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호텔멤버십을 통한 관계혜택이 고객만족과 고객충성도에 미치는 영향연구: 고객애착의 매개효과를 중심으로
이영섭,이충기 (사)한국관광레저학회 2019 관광레저연구 Vol.31 No.11
The primary purpose of this study is to estimate the relationships among relational benefits, customer satisfaction, attachment, and loyalty throughout hotel membership using structural equation model. The secondary purpose of this study is to investigate the mediating effect of customer attachment between customer satisfaction and loyalty; and between relational benefits and loyalty. To achieve these objectives, this study conducted onsite and telephone surveys from November 5 to 30, 2018, to those who own deluxe hotel membership. The results of this study show that relational benefits positively influenced customer satisfaction, attachment, and loyalty. Results also indicate that customer satisfaction had positive effects on attachment and loyalty. Customer attachment was found to have a positive impact on loyalty. Results reveal that customer attachment played important mediating roles between relational benefits and loyalty, and between customer satisfaction and loyalty. Theoretical and practical implications were discussed in conclusion section.
데이터 마이닝에서 배깅, 부스팅, SVM 분류 알고리즘 비교 분석
이영섭,오현정,김미경,Lee Yung-Seop,Oh Hyun-Joung,Kim Mee-Kyung 한국통계학회 2005 응용통계연구 Vol.18 No.2
데이터 마이닝에서 데이터를 효율적으로 분류하고자 할 때 많이 사용하고 있는 알고리즘을 실제 자료에 적용시켜 분류성능을 비교하였다. 분류자 생성기법으로는 의사결정나무기법 중의 하나인 CART, 배깅과 부스팅 알고리즘을 CART 모형에 결합한 분류자, 그리고 SVM 분류자를 비교하였다. CART는 결과 해석이 쉬운 장점을 가지고 있지만 데이터에 따라 생성된 분류자가 다양하여 불안정하다는 단점을 가지고 있다. 따라서 이러한 CART의 단점을 보완한 배깅 또는 부스팅 알고리즘과의 결합을 통해 분류자를 생성하고 그 성능에 대해 평가하였다. 또한 최근 들어 분류성능을 인정받고 있는 SVM의 분류성능과도 비교?평가하였다. 각 기법에 의한 분류 결과를 가지고 의사결정나무를 형성하여 자료가 가지는 데이터의 특성에 따른 분류 성능을 알아보았다. 그 결과 데이터의 결측치가 없고 관측값의 수가 적은 경우는 SVM의 분류성능이 뛰어남을 알 수 있었고, 관측값의 수가 많을 때에는 부스팅 알고리즘의 분류성능이 뛰어났으며, 데이터의 결측치가 존재하는 경우는 배깅의 분류성능이 뛰어남을 알 수 있었다. The goal of this paper is to compare classification performances and to find a better classifier based on the characteristics of data. The compared methods are CART with two ensemble algorithms, bagging or boosting and SVM. In the empirical study of twenty-eight data sets, we found that SVM has smaller error rate than the other methods in most of data sets. When comparing bagging, boosting and SVM based on the characteristics of data, SVM algorithm is suitable to the data with small numbers of observation and no missing values. On the other hand, boosting algorithm is suitable to the data with number of observation and bagging algorithm is suitable to the data with missing values.
이영섭,손승우,허재영,신동현 한국통합생물학회 2021 Animal cells and systems Vol.25 No.6
Although there have been many genome-wide association studies (GWAS) and selective sweep analyses to understand pig genomic regions related to growth performance, these methods considered only the gene effect and selection signal, respectively. In this study, we suggest the cross-population phenotype associated variant (XP-PAV) analysis as a novel method to determine the genomic variants with different effects between the two populations. XP-PAV analysis could reveal the differential genetic variants between the two populations by considering the gene effect and selection signal simultaneously. In this study, we used daily weight gain (DWG) and back fat thickness (BF) as phenotypes and the Landrace and Yorkshire populations were used for XP-PAV analysis. The main aim was to reveal the differential selection by considering the gene effect between Landrace and Yorkshire pigs. In the gene ontology analysis of XP-PAV results, differential selective genes in DWG analysis were involved in the regulation of interleukin-2 production and cell cycle G2/M transition. The protein modification and glycerophospholipid biosynthetic processes were the most enriched terms in the BF analysis. Therefore, we could identify genetic differences for immune and several metabolic pathways between Landrace and Yorkshire breeds using the XP-PAV analysis. In this study, we expect that XP-PAV analysis will play a role in determining useful selective variants with gene effects and provide a new interpretation of the genetic differences between the two populations.