• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of Korean Society of Forest Science
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• v.90 no.4
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• pp.573-581
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• 2001

The purposes of this study are to estimate mean willingness to pay (WTP) for preventing forest fires by contingent valuation method (CVM), and to calibrate the variables affecting WTP. The forest fire prevention fund was utilized as a payment vehicle to elicit respondents' willingness to pay (WTP). A total of 500 adults who reside in Seoul Metropolitan area were selected by two-stage cluster sampling and conducted the face-to-face interview. The scenario was designed to meet the requirements for double-bounded dichotomous choice CVM. More than half of the respondents (64.6%) have a willing to pay for the fund. The mean WTP was \4,532. Therefore a total WTP for the population was \34,165,758,000. The calibration of Weibull proportional hazard model showed that education level, environmental conservation intention and negative consciousness about the effect of forest fire were independent variables strongly influencing the WTP.

• Journal of Distribution Research
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• v.11 no.1
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• pp.69-97
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• 2006

This research aimed to establish and test a empirical model for antecedents and consequences of manufacturer's degree of channel concentration in multiple channels from strategic perspective. For this purpose, I suggested new concept of channel concentration based on related literature review and developed the measurement index of channel concentration. Second, I examined and applied the transaction cost theory and market power theory to provide broad understanding of multiple channel structure and to explain it. Finally, I present the theoretical and managerial implications to the firms that build up channel strategy under multiple channel contexts on this research results. For the purpose of these goals, eight hypotheses were drawn from the previous researches. To verify these hypotheses, 248 data were collected as samples, and the data were tested by reliability test, factor analysis, and covariance structure analysis. Empirical findings strongly support that strategic management of distribution channel especially are important in multiple channels. The overall implications to researchers and practitioners are presented, and limits and further study direction were discussed as a final.

• Journal of Labour Economics
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• v.40 no.2
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• pp.31-68
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• 2017

This study examined the moonlighting behavior in Korea, to which relatively less attention has been paid. Based on the wage earners of 25 to 65 year old married, the results show that about 1.4% of the sample have dual jobs, working very long hours, on average 60 hours for a week combining both the primary job and the secondary job. The results of the fixed effects logit model on the moonlighting participation indicate that the wage rate and the hours of work in the primary job have a negative effect on moonlighting participation while the insecurity of the primary job appears to lead to a higher probability of taking a secondary job. The results of the moonlighting hours analysis suggest that hours worked in the primary job have a negative effect on moonlight hours while the wage of the primary job does not appear to have any significant effect on moonlighting hours. Interestingly enough, the wage of the secondary job appears to have a negative impact on moonlighting hours, which might be very plausible considering the long working hours moonlighters are engaged in.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.6
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• pp.2528-2534
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• 2011

This paper investigates the relationship between the change of age structure of population and the efficiency of education investment, using cross-section of 106 countries. Based on the existing theoretical arguments, we establish a hypothesis concerning the relationship between age structure and education investment efficiency. The regression results suggest that a country's with a higher ratio of young age to total population results in a lower level of the efficiency of education investment. However, there exists a positive and significant relationship between the ratio of old age to total population and the efficiency of education investment. Therefore, it does suggest that countries experiencing reducing in fertility rate and increasing in expected longevity, such as Korea, not only should be maximized the education efficiency but also contrived for the institutional system for maximization the efficiency of education performance.

• 한국벤처창업학회:학술대회논문집
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• 2020.11a
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• pp.39-44
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• 2020

본 연구는 농촌융복합산업에 관심이 있는 예비 농촌융복합산업 창업인들의 농촌융복합산업 창업의도 발현에 대한 영향요인들을 실증적으로 분석하였다. 농촌융복합산업 예비창업자들이 농촌융복합산업 창업이라는 의사결정을 하는데 미치는 영향요인을 실증적으로 분석하여 영향관계를 규명하는데 목적이 있다. 특히 농촌융복합산업 창업도 창업의 한 형태로 이해할 수 있는 것이라는 관점에서 논의를 전개하였으며, 이를 위해 창업연구 분야에서 농촌융복합산업 창업의도에 영향을 미치는 요인 분석에 사용되는 연구분석틀을 응용하여 분석을 수행하였다. 잠재적 농촌융복합산업 창업자들인 예비농업인들의 창업 기초 자료를 제공하고 관련 정책에 대한 시사점을 도출하는 데 목적이 있다. 이에 따라 본 연구는 예비 농촌융복합산업 창업자들이 현재의 환경 하에서 농촌융복합산업 창업을 고려할 때 창업의도에 미치는 요인들로서 개인적요인과 외부적요인으로 귀농지역적 요인, 정책적요인을 선정하였다. 이후 선행연구 및 정책적 자료들에 대한 문헌연구를 통해 이론적인 개념을 정립하고 연구모형을 설정하였다. 선택된 연구의 변수들인 내적 개인특성, 외부 환경요인, 정책적요인, 농촌융복합산업 창업의도들 간의 관계를 실증분석하고, 이를 토대로 의미 있는 이론적 및 정책적 시사점들을 제시하고자 한다. 첫째, 농촌융복합산업 창업의도에 영향을 미치는 요인들에 대해 알아볼 것이다. 이를 위해 연구대상인 농촌융복합산업 예비창업자 개인적 요인과 외부적인 지역적요인, 정책요인을 변수로 제시하고자 한다. 둘째, 표본의 일반적 특성과 농촌융복합산업 창업의도와의 상관관계에 대해 분석할 것이다. 연령, 현재 회사에서 맡고 있는 업무분야, 기업규모, 성별, 학력, 농촌융복합산업 유형, 근무경력 등 인구통계적 특성이 개인의 농업·농촌 관심도와 농촌융복합산업 창업의도에 어떤 영향을 미치는지를 집단간 비교분석을 통해 알아볼 것이다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.518-526
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• 2017

This study analyzed the impact of family firms and their characteristics on how they use debts to analyze the decision-making process of Korean family firms. For analysis, we classified the characteristics of family firms into three categories, through the influence of the relationship between the lack of funds and net debt issuance, which was confirmed as the 'packing order theory' of family firms. There was a total of 4,503 enterprises in the Korean Exchange (KRX). The period of analysis was 10 years, between 2004 and 2014. To summarize, Shyam-Sunder and Myers (1999) validated the packing order theory by presenting a model of family businesses that showed greater applicable to higher packing order theory than a model of non-family businesses. Moreover, the results also confirmed the application of the packing order theory by the family stronger corporate governance and ownership structure. The ownership and governance characteristics of the ruling family has also shown the applicability of higher packing order theory.

• The korean journal of orthodontics
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• v.26 no.1 s.54
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• pp.17-32
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• 1996

It is important to understand the operating mechanism and force system of fixed appliance that most effective for individual tooth movement in various orthodontic appliances. The archwire system of fixed appliance is devided into 3 types, which is continuous arch, segmented arch and sectional arch. The last two types have longer interbracket distance and simple force operating points, so it is easy to control force system by operator. But the continuous arch has shorter interbracket distance and various bracket geometry, so it is hard to control and anaylze the force system. The purpose of this study was three dimentional force and moment analysis of continuous arch system by finite element method, which is similar situation to three dimentional elastic beam in structural engineering. Several sample form of various bracket geometry and artificial lower crowding typodont made by author were constructed, analyzed and compared each other. The results were as follows : 1. The force magnitude is linear proportional to the degree of displacement or tilting of the bracket. 2. The force magnitude is inversely non-linear proportional to the interbracket distance. 3. In three dimensional typodont model, while the force can be compared with that of the sample form in the area where adjacent bracket geometry is simple, the force is much more than the expected value in the area where adjacent bracket geometry is complex.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.199-207
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• 2016

This study was conducted to develop a forest fire occurrence model using meteorological characteristics for practical forecasting of forest fire danger rate by reflecting the climate change for the time period of 2000yrs. Forest fire in South Korea is highly influenced by humidity, wind speed, temperature, and precipitation. To effectively forecast forest fire occurrence, we developed a forest fire danger rating model using weather factors associated with forest fire in 2000yrs. Forest fire occurrence patterns were investigated statistically to develop a forest fire danger rating index using times series weather data sets collected from 76 meteorological observation centers. The data sets were used for 11 years from 2000 to 2010. Development of the national forest fire occurrence probability model used a logistic regression analysis with forest fire occurrence data and meteorological variables. Nine probability models for individual nine provinces including Jeju Island have been developed. The results of the statistical analysis show that the logistic models (p<0.05) strongly depends on the effective and relative humidity, temperature, wind speed, and rainfall. The results of verification showed that the probability of randomly selected fires ranges from 0.687 to 0.981, which represent a relatively high accuracy of the developed model. These findings may be beneficial to the policy makers in South Korea for the prevention of forest fires.

• Korea journal of population studies
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• v.21 no.1
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• pp.162-183
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• 1998

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.