• 한국가정과교육학회지
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• 제25권1호
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• pp.95-118
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• 2013

이 연구는 교육과정이 고시된 1차 교육과정부터 현 2009 개정 교육과정에 이르기까지 9회 시기의 가정과 교육과정 문서에서 주생활 영역과 관련된 내용이 어떻게 변화되어왔는지를 성격, 목표, 내용 체계를 중심으로 분석하는데 목적을 두고 있다. 자료는 국가교육과정 정보센터(NCIC) 홈페이지(http://www.ncic.re.kr/2012. 04. 08)의 교육과정 자료실에 탑재된 1차 교육과정(1955. 08)부터 2009 개정 교육과정(2012. 03)에서 중 고등학교 가정과(실업 가정과) 교육과정을 다운 받아 주생활 영역에 중점을 두어 내용을 추출하여 분석하였다. 시기별로 교육과정의 성격과 목표에서 주생활 영역을 살펴본 후, 주생활 내용 체계를 중 고를 나눠 대단원, 중단원, 소단원, 내용요소를 중심으로 분석하였다. 연구결과, 가정과 교육과정의 개정 시기를 거치면서 교과명, 교육목표, 교육내용, 이수범위, 학년별 시간 배당, 교육내용 선정 및 조직과 강조점이 변화하였다. 교과명은 실업(교수요목기)->실업 가정(1차교육과정)->실업 가정, 가정(2차~6차)->실과(7차 이후)로 변화하였다. 교육목표는 직업교육적 접근(1차~3차 교육과정)->보통 교육적 교양 교육적 접근(4차~7차)->비판적 접근(2007 개정 이후)으로 변화하였다. 가정과목의 이수는 여학생만 대상으로 하다가 6차 교육과정부터 남녀 공통이수로 변화하게 되었으며, 학년별 이수시간은 감소하였다. 교육내용은 노작교육의 형태에서 가족 및 일상생활과 가정과 관련된 직업을 이해할 수 있는 형태로 변화하였다. 둘째, 교과의 성격은 1차 교육과정에서는 제시되었으나 2차 교육과정 이후 5차 교육과정까지는 제시되지 않다가 6차 교육과정부터 중 고로 나눠 다시 제시되었고, 7차 교육과정부터는 고등학교 가정과학에서 주생활 영역의 성격을 따로 기술하고 있다. 셋째, 목표는 1차에서 5차 교육과정까지는 교과 목표와 과목 목표를 모두 제시하였고, 6차 교육과정에서는 가정 교과의 목표만 제시되었고, 7차 교육과정부터는 목표와 성격이 통합적으로 제시되었다. 2009 개정 교육과정에서는 일반적인 교육수준을 달성하기 위해 성취해야 하는 성취기준을 제시하면서 목표가 포함되어 기술되었다. 교육과정에 반영되는 시대적인 관점에 따라 제시되는 관점도 변화하였는데, 점차 사회적인 변화를 반영하는 목표가 설정된 가치관 교육으로 변화하였다. 넷째, 주생활 교육내용은 교육과정이 개정 될 때마다 지도범위의 증가와 감소 및 영역별 변화가 크게 나타났으며 사회적인 흐름이 반영되어 변화하였다. 중학교 수업시수의 감소와 함께 일부 학년으로의 집중현상과 영역별로 제시되었던 단원이 통합되어 나타나는 형태로 변화하였다. 환경에 대한 관심에 따라 친환경 주거, 코하우징, 유니버설 등 새로운 개념들이 도입되었고, 이웃과 더불어 살아가기 위한 주생활에 대한 인식이 확산되면서 사회 인간 환경에 대한 배려와 나눔에 관한 내용을 주요 학습내용으로 제시되면서 시대적인 흐름을 반영하고 있었다. 고등학교는 국민공통기본교육과정의 변화로 필수에서 선택이수로 변화하였고, 영역은 더 세분화되었다. 세계화의 흐름에 맞추어 다른 나라의 주생활 문화를 비교하는 내용이 등장하였으며 환경친화적인 가치관과 지속가능한 주생활 양식, 사회 인간 환경에 대한 배려와 나눔에 관한 내용이 제시되면서 사회적 관심사를 반영하고 있었다. 고등학교의 학습내용은 중학교의 학습내용에서 세분화되고 심화되어 구성되었으며, 고등학교는 중학교와 달리 주거와 개인을 대상으로 한 것이 아니라 그 범위가 확대되어 지역사회 및 환경, 주택 시장의 상황, 공동체적 삶까지 고려한 거시적인 관점으로 제시되었다.

• Asia pacific journal of information systems
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• 제21권1호
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• pp.103-122
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• 2011

Recently, numerous documents have been made available electronically. Internet search engines and digital libraries commonly return query results containing hundreds or even thousands of documents. In this situation, it is virtually impossible for users to examine complete documents to determine whether they might be useful for them. For this reason, some on-line documents are accompanied by a list of keywords specified by the authors in an effort to guide the users by facilitating the filtering process. In this way, a set of keywords is often considered a condensed version of the whole document and therefore plays an important role for document retrieval, Web page retrieval, document clustering, summarization, text mining, and so on. Since many academic journals ask the authors to provide a list of five or six keywords on the first page of an article, keywords are most familiar in the context of journal articles. However, many other types of documents could not benefit from the use of keywords, including Web pages, email messages, news reports, magazine articles, and business papers. Although the potential benefit is large, the implementation itself is the obstacle; manually assigning keywords to all documents is a daunting task, or even impractical in that it is extremely tedious and time-consuming requiring a certain level of domain knowledge. Therefore, it is highly desirable to automate the keyword generation process. There are mainly two approaches to achieving this aim: keyword assignment approach and keyword extraction approach. Both approaches use machine learning methods and require, for training purposes, a set of documents with keywords already attached. In the former approach, there is a given set of vocabulary, and the aim is to match them to the texts. In other words, the keywords assignment approach seeks to select the words from a controlled vocabulary that best describes a document. Although this approach is domain dependent and is not easy to transfer and expand, it can generate implicit keywords that do not appear in a document. On the other hand, in the latter approach, the aim is to extract keywords with respect to their relevance in the text without prior vocabulary. In this approach, automatic keyword generation is treated as a classification task, and keywords are commonly extracted based on supervised learning techniques. Thus, keyword extraction algorithms classify candidate keywords in a document into positive or negative examples. Several systems such as Extractor and Kea were developed using keyword extraction approach. Most indicative words in a document are selected as keywords for that document and as a result, keywords extraction is limited to terms that appear in the document. Therefore, keywords extraction cannot generate implicit keywords that are not included in a document. According to the experiment results of Turney, about 64% to 90% of keywords assigned by the authors can be found in the full text of an article. Inversely, it also means that 10% to 36% of the keywords assigned by the authors do not appear in the article, which cannot be generated through keyword extraction algorithms. Our preliminary experiment result also shows that 37% of keywords assigned by the authors are not included in the full text. This is the reason why we have decided to adopt the keyword assignment approach. In this paper, we propose a new approach for automatic keyword assignment namely IVSM(Inverse Vector Space Model). The model is based on a vector space model. which is a conventional information retrieval model that represents documents and queries by vectors in a multidimensional space. IVSM generates an appropriate keyword set for a specific document by measuring the distance between the document and the keyword sets. The keyword assignment process of IVSM is as follows: (1) calculating the vector length of each keyword set based on each keyword weight; (2) preprocessing and parsing a target document that does not have keywords; (3) calculating the vector length of the target document based on the term frequency; (4) measuring the cosine similarity between each keyword set and the target document; and (5) generating keywords that have high similarity scores. Two keyword generation systems were implemented applying IVSM: IVSM system for Web-based community service and stand-alone IVSM system. Firstly, the IVSM system is implemented in a community service for sharing knowledge and opinions on current trends such as fashion, movies, social problems, and health information. The stand-alone IVSM system is dedicated to generating keywords for academic papers, and, indeed, it has been tested through a number of academic papers including those published by the Korean Association of Shipping and Logistics, the Korea Research Academy of Distribution Information, the Korea Logistics Society, the Korea Logistics Research Association, and the Korea Port Economic Association. We measured the performance of IVSM by the number of matches between the IVSM-generated keywords and the author-assigned keywords. According to our experiment, the precisions of IVSM applied to Web-based community service and academic journals were 0.75 and 0.71, respectively. The performance of both systems is much better than that of baseline systems that generate keywords based on simple probability. Also, IVSM shows comparable performance to Extractor that is a representative system of keyword extraction approach developed by Turney. As electronic documents increase, we expect that IVSM proposed in this paper can be applied to many electronic documents in Web-based community and digital library.

• 경영정보학연구
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• 제16권3호
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• pp.161-177
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• 2014

기업신용등급은 금융시장의 신뢰를 구축하고 거래를 활성화하는데 있어 매우 중요한 요소로서, 오래 전부터 학계에서는 보다 정확한 기업신용등급 예측을 가능케 하는 다양한 모형들을 연구해 왔다. 구체적으로 다중판별분석(Multiple Discriminant Analysis, MDA)이나 다항 로지스틱 회귀분석(multinomial logistic regression analysis, MLOGIT)과 같은 통계기법을 비롯해, 인공신경망(Artificial Neural Networks, ANN), 사례기반추론(Case-based Reasoning, CBR), 그리고 다분류 문제해결을 위해 확장된 다분류 Support Vector Machines(Multiclass SVM)에 이르기까지 다양한 기법들이 학자들에 의해 적용되었는데, 최근의 연구결과들에 따르면 이 중에서도 다분류 SVM이 가장 우수한 예측성과를 보이고 있는 것으로 보고되고 있다. 본 연구에서는 이러한 다분류 SVM의 성능을 한 단계 더 개선하기 위한 대안으로 유전자 알고리즘(GA, Genetic Algorithm)을 활용한 최적화 모형을 제안한다. 구체적으로 본 연구의 제안모형은 유전자 알고리즘을 활용해 다분류 SVM에 적용되어야 할 최적의 커널 함수 파라미터값들과 최적의 입력변수 집합(feature subset)을 탐색하도록 설계되었다. 실제 데이터셋을 활용해 제안모형을 적용해 본 결과, MDA나 MLOGIT, CBR, ANN과 같은 기존 인공지능/데이터마이닝 기법들은 물론 지금까지 가장 우수한 예측성과를 보이는 것으로 알려져 있던 전통적인 다분류 SVM 보다도 제안모형이 더 우수한 예측성과를 보임을 확인할 수 있었다.

• Asia pacific journal of information systems
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• 제23권3호
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• pp.25-53
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• 2013

This study analyzes the effect of Computer Aided Innovation (CAI) to improve R&D Capabilities empirically. Survey was distributed by e-mail and Google Docs, targeting CTO of 235 SMEs. 142 surveys were returned back (rate of return 60.4%) from companies. Survey results from 119 companies (83.8%) which are effective samples except no-response, insincere response, estimated value, etc. were used for statistics analysis. Companies with less than 50billion KRW sales of entire researched companies occupy 76.5% in terms of sample traits. Companies with less than 300 employees occupy 83.2%. In terms of the type of company business Partners (called 'partners with big companies' hereunder) who work with big companies for business occupy 68.1%. SMEs based on their own business (called 'independent small companies') appear to occupy 31.9%. The present status of holding IT system according to traits of company business was classified into partners with big companies versus independent SMEs. The present status of ERP is 18.5% to 34.5%. QMS is 11.8% to 9.2%. And PLM (Product Life-cycle Management) is 6.7% to 2.5%. The holding of 3D CAD is 47.1% to 21%. IT system-holding and its application of independent SMEs seemed very vulnerable, compared with partner companies of big companies. This study is comprised of IT infra and IT Utilization as CAI capacity factors which are independent variables. factors of R&D capabilities which are independent variables are organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability. The highest average value of variables was 4.24 in organization capability 2. The lowest average value was 3.01 in IT infra which makes users access to data and information in other areas and use them with ease when required during new product development. It seems that the inferior environment of IT infra of general SMEs is reflected in CAI itself. In order to review the validity used to measure variables, Factors have been analyzed. 7 factors which have over 1.0 pure value of their dependent and independent variables were extracted. These factors appear to explain 71.167% in total of total variances. From the result of factor analysis about measurable variables in this study, reliability of each item was checked by Cronbach's Alpha coefficient. All measurable factors at least over 0.611 seemed to acquire reliability. Next, correlation has been done to explain certain phenomenon by correlation analysis between variables. As R&D capabilities factors which are arranged as dependent variables, organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability turned out that they acquire significant correlation at 99% reliability level in all variables of IT infra and IT Utilization which are independent variables. In addition, correlation coefficient between each factor is less than 0.8, which proves that the validity of this study judgement has been acquired. The pair with the highest coefficient had 0.628 for IT utilization and technology-accumulating capability. Regression model which can estimate independent variables was used in this study under the hypothesis that there is linear relation between independent variables and dependent variables so as to identify CAI capability's impact factors on R&D. The total explanations of IT infra among CAI capability for independent variables such as organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability are 10.3%, 7%, 11.9%, 30.9%, and 10.5% respectively. IT Utilization exposes comprehensively low explanatory capability with 12.4%, 5.9%, 11.1%, 38.9%, and 13.4% for organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability respectively. However, both factors of independent variables expose very high explanatory capability relatively for technology-accumulating capability among independent variable. Regression formula which is comprised of independent variables and dependent variables are all significant (P<0.005). The suitability of regression model seems high. When the results of test for dependent variables and independent variables are estimated, the hypothesis of 10 different factors appeared all significant in regression analysis model coefficient (P<0.01) which is estimated to affect in the hypothesis. As a result of liner regression analysis between two independent variables drawn by influence factor analysis for R&D capability and R&D capability. IT infra and IT Utilization which are CAI capability factors has positive correlation to organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability with inside and outside which are dependent variables, R&D capability factors. It was identified as a significant factor which affects R&D capability. However, considering adjustable variables, a big gap is found, compared to entire company. First of all, in case of partner companies with big companies, in IT infra as CAI capability, organization capability, process capability, human resources capability, and technology capability out of R&D capacities seems to have positive correlation. However, collaboration capability appeared insignificance. IT utilization which is a CAI capability factor seemed to have positive relation to organization capability, process capability, human resources capability, and internal/external collaboration capability just as those of entire companies. Next, by analyzing independent types of SMEs as an adjustable variable, very different results were found from those of entire companies or partner companies with big companies. First of all, all factors in IT infra except technology-accumulating capability were rejected. IT utilization was rejected except technology-accumulating capability and collaboration capability. Comprehending the above adjustable variables, the following results were drawn in this study. First, in case of big companies or partner companies with big companies, IT infra and IT utilization affect improving R&D Capabilities positively. It was because most of big companies encourage innovation by using IT utilization and IT infra building over certain level to their partner companies. Second, in all companies, IT infra and IT utilization as CAI capability affect improving technology-accumulating capability positively at least as R&D capability factor. The most of factor explanation is low at around 10%. However, technology-accumulating capability is rather high around 25.6% to 38.4%. It was found that CAI capability contributes to technology-accumulating capability highly. Companies shouldn't consider IT infra and IT utilization as a simple product developing tool in R&D section. However, they have to consider to use them as a management innovating strategy tool which proceeds entire-company management innovation centered in new product development. Not only the improvement of technology-accumulating capability in department of R&D. Centered in new product development, it has to be used as original management innovative strategy which proceeds entire company management innovation. It suggests that it can be a method to improve technology-accumulating capability in R&D section and Dynamic capability to acquire sustainable competitive advantage.

• 한국식품영양과학회지
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• 제35권4호
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• pp.464-469
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• 2006

진주 채취 후 폐기되는 진주조개 육 및 패주를 기능성 식품의 추출소재 또는 가공품의 소재와 같이 효율적으로 이용하기 위한 기초 연구로서 진주조개 육 및 패주의 식품성분특성에 대하여 살펴보았다 진주조개 육의 중금속은 수은과 크롬의 경우 검출되지 않았고, 카드뮴의 경우 0.06 ppm, 납의 경우 0.11 prm이 검출되었다. 또한 패주의 경우 검토한 4종의 중금속이 모두 검출되지 않았다. 휘발성염기질소 함량과 pH는 진주조개 육의 경우 각각 11.6 mg/100 g 및 6.31이었고, 패주의 경우 각각 8.6 mg/100 g 및 6.33을 나타내었다. 이와 같은 결과로 미루어 보아 진주조개 패주 및 육은 식품가공 소재로서 식품위생적인 면에서 문제가 없었다. 패주의 조단백질 및 총 아미노산 함량은 각각 16.5%와 15.691 mg/100 g으로서, 진주조개 육(11.2% and 10,131 mg/100 g)과 대조구인 굴(12.1% and 11,213 mg/100 g)보다 높았으며, 칼슘과 인의 함량은 육이 각각 93.4mg/100g과 116.0mg/100g, 패주가 75.2 mg/100 g과 148.1 mg/100 g이었다. 유리아미노산과 taste value는 진주조개 육이 각각 635.5 mg/100 g과 40.2, 패주가 각각 734.9 mg/100 g과 24.1이었으나, 굴의 경우 각각 883.8 mg/100 g과 40.2로 진주 가공부산물보다 높은 수치를 나타내었다. 이상의 이화학적, 영양적 특성으로 살펴본 결과, 진주조개 패주는 육에 비하여 단백질 및 탄수화물, 총 아미노산 함량 및 무기질 함량이 높아 근육에 비하여 영양적인 면에서 식품 재자원으로서 우수하다고 판단되었다. 하지만 진주조개 패주 및 육은 굴이나 기타 패류에 비하여 맛 특성은 낮아 맛 추출 소재로는 부적절하다고 판단되었다.련이 필요한 것으로 사료된다. 세부속성별로는 "분위기가 조용하고 편안하다.", "불만이나 고충이 신속히 처리된다."라는 속성이 중점개선 영역에 포함되어 분위기와 고충처리 부분에 대한 개선을 위한 집중적인 노력이 필요한 것으로 분석되었고, "내부시설 및 기물이 쾌적하다.", "종업원이 친절하다." 항목은 유지관리 영역에 포함되기는 하였으나, 수행도 수준이 중요도에는 다소 못 미쳐 일부 개선이 필요한 것으로 사료된다. 전반적으로 기존의 일반 베이커리 연구들에서 나타난 선택속성 및 고객인지 중요도가 제품중심이었던 결과와는 달리 베이커리카페에 대해 고객이 인지하는 중요 선택속성은 제품, 서비스, 인테리어 등의 복합적인 요소가 포함되는 것으로 나타나 향후 베이커리카페 관련연구에서는 이러한 차이를 명확히 파악하고 연구를 전개해 나가야 할 것으로 사료된다. 또한 업체의 마케팅전략 수립에 있어서도 고씩의 욕구에 부응하기 위해 중요도와 수행도의 차이가 큰 선택속성 차원과 세부항목을 중점대상으로 하여 일반 베이커리와는 구분되는 방식으로 접근해야 할 것으로 판단된다. 이상의 결과를 종합해볼 때, 베이커리카페 이용고객은 특징적인 선택속성을 기준으로 베이커리카페를 선택하는 것으로 나타나 새로운 외식 산업 군인 베이커리카페의 조기정착과 발전을 위해서는 이러한 선택속성에 대한 이해를 바탕으로 활발한 연구가 진행되어야 할 것으로 사료된다. 또한 본 연구를 통해 도출된 선택속성 차원 중 많은 경우에 있어 고객이 인지하고 있는 중요도에 비해 수행도가 낮은 것으로 나타나 해당 차원의 개선을 위한 경영자들의 노력이 요구되어 진다. 체중군(0.82)에 비해 영양 질적 지수(INQ)가 높았으며(p<0.0335), 비타민 $B_1$은 정상 체중군이 유의적으로 가장 높은 영양 질적 지수를 보여주었다(p<0.0452). 이상의 결과로

• 마케팅과학연구
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• 제18권2호
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• pp.89-111
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• 2008

디지털 기술의 발전으로 일상생활에 접목시킨 스마트 의류 개발에 관한 연구가 활발히 진행되고 있으나, 실질적으로 착용하게 될 소비자의 인식이나 태도에 관한 연구가 이루어지지 않고 있다. 본 연구에서는 스마트의류의 지각된 혁신속성과 위험지각 차원이 제품 태도와 수용의도에 미치는 영향을 알아보고자 대학생을 대상으로 설문지법을 이용하여 조사하였다. 연구의 결과, 스마트의류의 지각된 혁신속성은 상대적 이점, 가시성, 복잡성의 3가지 요인으로, 지각된 위험은 신체/성과적 위험, 사회심리적 위험, 시간손실 위험, 경제적 위험 4가지 요인으로 추출되었다. 혁신특성 중 상대적 이점, 가시성이, 위험지각 중 사회심리적 위험과 경제적 위험이 제품 태도와 구매의도 예측에 주요한 변인으로 나타났다. 한편 사회심리적, 경제적 위험은 상대적이점과 복잡성을 설명하는데, 신체성과적, 사회심리적, 시간손실 위험은 가시성을 설명하는데 유의한 변인으로 나타났다. 제품 태도는 혁신특성과 구매 의도 사이에서는 부분매개 역할을, 위험지각과 구매의도 사이에서는 완전매개역할을 하는 것으로 나타났다. 본 연구는 스마트의류 구입 시 소비자가 인지하는 혁신특성과 지각된 위험의 유형을 파악함으로써 스마트의류 마케터들이 소비자의 긍정적인 태도 형성을 위한 마케팅 전략 수립 시 활용할 수 있는 기초 정보를 제시하였다.

• Journal of Nutrition and Health
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• 제47권1호
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• pp.77-88
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• 2014

본 연구는 기숙사 생활을 하는 제주지역 고등학생을 대상으로 기숙사급식 만족도와 급식에서 제공되는 메뉴에 대한 기호도를 조사 분석함으로써 기숙사 학생들의 다양한 요구와 필요에 부합하고 기숙사 급식의 질적 향상을 모색하기 위한 기초자료로 활용하고자 실시하였다. 조사대상 고등학생의 성별은 남자가 71.1%, 학년은 2학년 46.0%, 기숙사 거주기간이 2~3학기인 학생이 45.3%, 월평균 용돈은 3만원 미만이 39.0%, 동지역에 거주하는 학생이 68.3%로 나타났다. 방학 중 외식횟수는 한 달에 1~2회가 51.4%, 부모가 맞벌이를 하는 학생은 73.7%, 어머니의 학력은 고졸이 46.9%, 본인이 건강하다고 생각하는 학생은 60.3%로 나타났다. 조사대상의 기숙사급식 만족도에 있어서는 메뉴 품질에 대한 만족도 (3.26)보다 서비스 및 위생에 대한 만족도 (3.46)가 높았고, 메뉴 품질에 있어서는 주식 (밥)의 양 (3.70), 음식의 온도 (3.50), 음식의 신선도 (3.42), 음식의 맛 (3.14)의 순으로, 서비스 및 위생에 있어서는 급식 정보 제공 (3.66), 식당 분위기(3.53), 급식 위생 (3.48), 식사질서 지도 (3.43), 원활한 배식 (3.34), 조리종사자의 친절도 (3.33)의 순으로 나타났다. 조사대상 고등학생의 끼니별 급식 만족도는 저녁식사 (3.70), 점심식사 (3.50), 아침식사 (3.14)의 순으로 나타났으며, 성별에 있어서는 아침식사의 경우 여학생의 만족도 (3.36)가 남학생의 만족도 (2.93)보다 유의적으로 높게 나타났다 (p < .01). 조사대상이 기숙사급식에서 제공받은 음식의 섭취량을 끼니별로 분석한 결과 저녁식사 (3.70), 점심식사 (3.50), 아침식사 (3.14)의 순으로 나타났고 점심식사와 저녁식사는 남학생의 섭취량 (각 4.12, 4.17)이 여학생 (각 3.72, 3.76) 보다 유의적으로 많았다 (p < .001). 조사대상 고등학생의 기숙사급식에 대한 개선점에 있어서는 맛의 향상 (43.4%), 메뉴의 다양성 (31.0%), 배식량 증가 (17.4%), 급식위생 (3.8%), 급식환경 (3.3%)의 순으로 응답율을 보였고 남학생의 경우 맛의 향상 (49.2%), 메뉴의 다양성 (28.7%), 배식량 증가 (14.9%), 급식환경 (4.6%), 급식위생 (1.3%)의 순으로, 여학생은 메뉴의 다양성 (36.6%), 맛의 향상 (29.3%), 배식량 증가 (23.6%), 급식위생 (8.1%), 급식환경 (1.6%)의 순으로 나타났다 (p < .001). 조사대상의 주식류에 대한 기호도는 면류 (4.06), 일품음식류 (3.92), 밥류 (3.66)의 순으로 높게 나타났고 밥류에 있어서는 검정쌀밥 (3.80), 일품음식류는 볶음밥 (4.05), 면류에 있어서는 스파게티 (4.21)의 기호도가 가장 높게 나타났다. 국 및 찌개류에 대한 기호도는 갈비탕 (4.10), 김치찌개 (3.99), 된장찌개 (3.92), 순두부찌개 (3.79), 육개장 (3.78)의 순으로 나타났고 동태찌개 (2.72)와 북어국 (2.61)은 보통 이하의 기호도를 보였다. 조사대상의 부식류에 대한 기호도에 있어서는 찜류 (3.95), 튀김류 (3.87), 볶음류 (3.57), 김치류 (3.54), 구이류 (3.49), 조림류 (3.27)의 순으로 나타났고 무침류는 3점 미만인 2.89를 나타내 보통 이하의 기호도를 보였다. 메뉴 아이템에 있어서는 갈비찜 (4.24), 닭튀김 (4.23), 닭볶음 (4.19), 돈까스 (4.17), 탕수육 (4.10), 돼지고기볶음 (4.04)의 순으로 높은 기호도를 보였고, 5점 만점에 대해 4점 이상을 나타냈으며, 콩조림 (2.94), 시금치무침 (2.94), 애호박무침 (2.89), 느타리버섯볶음 (2.84), 생선구이 (2.81), 마늘쫑무침 (2.69), 취나물무침 (2.67), 청경채 겉절이 (2.71), 톳무침 (2.65), 생선조림 (2.63), 건파래 무침 (2.59)은 5점 만점에 대해 3점 미만을 나타내 보통 이하의 기호도를 보여 생선이나 채소류보다 육류를 이용한 음식에 대한 기호도가 높음을 알 수 있었다. 후식류에 있어서는 쥬스류의 기호도 (4.52)가 가장 높았고 요구르트 (4.50), 생과일 (4.42), 빵류 (4.33), 우유 (4.08), 떡류 (4.01)의 순으로 나타났으며 빵류 (p < .05) 와 떡류 (p < .01)에 대해 남학생보다 여학생의 기호도가 유의적으로 높게 나타났다. 조사대상의 메뉴 기호도는 기숙사급식 만족도 (r = 0.369), 메뉴 품질 (r = 0.348), 서비스 및 위생 (r = 0.344), 끼니별 급식 만족도 (r = 0.418), 제공된 음식 섭취량 (r = 0.220)과 정 (+)의 상관관계를 (p < .01), 기숙사급식 만족도는 메뉴품질 (r = 0.944), 서비스 및 위생 (r = 0.931), 끼니별 급식 만족도 (r = 0.707)와 다소 높은 정 (+)의 상관관계를 (p < .01), 메뉴품질은 서비스 및 위생 (r = 0.758), 끼니별 만족도 (r = 0.717)와 다소 높은 정 (+)의 상관관계를 (p < .01), 서비스 및 위생은 끼니별 급식 만족도 (r = 0.604)와 정 (+)의 상관관계를 나타냈다 (p < .01). 이상의 연구결과를 토대로 살펴볼 때, 기숙사급식에의 의존도가 높은 기숙사생들이 영양적으로 균형 있는 음식을 섭취하고 올바른 식습관을 형성할 수 있도록 다각적이고 체계적인 영양교육이 병행되어야 하며 배식량 및 배식방법 등을 개선하고 다양한 조리법 및 이벤트 메뉴 등을 개발하는 등 학생들이 성장기에 필요한 영양소를 충분히 섭취할 수 있도록 다양한 방안이 모색되어야 할 것으로 사료된다.

• Asia pacific journal of information systems
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• 제18권4호
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• pp.27-55
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• 2008

Due to the increasing and intensifying competition in the Internet shopping market, it has been recognized as very important to develop an effective policy and strategy for acquiring loyal customers. For this reason, web site designers need to know if a new Internet shopping mall(ISM) will be accepted. Researchers have been working on identifying factors for explaining and predicting user acceptance of an ISM. Some studies, however, revealed inconsistent findings on the antecedents of user acceptance of a website. Lack of consideration for individual differences in user ability is believed to be one of the key reasons for the mixed findings. The elaboration likelihood model (ELM) and several studies have suggested that individual differences in ability plays an moderating role on the relationship between the antecedents and user acceptance. Despite the critical role of user ability, little research has examined the role of user ability in the Internet shopping mall context. The purpose of this study is to develop a user acceptance model that consider the moderating role of user ability in the context of Internet shopping. This study was initiated to see the ability of the technology acceptance model(TAM) to explain the acceptance of a specific ISM. According to TAM. which is one of the most influential models for explaining user acceptance of IT, an intention to use IT is determined by usefulness and ease of use. Given that interaction between user and website takes place through web interface, the decisions to accept and continue using an ISM depend on these beliefs. However, TAM neglects to consider the fact that many users would not stick to an ISM until they trust it although they may think it useful and easy to use. The importance of trust for user acceptance of ISM has been raised by the relational views. The relational view emphasizes the trust-building process between the user and ISM, and user's trust on the website is a major determinant of user acceptance. The proposed model extends and integrates the TAM and relational views on user acceptance of ISM by incorporating usefulness, ease of use, and trust. User acceptance is defined as a user's intention to reuse a specific ISM. And user ability is introduced into the model as moderating variable. Here, the user ability is defined as a degree of experiences, knowledge and skills regarding Internet shopping sites. The research model proposes that the ease of use, usefulness and trust of ISM are key determinants of user acceptance. In addition, this paper hypothesizes that the effects of the antecedents(i.e., ease of use, usefulness, and trust) on user acceptance may differ among users. In particular, this paper proposes a moderating effect of a user's ability on the relationship between antecedents with user's intention to reuse. The research model with eleven hypotheses was derived and tested through a survey that involved 470 university students. For each research variable, this paper used measurement items recognized for reliability and widely used in previous research. We slightly modified some items proper to the research context. The reliability and validity of the research variables were tested using the Crobnach's alpha and internal consistency reliability (ICR) values, standard factor loadings of the confirmative factor analysis, and average variance extracted (AVE) values. A LISREL method was used to test the suitability of the research model and its relating six hypotheses. Key findings of the results are summarized in the following. First, TAM's two constructs, ease of use and usefulness directly affect user acceptance. In addition, ease of use indirectly influences user acceptance by affecting trust. This implies that users tend to trust a shopping site and visit repeatedly when they perceive a specific ISM easy to use. Accordingly, designing a shopping site that allows users to navigate with heuristic and minimal clicks for finding information and products within the site is important for improving the site's trust and acceptance. Usefulness, however, was not found to influence trust. Second, among the three belief constructs(ease of use, usefulness, and trust), trust was empirically supported as the most important determinants of user acceptance. This implies that users require trustworthiness from an Internet shopping site to be repeat visitors of an ISM. Providing a sense of safety and eliminating the anxiety of online shoppers in relation to privacy, security, delivery, and product returns are critically important conditions for acquiring repeat visitors. Hence, in addition to usefulness and ease of use as in TAM, trust should be a fundamental determinants of user acceptance in the context of internet shopping. Third, the user's ability on using an Internet shopping site played a moderating role. For users with low ability, ease of use was found to be a more important factors in deciding to reuse the shopping mall, whereas usefulness and trust had more effects on users with high ability. Applying the EML theory to these findings, we can suggest that experienced and knowledgeable ISM users tend to elaborate on such usefulness aspects as efficient and effective shopping performance and trust factors as ability, benevolence, integrity, and predictability of a shopping site before they become repeat visitors of the site. In contrast, novice users tend to rely on the low elaborating features, such as the perceived ease of use. The existence of moderating effects suggests the fact that different individuals evaluate an ISM from different perspectives. The expert users are more interested in the outcome of the visit(usefulness) and trustworthiness(trust) than those novice visitors. The latter evaluate the ISM in a more superficial manner focusing on the novelty of the site and on other instrumental beliefs(ease of use). This is consistent with the insights proposed by the Heuristic-Systematic model. According to the Heuristic-Systematic model. a users act on the principle of minimum effort. Thus, the user considers an ISM heuristically, focusing on those aspects that are easy to process and evaluate(ease of use). When the user has sufficient experience and skills, the user will change to systematic processing, where they will evaluate more complex aspects of the site(its usefulness and trustworthiness). This implies that an ISM has to provide a minimum level of ease of use to make it possible for a user to evaluate its usefulness and trustworthiness. Ease of use is a necessary but not sufficient condition for the acceptance and use of an ISM. Overall, the empirical results generally support the proposed model and identify the moderating effect of the effects of user ability. More detailed interpretations and implications of the findings are discussed. The limitations of this study are also discussed to provide directions for future research.

• Asia pacific journal of information systems
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• 제22권1호
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• pp.29-52
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• 2012

Consumers differ in the way they make a purchase. An audio mania would willingly make a bold, yet serious, decision to buy a top-of-the-line home theater system, while he is not interested in replacing his two-decade-old shabby car. On the contrary, an automobile enthusiast wouldn't mind spending forty thousand dollars to buy a new Jaguar convertible, yet cares little about his junky component system. It is product involvement that helps us explain such differences among individuals in the purchase style. Product involvement refers to the extent to which a product is perceived to be important to a consumer (Zaichkowsky, 2001). Product involvement is an important factor that strongly influences consumer's purchase decision-making process, and thus has been of prime interest to consumer behavior researchers. Furthermore, researchers found that involvement is closely related to perceived risk (Dholakia, 2001). While abundant research exists addressing how product involvement relates to overall perceived risk, little attention has been paid to the relationship between involvement and different types of perceived risk in an electronic commerce setting. Given that perceived risk can be a substantial barrier to the online purchase (Jarvenpaa, 2000), research addressing such an issue will offer useful implications on what specific types of perceived risk an online firm should focus on mitigating if it is to increase sales to a fullest potential. Meanwhile, past research has focused on such consumer responses as information search and dissemination as a consequence of involvement, neglecting other behavioral responses like online merchant selection. For one example, will a consumer seriously considering the purchase of a pricey Guzzi bag perceive a great degree of risk associated with online buying and therefore choose to buy it from a digital storefront rather than from an online marketplace to mitigate risk? Will a consumer require greater trust on the part of the online merchant when the perceived risk of online buying is rather high? We intend to find answers to these research questions through an empirical study. This paper explores the impact of enduring product involvement and perceived risks on required trust level, and further on online merchant choice. For the purpose of the research, five types or components of perceived risk are taken into consideration, including financial, performance, delivery, psychological, and social risks. A research model has been built around the constructs under consideration, and 12 hypotheses have been developed based on the research model to examine the relationships between enduring involvement and five components of perceived risk, between five components of perceived risk and required trust level, between enduring involvement and required trust level, and finally between required trust level and preference toward an e-tailer. To attain our research objectives, we conducted an empirical analysis consisting of two phases of data collection: a pilot test and main survey. The pilot test was conducted using 25 college students to ensure that the questionnaire items are clear and straightforward. Then the main survey was conducted using 295 college students at a major university for nine days between December 13, 2010 and December 21, 2010. The measures employed to test the model included eight constructs: (1) enduring involvement, (2) financial risk, (3) performance risk, (4) delivery risk, (5) psychological risk, (6) social risk, (7) required trust level, (8) preference toward an e-tailer. The statistical package, SPSS 17.0, was used to test the internal consistency among the items within the individual measures. Based on the Cronbach's ${\alpha}$ coefficients of the individual measure, the reliability of all the variables is supported. Meanwhile, the Amos 18.0 package was employed to perform a confirmatory factor analysis designed to assess the unidimensionality of the measures. The goodness of fit for the measurement model was satisfied. Unidimensionality was tested using convergent, discriminant, and nomological validity. The statistical evidences proved that the three types of validity were all satisfied. Now the structured equation modeling technique was used to analyze the individual paths along the relationships among the research constructs. The results indicated that enduring involvement has significant positive relationships with all the five components of perceived risk, while only performance risk is significantly related to trust level required by consumers for purchase. It can be inferred from the findings that product performance problems are mostly likely to occur when a merchant behaves in an opportunistic manner. Positive relationships were also found between involvement and required trust level and between required trust level and online merchant choice. Enduring involvement is concerned with the pleasure a consumer derives from a product class and/or with the desire for knowledge for the product class, and thus is likely to motivate the consumer to look for ways of mitigating perceived risk by requiring a higher level of trust on the part of the online merchant. Likewise, a consumer requiring a high level of trust on the merchant will choose a digital storefront rather than an e-marketplace, since a digital storefront is believed to be trustworthier than an e-marketplace, as it fulfills orders by itself rather than acting as an intermediary. The findings of the present research provide both academic and practical implications. The first academic implication is that enduring product involvement is a strong motivator of consumer responses, especially the selection of a merchant, in the context of electronic shopping. Secondly, academicians are advised to pay attention to the finding that an individual component or type of perceived risk can be used as an important research construct, since it would allow one to pinpoint the specific types of risk that are influenced by antecedents or that influence consequents. Meanwhile, our research provides implications useful for online merchants (both online storefronts and e-marketplaces). Merchants may develop strategies to attract consumers by managing perceived performance risk involved in purchase decisions, since it was found to have significant positive relationship with the level of trust required by a consumer on the part of the merchant. One way to manage performance risk would be to thoroughly examine the product before shipping to ensure that it has no deficiencies or flaws. Secondly, digital storefronts are advised to focus on symbolic goods (e.g., cars, cell phones, fashion outfits, and handbags) in which consumers are relatively more involved than others, whereas e- marketplaces should put their emphasis on non-symbolic goods (e.g., drinks, books, MP3 players, and bike accessories).

• Asia pacific journal of information systems
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• 제21권2호
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• pp.89-116
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• 2011

In collaborative tagging systems such as Delicious.com and Flickr.com, users assign keywords or tags to their uploaded resources, such as bookmarks and pictures, for their future use or sharing purposes. The collection of resources and tags generated by a user is called a personomy, and the collection of all personomies constitutes the folksonomy. The most significant need of the folksonomy users Is to efficiently find useful resources or experts on specific topics. An excellent ranking algorithm would assign higher ranking to more useful resources or experts. What resources are considered useful In a folksonomic system? Does a standard superior to frequency or freshness exist? The resource recommended by more users with mere expertise should be worthy of attention. This ranking paradigm can be implemented through a graph-based ranking algorithm. Two well-known representatives of such a paradigm are Page Rank by Google and HITS(Hypertext Induced Topic Selection) by Kleinberg. Both Page Rank and HITS assign a higher evaluation score to pages linked to more higher-scored pages. HITS differs from PageRank in that it utilizes two kinds of scores: authority and hub scores. The ranking objects of these pages are limited to Web pages, whereas the ranking objects of a folksonomic system are somewhat heterogeneous(i.e., users, resources, and tags). Therefore, uniform application of the voting notion of PageRank and HITS based on the links to a folksonomy would be unreasonable, In a folksonomic system, each link corresponding to a property can have an opposite direction, depending on whether the property is an active or a passive voice. The current research stems from the Idea that a graph-based ranking algorithm could be applied to the folksonomic system using the concept of mutual Interactions between entitles, rather than the voting notion of PageRank or HITS. The concept of mutual interactions, proposed for ranking the Semantic Web resources, enables the calculation of importance scores of various resources unaffected by link directions. The weights of a property representing the mutual interaction between classes are assigned depending on the relative significance of the property to the resource importance of each class. This class-oriented approach is based on the fact that, in the Semantic Web, there are many heterogeneous classes; thus, applying a different appraisal standard for each class is more reasonable. This is similar to the evaluation method of humans, where different items are assigned specific weights, which are then summed up to determine the weighted average. We can check for missing properties more easily with this approach than with other predicate-oriented approaches. A user of a tagging system usually assigns more than one tags to the same resource, and there can be more than one tags with the same subjectivity and objectivity. In the case that many users assign similar tags to the same resource, grading the users differently depending on the assignment order becomes necessary. This idea comes from the studies in psychology wherein expertise involves the ability to select the most relevant information for achieving a goal. An expert should be someone who not only has a large collection of documents annotated with a particular tag, but also tends to add documents of high quality to his/her collections. Such documents are identified by the number, as well as the expertise, of users who have the same documents in their collections. In other words, there is a relationship of mutual reinforcement between the expertise of a user and the quality of a document. In addition, there is a need to rank entities related more closely to a certain entity. Considering the property of social media that ensures the popularity of a topic is temporary, recent data should have more weight than old data. We propose a comprehensive folksonomy ranking framework in which all these considerations are dealt with and that can be easily customized to each folksonomy site for ranking purposes. To examine the validity of our ranking algorithm and show the mechanism of adjusting property, time, and expertise weights, we first use a dataset designed for analyzing the effect of each ranking factor independently. We then show the ranking results of a real folksonomy site, with the ranking factors combined. Because the ground truth of a given dataset is not known when it comes to ranking, we inject simulated data whose ranking results can be predicted into the real dataset and compare the ranking results of our algorithm with that of a previous HITS-based algorithm. Our semantic ranking algorithm based on the concept of mutual interaction seems to be preferable to the HITS-based algorithm as a flexible folksonomy ranking framework. Some concrete points of difference are as follows. First, with the time concept applied to the property weights, our algorithm shows superior performance in lowering the scores of older data and raising the scores of newer data. Second, applying the time concept to the expertise weights, as well as to the property weights, our algorithm controls the conflicting influence of expertise weights and enhances overall consistency of time-valued ranking. The expertise weights of the previous study can act as an obstacle to the time-valued ranking because the number of followers increases as time goes on. Third, many new properties and classes can be included in our framework. The previous HITS-based algorithm, based on the voting notion, loses ground in the situation where the domain consists of more than two classes, or where other important properties, such as "sent through twitter" or "registered as a friend," are added to the domain. Forth, there is a big difference in the calculation time and memory use between the two kinds of algorithms. While the matrix multiplication of two matrices, has to be executed twice for the previous HITS-based algorithm, this is unnecessary with our algorithm. In our ranking framework, various folksonomy ranking policies can be expressed with the ranking factors combined and our approach can work, even if the folksonomy site is not implemented with Semantic Web languages. Above all, the time weight proposed in this paper will be applicable to various domains, including social media, where time value is considered important.