the topic analysis, we conduct a sentiment analysis on purchase reviews and analyze the characteristics of each topic on the positive or negative sentiments of omni-channel app users. Results: As a result of a topic analysis, four main topics are derived: delivery and events, economic value, recommendations and convenience, and product quality and brand awareness. The emotional analysis reveals that the reviewers have many positive evaluations for price policy and product promotion, but negative evaluations for app use, delivery, and product quality. Conclusions: Retailers can establish customized marketing strategies by identifying the customer's major interests through text mining analysis. Additionally, the analysis of sentiment by subject becomes an important indicator for developing products and services that customers want by identifying areas that satisfy customers and areas that evoke negative reactions.

• Journal of Korea Trade
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• 제24권7호
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• pp.1-28
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• 2020

Purpose - This paper empirically investigates the predictors and main determinants of consumers' ratings of mobile applications in the Google Play Store. Using a linear and nonlinear model comparison to identify the function of users' review, in determining application rating across countries, this study estimates the direct effects of users' reviews on the application rating. In addition, extending our modelling into a sentimental analysis, this paper also aims to explore the effects of review polarity and subjectivity on the application rating, followed by an examination of the moderating effect of user reviews on the polarity-rating and subjectivity-rating relationships. Design/methodology - Our empirical model considers nonlinear association as well as linear causality between features and targets. This study employs competing theoretical frameworks - multiple regression, decision-tree and neural network models - to identify the predictors and main determinants of app ratings, using data from the Google Play Store. Using a cross-validation method, our analysis investigates the direct and moderating effects of predictors and main determinants of application ratings in a global app market. Findings - The main findings of this study can be summarized as follows: the number of user's review is positively associated with the ratings of a given app and it positively moderates the polarity-rating relationship. Applying the review polarity measured by a sentimental analysis to the modelling, it was found that the polarity is not significantly associated with the rating. This result best applies to the function of both positive and negative reviews in playing a word-of-mouth role, as well as serving as a channel for communication, leading to product innovation. Originality/value - Applying a proxy measured by binomial figures, previous studies have predominantly focused on positive and negative sentiment in examining the determinants of app ratings, assuming that they are significantly associated. Given the constraints to measurement of sentiment in current research, this paper employs sentimental analysis to measure the real integer for users' polarity and subjectivity. This paper also seeks to compare the suitability of three distinct models - linear regression, decision-tree and neural network models. Although a comparison between methodologies has long been considered important to the empirical approach, it has hitherto been underexplored in studies on the app market.

• 정보관리학회지
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• 제35권1호
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• pp.13-32
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• 2018

본 연구의 목적은 빅데이터 연구 논문의 주제 분야 간의 연관관계를 분석하는데 있다. 동시 인용관계를 적용하여 분석 대상의 주제 분야를 추출하였으며, R 프로그램의 Apriori 알고리즘을 이용하여 연관관계의 규칙을 분석하고, arulesViz 패키지를 사용하여 시각화하였다. 연구 결과 22개 주제 분야가 추출되었는데, 이들 주제 분야는 3가지 군집으로 구분되었다. 주제 분야의 연관관계 유형을 분석한 결과, 연관관계의 복잡성에 따라 '전문형', '일반형', '확대형'으로 구분되었다. 전문형에는 문헌정보학, 신문방송학 등이 포함되었고, 일반형에는 정치외교학, 무역학, 관광학 등이 포함되었고, 확대형에는 기타인문학, 사회과학일반, 관광학일반 등이 포함되었다. 이 연관관계는 빅데이터 연구자가 한 주제분야를 인용할 때 관계가 있는 다른 주제 분야를 인용하는 경향을 보여주는 것으로, 도서관에서 학술정보서비스를 위해 연관관계를 활용한 서비스를 고려해야 할 필요가 있다.

• 한국건설관리학회논문집
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• 제18권6호
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• pp.13-25
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• 2017

아파트는 우리나라 전체 주택 중 상당 부분을 차지하는 중요한 거주형태이며 매년 증가하는 추세이다. 아파트는 일반 국민에게 주거용뿐만 아니라 수익 상품으로서의 가치를 지니며, 건설기업에게는 주요 상품, 정부에게는 공공 복지를 위한 중요한 수단중 하나이다. 따라서 아파트의 수요 트렌드를 이해하고 분석하는 것은 고객의 요구 가치에 대응하는 아파트 개발과 부동산 정책수립을 위해 중요한 현안이다. 본 연구의 목적은 주요 일간지의 뉴스기사를 빅데이터 소스로 설정하고 텍스트 마이닝 기법을 활용하여 아파트 수요 트렌드를 분석하고 주요 특징을 도출하는데 있다. 연구 결과, 빅데이터 분석을 통해 개발, 거래, 분양, 입지, 정책, 주거환경, 투자 수익 등 7개의 테마별로 아파트 수요 관련 17개 주요 트렌드가 도출되었다. 본 연구에서 제안된 연구방법론은 향후 건설산업 관련 연구에 빅데이터 분석을 접목시키는데 유용하게 활용될 수 있다.