• Korean Journal of Organic Agriculture
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• v.26 no.3
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• pp.327-349
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• 2018

The purpose of the study focuses on the agriculture education services in the changing rural areas conditions such as population decline, aging society, and returning farmers. The study reviews the effects of agricultural education services on returning farmers and local residents for satisfaction, intention for recommendation, and intention to continue participation. Further, the study aims to investigate any difference in the level of satisfaction for two groups. The results suggested that there is a meaningful difference between return-farmers and local residents. Among the demographic variables, age and income showed a notable difference. However, sex, level of education and type of household did not suggest noticeable differences. In addition, the study accessed agricultural education from a service perspective and analyzed its service quality and customer satisfaction, loyalty and relationship using a service profit chain model. Like the result of most other studies, the analysis showed that these had positive relationships. While the study focused on the efficiency of agriculture education training program in agriculture technology centers, the study carries a meaningful value in that it discovered a meaningful difference in the satisfaction level between returning farmers and locals despite the fact that agriculture education was applied as a part of service. In practical terms, the study pointed out the need for consumer-centered education that reflects the characteristics of the groups rather than standardized education.

• IE interfaces
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• v.17 no.4
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• pp.482-489
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• 2004

As the functional characteristics of passenger cars have reached to a satisfactory level, customers place more concerns with the aesthetic aspects of interior designs. The present study developed satisfaction models of passenger car interior materials for six parts including crash pad, steering wheel, transmission gearshift knob, audio panel, metal grain, and wooden grain. Eight to fifteen material design variables such as color, embossing, and smoothness were defined for the six interior parts based on literature survey, customer reviews, and expert opinions. A satisfaction survey was conducted for 30 vehicles with 30 participants ($mean{\pm}SD$ of age = $28.7{\pm}6.6$) by using a modified magnitude estimation scale. Based on the survey results, the material design variables were screened from statistical, technical, and practical aspects. With the screened variables, satisfaction models were developed by using the quantification I method for the six interior parts, indicating the importance of material design variables and preferred material properties.

• Journal of Distribution Science
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• v.16 no.10
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• pp.5-21
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• 2018

Purpose - This case study reviews the development history of Lotte Shopping, which has played a key role in modernizing Korea's retail industry. Research design, data, and methodology - Lotte Shopping's expansion to various channel types has been reviewed from the perspective of the resource-based view of strategy. The opening of Lotte Department Store in 1979 signaled the beginning of the modernized distribution system in Korea. Lotte Shopping expanded its business domains to various types of retail channels, such as discount stores, online shopping malls, TV home shopping, convenience stores, supermarkets, home appliances specialty stores and health & beauty stores. Results - Lotte Shopping has been able to maintain high level of customer satisfaction with leading merchandising skills. It has developed mutually beneficial relationship with the partner firms. It has also been a leading firm in implementing corporate social responsibility activities and environment-friendly management. Lotte Shopping has applied advanced information and communication technology to provide customized goods/services. Conclusions - This study summarizes the business environment and new challenges Lotte Shopping faces currently. Lotte Shopping is trying to reinforce the omni-channel strategy, which can create synergy among various distribution channels based on its core competences.

• Journal of Korean Society for Quality Management
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• v.44 no.2
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• pp.265-276
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• 2016

Purpose: This paper reviews the papers on service quality issues which are published in the Journal of the Korean Society for Quality Management (KSQM) since 1965. The literature review is purposed to survey a variety of service quality issues for several categories in terms of industry as well as research model. Methods: By use of the double diamond design process model 71 papers are analyzed 4 stages which are discover, define, develop and deliver. And all of service quality issues are classified into 4 categories: service factory, mass service, service shop and professional service by the service process matrix typology. Results: According to this review, there are several features of research trends. There are 'from physical service to information-intensive service pattern' and 'from private sector to public sector pattern'. And the Kano model has been a steady-selling model to measure the service quality as like a SERVQUAL. Another meaningful issue was a convergency of the research method and tools such as BSC, CRM, AHP, DEA, Information System, Systgem Dynamics and 6 Sigma. Conclusion: The review paper is expected to provide future direction to improve service quality theories and applications. There are three future research topics: Application area, measurement model and research purpose.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.44-58
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• 2017

The purpose of this study is to prove the Korean Internet company, Kakao's resilience capacity. For it, this paper reviews the previous literatures regarding Kakao's business models and discusses 'resilience' theory. Then, it organizes the research questions based on the theoretical background and explains the research methodology. It investigates the case of Kakao's business and organization. The case analysis shows that five levers of resilience are a good indicator for a successful platform business evolution. The five levers are composed of coordination, cooperation, clout, capability, and connection: First lever, coordination that makes the company to restructure its silo governance in order to respond to actual business flow starting from the basic asset like game and music content; second lever, cooperation where the firm provides creative people with playground for startups such as KakaoPage; third lever, clout where the company shares its data by opening its API of AI and chatbot to $3^{rd}$ party developers; fourth lever, capability where the firm establishes AI R&D center, KakaoBrain as the function of multi-domain generalist for developing diverse platforms tackling customer needs; and the last fifth lever, connection where the firm continues to expand its platform business to the peripheries, O2O businesses such as KakaoTaxi, KakaoOrder, KakaoPay, and KakaoBank. In conclusion, this study proposes Internet companies to be a resilient platform utilizing those five levers of resilience in order to form successful platform. This study contributes to the agile innovation of Internet platform with ecological sense.

• The Journal of Information Systems
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• v.14 no.1
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• pp.67-85
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• 2005

This study is to find out empirically the success factors on the development stages of e-business in Korean enterprises, to formulate e-business strategy and to decide e-business policy. For this purpose, the study reviews the conceptual framework on the success factors for the development stages of e-business and the data is collected from 304 companies implementing e-business. The study is conducted in three ophases an follows; First, according to this study, the development stage of e-business in Korean Enterprises is between 'Information Access Stage' and 'Core Business Transaction Stage'. Second, four factors comsisted of 29 items derived from factor analysis are named as 'Environmental Adaptation','Customer Relationship management','Marketing' and 'Environment of Organization'. Third, the success factors of first stage(Information Access Statge) include 'Marketing' and 'Environmental Adapotation', the success factors of second stage(Electronic Collaboration Stage) include 'Environmental Adaptation' and 'Environment of Organization' and the success factor of third stage(Core Business Transaction Stage) include 'Environment of Organization'. The results of this study show that; 1) the Korean enterprise seems to be in the Electronic Collaboration Stage of e-business development, and 2) the success factors are 'Marketing' for first stage, 'Environmental Adaptation' for second stage, and 'Environment of Organization' for third stage.

• Annual Conference on Human and Language Technology
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• 2008.10a
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• pp.58-62
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• 2008

인터넷 상에서 상품을 구입할 때 고려하는 부분 중의 하나가 상품평이다. 하지만 이러한 상품평들을 개인이 일일이 확인 하는데에는 상당한 시간이 소요된다. 이러한 문제점을 줄이기 위해서 본 논문에서는 인터넷 상의 상품평에 대한 의견을 긍정, 부정, 일반으로 나누는 시스템을 제안한다. 제안 시스템은 CRFs 기계학습모델을 기반으로 하며, 연결어미, 형태소 유니그램, 슬라이딩 윈도우 기법의 형태소 바이그램을 자질로 사용한다. 실험을 위해서 가격비교 사이트의 모니터 카테고리에서 561개의 상품평을 수집하였다. 이 중 465개의 상품평을 학습 문서로 사용하였고 96개의 상품평을 실험 문서로 사용하였다. 제안 시스템은 실험결과 79% 정도의 정확도를 보였다. 추가 실험으로 제안 시스템이 사람들과 얼마나 비슷한 성능을 보이는지 알아보기 위해서 카파 테스트를 실시하였다. 카파 테스트를 실시한 결과, 사람간의 카파 계수는 0.6415였으며, 제안 시스템과 사람 간의 카파 계수는 평균 0.5976이였다. 결론적으로 제안 시스템이 사람보다는 떨어지지만 유사한 정도의 성능을 보임을 알 수 있었다.

• Annual Conference on Human and Language Technology
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• 2013.10a
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• pp.53-58
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• 2013

온라인 소비자들은 amazon.com과 같은 온라인 상점 플랫폼에 상품 평가(리뷰: review) 글을 남김으로써 대상 상품에 대한 의견을 표현한다. 이러한 상품 리뷰는 다른 소비자들의 구매 결정에도 큰 영향을 끼친다는 관점에서 볼 때, 매우 중요한 정보원이라고 할 수 있다. 사람들이 남긴 의견 정보(opinion)를 자동으로 추출하거나 분석하고자 하는 연구인 감성 분석(sentiment analysis)분야에서 과거에 진행된 대다수의 연구들은 크게는 문서 단위에서 작게는 상품의 요소(aspect) 단위로 사용자들이 남긴 의견이 긍정적 혹은 부정적 감정을 포함하고 있는지 분석하고자 하였다. 이렇게 소비자들이 남긴 의견이 대상 상품 혹은 상품의 요소를 긍정적 혹은 부정적으로 판단했는지 여부를 판단하는 것이 유용한 경우도 있겠으나, 본 연구에서는 소비자들이 '어떤 관점'에서 대상 상품 혹은 상품의 요소를 평가했는지를 자동으로 추출하는 방법에 초점을 두었다. 본 연구에서는 형용사의 대표적인 성질 중 하나가 자신이 수식하는 명사의 속성에 값을 부여하는 것임에 주목하여, 수식된 명사의 속성을 추출하고자 하였고 이를 위해 WordNet을 사용하였다. 제안하는 방법의 효과를 검증하기 위해 3명의 평가자를 활용하여 실험을 하였으며 그 결과는 본 연구 방향이 감성분석에 있어 새로운 가능성을 열기에 충분하다는 것을 보여주었다.

• Knowledge Management Research
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• v.20 no.3
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• pp.139-154
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• 2019

With the increasing use of smartphone apps, many apps are coming out in various fields. In order to analyze the current status and trends of apps in a specific field, it is necessary to establish a classification scheme. Various schemes considering users' behavior and characteristics of apps have been proposed, but there is a problem in that many apps are released and a fixed classification scheme must be updated according to the passage of time. Although it is necessary to consider many aspects in establishing classification scheme, it is possible to grasp the trend of the app through the proposal of a classification scheme according to the characteristic of the app. This research proposes a method of establishing an app classification scheme through the description of the app written by the app developers. For this purpose, we collected explanations about apps in the tourism field and identified major categories through topic modeling. Using only the apps corresponding to the topic, we construct a network of words contained in the explanatory text and identify subcategories based on the networks of words. Six topics were selected, and Clauset Newman Moore algorithm was applied to each topic to identify subcategories. Four or five subcategories were identified for each topic.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.33-39
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• 2020

The paper is to build recommendation systems leveraging Deep Learning and Big Data platform, Spark to predict item ratings of the Amazon e-commerce site. Recommendation system in e-commerce has become extremely popular in recent years and it is very important for both customers and sellers in daily life. It means providing the users with products and services they are interested in. Therecommendation systems need users' previous shopping activities and digital footprints to make best recommendation purpose for next item shopping. We developed the recommendation models in Amazon AWS Cloud services to predict the users' ratings for the items with the massive data set of Amazon customer reviews. We also present Big Data architecture to afford the large scale data set for storing and computation. And, we adopted deep learning for machine learning community as it is known that it has higher accuracy for the massive data set. In the end, a comparative conclusion in terms of the accuracy as well as the performance is illustrated with the Deep Learning architecture with Spark ML and the traditional Big Data architecture, Spark ML alone.