• 대한가정학회지
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• 제38권1호
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• pp.139-154
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• 2000

The purpose of this study was to identify the changes in transportation expenditure patterns of urban households during 1985-19o8. The data were drawn from 'Annual Report on the family Income and Expenditure Survey' by National Statistical Office, Republic of Korea. For data analysis, frequency, percentile, mean, and multiple regression analysis were utilized by the SAS window program. The results of this study were as follows; Frist, the levels of public transportation expenditure showed increasing trend, whereas the portions of public transportation expenditure have showed decreasing trend during 1985-1998. And both the level and the portion of private transportation expenditure showed increasing trends during 1985-1998. Second, the marginal propensities to consume of public transportation have decreased, whereas the marginal propensities to consume of private transportation have increased during 1985-1998. Third, income elasticities of public transportation showed decreasing trend during 1985-1998, impling that consumers have less demand public transportation with increasing income. And income elasticities of private transportation showed increasing trend till 1993, and then showed decreasing trend till 1998, impling that consumers have perceived the car as one of necessary goods rather than luxury goods gradually since 1993.

• 한국생활과학회지
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• 제18권2호
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• pp.465-476
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• 2009

The purpose of this study is to investigate recognition degree and acceptability of fashion trends of new consumers who live in digital era, and to determine how these factors have influence on their use of fashion trend information. The study was conducted with 696 people from 15 to 34 years old. A self-administrated questionnaire based on the results of previous researches was developed. The data were analyzed with statistical analyses such as frequency analysis, mean, factor analysis, t-test, ANOVA, correlation and regression analysis. The results are as follows: first, new digital consumer's recognition degree (RD) of fashion trends is 7.85 on the average, given that the top of scale is 20.0, it is quite low. Of fashion trend RD, fashion item RD is the highest. The female subjects recognize fashion trends better than the male subjects. Second, fashion trend acceptance of new digital generation is classified into 5 factors: 'search acceptance', 'lead acceptance', 'follow acceptance', 'non-acceptance', and 'delay acceptance'. The female subjects show higher degree in the factors of 'search acceptance', 'lead acceptance' and 'follow acceptance' of fashion trend than the males; hence it means that the females have more positive attitudes in fashion trend acceptance than the males. Third, there are significant differences between genders in the fashion information utilization. Compared to the males, the females more use fashion information on style, fabrics and color. Concludingly, their fashion trend recognition degree and acceptance made an influence in part on their utilization of fashion information.

• 디지털융복합연구
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• 제18권2호
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• pp.367-376
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• 2020

최근 신 소비시장 트렌드에 관한 통계에 따르면 그 중심에 '나홀로 소비' 가 있다. 본 연구는 특정 사회적 트렌드는 그것에 대한 배경을 형성하고 있는 사회와 지역성, 문화, 경제, 심리 등 삶의 다양한 측면들을 통합적인 시각으로 해석하는 것이 중요하다는 측면에서, 수많은 대중의 의견이 수렴되는 신 소비시장 관련 리서치 데이터에서 추출한 '나홀로 소비' 연관어를 분석 키워드로 설정하였고, 분석솔루션 중 하나인 소셜메트릭스TM를 통한 오피니언 분석(Opinion Analisys) 기법을 활용하여 신 소비시장 트렌드에 관한 연구를 진행하였다. 신 소비시장 고찰결과 '혼밥', '혼술', '혼영'이라는 키워드가 도출되었고 이를 활용하여 신 소비시장 트렌드를 분석하였다. 나홀로 소비는 기존 소비자 트렌드 가운데 글로벌 경제위기 이후에 인구변화와 함께 야기된 필연적 새로운 소비 트렌드가 되었고 연관어에 따른 긍, 부정 감정분석의 결과도 대체로 긍정적인 데이터 결과를 확인할 수 있었으며, 이 소비 트렌드는 시대를 반영하는 새로운 트렌드로서의 중요성이 더욱 강화될 것이다. 향후 소셜 빅데이터에 의한 트렌드 분석이 본 연구보다 다양한 분석 도구를 통해 실행된다면 신 소비시장에 관한 새롭고 가치 있는 유통전략 및 기획에 도움이 될 것이다.

• 한국경영과학회지
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• 제38권2호
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• pp.65-73
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• 2013

In the simulation output analysis, bootstrap method is an applicable resampling technique to insufficient data which are not significant statistically. The moving block bootstrap, the stationary bootstrap, and the threshold bootstrap are typical bootstrap methods to be used for autocorrelated time series data. They are nonparametric methods for stationary time series data, which correctly describe the original data. In the simulation output analysis, however, we may not use them because of the non-stationarity in the data set caused by the trend such as increasing or decreasing. In these cases, we can get rid of the trend by differencing the data, which guarantees the stationarity. We can get the bootstrapped data from the differenced stationary data. Taking a reverse transform to the bootstrapped data, finally, we get the pseudo-samples for the original data. In this paper, we introduce the applicability of bootstrap methods to the time series data having trend, and then verify it through the statistical analyses.

• 패션비즈니스
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• 제4권3호
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• pp.103-114
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• 2000

The purpose of this study was to test the discriminant analysis model of Quick Response system and to examine the detailed relationship between each discriminant factor and Quick Response adoption. In this discriminant analysis model of Quick Response system, firm size, strategic type, product category, fashion trend, selling time and the Quick Response benefits were included as discriminant factors. Onehundred and two subjects were randomly selected for the survey study and discriminant analysis, descriptive analysis, t-test, and x square test were used for the data analysis. The results of this study were: 1. Wilks Lambda and F value support the discriminant analysis model that, taken together firm size, strategic type, product category, fashion trend, selling time and the Quick Response benefits significantly help to explain Quick Response adoption. 2. The importance of discriminant ability was, in order, firm size, the Quick Response benefits, women's wear, fashion trend, analyzer, selling time, reactor, defender and men's wear. 3. The discriminant function had the high hit ratio, so this can be well used for the classification of Quick Response adoption/nonadoption.

• 한국콘텐츠학회논문지
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• 제20권2호
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• pp.96-104
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• 2020

온라인 쇼핑몰의 활성화로 소비자들의 소비 활동이 활발해짐에 따라 기업들은 매출 증대를 위해 소비자의 상품 트렌드 분석을 수행하고 있다. 기존의 상품 트렌드 분석 기법들은 온라인 쇼핑몰 사용자의 활동만을 고려하여 분석하기 때문에 구매 이력이 없거나 새로운 상품에 대한 트렌드를 파악하기 어렵다. 본 논문에서는 쇼핑몰에서 사용자의 트렌드와 잠재적 고객의 트렌드를 분석하기 위해 온라인 쇼핑몰 데이터와 소셜 네트워크 데이터를 결합한 트렌드 분석 기법을 제안한다. 제안하는 기법은 서비스 내 데이터 분석을 위해 사용자의 활동로그를 분석하고 활동 로그가 없는 잠재적인 사용자들의 관심도를 반영하기 위해 소셜 네트워크 데이터에서 단어 집합 추출을 통해 생성한 핫 토픽을 결합하였다. 최종적으로 상품 지수와 소셜 네트워크에서의 언급수를 활용하여 시간에 따른 상품 트렌드 변화를 탐지한다. 소셜 네트워크 데이터를 활용한 성능 평가를 통해 제안하는 기법의 우수성을 입증한다.

• Industrial Engineering and Management Systems
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• 제11권2호
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• pp.134-141
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• 2012

It is difficult to find an appropriate ordering policy for a many types of items. One of the reasons for this difficulty is that each item has a different demand trend. We will classify items by shipment trend and then decide the ordering policy for each item category. In this study, we indicate that categorizing items from their statistical characteristics leads to an ordering policy suitable for that category. We analyze the ordering policy and shipment trend and propose a new method for selecting the ordering policy which is based on finding the strongest relation between the classification of the items and the ordering policy. In our numerical experiment, from actual shipment data of about 5,000 items over the past year, we calculated many statistics that represent the trend of each item. Next, we applied the canonical correlation analysis between the evaluations of ordering policies and the various statistics. Furthermore, we applied the cluster analysis on the statistics concerning the performance of ordering policies. Finally, we separate items into several categories and show that the appropriate ordering policies are different for each category.

• 융합보안논문지
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• 제11권3호
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• pp.19-24
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• 2011

소프트웨어 고장 시간은 테스팅 시간과 관계없이 일정하거나, 단조증가 혹은 단조 감소 추세를 가지고 있다. 이러한 소프트웨어 신뢰모형들을 분석하기 위한 자료척도로 자료에 대한 추세 검정이 개발되어 있다. 추세 분석에는 산술평균 검정과 라플라스 추세 검정 등이 있다. 추세분석들은 전체적인 자료의 개요의 정보만 제공한다. 본 논문에서는 고장시간을 측정하다가 시간 절단이 될 경우에 미래의 고장 시간 예측에 관하여 연구 하였다. 시계열 분석에 이용되는 단순이동 평균법과 가중이동평균법, 지수평활법을 이용하여 미래고장 시간을 예측하여 비교하고자 한다. 실증분석에서는 고장간격 자료를 이용하여 모형들에 대한 예측값을 평균자승오차를 이용하여 비교하고 효율적 모형을 선택 하였다.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2008년도 추계학술대회 논문집
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• pp.325-328
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• 2008

With intensive research and development to mass particular nanostructure of 10nm, Nanoimprint lithography will soon be put to practical use. This paper reviews latest research and application trend and also covers technical articles about Nanoimprint lithography technology Published since 1998, including statistical analysis of collected data(Web of Science DB) and related technical trend.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.201-204
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• 2000

It seems that the \"fuzzy boom\" which began with its applications has calmed down and fallen into decay at least in Korea. But many foreign researchers say the research related to fuzzy theory has been only running its right course. In this paper, we discuss the trend and direction of reaserch related to fuzzy theory. The search trend is obtained through the analysis of the papers of the latest 10years papers in the journals of three societies: KFIS, SOFT and IFSA.