• Management Science and Financial Engineering
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• v.14 no.2
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• pp.67-87
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• 2008

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations which is of vital practical importance in managerial decision making. While DEA assumes exact input and output data, the development of imprecise DEA (IDEA) broadens the scope of applications to efficiency evaluations involving imprecise information which implies various forms of ordinal and bounded data possibly or often occurring in practice. The primary purpose of this article is to characterize the variable efficiency in IDEA. Since DEA describes a pair of primal and dual models, also called envelopment and multiplier models, we can basically consider two IDEA models: One incorporates imprecise data into envelopment model and the other includes the same imprecise data in multiplier model. The issues of rising importance are thus the relationships between the two models and how to solve them. The groundwork we will make includes a duality study which makes it possible to characterize the efficiency solutions from the two models. This also relates to why we take into account the variable efficiency and its bounds in IDEA that some of the published IDEA studies have made. We also present computational aspects of the efficiency bounds and how to interpret the efficiency solutions.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.141-150
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• 2018

Crop type classification is essential for supporting agricultural decisions and resource monitoring. Remote sensing techniques, especially using hyperspectral imagery, have been effective in agricultural applications. Hyperspectral imagery acquires contiguous and narrow spectral bands in a wide range. However, large dimensionality results in unreliable estimates of classifiers and high computational burdens. Therefore, reducing the dimensionality of hyperspectral imagery is necessary. In this study, the Random Forest (RF) classifier was utilized for dimensionality reduction as well as classification purpose. RF is an ensemble-learning algorithm created based on the Classification and Regression Tree (CART), which has gained attention due to its high classification accuracy and fast processing speed. The RF performance for crop classification with airborne hyperspectral imagery was assessed. The study area was the cultivated area in Chogye-myeon, Habcheon-gun, Gyeongsangnam-do, South Korea, where the main crops are garlic, onion, and wheat. Parameter optimization was conducted to maximize the classification accuracy. Then, the dimensionality reduction was conducted based on RF variable importance. The result shows that using the selected bands presents an excellent classification accuracy without using whole datasets. Moreover, a majority of selected bands are concentrated on visible (VIS) region, especially region related to chlorophyll content. Therefore, it can be inferred that the phenological status after the mature stage influences red-edge spectral reflectance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.3837-3844
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• 2015

This study recommends effective ways to establish management strategies by suggesting to hog farm managers the importance of variables' tendency to affect MSY according to hog management. Study subjects included 55 hog farms, which were analyzed using factor and regression analyses to determine each variable's importance (22 total) for hog management, using MSY as the dependent variable. In the analysis result, the main necessary factor controlling MSY improvement was vaccination, followed, according to decreasing significance, by stages of growth classified breeding, thermo-humidity and ventilation control, and veterinary and hygienic control. Based on these results, suggesting the main factors to improve MSY to hog farms will establish management strategies.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.156-156
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• 2022

Explicitly spatially distributed and reliable data on industrial water demand is very much important for both policy makers and researchers in order to carry a region-specific analysis of water resources management. However, such type of data remains scarce particularly in underdeveloped and developing countries. Current research is limited in using different spatially available socio-economic, climate data and geographical data from different sources in accordance to predict industrial water demand at finer resolution. This study proposes a random forest regression (RFR) model to predict the industrial water demand at 0.50× 0.50 spatial resolution by combining various features extracted from multiple data sources. The dataset used here include National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL), Global Power Plant database, AQUASTAT country-wise industrial water use data, Elevation data, Gross Domestic Product (GDP), Road density, Crop land, Population, Precipitation, Temperature, and Aridity. Compared with traditional regression algorithms, RF shows the advantages of high prediction accuracy, not requiring assumptions of a prior probability distribution, and the capacity to analyses variable importance. The final RF model was fitted using the parameter settings of ntree = 300 and mtry = 2. As a result, determinate coefficients value of 0.547 is achieved. The variable importance of the independent variables e.g. night light data, elevation data, GDP and population data used in the training purpose of RF model plays the major role in predicting the industrial water demand.

• East Asian Journal of Business Economics (EAJBE)
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• v.6 no.2
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• pp.1-13
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• 2018

Purpose - The present research is to investigate the effect of psychological empowerment on turnover intention through job satisfaction and organizational commitment. Research design, data, and methodology - These include turnover intention as dependent variable, psychological empowerment as an independent variable and for mediating variables job satisfaction and organizational commitment. Also nationality of employee is used as a moderating variable. Survey data was collected was total 886 respondents from 345 Korean, 313 Chinese, 228 Japanese. Data analysis was conducted with SPSS to test reliability of variables with Cronbach's alpha and one variable confirmatory factor analysis to test common method bias. And regression analysis was conducted to confirm relationship among variables. AMOS was used for path analysis and to analysis moderating effect of employees' country. Results - The results of regression indicate that psychological empowerment increase job satisfaction, affective commitment, normative commitment and turnover intention. Job satisfaction, affective commitment and normative commitment decrease turnover intention. As for the moderating role of country, it seems that country does matter. Conclusions - Main conclusions of this research implicate that to decrease employee turnover intention company need to manage psychological empowerment, job satisfaction, and organizational commitment. Also there is need to consider similarity and difference in managing employees of Korea, China and Japan employees. Manager need to verify direction and importance of each antecedent then apply to employees.

• Steel and Composite Structures
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• v.33 no.6
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• pp.767-776
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• 2019

In this article, a simple and robust multi-objective assessment method to control design angles and node positions connected among steel outrigger truss members is proposed to approve both structural safety and economical cost. For given outrigger member layouts, the present method utilizes general-purpose prototypes of outrigger members, having resistance to withstand lateral load effects directly applied to tall buildings, which conform to variable connecting node and design space deposition. Outrigger layouts are set into several initial design conditions of height to width of an arbitrary given design space, i.e., variable design space. And then they are assessed in terms of a proposed multi-objective function optimizing both minimal total displacement and material quantity subjected to design impact factor indicating the importance of objectives. To evaluate the proposed multi-objective function, an analysis model uses a modified Maxwell-Mohr method, and an optimization model is defined by a ground structure assuming arbitrary discrete straight members. It provides a new robust assessment model from a local design point of view, as it may produce specific optimal prototypes of outrigger layouts corresponding to arbitrary height and width ratio of design space. Numerical examples verify the validity and robustness of the present assessment method for controlling prototypes of outrigger truss members considering a multi-objective optimization achieving structural safety and material cost.

• Journal of Korean Academy of Nursing
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• v.15 no.2
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• pp.5-15
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• 1985

This study was conducted for the purpose of fin-ding out the variance explaining the medical facilities utilization behavior, which is defined adaptation behavior Process by focal, contextual, residual stimuli in Roy's Adaptation Model. What kinds of characteristics can explain adaptation behavior in Roy's Model? And which is the relative importance of input variables? For this analysis, stepwise multiple regression and path analysis was used. The data come from the 1981 Baseline Household Interview Survey in remote rural area. The findings of the analysis can be summarized as follows: First, Total variance of independant variables for adaptation behavior, that is medical facilities utilization including clinic, drug store, health center, herb medicine was shown 16.2 percent. The most important variable which explain the dependent variable was the occurance of illness with the Ra of value 0.112. The illness symptom, living level, regular care source was shown important variables with relatively high the R²value and significant beta coefficient. Second, in the path analysis of variables which is selected important variables, the occurance of illness was shown variable which has the highest direct effect which 0.297 path coefficient. Also the education level of household was shown variable which has the highest indirect effect through living level and the occurance of illness in causal model. Third, This analysis suggests that the occurance of illness belonging focal stimuli are more influenced than others. To sum up, It is seem to the occurance of illness, illness symptom belonging focal stimuli have high explanation ability through direct effect, education level of household among contextual stimuli have explanation ability through indirect effect.

• Asia pacific journal of information systems
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• v.25 no.4
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• pp.784-804
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• 2015

This study investigates the effects of a two-sided message on product attitude and purchase intention by using a message structure variable, such as attribute importance in the context of online consumer reviews (OCRs). Study 1 explains the previous inconsistent results of a two-side message by comparing a one-side message and a two-side message by using the attribute importance in negative reviews. Study 2 determines the reasons for the inconsistent results of a refutational two-sided message research by using the attribute importance in negative reviews and website trust. Two experiments are designed to test our hypotheses. The first experiment is a $2{\times}2$ factorial design with 84 participants. The second experiment uses a $2{\times}2{\times}2$ factorial design with 196 participants. In study 1, two-sided OCRs are more credible than one-sided OCRs, and two-sided OCRs that use low important attributes are more effective in making favorable product attitude/purchase intention. In study 2, refutational two-sided OCRs that use high attribute importance render positive effects on product attitudes in trustworthy websites. However, the refutation could negatively affect product attitude/purchase intention in low trustworthy websites.

• Asian Journal of Business Environment
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• v.10 no.3
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• pp.5-12
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• 2020

Purpose: The main purposes of this study are to examine what the most important hotel facilities that sharia hotels must provide, and to study the relationship between importance of sharia compliance and Muslim tourists' judgment on the performance of sharia hotels. Research Design, Data, and Methodology: The data were collected in Lombok Island. Questionnaires were distributed to Muslim tourists who stayed at one of the sharia hotels, with a total sample of 205 respondents. Factor Analysis Method and Two Independent Sample Tests have been applied in this research to analyze and interpret the data. Result: The results show only one factor is formed from all statements of Sharia compliance variable, and there is a significant difference in the customer experience and customer satisfaction ratings based on the importance of hotel facilities. Conclusion: The present study revealed that Muslim tourists who place a high level of importance in sharia compliance present a more positive assessment for all services provided by sharia hotels. The assessment from Muslim tourists with higher level of importance in Sharia compliance is more positive about their experiences during their stay at the sharia hotels, which also affects their satisfaction.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.88-96
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• 2010

We propose the efficient channel coding method combined with a 2.4kbps speech coder. The code rate of a channel coder is given by 1/2 and 1/2 rate convolutional coder is obtained from the punctured convolutional coder with rate of 1/3. The punctured convolutional coder is used for a variable rate allocation. The puncturing method according to the importance of the output data of the source encoder is applied for the convolutional coder. The importance of output data is analyzed by evaluating the bit error sensitivity of speech parameter bits. The performance of proposed coder is analyzed and simulated in Rayleigh fading channel and AWGN channel. The experimental results with 2.4kbps EHSX coder show that the variable rate channel coding method is superior to non-variable channel coding method from the subjective speech quality.