• 품질경영학회지
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• 제47권2호
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• pp.327-344
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• 2019

Purpose: This study aims to conduct a systematic literature review to suitably identify wide and specific issues and topics on service quality in supply chain. Methods: This study is to investigate service quality in supply chain research using a systematic literature review methodology. In order to extract influential journals and papers, we used the SJR impact factor provided by the SCOPUS database. The collected 169 papers were analyzed using bibliometric analysis, citation analysis as well as keywords network. Results: We conducted a bibliometric analysis to identify top authors contributing to service quality in supply chain and their issues, and further examined important keywords and new emerging keywords. In addition, we extracted five influential papers by PageRank to clarify critical issues and divided into five clusters to identify topics of service quality in supply chain by using network-based approach. In order to examine comprehensive issues and topics of service quality in supply chain, we constructed a keyword network to observe difference in the classification of important keywords across network centrality measures. Conclusion: Our study reviewed literature on service quality in supply chain and explored the future directions and trends of service quality in supply chain.

• 품질경영학회지
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• 제47권2호
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• pp.381-395
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• 2019

Purpose: This study aims to conduct a systematic literature review to suitably identify wide and specific issues and topics on service quality in supply chain. Methods: This study is to investigate service quality in supply chain research using a systematic literature review methodology. In order to extract influential journals and papers, we used the SJR impact factor provided by the SCOPUS database. The collected 169 papers were analyzed using bibliometric analysis, citation analysis as well as keywords network. Results: We conducted a bibliometric analysis to identify top authors contributing to service quality in supply chain and their issues, and further examined important keywords and new emerging keywords. In addition, we extracted five influential papers by PageRank to clarify critical issues and divided into five clusters to identify topics of service quality in supply chain by using network-based approach. In order to examine comprehensive issues and topics of service quality in supply chain, we constructed a keyword network to observe difference in the classification of important keywords across network centrality measures. Conclusion: Our study reviewed literature on service quality in supply chain and explored the future directions and trends of service quality in supply chain.

• 대한인간공학회지
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• 제33권1호
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• pp.69-76
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• 2014

Objective: This study aims to present literature providing researchers with insights on specific fields of research and highlighting the major issues in the research topics. A systematic review is suggested using content analysis on literatures regarding "visual search", "eye movement", and "eye track". Background: Literature review can be classified as "narrative" or "systematic" depending on its approach in structuring the content of the research. Narrative review is a traditional approach that describes the current state of a study field and discusses relevant topics. However, since literatures on specific area cover a broad range, reviewers inherently give subjective weight on specific issues. On the contrary, systematic review applies explicit structured methodology to observe the study trends quantitatively. Method: We collected meta-data of journal papers using three search keywords: visual search, eye movement, and eye track. The collected information contains an unstructured data set including many natural languages which compose titles and abstracts, while the keyword of the journal paper is the only structured one. Based on the collected terms, seven categories were evaluated by inductive categorization and quantitative analysis from the chronological trend of the research area. Results: Unstructured information contains heavier content on "stimuli" and "condition" categories as compared with structured information. Studies on visual search cover a wide range of cognitive area whereas studies on eye movement and eye track are closely related to the physiological aspect. In addition, experimental studies show an increasing trend as opposed to the theoretical studies. Conclusion: By systematic review, we could quantitatively identify the characteristic of the research keyword which presented specific research topics. We also found out that the structured information was more suitable to observe the aim of the research. Chronological analysis on the structured keyword data showed that studies on "physical eye movement" and "cognitive process" were jointly studied in increasing fashion. Application: While conventional narrative literature reviews were largely dependent on authors' instinct, quantitative approach enabled more objective and macroscopic views. Moreover, the characteristics of information type were specified by comparing unstructured and structured information. Systematic literature review also could be used to support the authors' instinct in narrative literature reviews.

• 유통과학연구
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• 제18권10호
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• pp.65-75
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• 2020

Purpose: This study aims to examine how to review contents of experiential and utilitarian products (e.g., skincare products) and how to affect review helpfulness by applying natural language processing techniques. Research design, data, and methodology: This study uses 69,633 online reviews generated for the products registered at Amazon.com by 13 Korean cosmetic firms. The authors identify key topics that emerge about consumers' use of skincare products such as skin type and skin trouble, by applying bigram analysis. The review content variables are included in the review helpfulness model, including other important determinants. Results: The estimation results support the positive effect of review extremity and content on the helpfulness. In particular, the reviewer's skin type information was recognized as highly useful when presented together as a basis for high-rated reviews. Moreover, the content related to skin issues positively affects review helpfulness. Conclusions: The positive relationship between extreme reviews and helpfulness of reviews challenges the findings from prior literature. This result implies that an in-depth study of the effect of product types on review helpfulness is needed. Furthermore, a positive effect of review content on helpfulness suggests that applying big data analytics can provide meaningful customer insights in the online retail industry.

• 의학교육논단
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• 제19권3호
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• pp.158-168
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• 2017

There is a more urgent call for educational methods of machine learning in medical education, and therefore, new approaches of teaching and researching machine learning in medicine are needed. This paper presents a case using machine learning through text analysis. Topic modeling of news articles with the keyword 'asbestos' were examined. Two hypotheses were tested using this method, and the process of machine learning of texts is illustrated through this example. Using an automated text analysis method, all the news articles published from January 1, 1990 to November 15, 2016 in South Korea which included 'asbestos' in the title and the body were collected by web scraping. Differences in topics were analyzed by structured topic modelling (STM) and compared by press companies and periods. More articles were found in liberal media outlets. Differences were found in the number and types of topics in the articles according to the partisanship and period. STM showed that the conservative press views asbestos as a personal problem, while the progressive press views asbestos as a social problem. A divergence in the perspective for emphasizing the issues of asbestos between the conservative press and progressive press was also found. Social perspective influences the main topics of news stories. Thus, the patients' uneasiness and pain are not presented by both sources of media. In addition, topics differ between news media sources based on partisanship, and therefore cause divergence in readers' framing. The method of text analysis and its strengths and weaknesses are explained, and an application for the teaching and researching of machine learning in medical education using the methodology of text analysis is considered. An educational method of machine learning in medical education is urgent for future generations.

• 복식
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• 제57권5호
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• pp.123-139
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• 2007

Since the late 1980's, the number of research papers published in the Journal of the Korean Society of Costume(JKSC) has increased. The JKSC is usually known for its focus on issues relevant to the aesthetics of dress, fashion design, and the history of Western or Oriental dress. The main goal of this paper is to link the academic importance of the fashion marketing field to the expansion of the journal and society. First, we defined the scope of the fashion marketing field, based on a literature review and general practices of other competitive societies and journals. First, we reviewed the curricula of the fashion marketing field from 49 universities in Korea. Next, we examined the research topics and methodology of 271 papers in the fashion marketing field published in JKSC since its first issue in 1977. By comparing the findings from the curricula and research, we drew conclusions for the fashion marketing field of the journal and society. We found that the approximately 80% of the fashion marketing courses provided at the undergraduate level are related to merchandise planning and selling processes from the company perspective. However, in more than 85% of the research papers, consumer characteristics and decision-making processes were the main focus and were used as key variables. These findings imply that more various methodological approaches are required for the research to enrich the theoretical background which, in turn, can support curricular development in fashion marketing field. The fashion marketing field in JKSC and society should make the most of accumulated knowledge in product design, symbolic aspects of fashion, and the qualitative approach in the research topics of the JKSC and society.

• 한국정보시스템학회지:정보시스템연구
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• 제27권4호
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• pp.1-33
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• 2018

Purpose The purpose of this study is to review topic and survey methodological trends in 'The Journal of Information Systems' in order to present the practical guidelines for the future IS research. By attempting to conduct a meta-analysis on both topic and survey methodological trends, this study could provide researchers wishing to pursue this line of work further with what can be done to improve IS disciplines. Design/methodology/approach In this study, we have reviewed 185 papers that were published in 'The Journal of Information Systems' from 2010 to 2018 and classified them based on topics studied and survey methodologies used. The classification guidelines, which was developed by Palvia et al.(2015), has been used to capture the topic trends. We have also employed Struab et al.(2004)s' guidelines for securing rigor of validation issues. By using two guidelines, this study could also present topic and rigor trends in 'The Journal of Information Systems' and compare them to those trends in International Journals. Findings Our findings have identified dominant research topics in 'The Journal of Information Systems'; 1) social media and social computing, 2) IS usage and adoption, 3) mobile computing, 4) electronic commerce/business, 5) security and privacy, 6) supply chain management, 7) innovation, 8) knowledge management, and 9) IS management and planning. This study also could offer researchers who pursue this line of work further practical guidelines on mandatory (convergent and discriminant validity, reliability, and statistical conclusion validity), highly recommended (common method bias testing), and optional validations (measurement invariance testing for subgroup analysis, bootstrapping methods for testing mediating effects).

• 무역학회지
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• 제48권1호
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• pp.55-81
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• 2023

본 연구의 목적은 한국 무역의 주요 이슈와 동향을 분석하고 향후 무역규범 연구에 대한 시사점을 도출하는데 있다. 분석자료로서 Korean Journal Citation Index 데이터베이스에서 2000년부터 2022년 7월까지 'Trade Rules'로 검색된 영문 키워드로 총 476개의 학술지를 분석하였다. 분석 방법으로는 동시발생네트워크와 텍스트마이닝 방법의 하나인 토픽트렌드 분석이 있다. 분석 결과, 최근 한국 무역을 대표하는 키워드는 연구 저널 수가 급증한 카테고리인 Topic 4(투자조약), Topic 7(무역안보), Topic 8(중국 보호무역주의), Topic 11(무역결제) 4가지로 나타났다. 이들 주제의 주요 배경은 기존의 국제무역 체제를 위협하는 미국과 중국 간의 무역마찰이며, 중국의 보호주의, 무역 안보 시스템의 변화, 새로운 투자 협정, 지불 방법의 변화에 대한 상세한 연구는 가까운 장래에 도전 과제가 될 것이다.

• 한국가정과교육학회지
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• 제21권3호
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• pp.143-161
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• 2009

본 연구는 지난 20년 동안에 한국가정과교육학회지에 실린 인간발달과 가족분야에 관한 논문을 교과교육학(가정과교육철학과 교사의 전문성, 가정과교육과정, 가정과교수 학습자료 개발 및 활용)과 교과내용학(인간발달, 가족학)으로 나누어 연구주제, 연구방법 측면에서 분석하여 연구동향과 성과를 파악하고, 향후 연구의 방향을 제시하고자 하였다. 총 93편의 논문을 5영역에서 분석한 연구결과는 다음과 같다. 첫째, 가정과교육철학과 교사의 전문성 연구는 다른 주제의 연구에 비해 연구가 매우 부족하였으며, 주로 가정과 교육의 본질에 대한 연구가 이루어졌고 가정교과의 당위성을 나타내었다. 둘째, 가정과 교육과정의 이해 연구는 최근 들어 연구가 크게 증가하고 있으며, 가정과 교육과정의 체계, 가정과 교육과정과 수업과의 관계, 가정과 교육과정의 개발에 대한 연구가 이루어졌으나, 주된 연구는 가정교과 교과서 내용 분석에 관한 연구였다. 이론을 적용하여 교과서를 분석한 연구는 매우 적었고, 주로 출판사별로 비교하거나 외형적인 분석을 하고 교과내용의 구성을 연구한 경우가 많았다. 셋째, 가정과 교수 학습 및 평가에 관한 연구는 가정과 교수 학습자료 개발 및 활용과 교수 학습방법과 실제에 관한 연구가 다수를 차지하고 있었다. 그러나 상대적으로 가정과 평가방법과 실제에 관한 연구는 매우 부족한 실정이었다. 따라서 앞으로의 가정과 교과교육학의 발전을 위해 가정과 평가에 대한 연구가 더욱 이루어져야 할 것으로 본다. 넷째, 인간발달과정에서 청소년기를 중심으로 발달 특성과 문제를 다루고, 부모됨과 부모역할에서 청소년기 자녀를 둔 부모역할을 주로 다루어 대부분의 연구가 청소년의 긍정적 발달을 위한 가정과 교육의 기초 자료를 제시하고자 하였다. 다섯째, 가족관계와 가족문제가 가장 많이 연구되었고 가족환경 특히, 부모와의 의사소통이 청소년의 학교적응과 심리적 적응에 긍정적인 관계를 보였다. 전체적으로, 교과교육과 관련된 연구가 교과내용에 관한 연구보다 적어 가정과 교육의 현장적용에 대한 연구가 앞으로 연구되어져야 한다. 또한 편의표집으로 설문지를 통한 한사람의 응답으로만 수행된 조사연구가 많아 다양한 연구방법, 현장적용연구의 확대 등의 문제는 향후연구가 극복해야 할 과제로 나타났다.

• 한국정보시스템학회지:정보시스템연구
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• 제30권4호
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• pp.277-301
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• 2021

Purpose The purpose of this study is to analyze the sentiment responses of the general public to non-face-to-face work using text mining methodology. As the number of non-face-to-face complaints is increasing over time, it is difficult to review and analyze in traditional methods such as surveys, and there is a limit to reflect real-time issues. Approach This study has proposed a method of the research model, first by collecting and cleansing the data related to non-face-to-face work among tweets posted on Twitter. Second, topics and keywords are extracted from tweets using LDA(Latent Dirichlet Allocation), a topic modeling technique, and changes for each section are analyzed through DTM(Dynamic Topic Modeling). Third, the complaints of non-face-to-face work are analyzed through the classification of positive and negative polarity in the COVID-19 section. Findings As a result of analyzing 1.54 million tweets related to non-face-to-face work, the number of IDs using non-face-to-face work-related words increased 7.2 times and the number of tweets increased 4.8 times after COVID-19. The top frequently used words related to non-face-to-face work appeared in the order of remote jobs, cybersecurity, technical jobs, productivity, and software. The words that have increased after the COVID-19 were concerned about lockdown and dismissal, and business transformation and also mentioned as to secure business continuity and virtual workplace. New Normal was newly mentioned as a new standard. Negative opinions found to be increased in the early stages of COVID-19 from 34% to 43%, and then stabilized again to 36% through non-face-to-face work sentiment analysis. The complaints were, policies such as strengthening cybersecurity, activating communication to improve work productivity, and diversifying work spaces.