• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.615-632
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• 2017

Unlike randomized trial, statistical strategies for inferring the unbiased causal relationship are required in the observational studies. The matching with the propensity score is one of the most popular methods to control the confounders in order to evaluate the effect of the treatment on the outcome variable. Recently, new methods for the causal inference in latent class analysis (LCA) have been proposed to estimate the average causal effect (ACE) of the treatment on the latent discrete variable. They have focused on the application study for the real dataset to estimate the ACE in LCA. In practice, however, the true values of the ACE are not known, and it is difficult to evaluate the performance of the estimated the ACE. In this study, we propose a method to generate a synthetic data using the propensity score in the framework of LCA, where treatment and outcome variables are latent. We then propose a new method for estimating the ACE in LCA and evaluate its performance via simulation studies. Furthermore we present an empirical analysis based on data form the 'National Longitudinal Study of Adolescents Health,' where puberty as a latent treatment and substance use as a latent outcome variable.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.51-58
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• 2023

The purpose of this study is to identify various variables that affect the intention to use the metaverse, which has recently attracted attention. In particular, while previous studies have focused only on the variables that have a positive effect on the spread of the metaverse, this study tried to examine both the use and resistance perspectives by examining the psychological variables of consumers who reject specific changes, such as innovation resistance. By constructing consumer characteristics and innovation characteristic variables that affect innovation diffusion, the relationship between innovation resistance, attitude toward the metaverse, and intention to use the metaverse was examined. As a result of the study, it was found that innovation propensity, social image, and conformity had a negative effect on resistance to the metaverse. In addition, innovation propensity, social image, suitability, relative advantage, complexity, and observability mediate innovation resistance and attitudes toward the metaverse, and were finally revealed as variables that have positive or negative influences on the intention to use the metaverse.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.1
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• pp.71-82
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• 2022

Most of the predictions using machine learning are neutral predictions considering the symmetrical situation where the predicted value is not smaller or larger than the actual value. However, in some situations, asymmetric prediction such as over-prediction or under-prediction may be better than neutral prediction, and it can induce better judgment by providing various predictions to decision makers. A method called Asymmetric Twin Support Vector Regression (ATSVR) using TSVR(Twin Support Vector Regression), which has a fast calculation time, was proposed by controlling the asymmetry of the upper and lower widths of the ε-tube and the asymmetry of the penalty with two parameters. In addition, by applying the existing GSVQR and the proposed ATSVR, prediction using the prediction propensities of over-prediction, under-prediction, and neutral prediction was performed. When two parameters were used for both GSVQR and ATSVR, it was possible to predict according to the prediction propensity, and ATSVR was found to be more than twice as fast in terms of calculation time. On the other hand, in terms of accuracy, there was no significant difference between ATSVR and GSVQR, but it was found that GSVQR reflected the prediction propensity better than ATSVR when checking the figures. The accuracy of under-prediction or over-prediction was lower than that of neutral prediction. It seems that using both parameters rather than using one of the two parameters (p_1,p_2) increases the change in the prediction tendency. However, depending on the situation, it may be better to use only one of the two parameters.

• 한국벤처창업학회:학술대회논문집
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• 2021.11a
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• pp.113-117
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• 2021

Due to the recent COVID-19 pandemic, SMEs are forced to converge themselves into online business to cope with the rapidly changing business environment. However, due to various difficulties of becoming an online business, most SMEs choose to use services provided by the online sales platform. These platforms offer valuable support such as DSS in return for the high amount of commission fee. We analyze a novel data set from Naver Corporation's 'Smart Store' platform with the quasi-experimental method (propensity score matching technique combined with the difference in differences analysis) to analyze DSS usage and SME's performance empirically. Our results suggest that DSS usage leads to an increase in SME's sales performance in means of sales frequency and sales amount. Additionally, we have found weak support that DSS usage enables SMEs to attract customers better than those not using DSS.

• Journal of the Korean housing association
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• v.23 no.6
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• pp.31-38
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• 2012

In this paper, we draws tendency of the electricity consumption in residential buildings according to inhabitants Composition types and the level of incomes. it is necessary to reduce energy cost and keep energy security through the electricity demand forecasting and management technology. Progressive social change such as increases of single household, the aging of society, increases in the income level will replace the existing residential electricity demand pattern. However, Only with conventional methods that using only the energy consumption per-unit area are based on Energy final consumption data can not respond to those social and environmental change. To develop electricity demand estimation model that can cope flexibly to changes in the social and environmental, In this paper researches propensity of electricity consumption according to the type of residents configuration, the level of income. First, we typed form of inhabitants in residential that existed in Korea. after that we calculated hourly electricity consumption for each type through National Time-Use Survey performed at the National Statistical Office with considering overlapping behavior. Household appliances and retention standards according to income level is also considered.

• Human Ecology Research
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• v.56 no.4
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• pp.391-405
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• 2018

There has been an increasing and widespread use of smartphones to make consumer purchases. Given the stark increases in the sales of business transactions using mobile phones, it is obvious that mobile phones have become major mediums for consumer purchases. Through mobile phones, people can make their purchases anytime, anywhere, which leads their impulse of consumption directly to actual actions of consumption. Consequently, mobile commerce has become widely spread and the competition of the market has intensified. The main findings and implications of this study are as follows. First, it is shown that, among the features of mobile commerce, elements of fun, usefulness, convenience, immediateness, and security affect mobile commerce user satisfaction. Second, among mobile commerce-related consumers' propensity, innovative consumption tendency appears to impact mobile commerce user satisfaction and repurchase intention. Third, recognition of elements in regards to fun, usefulness, convenience, immediateness, and security among features of mobile commerce affect consumers' intention to repurchase mobile commerce. Future recognition for mobile commerce has a direct impact on increasing consumers' repurchase intentions. Last, a higher mobile commerce user satisfaction leads to the higher repurchase intentions.

• Journal of Korean Academy of Nursing
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• v.37 no.3
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• pp.414-421
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• 2007

Background: Nursing intervention studies often suffer from a selection bias introduced by failure of random assignment. Evaluation with selection bias could under or over-estimate any intervention's effects. PS matching (PSM) can reduce a selection bias through matching similar Propensity Scores (PS). PS is defined as the conditional probability of being treated given the individual's covariates and it can be reused to balance the covariates of two groups. Purpose: This study was done to assess the significance of PSM as an alternative evaluation method of nursing interventions. Method: An intervention study for patients with some baseline individual characteristic differences between two groups was used for this demonstration. The result of a t-test with PSM was compared with a t-test without matching. Results: The level of HbA1c at 12 months after baseline was different between the two groups in terms of matching or not. Conclusion: This study demonstrated the effects of a quasi-random assignment. Evaluation using PSM can reduce a selection bias impact that affects the result of the nursing intervention. Analyzing nursing research more objectively to reduce selection bias using PSM is needed.

• Journal of Digital Convergence
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• v.17 no.5
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• pp.157-165
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• 2019

The objective of this study is to identify the relationship between tourists' intention upon UTAUT and purchase intention on tourism omnichannel considering moderating effect of trust and purchase propensity. As the results, 1) there are partially significant and positive relationship between tourists' intention and purchase intention. There are partially significant and positive moderating effect of 2) trust and 3) purchase propensity upon the relationship between tourists' intention and purchase intention on tourism omnichannel. In order to increase the purchase intention of diversified customers, it is necessary to secure the reliability of OmniChannel which integrates the on-off line, for the future, more in-depth study of purchase propensity of tourism omnichannel should be needed.

• 한국노년학
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• v.38 no.3
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• pp.481-499
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• 2018

The purpose of this study is to examine the impacts of smartphone use on structured social network types in the Korean elderly population. Data was derived from the 2014 survey of living conditions and welfare needs of Korean older persons collected by Korea Institute for Health and Social Affairs. A total of 4,180 participants were selected for the Propensity Score Matching (PSM) analysis. Based on propensity score estimates, the 491 smartphone users (treatment group) and 491 featurephone users (control group) were matched. Ordinary Least Squares (OLS) regression analysis was conducted to examine the relationship between smartphone use and structural social network types. The results showed that among retired older adults, people using smartphone had significantly better structured social networks than those using featurephone even after controlling for covariates. Smartphone users had the higher levels of social contact and social activity. These findings suggested empirical evidence that using smartphone positively affects structured social networks, which might be used as the basis for designing intervention programs to promote social networks and social engagement of retired older adults.

• Journal of Information Technology Applications and Management
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• v.17 no.3
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• pp.99-119
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• 2010

The Radio Frequency IDentification (RFID), once used widely, is expected to provide improved convenience in our everyday life. Crude observations of RFID consumption show that there is a wide variation in the adoption of this technology across different individuals. One plausible explanation is that consumers with challenging mind who seek for new technologies and have a good grasp of the new RFID technology should have higher propensity to use the technology. A better understanding of such acceptance pattern of RFID is of high importance in establishing technology providers' marketing strategies. This study is aimed to explain differences in the level of RFID acceptance focusing on cognitive styles of potential RFID users. By presenting potential RFID users' discriminative propensity toward RFID technology, this study hopes to provide guidelines for the design of service strategies that facilitate consumers' acceptance of RFID.