• Journal of the Korean Applied Science and Technology
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• v.40 no.6
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• pp.1322-1329
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• 2023

This study attempted to verify how the selection attribute affects customer satisfaction and participation intention to provide basic data for the efficient operation strategy of domestic futsal fields. Therefore, people who used domestic futsal fields were selected as samples, and convenience sampling methods were used. The final analysis used 271 copies of data. The data processing was conducted with the SPSS (ver. 21.0) program, which conducted frequency analysis, factor analysis and reliability analysis, correlation analysis, simple and multiple regression analysis. First, the results of the study showed that domestic futsal field selection attributes had a significant impact on customer satisfaction in the order of service, convenience, price, and facility. Second, customer satisfaction had a significant effect on participation intention. Third, the optional attributes had a significant impact on participation intention in the order of facility, service, convenience, and price. Summarizing the above results, it is believed that domestic futsal courts need to provide facilities and services that allow consumers to enjoy futsal games more conveniently and safely.

• Journal of Industrial Convergence
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• v.19 no.6
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• pp.73-79
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• 2021

The purpose of this study was to find out how the importance and satisfaction of social commerce selection factors perceived by social commerce users differ, and how social commerce selection factors affect repurchase intention. A survey was conducted for 17 days from September 1st to September 17th, 2021, and 316 copies were used for empirical analysis. As a result of the analysis, the selection factors of social commerce were divided into six factors: safety, convenience, economy, informativity, collectivity, and SNS relevance. IPA results were in the order of convenience in the first quadrant, relevance and informativity in the second quadrant SNS, collectivity in the third quadrant, stability in the fourth quadrant, and economy. In the relationship between social commerce selection factors and repurchase intention, convenience, economy, safety, and information among social commerce selection factors were found to have a significant influence on repurchase intention. As a result of this study, it was confirmed that if existing social commerce was important at an affordable price, convenience is more important for non-face-to-face commerce in the COVID-19 situation. It is considered important to have a system that can continuously identify and preemptively respond to users' shopping trends through IPA.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1077-1085
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• 2017

In this study, we have found the major factors which affect Korean women's wage analysing the data provided by 2015 Korea Labor Panel Survey (KLIPS). In general, wage data is difficult to analyze because random sampling is infeasible. Heckman sample selection model is the most widely used method for analysing the data with sample selection. Heckman proposed two kinds of selection models: the one is the model with maximum likelihood method and the other is the Heckman two stage model. Heckman two stage model is known to be robust to the normal assumption of bivariate error terms. Recently, Marchenko and Genton (2012) proposed the Heckman selectiont model which generalizes the Heckman two stage model and concluded that Heckman selection-t model is more robust to the error assumptions. Employing the two models, we carried out the analysis of the data and we compared those results.

• 프린팅코리아
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• s.22
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• pp.112-116
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• 2004

한국인쇄학회(회장 김성빈)는 최근 인쇄학회지 제21권을 발행했다. 이 학회지에는 '오프셋 인쇄용지의 펄프 혼합비율에 따른 잉크전이율 변화' 등 20편의 논문이 게재돼 있다. 이에 본지에서는 이광숙(중부대), 윤혜영(중부대) 씨가 공동 연구한 '브랜드 이미지 형성을 위한 색상 선택에 관한 연구' 를 요약 소개한다.

• Environmental and Resource Economics Review
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• v.28 no.4
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• pp.645-673
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• 2019

The hypothetical nature of stated preferences can lead to a hypothetical bias that might work as a normative pressure, influencing survey responses. This paper aims to test the impact of social desirability bias by comparing economic estimates based on both subjective and objective valuation questions. The case study is about an urban riverine restoration project in Deajeon, South Korea. As valuation methods both contingent valuation and choice experiments were comparatively applied. Based on a nationally representative sample of 1,000 respondents, the test results offered contrasting conclusions between two test approaches. Accroding to the estimation results based on the conventional valuation, the marginal willingness to pay estimates are 10,500 KRW from CV; and 18,600 KRW for improving water quality, 2,200 KRW for the inside view, 8,900 KRW for the outside view, and 5,800 KRW for biodiversity from CE. A segmentation-based approach is a conventionally used method, which showed a limited impact of social desirability on willingness to pay estimates. The alternative parameterization-based approach measures a model-wide impact of social desirability, proving a significant bias. Although the study positioned a cheap-talk statement before the valuation section of the survey questionnaires, which might have pre-screened the bias, the overall implications of the results suggest a caution in reducing and observing hypothetical bias. There might remain a significant and substantial hypothetical bias even after cheap-talk, particularly in situations with strong social desirability, so that the potential role of objective valuation questions is guaranteed.

• Environmental and Resource Economics Review
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• v.13 no.3
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• pp.387-415
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• 2004

This paper is intended to valuate air quality of the Seoul Metropolitan Area using triple-bound dichotomous choice (TBDC) contingent valuation method (CVM), supplemented by open-ended (OE) questionnaires. In the OE questionnaires, some respondents would state their willingness to pay (WTP) outside the limits of the WTP interval. It implies that WTP estimates based on the customary dichotomous choice (DC) questionnaires can be biased. We argue that the TBDC-CVM refined with OE questions is more efficient, because the latter helps purge the former of corrupted data that may have been collected by the TBDC interview process.

• The Korean Journal of Applied Statistics
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• v.32 no.2
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• pp.199-211
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• 2019

This paper is concerned with issues in the finite mixture of regression modeling as well as the simultaneous selection of the number of mixing components and relevant predictors. We propose a penalized likelihood method for both mixture components and regression coefficients that enable the simultaneous identification of significant variables and the determination of important mixture components in mixture of regression models. To avoid over-fitting and bias problems, we applied smoothly clipped absolute deviation (SCAD) penalties on the logarithm of component probabilities suggested by Huang et al. (Statistical Sinica, 27, 147-169, 2013) as well as several well-known penalty functions for coefficients in regression models. Simulation studies reveal that our method is satisfactory with well-known penalties such as SCAD, MCP, and adaptive lasso.

• 한국벤처창업학회:학술대회논문집
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• 2018.11a
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• pp.85-92
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• 2018

최근 커피 전문점의 한계를 극복하기 위하여 카페와 디저트의 결합 형태인 디저트카페가 활성화 되었으며,이 또한 치열한 경쟁상황에 놓여 있는 관계로 경쟁에서 보다 유리한 위치를 확보하기 위한 고객맞춤형 마케팅전략이 필요함으로 본 연구를 수행한다. 최근, 연구방향이 디저트카페의 서비스품질, 브랜드이미지, 물리적환경 및 선택속성에 관한 연구가 활발하게 진행되고 있으나 고객의 감성 지능과 연계한 연구는 없었던 관계로 본 연구에서는 고객의 감성지능과 연관된 효과를 검증하고자 한다, 또한, 스마트폰의 보급으로 모바일쿠폰이 매우 활성화 되어 있음으로 디저트카페의 환경과 모바일쿠폰의 특성이 어떠한 영향관계를 보이고 있는지 살펴보고자 한다. 디저트카페의 물리적환경(심미성,공간효율성,청결성,쾌적성,편의성),선택속성(서비스,맛과향,가격,다양성,독창성),모바일쿠폰(획득용이성,사용편의성,유희성,경제성)이 고객만족에 미치는 영향력을 살펴본다. 또한 고객의 감성지능이 조절효과로서 각각의 요인들에 대하여 고객만족도에 어떠한 관계를 가지게 되는지 살펴보며, 본 연구를 통하여 기존의 마케팅전략에서 고객의 감성지능 맞춤형 마케팅전략을 구사함으로써 보다 효율적이고 목표를 명확화 함으로써 마케팅 비용과 노력을 줄이는데 기여할 수 있을 것이라고 판단된다.

• Journal of Labour Economics
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• v.26 no.1
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• pp.23-52
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• 2003

This study focus on unemployment and nonparticipation of youth. By dividing youth nonparticipants into 'house work and child care', 'studying and training', 'the others' categories, we estimate the potential wages with selectivity bias model and analyse the factors of choosing unemployment or nonparticipation with multinomial logit model. The differences between the potential market wage and the desired wage of the groups of 'studying and training', 'the others' in the nonparticipants are greater than those of the unemployment group. In the case of the man and lower age, and low schooling the differences of potential and desire wage are larger than woman and higher age, and high schooling. In the choice of unemployment and nonparticipation, man and higher age, and householder, and holder of qualification are not likely to opt nonparticipation. The experience of job lower the rate of probability to choose employment, but raise the rate of probability to choose unemployment and nonparticipation. These results mean that the quality of youth employment is very inferior.

• Korea journal of population studies
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• v.11 no.1
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• pp.1-13
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• 1988

This study examines the sampling bias that may have resulted from the large number of missing observations. Despite well-designed and reliable sampling procedures, the observed sample values in DSFH(Demographic Survey on Changes in Family and Household Structure, Japan) included many missing observations. The head administerd survey method of DSFH resulted in a large number of missing observations regarding characteristics of elderly non-head parents and their children. In addition, the response probability of a particular item in DSFH significantly differs by characteristics of elderly parents and their children. Furthermore, missing observations of many items occurred simultaneously. This complex pattern of missing observations critically limits the ability to produce an unbiased analysis. First, the large number of missing observations is likely to cause a misleading estimate of the standard error. Even worse, the possible dependency of missing observations on their latent values is likely to produce biased estimates of covariates. Two models are employed to solve the possible inference biases. First, EM algorithm is used to infer the missing values based on the knowledge of the association between the observed values and other covariates. Second, a selection model was employed given the suspicion that the probability of missing observations of proximity depends on its unobserved outcome.