• Journal of Distribution Science
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• v.11 no.10
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• pp.93-105
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• 2013

Purpose - This empirical analysis determines the structured causal relations between perceived value, customer satisfaction, and repurchase intention among users of traditional markets. The results of this analysis would help merchants and market operators indevisingan appropriate strategy to successfully manage traditional markets. Research design, data, methodology - The perceived value model of traditional markets includes functional value (price), functional value (quality), emotional value, and social value. In this study, the perceived value of traditional markets is considered as an independent variable, while customer satisfaction and repurchase intention are shown as the dependent variables, where customer satisfaction is also considered as the mediating variable. The study aims to ascertain the extent of influence of the perceived value of traditional markets on customer satisfaction and repurchase intention. We use regression analysis to verify the effects. The measurement items were already deemed as reliable and valid in the previous study, but for this purpose, we made some modifications. We distributed questionnaires to 300 consumers on a national scale, and finally used 241 consumer responses among these as a sample. We analyzed the data using the SPSS 21.0 statistical program. Results - We obtained the following results. First, the order of perceived value dimensions of traditional markets that positively impact customer satisfaction is functional value (price), social value, emotional value, and functional value (quality). Second, the perceived value sometimes directly affects repurchase intention; its effect is typically strong with customer satisfaction as a parameter. The order of perceived value dimensions that positively impact repurchase intention is social value, functional value (price), emotional value, and functional value (quality). Third, the perceived value significantly influences repurchase intention, with customer satisfaction as the mediating variable. Conclusions - We should recognize the importance of perceived value in retail distribution markets, such as traditional markets. Moreover, we need to develop strategies to improve the perceived value. The practical implications of the study are as follows. First, with regards to functional value (quality; price) dimensions, we should have an appropriate assortment of high quality products that are reasonably priced. In addition, customers are satisfied with the friendly service, discounts, and other benefits provided by the merchants. Second, in terms of emotional value dimension, we need to develop differentiated events that provide fun and emotional experience to the customers. Third, in the context of social values dimension, we should strive to positively influence society to enhance social image through activities such as social services and contribution to community development. On the basis of these results, we present the implications, limitations, and future directions for the research. One of the policy implications of the study is that merchants of traditional markets must actively select customers and develop customer value. However, this study is limited in the fact that the population used for data collection is not fully representative, as the survey only covered some specific areas. Moreover, future studies could also benefit with additional research using moderating variables.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.361-366
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• 2019

In developing the avionics system, a system integration laboratory (SIL) is established to verify the function and interworking of individual components. In case of individual verification of SIL's components and system integration, a SIL model that simulates the function and interworking of each equipment is developed and used. A SIL model shall be pre-verified against all data defined in the interface control document (ICD) before interworking with the actual equipment and reverified even when the ICD changes or functions change. However, if the verification of the SIL model is performed manually, the verification of the individual SIL model takes considerable time. For this reason, selective regression tests are often performed to determine a impact of SIL models on ICD changes and some functional changes. In this paper, we designed SIL model verification automation method to perform regession test by reducing verification time of SIL model and verify the usefulness of verification automation design by developing SIL model verification automation tool.

• Journal of Korean Academy of Nursing
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• v.43 no.1
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• pp.1-10
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• 2013

Purpose: The purpose of this study was to develop a prediction model for the characteristics of older adults with depression using the decision tree method. Methods: A large dataset from the 2008 Korean Elderly Survey was used and data of 14,970 elderly people were analyzed. Target variable was depression and 53 input variables were general characteristics, family & social relationship, economic status, health status, health behavior, functional status, leisure & social activity, quality of life, and living environment. Data were analyzed by decision tree analysis, a data mining technique using SPSS Window 19.0 and Clementine 12.0 programs. Results: The decision trees were classified into five different rules to define the characteristics of older adults with depression. Classification & Regression Tree (C&RT) showed the best prediction with an accuracy of 80.81% among data mining models. Factors in the rules were life satisfaction, nutritional status, daily activity difficulty due to pain, functional limitation for basic or instrumental daily activities, number of chronic diseases and daily activity difficulty due to disease. Conclusion: The different rules classified by the decision tree model in this study should contribute as baseline data for discovering informative knowledge and developing interventions tailored to these individual characteristics.

• Journal of Korea Water Resources Association
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• v.48 no.10
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• pp.793-806
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• 2015

The simulation of natural streamflow at ungauged basins is one of the fundamental challenges in hydrology community. The key to runoff simulation in ungauged basins is generally involved with a reliable parameter estimation in a rainfall-runoff model. However, the parameter estimation of the rainfall-runoff model is a complex issue due to an insufficient hydrologic data. This study aims to regionalize the parameters of a continuous rainfall-runoff model in conjunction with a Bayesian statistical technique to consider uncertainty more precisely associated with the parameters. First, this study employed Bayesian Markov Chain Monte Carlo scheme for the estimation of the Sacramento rainfall-runoff model. The Sacramento model is calibrated against observed daily runoff data, and finally, the posterior density function of the parameters is derived. Second, we applied a multiple linear regression model to the set of the parameters with watershed characteristics, to obtain a functional relationship between pairs of variables. The proposed model was also validated with gauged watersheds in accordance with the efficiency criteria such as the Nash-Sutcliffe efficiency, index of agreement and the coefficient of correlation.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.6
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• pp.2639-2642
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• 2012

Background: The patterns of gastric cancer recurrence vary across societies. We designed the current study in an attempt to evaluate and reveal the outbreak of the recurrence patterns of gastric cancer and also prediction of time to recurrence and its effected factors in Iran. Materials and Methods: This research was performed from March 2003 to February 2007. Demographic characteristics, clinical and pathological diagnosis and classification including pathologic stage, tumor grade, tumor site and tumor size in of patients with GC recurrent were collected from patients' data files. To evaluate of factors affected on the relapse of the GC patients, gender, age at diagnosis, treatment type and Hgb were included in the research. Data were analyzed using Kaplan-Meier and logistic regression models. Results: After treatment, 82 patients suffered recurrence, 42, 33 and 17 by the ends of first, second and third years. The mean ( SD) and median ( IQR) time to recurrence in patients with GC were 25.5 (20.6-30.1) and 21.5 (15.6-27.1) months, respectively. The results of multivariate analysis logistic regression showed that only pathologic stage, tumor grade and tumor site significantly affected the recurrence. Conclusions: We found that pathologic stage, tumor grade and tumor site significantly affect on the recurrence of GC which has a high positive prognostic value and might be functional for better follow-up and selecting the patients at risk. We also showed time to recurrence to be an important factor for follow-up of patients.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.597-604
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• 2004

Accurate software cost estimation is essential to both developers and customers. Most of the cost estimating models based on the size measure methods, such as LOC and FP, are obtained through size estimation. The accuracy of size estimation directly influences the accuracy of cost estimation. As a result, the overall structure of regression-based cost models applies the power function based on software size. Many growth phenomenon in nature such as the growth in living organism, performance of technology, and learning capability of human show an S-shaped curve. This paper proposes a model which estimates the developing effort by using the growth curve. The presented model assumes that the relation cost and size follows the growth curve. The appropriateness of the growth curve model based on Function Point, Full-Function Point and Use-Case Point, which are the general methods in estimating the software size have been confirmed. The proposed growth curve model shows similar performance with power function model. In conclusion, the growth curve model can be applied in the estimation of the software cost.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.21 no.11
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• pp.987-994
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• 2008

The optimal structure of the Tonpilz transducer was designed. First, the FE model of the transducer was constructed, that included all the details of the transducer which used practical environment. The validity of the FE model was verified through the impedance analysis of the transducer. Second, the resonance frequency, the sound pressure, the bandwidth, and the impulsive shock pressure of the transducer in relation to its structural variables were analyzed. Third, the design method of $2^n$ experiments was employed to reduce the number of analysis cases, and through statistical multiple regression analysis of the results, the functional forms of the transducer performances that could consider the cross-coupled effects of the structural variables were derived. Based on the all results, the optimal geometry of the Tonpilz transducer that had the highest sound pressure level at the desired working environment was determined through the optimization with the SQP-PD method of a target function composed of the transducer performance. Furthermore, for the convenience of a user, the automatic process program making the optimal structure of the acoustic transducer automatically at a given target and a desired working environment was made. The developed method can reflect all the cross-coupled effects of multiple structural variables, and can be extended to the design of general acoustic transducers.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.787-796
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• 2021

This study investigates the effect of chief executive officers (CEO) demographic characteristics such as age, functional experience, education, and gender, on corporate leverage decisions. This study investigates the independent commissioner's role in moderating the relationship between CEO demographic characteristics and leverage decisions. The data used is panel data with a sample of 283 non-financial companies listed on the Indonesia Stock Exchange (BEI) from 2010-2017. Moderated regression analysis is used as an analytical technique, with the selected model fixed effects model. The results showed that male and young CEOs were more risk-averse, so they tended to use debt more. However, this study found no evidence of the effect of CEO experience and education on leverage. This study finds evidence that independent commissioners reduce the influence of CEO age and gender on leverage decisions. It shows the role of independent commissioners in controlling risk-taking from male and young CEOs related to leverage decisions. These results become input for companies to consider demographic characteristics in choosing a CEO. Also, companies need a board (in this study seen from independent commissioners) that is strong enough to control the CEO regarding risky decision making, such as leverage decisions.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.99-118
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• 2012

The aim of this study is to define a correlation between spatial distribution characteristics of FFG(Functional Feeding Groups) of aquatic insects and related environmental factors in the Geum River based on the theory of RCC(River Continuum Concept). For that objective we had used SMRA(Stepwise Multiple Regression Analysis) method to analyze close relationship between the distribution of aquatic insects and the physical and chemical factors that may affect their inhabiting environment in the study area. And then, a probabilistic method named Frequency Ratio Model(FRM) and spatial analysis function of GIS were applied to produce a predictive distribution map of biota community considering their distribution characteristics according to the environmental factors as related variables. As a result of SMRA, the values of decision coefficient for factors of elevation, stream width, flow velocity, conductivity, temperature and percentage of sand showed higher than 0.5. Therefore these 6 environmental factors were considered as major factors that might affect the distribution characteristics of aquatic insects. Finally, we had calculated RMSE(Root Mean Square Error) between the predicted distribution map and prior survey database from other researches to verify the result of this study. The values of RMSE were calculated from 0.1892 to 0.4242 according to each FFG so we could find out a high reliability of this study. The results of this study might be used to develop a new estimation method for aquatic ecosystem with macro invertebrate community and also be used as preliminary data for conservation and restoration of stream habitats.

• Structural Engineering and Mechanics
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• v.86 no.4
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• pp.547-571
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• 2023

To deeply probe the actual earthquake level and fragility of typical reinforced concrete (RC) structures under multiple intensity grades, considering diachronic measurement building stock samples and actual observations of representative catastrophic earth shocks in China from 1990 to 2010, RC structures were divided into traditional RC structures (TRCs) and bottom reinforced concrete frame seismic wall masonry (BFM) structures, and the empirical damage characteristics and mechanisms were analysed. A great deal of statistics and induction were developed on the historical experience investigation data of 59 typical catastrophic earthquakes in 9 provinces of China. The database and fragility matrix prediction model were established with TRCs of 4,122.5284×104 m² and 5,844 buildings and BFMs of 5,872 buildings as empirical seismic damage samples. By employing the methods of structural damage probability and statistics, nonlinear prediction of seismic vulnerability, and numerical and applied functional analysis, the comparison matrix of actual fragility probability prediction of TRC and BFM in multiple intensity regions under the latest version of China's macrointensity standard was established. A novel nonlinear regression prediction model of seismic vulnerability was proposed, and prediction models considering the seismic damage ratio and transcendental probability parameters were constructed. The time-varying vulnerability comparative model of the sample database was developed according to the different periods of multiple earthquakes. The new calculation method of the average fragility prediction index (AFPI) matrix parameter model has been proposed to predict the seismic fragility of an areal RC structure.