• 융합경영연구
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• 제8권2호
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• pp.19-26
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• 2020

Purpose: The goal of this study is to comprehensively grasp the current status of ecommerce and to use as basic data for information-related policies. In this work, we understand recent ecommerce utilization, purchasing business by main factors, and look over the association between business type on sales orders (BTSO) and three variables: region, occupation and group type. Research design, data and methodology: The resource of this research is obtained by Ministry of Science and Technology Information and Communication in 2017, and investigated about 14,000 national business samples. Two statistical methods are used to analyze the association between the three variables: chi-square test and correspondence analysis. Results: The findings show that BTSO is pairwise associated with thee categorical variables, and the association between the categories of the two variables can be visually examined on two dimensional plane. Conclusions: This study suggests 'household & individual consumers' among BTSO are closely connected with 'Chungbuk' and 'Kyungnam' for region, 'others', 'finance & insurance' and 'association, repairing & other personal service' for occupation, and 'national & local government' for group type. Additionally, 'other companies' among BTSO are, particularly, related to 'Chunnam' for region, 'manufacturing industry' for occupation, and 'company corporations' for group type.

• 한국토양비료학회지
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• 제44권5호
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• pp.944-958
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• 2011

Soil hydraulic properties such as hydraulic conductivity or water retention which are costly to measure can be indirectly generated by soil pedotransfer function (PTF) using easily obtainable soil data. The field soil structure description which is routinely recorded could also be used in PTF as an input to reduce the uncertainty. The purposes of this study were to use qualitative morphological soil structure descriptions and soil structural index into PTF and to evaluate their contribution in the prediction of soil hydraulic properties. We transformed categorical morphological descriptions of soil structure into quantitative values using categorical principal component analysis (CATPCA). This approach was tested with a large data set from the US National Pedon Characterization database with the aid of a categorical regression tree analysis. Six different PTFs were used to predict the saturated hydraulic conductivity and those results were averaged to quantify the uncertainty. Quantified morphological description was successively used in multiple linear regression approach to predict the averaged ensemble saturated conductivity. The selected stepwise regression model with only the transformed morphological variables and structural index as predictors predicted the $K_{sat}$ with $r^2$ = 0.48 (p = 0.018), indicating the feasibility of CATPCA approach. In a regression tree analysis, soil structure index and soil texture turned out to be important factors in the prediction of the hydraulic properties. Among structural descriptions size class turned out to be an important grouping parameter in the regression tree. Bulk density, clay content, W33 and structural index explained clusters selected by a two step clustering technique, implying the morphologically described soil structural features are closely related to soil physical as well as hydraulic properties. Although this study provided relatively new method which related soil structure description to soil structure index, the same approach should be tested using a datasets containing the actual measurement of hydraulic properties. More insight on the predictive power of soil structure index to estimate hydraulic properties would be achieved by considering measured the saturated hydraulic conductivity and the soil water retention.

• 한국정보시스템학회지:정보시스템연구
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• 제28권4호
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• pp.333-358
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• 2019

Purpose The study aims to develop a data-based decision model for private bankers when recommending hedge funds to their customers in financial institutions. Design/methodology/approach The independent variables are set in two groups. The independent variables of the first group are aggressive investors, active investors, and risk-neutral type investors. In the second group, variables considered by private bankers include customer propensity to invest, reliability, product subscription experience, professionalism, intimacy, and product understanding. A decision-making variable for a private banker is in recommending a first-rate general private fund composed of foreign and domestic FinTech products. These contain dependent variables that include target return rate(%), fund period (months), safeguard existence, underlying asset, and hedge fund name. Findings Based on the research results, there is a 94.4% accuracy in decision-making when the independent variables (customer rating, reliability, intimacy, product subscription experience, professionalism and product understanding) are used according to the following order of relevant dependent variables: step 1 on safeguard existence, step 2 on target return rate, step 3 on fund period, and step 4 on hedge fund name. Next, a 93.7% accuracy is expected when decision-making uses the following order of dependent variables: step 1 on safeguard existence, step 2 on target return rate, step 3 on underlying asset, and step 4 on fund period. In conclusion, a private banker conducts a decision making stage when recommending hedge funds to their customers. When examining a private banker's recommendations of hedge funds to a customer, independent variables influencing dependent variables are intimacy, product comprehension, and product subscription experience according to a categorical regression model and artificial neural network analysis model.

• 대한인간공학회지
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• 제23권3호
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• pp.101-109
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• 2004

This paper reports the results on age and gender of Korean elderly people for the level of difficulty in performing household tasks (meal preparation, grocery shopping, house cleaning, laundry), personal tasks (dressing, bathing, grooming), transfer tasks (getting in and out of chairs, getting in and out of bath-tub, using stairs) and management tasks (using telephone, accessing mail, operating door locks). A questionnaire based on the Activities of Daily Living (ADL) scale was constructed and administered to 40 Korean elderly subjects aged from 65 to 84(mean age: 74.5, SD: 5.8) in Busan. Additionally, a logistic regression was performed with age (continuous variable) and gender as predictor variables, and reponses to individual questions as the categorical ordinal response variables. To determine appropriate age separation at which difficulty levels in performing activities of daily living change, a discriminant analysis was performed on the responses. All predictor variables were used in the analysis. Accommodating age related changes in functional abilities, and increasing functional independence of elderly people will entail significant design modifications to products, systems and environments for daily use and living.

• 응용통계연구
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• 제30권5호
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• pp.793-808
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• 2017

본 논문에서는 초고차원 자료의 다항분류를 위한 변수선별 방법에 대해 비교 연구를 진행하였다. 다항분류를 위한 변수선별 방법에는 일대일 혹은 일대다 비교를 통해 이항분류를 위한 방법을 확장시켜 적용하는 방법과 다항 반응 변수에 직접 적용할 수 있는 방법이 있다. 다항분류를 위한 변수선별 성능을 확인하기 위하여 여러가지 상황-설명변수의 꼬리가 두꺼운 경우, 신호변수와 잡음변수가 서로 연관된 경우, 결합분포상으로 연관되어 있지만 주변분포 상으로는 연관되어 있지 않은 경우, 다범주 반응변수의 분포가 불균형인 경우-을 가정하고 모의실험을 진행하였고, 실제 자료에도 적용해 보았다. 그 결과, 모형 가정을 필요로 하지 않는 방법들이 안정적인 성능을 보이는 것을 확인하였다.

• Communications for Statistical Applications and Methods
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• 제24권2호
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• pp.173-191
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• 2017

This study develops a new type of latent class analysis (LCA) in order to explain the associations between one latent variable and several other categorical latent variables. Our model postulates that the prevalence of the latent variable of interest is affected by another latent variable composed of other several latent variables. For the parameter estimation, we propose deterministic annealing EM (DAEM) to deal with local maxima problem in the proposed model. We perform simulation study to demonstrate how DAEM can find the set of parameter estimates at the global maximum of the likelihood over the repeated samples. We apply the proposed LCA model in an investigation of the effect of and joint patterns for drug-using behavior to violent behavior among US high school male students using data from the Youth Risk Behavior Surveillance System 2015. Considering the age of male adolescents as a covariate influencing violent behavior, we identified three classes of violent behavior and three classes of drug-using behavior. We also discovered that the prevalence of violent behavior is affected by the type of drug used for drug-using behavior.

• 한국주거학회논문집
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• 제25권4호
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• pp.59-72
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• 2014

This study proposes a data-mining analysis method for examining variable multi-attribute big-data, which is considered to be more applicable in social science using a Correspondence Analysis of variables obtained by AIC model selection. The proposed method was applied on the Seoul Survey from 2005 to 2010 in order to extract interesting rules or patterns on characteristics of single household. The results found as follows. Firstly, this paper illustrated that the proposed method is efficiently able to apply on a big dataset of huge categorical multi attributes variables. Secondly, as a result of Seoul Survey analysis, it has been found that the more dissatisfied with residential environment the higher tendency of residential mobility in single household. Thirdly, it turned out that there are three types of single households based on the characteristics of their demographic characteristics, and it was different from recognition of home and partner of counselling by the three types of single households. Fourthly, this paper extracted eight significant variables with a spatial aggregated dataset which are highly correlated to the ratio of occupancy of single household in 25 Seoul Municipals, and to conclude, it investigated the relation between spatial distribution of single households and their demographic statistics based on the six divided groups obtained by Cluster Analysis.

• 동아시아경상학회지
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• 제9권3호
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• pp.83-100
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• 2021

Purpose - The purpose of this study is to comprehensively understand the recent status of domestic e-commerce market and provide useful information for the revitalization of domestic on-line economy. This study looks over the association between type of e-commerce and demographic variables for each purchase ordering and sales order business. The demographics under consideration is administrative district, occupation and business organization type and type of e-commerce is B2B, B2C and B2G to deal with. Research design, data, and methodology - From January 2017 to December 2017, about 14000 samples are extracted from all businesses with experience in purchasing or selling products or services through e-commerce. The association between the two categorical variables considered by using two major statistical techniques such as chi-square test and correspondence analysis can be quantitatively and visually detected. Result - This study shows the association between the type of e-commerce with the administrative district and the occupation is completely different, but B2B and B2C are identical for organization type, with respect to both purchase and sales orders. Conclusion - The association between the type of e-commerce with the administrative district and the occupation is completely different, but B2B and B2C are identical for organization type, with respect to both purchase and sales orders.

• 디지털융복합연구
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• 제11권12호
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• pp.93-100
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• 2013

본 논문은 다중회귀모형을 이용하여 강릉단오제 관광객의 소비지출의 결정요인을 분석하였다. 소비지출의 결정요인을 소득, 직업 등 12개 설명변수로 종속변수는 총 지출 및 5개의 항목별 지출로 설정하여 분석하였다. 논문의 주요 분석결과로 소득은 관광소비의 중요한 결정요인이며 소득이 소비에 양(+)의 효과를 준다는 사실이 입증되었다. 둘째, 나이가 많고 수도권 거주 관광객일수록 전체 및 항목별 소비지출이 증가하는 경향이 있다. 셋째, 동반인수가 많을수록 소비지출은 감소한다. 넷째, 참가일 수와 체류기간은 소비지출에 양(+)의 효과를 준다. 남자이며 기혼이고 자비 숙박 관광객일수록 소비지출은 증가한다. 다섯째, 항목별 소비지출의 결정요인으로 소득과 같은 공통적인 변수도 있으나 항목별 소비지출의 고유한 특성을 반영하는 차별적인 결정요인이 있는 것으로 추정된다. 본 논문은 지역경제 및 관광산업의 활성화를 위한 효율적인 관광전략을 도출하는 데 기초자료로 활용될 것으로 기대된다.

• 한국콘텐츠학회논문지
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• 제16권2호
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• pp.729-739
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• 2016

본 연구의 주된 수행 동기는 국내,외 기업재무 분야에서 현재 학문적 관심이 점증되고 있는 현금유보 수준의 결정요인에 대한 기존의 유사주제 연구들에 대한 추가적인 실증분석이다. 연구설정 기준과 관련하여, 국제금융위기 이후의 표본기간 (2009-2013)과 국내 재벌기업들의 표본을 대상으로 구도화되었으며, 본문에 설명되었듯이 2가지의 주요가설들이 검정되었다. 첫 번째 가설 검정에서는 조건부 분위회기모형을 응용한, 현금유동성 분위 (계층) 수준별 유의성있는 재무변수들을 계량적으로 측정하는 것이었으며, 두 번째 검정에서는 다중로지스틱 모형을 활용한 국제금융위기 이후 기업들의 현금 유동성 수준 증감과 관련된 비교그룹들 상호 간에 대한 비교연구가 수행되었다, 결과적으로, 전자에서는 유동성, 대리인비용, 그리고 현금전환기간과 관련된 변수들이 유의성있는 재무변수로서 판명되었으며, 후자에서는 현금보유 수준의 변화가 상대적으로 큰 재벌계열사들이, 비교그룹 (즉, 기준그룹)에 속하는 계열사들 보다 유동성, 기업규모, 그리고 배당수익률 등의 측면에서 유의성 있는 통계적 차별성을 보이는 것으로 판명되었다.