• Journal of Korean Academy of Nursing
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• v.23 no.3
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• pp.417-430
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• 1993

이 연구는 환경적 요소(간호사의 자율성, 조직의 표준화)와 개인의 특성(통제위, 나이, 경험. 간호역할개념, 도덕성), 직무 스트레스, 윤리적 의사결정 사이의 관계를 이론적 틀을 구성하여 테스트함으로써 그 인과관계를 탐구하였다. 본 연구를 위해 개발된 모형은 1) Katz와 Kahn의 조직에 대한 개방체계 이론(open systems theory of organization) ; 2) Kahn. Wolfe, Quinn, Snoek의 스트레스 이론 (theory of stress) : 3) Kohlberg의 도덕발달 이론(theory of moral develop-ment): 그리고 4) 여러 문헌고찰을 기초로 하였다. 본 연구의 모형은 2가지의 주요 종속변수(직무 스트레스, 윤리적 간호행위), 2가지 매개변수(간호 역할개념, 도덕성 발달정도) 그리고 여러 독립변수들(조직의 표준화, 자율성, 통제위, 교육, 나이, 경험 등)로 구성되었다. 간단히 말해, 간호사의 스트레스와 윤리적 간호행위 를 개인 자신과 환경이라는 두 요소의 결과로 간주한 것이다. 미국(2개주)의 여러 건강관리기관에 근무하는 224명의 정규 간호사를 대상으로 하였고. 가설 검증을 위하여 1) 변수간의 인과관계를 조사하기 위한 Linear Structural Relationships(LISREL)기법과 2) 나이, 경험, 교육이 변수간의 관계에 미치는 중간역할을 알아보기 위해 상관분석을 이용하였다. LISREL결과를 보면 제시된 모델이 각 내재 변수에 상당한 설명력을 가지면서 자료에 잘 맞는 것으로 나타났다. 이 연구에서 가장 뚜렷한 점으로 나타난 것은 개인의 특성보다 환경적 요소로서의 자율성이 직무스트레스와 윤리적 의사결정을 예견하는데 훨씬 중요한 변수로 부각되었다는 점이다. 또한 간호사의 전문적 역할개념과 봉사적 역할개념이 간호사의 윤리적 의사결정을 예견하는 가장 중요한 요소로 나타났다. 중간영향(moderation effect)을 보면, 젊고 경험이 적은 간호사일수록 나이가 많고 경험있는 간호사보다 환경적 요소(자율성)에 더 큰 영향을 받는다는 것을 암시하고 있다. 또한 4년제 대학 이상을 졸업한 간호사의 윤리 적 간호행 위 는 2, 3년제 를 졸업 한 간호사 보다 환경적 요소에 의해 덜 영향을 받는 것으로 나타났다. 한편 자율성의 부족은 2, 3년제 졸업 간호사보다 4년제 졸업 간호사에게 더 심한 스트레스가 되고 있음을 시사하였다. 이 연구의 결과로부터 적어도 다음과 같은 두 가지 실제적인 제언을 도출할 수 있다. 첫째, 이 연구는 환경적요소로서의 자율성이 다른 어떤 개인적인 요소보다 직무 스트레스를 예견하는 데 중요한 요소라는 것을 제시하였다. 이것은 간호행정가들에게, 간호사의 직무 스트레스를 감소시키기 위해선 “자율성”이 아주 중요히 다루어져야 한다는 것을 의미한다. 만일 간호사들의 직무스트레스가 그 개인의 복지에 큰 해가 되고 환자를 간호하는 데 직접적으로 관계된다면, 간호행정가는 그 조직의 직무체계를 다시 평가해서 일에 대한 새로운 설계가 필요한지를 파악해야 한다. 또한 이 연구는 직무를 다시 설계할 경우, 누구에게 먼저 촛점을 두고 시작해야 하는지를 밝혀주고 있다. 즉, 젊고 경험이 미숙한 간호사들에게 촛점을 두고 시작해야 하며, 작업환경의 가장 중요한 차원중의 하나인 사회적 지원(social support)을 조심스럽게 고려해 보아야 한다. 둘째, 간호사의 윤리적 간호행위를 높히기 위해 전문적 역할개념과 봉사적 역할개념이 재강조될 필요가 있다. 이 두 역할개념 들을 교육을 통하여 효과적으로 가르칠 필요가 있다고 본다. 이 두 개념들이 간호사의 바람직한 간호행 위에 영향을 미치는 가장 중요한 요소로 나타났기 때문이다. 또한, 본 연구결과에 따르면, 경험이 많을수록 일에 싫증을 느껴 바람직한 윤리적 간호행위가 감소되는 경향이 있었다. 따라서, 건강관리체제 (health care system) 안에서의 간호사의 역할이-전문직으로서의, 그리고 환자를 위한 옹호자로서의-학교와 임상에서 효과적으로 교육되어져야 한다고 본다. 간호사들의 역할에 대한 계속적인 교육이 학생은 물론 임상 간호사들에게도 실시되어져야 할 것이다. 미래연구의 방향을 제시해 보면 첫째로 연구의 일반화를 높히기 위해 더 많은 대상자를 포함시켜야 한다. 이는 여러 종류의 표본을 반드시 한번에 전부 포함시켜야 한다는 것을 의미하는 것이 아니고, 특정한 여러 표본들을 연속적으로 연구함으로서 이 목표를 성취할 수 있다고 생각한다. 둘째는 여러 construct들(윤리적 간호행위, 직무 스트레스, 간호 역할개념 등)에 대한 적절한 측정도구를 개발해야 한다. 측정도구를 개발하기 위해서는 풍부하고 세세한 통찰력을 제공하는 질적인 정보를 얻는 것이 선행되어야 한다. 셋째, 윤리적 간호행위와 직무 스트레스에 관한 연구를 증진시키기 위해 실험설계 및 종단적 연구(expel-imental, longitudinal design)가 시도될 필요가 있다. 마지막으로, 윤리적 간호행위와 직무 스트레스를 예견할 수 있는 이론적 탐구(theoretical exploration), 즉 이론정립을 위하여, 환경적 요소와 개인의 특성에 대한 자세한 정보를 제공해 줄 수 있는 질적 연구들이 요구된다.

• Journal of Radiation Protection and Research
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• v.40 no.4
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• pp.252-260
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• 2015

This paper describes the technical background for the Korean wildlife radiation dose assessment code, K-BIOTA, and the summary of its application. The K-BIOTA applies the graded approaches of 3 levels including the screening assessment (Level 1 & 2), and the detailed assessment based on the site specific data (Level 3). The screening level assessment is a preliminary step to determine whether the detailed assessment is needed, and calculates the dose rate for the grouped organisms, rather than an individual biota. In the Level 1 assessment, the risk quotient (RQ) is calculated by comparing the actual media concentration with the environmental media concentration limit (EMCL) derived from a bench-mark screening reference dose rate. If RQ for the Level 1 assessment is less than 1, it can be determined that the ecosystem would maintain its integrity, and the assessment is terminated. If the RQ is greater than 1, the Level 2 assessment, which calculates RQ using the average value of the concentration ratio (CR) and equilibrium distribution coefficient (Kd) for the grouped organisms, is carried out for the more realistic assessment. Thus, the Level 2 assessment is less conservative than the Level 1 assessment. If RQ for the Level 2 assessment is less than 1, it can be determined that the ecosystem would maintain its integrity, and the assessment is terminated. If the RQ is greater than 1, the Level 3 assessment is performed for the detailed assessment. In the Level 3 assessment, the radiation dose for the representative organism of a site is calculated by using the site specific data of occupancy factor, CR and Kd. In addition, the K-BIOTA allows the uncertainty analysis of the dose rate on CR, Kd and environmental medium concentration among input parameters optionally in the Level 3 assessment. The four probability density functions of normal, lognormal, uniform and exponential distribution can be applied.The applicability of the code was tested through the participation of IAEA EMRAS II (Environmental Modeling for Radiation Safety) for the comparison study of environmental models comparison, and as the result, it was proved that the K-BIOTA would be very useful to assess the radiation risk of the wildlife living in the various contaminated environment.

• 한국노년학
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• v.41 no.2
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• pp.217-240
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• 2021

The purpose of this study is to examine the effect of care workers' employment characteristics and perception of facility directors' transformational leadership on quality of service through a hierarchical linear model. For this aim, survey data were collected amongst 240 older adults and 200 care workers who are affiliated within 45 long-term care facilities in Seoul, and analyzed using SPSS 26.0 and HLM 8.0. As a result, one's perception of transformational leadership had a positive effect, whereas, among employment characteristics, employment type and working hours had negative effects on quality of service. Regular workers with fewer working hours and higher awareness of transformational leadership toward the director provided higher quality of service. But wage, total experience and tenure didn't meaningfully affect it. Therefore, the following suggestions were presented. First, it is necessary to reorganize incentive, salary systems and budgets, changing the status of temporary workers' hourly wage system into that of regular workers' monthly one in order to strengthen employment security with acknowledging fundamental professional values through reinforcement of expertise. Reinforcement of long-term care's publicness and establishment of base facilities are also suggested. Second, maintaining appropriate hours of work and rest including annual leave under the Labor Standards Act is needed. Also, increasing the salary of and decreasing working hours for night shift workers are required. Third, education and intervention for inspiring transformational leadership of directors and strengthening qualification standards of them are required.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.59-83
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• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.

• The Journal of Small Business Innovation
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• v.19 no.4
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• pp.19-39
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• 2016

With increasing adoption of smart products and complexity, companies have shifted their strategies from stand alone and competitive strategies to business ecosystem oriented and cooperative strategies. The win-win growth of business refers to corporate efforts undertaken by companies to pursue the healthiness of business between conglomerates and partnering companies such as suppliers for mutual prosperity and a long-term corporate soundness based on their business ecosystem and cooperative strategies. This study is designed to validate a theoretical proposition that the win-win growth strategy of Samsung Electronics and cooperative efforts among companies can create a healthy business ecosystem, based on results of case studies and surveys. In this study, a level of global market access of small and mid-sized companies is adopted as the key achievement index. The foreign market entry is considered as one of vulnerabilities in the ecosystem of small and mid-sized enterprises (SMEs). For SMEs, the global market access based on the research and development (R&D) has become the critical component in the process of transforming them into global small giants. The results of case studies and surveys are analyzed mainly based on a model of a virtuous cycle of Creativity, Opportunity, Productivity, and Proactivity (the COPP model) that features the characteristics of the healthiness of a business ecosystem. In the COPP model, a virtuous circle of profits made by the first three factors and Proactivity, which is the manifestation of entrepreneurship that proactively invests and reacts to the changing business environment of the future, enhances the healthiness of a given business ecosystem. With the application of the COPP model, this study finds major achievements of the win-win growth of Samsung Electronics as follows. First, Opportunity plays a role as a parameter in the relations of Creativity, Productivity, and creating profits. Namely, as companies export more (with more Opportunity), they are more likely to link their R&D efforts to Productivity and profitability. However, companies that do not export tend to fail to link their R&D investment to profitability. Second, this study finds that companies with huge investment on R&D for the future, which is the result of Proactivity, tend to hold a large number of patents (Creativity). And companies with significant numbers of patents tend to be large exporters as well (Opportunity), and companies with a large amount of exports tend to record high profitability (Productivity and profitability), and thus forms the virtuous cycle of the COPP model. In addition, to access global markets for sustainable growth, SMEs need to build and strengthen their competitiveness. This study concludes that companies with a high level of proactivity to invest for the future can create a virtuous circle of Creativity, Opportunity, Productivity, and Proactivity, thereby providing a strategic implication that SMEs should invest time and resources in forming such a virtuous cycle which is a sure way for the SMEs to grow into global small giants.

• Journal of Distribution Research
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• v.16 no.4
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• pp.29-64
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• 2011

Overview of Research: Product availability is one of important competences of store to fulfill consumer needs. If stock-outs which means a product what consumer wants to buy is not available occurs, consumer will face decision-making uncertainty that leads to consumer's negative responses such as consumer dissatisfaction on store. Stockouts was much studied in the field of academia as well as practice in other countries. However, stock-outs has not been researched at all in Marketing and/or Distribution area in Korea. The main objectives of this study are to find out determinants of consumer responses such as Substitute, Delay, and Leave(SDL) when consumer encounters out-of-stock situation and then to examine the effects of these factors on consumer responses. Specifically, this study focuses on situational characteristics(e.g., purchase urgency and surprise), store characteristics (e.g., product assortment and store convenience), and consumer characteristics (e.g., brand loyalty and store loyalty). Then, this study empirically investigates relationships these factors with consumers behaviors such as product substitution, purchase delay, and store switching.