Analysis of Success Factors for Mobile Commerce using Text Mining and PLS Regression

Kim, Yong-Hwan,Kim, Ja-Hee,Park, Ji hoon,Lee, Seung-Jun 한국컴퓨터정보학회 2016 韓國컴퓨터情報學會論文誌 Vol.21 No.11

In this paper, we propose factors that influence on the mobile commerce satisfaction conducted by data mining and a PLS regression analysis. We extracted the most frequent words from mobile application reviews in which there are a large number of user's requests. We employed the content analysis to condense the large number of texts. We took a survey with the categories by which data are condensed and specified as factors that influence on the mobile commerce satisfaction. To avoid multicollinearity, we employed a PLS regression analysis instead of using a multiple regression analysis. Discovered factors that are potential consequences of customer satisfaction from direct requests by customers, the result may be an appropriate indicator for the mobile commerce market to improve its services.

지역특성이 전세·매매가격비율에 미치는 영향요인분석 -수도권 아파트 규모 및 지역별 중심으로-

강남훈 ( Kang Nam Hoon ),김영중 ( Kim Young Jung ) 한국부동산학회 2012 不動産學報 Vol.49 No.-

1. CONTENTS(1) RESEARCH OBJECTIVES Recently, in spite of falling the housing price, the price of rent and Jeon-se are rising in Seoul Metropolitan area. The government makes an effort to be stable housing market but, after March, 2009 the Jeon-se price keep increasing. Because of the flows of sale price and Jeon-se price change different way, the study for ratio of Jeon-se to sale price is necessary. The ratio of Jeon-se to sale price consist of two different prices. So, it can consider Jeon-se and sale price at once.(2) RESEARCH METHODThis study suggests that we need to introduce a region-specific housing policy. The results are means that each sub-market are affected by different factor. Therefore, the policy has to focus to solve the imbalance with a respective way.(3) RESEARCH FINDINGSThe data consist of 62 districts in Seoul Metropolitan area. Data were analyzed with descriptive, bivariate correlation, cluster, PLS regression by SPSS 18.0 for window. The housing sub-market is divided to 2 groups by cluster analysis according to the housing sale price, Jeon-se price, and ratio of Jeon-se to sale price. And the housing categorized according to size which divided into under 60㎡, between 60 to under 85㎡, over85㎡.2. RESULTSThrough the analysis of PLS regression, the following results were obtained. Firstly, the characteristic of industry, location, public transportation and opportunity of development has positive effect to ratio of Jeon-se to sale price in all Seoul metropolitan area and size of apartment. These factors represent to monetary facilities, industry, subway, park and university and that means the ratio of Jeon-se to sale price in Seoul metropolitan area are sensitive to physical environment. Secondly, the ratio of Jeon-se to sale price is consisting of the price of Jeon-se and sale. So, it cans analysis to the regional characteristics impact different way to Jeon-se and sale price. Lastly, The cluster analysis shows the spatial pattern of the ratio of Jeon-se price to sale price is different in the regions and size of apartment.

Rapid Discrimination of F1Hybrid Seeds from Their Parental Lines and Selection of Protein-Rich Corn Lines forSilage Corn Breeding Using FT-IR Spectroscopy Combined by Multivariate Analysis

허설혜,남석현,양승균,김석원,민병환 한국작물학회 2015 Journal of crop science and biotechnology Vol.18 No.3

This study aims to establish the discrimination of F1 hybrid seeds from their parental lines and rapid selection of proteinrich lines from inbreeding lines of corn using FT-IR spectroscopy combined by multivariate analysis. Eight individual seeds from the maternal and paternal lines of Gwangpyeongok and their F1 progeny seeds were subjected to FT-IR spectroscopy. A total of 176 corn inbreeding lines including commercial corn cultivars were subjected to FT-IR spectroscopy. To establish the prediction model for total protein content from corn seed, 33 corn inbreeding lines out of 176 were randomly selected and total seed protein contents using Bradford assay were examined. PLS-DA (partial least square regression discriminant analysis) could clearly discriminate F1 hybrid seeds from their parental lines. PC (principal component) loading values show that 1,700 1,500 cm-1 and 1,200 - 900 cm-1 regions of FT-IR spectra are significantly important for discrimination of corn lines. The prediction model for total protein contents was established by PLS (partial least square regression) algorithm, and its accuracy was confirmed by cross-validation test (R2 = 0.94). After external validation fromexternal 25 corn inbreeding lines, regression coefficient (R2) was 0.78 which indicated that the prediction model had relatively good accuracy. Thus, considering these results we suggest that FT-IR combined with multivariate analysis could be applied as a novel tool for high-throughput screening of F1 hybrid seeds from their parental lines and protein-rich lines for breeding of silage corn cultivar.

스포츠 시장가치망 분류에 따른 파생시장이 일자리 창출에 미치는 영향 : 소셜데이터와 PLS(partial least squares regression) 회귀분석을 중심으로

한남희 한국사회체육학회 2020 한국사회체육학회지 Vol.0 No.81

Purpose: In this study, using the INSIGHT Deep MiningG program, frequency of mentioning and Emotion-Keyword are compared on a percentage basis to analyze the effect of a derived market of demand-oriented market value network classification on the creation of sports-related jobs. Method: Based on the preceding factors derived from social data analysis, the following conclusions were reached by using the method, partial least-square (PLS), to determine what influence derivative market has on the critical attributes of job creation. The study used the INSIGHT Deep MiningG program to analyze the impact of derived markets on the creation of sports-related jobs by using the demand-oriented market value chain classification as a percentage of social data references and emotional keywords. The following conclusions were reached using the PLS (PLS) regression method to determine the impact of job creation. Results: The results of this study are as follows. First, social users had the highest interest in the sports information market and the sports service market, given the amount of mention in the sports derivatives market of social data. Regarding sports job factors, interest in recruiting and job information was high. Second, the Emotion-Keyword of the sports derivative market showed high positive sentiment corresponding to the image of the new growth industry, while the Emotion-Keyword of the sports job showed negative sentiment due to the anxiety caused by issues such as unfair recruitments. Third, derivative market in the market value network mostly affected sports jobs. Conclusion: Job seekers prefer to work in the sports information market, sports service market, sports athlete training market, and sports tourism market, but the actual employment status is reflected in the sports information market, sports service market, sports tourism market, and sports facility market.

특성별 서울 아파트 전세가격 결정모형에 관한 연구

성주한(Sung, Joo Han),서철수(Seo, Chul Soo),윤정득(Yoon, Jung Duck) 한국지적학회 2014 한국지적학회지 Vol.30 No.2

전세가격은 전세시장의 전반적인 상황을 나타내 주는 대표적인 지표이며, 전세가격의 변동은 여러 가지 요인에 의해 영향을 받는다. 또한, 전세가격의 변동은 다양한 요인들의 복합적인 변화를 전세 소비자에게 전달하는 신호 역할을 한다. 본 연구의 궁극적인 목적은 최근의 전세가격 상승 원인을 분석하여 미래에는 어떤 방향으로 변할 지에 대한 예측을 가능케 하고, 전세가격 변화에 대한 예고 지표로 활용될 수 있는 전세가격 결정모형을 설정하는 것이다. 즉, 횡단면 자료를 이용한 서울 아파트 전세가격 결정모형을 통하여 미시적인 측면에서 어떠한 요인들이 전세가격에 영향을 미치는지 헤도닉 가격 모형(Hedonic Price Model)을 적용하여 실증 분석을 하였다. 분석 결과, 4개의 특성(아파트 특성, 가격 특성, 수요ㆍ공급 특성, 사회적 특성) 중 아파트 특성이 가장 중요한 요인으로 나타났으며, 특히, 아파트 특성 중에서 물리적 특성과 경과 연수, 접근성에 대한 부분이 유의성 있는 것으로 분석됨에 따라 거주에 대한 효용 측면을 중요시 하는 것으로 판단되었다. 가격 특성에서는 전국지가변동률과 아파트 매매가격변동률, 아파트 전세가격변동률이 서울 아파트 전세가격에 영향을 주는 것으로 분석되었다. 그리고 수요ㆍ공급 특성에서는 수요 측면의 인구수와 공급 측면의 멸실주택수, 재건축입주량, 재개발입주량이 서울 아파트 전세가격에 영향을 주는 것으로 나타났다. 사회적 특성에서 장기전세주택 Shift가 있는 지역은 서울 아파트 전세가격에 영향을 주었다. 또한 OLS 및 PLS 회귀분석 결과를 살펴보면, 서울 아파트 전세가격에 영향력을 크게 미치는 변수들은 교육적인 측면, 쾌적성 측면, 가격특성 측면, 접근성 측면인 것으로 나타났다. The hedonic price model was applied to get the apartment Chonsei price decision model for Seoul by using cross-sectional data at the microstructural level. As a result of analysis, the apartment characteristic of four ones(apartment characteristic, price characteristic, demand and supply charac- teristic and social characteristic) was found to be the most important one. Especially, it was found that physical properties, the number of years of passage, accessibility were significant, which implies that value was put on the utility of residence. And it was found that price characteristics such as the fluctuation rate of land price, selling price and Chonsei price had an effect on the Chonsei price. And it was found that the number of the population had an effect on the Chonsei price in terms of demand and that the number of disappeared houses, quantities of occupied rebuilt houses and quantities of occupied redeveloped houses had an effect on the Chonsei price. The region where the shift, long-term Chonsei, had an effect on the Chonsei price in terms of social characteristics. In addition to, looking at OLS and PLS regression, Seoul apartment chonsei prices significantly are influenced by educational aspects, comfort aspects, characteristic aspects of price, aspects of accessibility, respectively.

Rapid Discrimination of F1 Hybrid Seeds from Their Parental Lines and Selection of Protein-Rich Corn Lines for Silage Corn Breeding Using FT-IR Spectroscopy Combined by Multivariate Analysis

허슬혜,남석현,양승견,김숙원,민병완 한국작물학회 2015 Journal of crop science and biotechnology Vol.18 No.5

This study aims to establish the discrimination of F1 hybrid seeds from their parental lines and rapid selection of proteinrich lines from inbreeding lines of corn using FT-IR spectroscopy combined by multivariate analysis. Eight individual seeds from the maternal and paternal lines of Gwangpyeongok and their F1 progeny seeds were subjected to FT-IR spectroscopy. A total of 176 corn inbreeding lines including commercial corn cultivars were subjected to FT-IR spectroscopy. To establish the prediction model for total protein content from corn seed, 33 corn inbreeding lines out of 176 were randomly selected and total seed protein contents using Bradford assay were examined. PLS-DA (partial least square regression discriminant analysis) could clearly discriminate F1 hybrid seeds from their parental lines. PC (principal component) loading values show that 1,700 – 1,500 cm−1 and 1,200 – 900 cm−1 regions of FT-IR spectra are significantly important for discrimination of corn lines. The prediction model for total protein contents was established by PLS (partial least square regression) algorithm, and its accuracy was confirmed by cross-validation test (R2 = 0.94). After external validation fromexternal 25 corn inbreeding lines, regression coefficient (R2) was 0.78 which indicated that the prediction model had relatively good accuracy. Thus, considering these results we suggest that FT-IR combined with multivariate analysis could be applied as a novel tool for high-throughput screening of F1 hybrid seeds from their parental lines and protein-rich lines for breeding of silage corn cultivar.

국가재정법 제정 이후 국회 예산심의 결정 요인분석

정창수 ( Changsoo Jeong ) 한국재정정책학회 2019 財政政策論集 Vol.21 No.2

본 연구는 2006년 국가재정법 제정이 국회 예산심의과정에 어떠한 영향을 주었는지 살펴보고자 예산심의 결정요인을 분석한다. 재정자료를 활용해 기술통계 분석과 PLS 회귀분석을 실시한 결과 국회의 예산심의 과정에서 예산 증감액은 정치적 요인에 따라, 기금 증감액은 예산결산위원회의 활동 정도에 따라 변동의 폭이 다르게 나타났다. 이러한 결과는 예산 심의 일정 부족 등과 같이 지적되는 제도적인 문제점들을 보완해야 함은 물론 투명성과 책임성을 높일 방안들을 모색해야 함을 시사한다. The purpose of this study is to find out how the ‘National Finance Act’ enacted in 2006 affected the budget review of the National Assembly and to analyze the determinants of the budget review. This study utilizes the finance data from 2007 to 2019 for analysis. Moreover, technical statistical analysis and PLS regression were performed on political, active, institutional, economic and external factors. The analysis showed that the overall budget plan was reducing, however the respective budget plan has increased while the fund has drastically reduced. In addition, the budget plan was influenced by political factors and the funding plan varied depending on the extent of the activities of the Budget and Accounts Committee. The process of budget deliberation at the National Assembly is important in terms of the realizing of fiscal democracy in modern countries. This study suggests that the institutional drawbacks such as tight schedule of budget deliberation, as well as ways to enhance transparency and accountability should be highlighted.

수도권 불안정주택시장에서 주택가격 변동에 영향을 미치는 요인 분석

이광균(Lee, Kwang-Kyun) 대한부동산학회 2015 大韓不動産學會誌 Vol.33 No.1

본 연구는 수도권 불안정 주택시장에서 아파트가격 변동에 영향을 미치는 요인을 분석하였다. 연구방법은 매매 및 전세가격지수의 변동의 정도에 따라 수도권의 주택시장에서 불안정주택시장을 분류하였다. 다음으로 PLS 회귀분석을 활용해 가격 변동 영향요인을 분석하였다. 분석결과를 종합하면 다음과 같다. 수도권 내 불안정 주택시장에서는 토지거래규모, 공동주택비율, 노후주택비율, 1인당주거지역면적, 인구밀도, 1인당 지방세, 아파트거래면적, 총건축허가 도시계획면적 등 8개 요인이 주택매매가격 변동에 영향을 미치는 요인으로 분석되었다. 다음으로 토지거래규모, 1인가구비율, 도로밀도, 노인인구비율, 재정자립도, 고학력 인구비율, 인구밀도, 만인당 기업본사수 등 8개 요인들은 주택전세가격 변동에 영향을 미치는 요인으로 분석되었다. This research analysis on the determinants of fluctuation of housing(apartment) price in unstable housing market of metropolitan. Research methods are below, first it divided types of unstable housing market base on 2 indicators as metropolitan property sale and rent price. Secondly, it explores some influential factors towards the change of those prices using PLS regression analysis. The deducted s tudy results a re b elow. E ight v ariables s uch as ‘size of land transaction’, ‘rate of apartment building’, ‘rate of deteriorated housing’, ‘per head of residential area’, ‘population density’, ‘local taxes per capita’, ‘the size of apartment transaction’, ‘total building permit area in urban planning zone’ were analyzed as determinants of housing purchase prices in unstable housing market. Also eight variables such as ‘size of land transaction’, ‘rate of single household’, ‘road density’, ‘population density of old people’, ‘financial independence rate’, ‘well-educated population ratio’, ‘population density’, ‘number of head office per 10,000 people’ were analyzed as determinants of housing rent prices in unstable housing market.

풍수해 재난 회복력에 영향을 미치는 지역특성요인 규명

박소연,윤상훈 국토연구원 2017 국토연구 Vol.92 No.-

The main purpose of this study is to deducted implication and examine factor of regional characteristics which can be influential to the resilience of damage by storm and flood focused on Daegu and Gyeongsangbuk-do(abbreviate to Gyeongbuk), nearby areas. According to the result, the most important factors are represented river area(VIP: 2.527), annual rainfall depth(VIP: 2.173). It is meaned that understanding of natural condition and characteristics of climate change in region are needed for increasing resilience about damage by storm and flood. And then, the important factor in other characteristics are represented rate of urbanization area(1.339) in land use, network of disaster information (1.496) in society/administration, financial independence ratio(1.466) in economy, rate of vacant house(1.316) in house/infra one. This study is very meaningful to analysis factor of regional characteristics affecting resilience of damage by storm and flood and suggest implication. It also may be useful research basis to making the further policy. 본 논문은 유사한 지역적 특성을 가지고 있는 대구․경북 및 인근 지역을 중심으로 풍수해 재난 회복력에 영향을 미치는 지역특성요인을 규명하고 그에 대한 시사점을 도출하고자 하였다. 분석결과, 풍수해 재난 회복력에 큰 영향을 미치는 요인은 기후/지역특성의 하천면적(2.527), 연 강수량(2.173)임이 밝혀졌다. 이는 풍수해 재난에 대한 회복력을 높이기 위해 지역의 자연적 여건 및 기후변화 특성에 대한 파악이 반드시 필요하다는 것을 의미한다. 다음으로, 토지이용 특성에서는 시가화비율(1.339)이, 사회/행정특성에서는 재난정보 네트워크(1.496)가, 경제특성의 경우 재정자주도(1.466)가, 주택/인프라 특성에서는 빈집 비율(1.316)이 풍수해 재난 회복력에 중요한 지역특성요인인 것으로 도출되었다. 본 논문은 풍수해 재난 회복력에 영향을 미치는 지역특성요인을 규명하고 그에 대한 시사점을 제시하였다는 점에서 그 의의를 가지며 향후 정책수립 시 기초자료로 활용할 수 있다고 판단된다.

해운대 센텀지역 아파트 및 오피스텔 매매가격 영향요인 분석

조성언(Cho, Sung-Eon),이성근(Lee, Sung-Gun) 한국부동산정책학회 2020 不動産政策硏究 Vol.21 No.1

The purpose of this study is to verify factors affecting apartment sales and office sales prices in the Centum City district, which is the central administrative district of Centum City, through actual transaction price data. In addition, the distance from Shinsegae Department Store was reflected in the analysis to see if it affected apartment sales prices. A PLS regression analysis was performed on factors affecting the change in the selling price of Centum City apartments for apartment complexes located in the Centum area (right 2nd, right 3rd, and again 1st Dong) within Haeundae District, which is subject to the analysis.The analysis showed that the public land price fluctuates, apartment transactions, distance to subway stations, distance from industrial complexes, number of houses, and land transactions affect changes in apartment sales prices. In the case of apartments in Centum City, it was analyzed that the increase in the rate of change in the public land price and the increase in the volume of transactions of apartments increased, and that the distance to the subway station was closer or the distance from the Centum general industrial complex also affected the selling price. Next, the analysis of factors that determine the change in the sales price of the officetel in the Centum area showed that the factors that affect the price of the officetel include apartment transaction volume, urbanization rate, number of new apartments, total number of households, distance to subway station, and the rate of change in the official land price. It was confirmed that the higher the volume of apartment transactions, the higher the number of households transferred, the higher the rate of urbanization, and the more the number of apartments that are close to subway stations, or the higher the total number of apartments, had a valid effect on the increase of the sales price in the market for officetel.