• Health Policy and Management
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• v.11 no.1
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• pp.62-86
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• 2001

This study purports to Investigate the determinant of job satisfaction and the organizational commitment of medical insurance review nurses working at Korean hospitals. The independent variables contain three groups of determinants: organizational characteristics variables(job autonomy, work unit control, role variety, role ambiguity, role conflict, workload, resource inadequacy, coworker support, supervisor support, distributive justice, promotional chances, job security, and job hazard), environmental variables(job opportunity, spouse support, and parent support), and psychological variables (met expectation, work involvement, positive affectivity, and negative affectivity). The sample used in this study consisted of 445 medical insurance review nurses from 89 hospitals nationwide. Data were collected with self-administered questionnaires and analyzed using multiple regression analysis. The results of the study are as follows : 1) the following variables, listed in order of size, have significant effects on job satisfaction : role ambiguity(－), distributive justice(＋), work involvement(＋), role variety(＋), met expectation(＋), negative affectivity(－), job autonomy(＋), and positive affectivity(＋). 2) the following variables, listed in order of size, have significant effects on organizational commitment: met expectation(＋), work involvement(.＋), distributive justice(＋), job security(＋), role variety(＋), positive affectivity(＋), negative affectivity(－), resource inadequacy(＋), and tenure(－). 3) the variance of job satisfaction and organizational commitment explained by the variables used in the study are 30.0% and 39.1% respectively. 4) In comparison to the results of other studies on the determinants of job satisfaction and organizational commitment of clinical nursing staff working at hospitals, the results of this study indicate that three variables of distributive justice, work involvement, and role variety are especially important for improving the level of job satisfaction and organizational commitment of medical insurance review nurses.

• Journal of the Ergonomics Society of Korea
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• v.19 no.3
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• pp.23-37
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• 2000

Usability is one of the most important factors that affect customers' decision to purchase a product. Several studies have been conducted to model the relationship between the product design variables and the product usability. Since there could be hundreds of design variables to be considered in the model, a variable screening method is required. Traditional variable screening methods are based on expert opinions (Expert screening) in most Kansei engineering studies. Suggested in this study are statistical methods for screening important design variables by using the principal component regression(PCR), cluster analysis, and partial least squares(PLS) method. Product variables with high effect (PCR screening and PLS screening) or representative variables (Cluster screening) can be used to model the usability. Proposed variable screening methods are used to model the usability for 36 audio/visual products. The three analysis methods (PCR, Cluster, and PLS) show better model performance than the Expert screening in terms of $R^2$, the number of variables in the model, and PRESS. It is expected that these methods can be used for screening the product design variables efficiently.

• Journal of Korean Society for Quality Management
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• v.39 no.2
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• pp.244-255
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• 2011

In this study, we try to evaluate the efficiency of the photonics industry using a data envelopment analysis(DEA) model. We first develope four stage procedures for selecting proper input and output variables which consist of selecting the first candidate variables from literature survey, selecting the second candidate variables through experts' discussion, measuring the partial efficiency of the selected variables based on Tofallis' profiling, and clustering some variables through the rank correlation analysis of partial efficiency proposed by Min and Kim(l998). With this procedure, we select 4 input variables(capital, number of employee, R&D cost, operating cost) and 2 output variables(sales, growth of sales) and then utilize CCR and BCC model to measure efficiencies of 26 photonics companies in Gwangju. Moreover, we perform the reference group analysis to figure out what causes inefficiencies and to provide the desirable values for input and output variables at which inefficient photonics companies become efficient. Finally, we classify 26 photonics companies into three groups such as optical communications, optical applications, and optical sources, and perform the Kruskal-Wallis test to check if there exist some differences between efficiencies of three groups.

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.2
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• pp.367-381
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• 2024

The sharing economy (SE) describes an economic system in which consumers share a product or service via collaborative consumption. Reasonably, the SE receives much attention in the fashion industry as a sustainable form of consumption. However, a systematic review of the antecedents and outcomes of consumer participation in SE is limited by researchers' and practitioners' hindered understanding of what consumers expect and gain from the SE. This study offers a systematic review of the SE research conducted from January 2016 to July 2021 and proposes a conceptual model. In terms of antecedents, three factors, composed of nine categories and 153 variables, were identified: 1) consumer factors (80 variables), 2) platform/product factors (69 variables), and 3) environmental factors (4 variables). The outcomes included 14 variables divided into two categories: 1) positive outcomes (8 variables) and 2) negative outcomes (6 variables). The results provide recommendations for future research on applying the SE to the fashion sector. First, to more thoroughly investigating antecedents of consumer participation in fashion sharing, the research must focus on barriers and environmental factors, in addition to demographic and psychological variables. Secondly, research on the outcomes of participating in fashion sharing, including economic and social benefits, is needed.

• The Journal of Fisheries Business Administration
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• v.22 no.1
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• pp.53-75
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• 1991

The objectives of this study are to conceptualize theoretically and to examine empirically the interrelationships among channel member's satisfaction, dependence, and performance being immanent between dealing partners, by integrating behavioral and economic approach to explain comprehensively the interrelationship between dealing partners in conventional marketing channel which have not studied in previous studies. To attain above objectives, latent variables and observed variables which had been immanent between licenced dealers and wholesalers in fish marketing channel were found out by exploratory study, and pre-test was conducted to select the proper variables, and then the model which could explain the interrelationships among the variables was set up. Three categories of varables were considered in this study. Namely, economic and noneconomic factors were identified as independent variable, the degree of satisfaction and dependence to dealing partner as intervening variable, and performance as dependent variable. The data for the study was obtained from a survey questionnaire of 214 licenced dealers who work in Pusan, Yusoo, and Kunsan and 190 wholesalers who work in whole country. Among them, 264 anayzable questionnaires(including 154 licenced dealers and 110 wholesalers)were collected. Statistical procedure to analyze the data was carried out by LISREL version 7. Major findings obtained from the results of the analysis are as follows. First, economic variables have a great influence on the degree of both licenced dealers' and wholesalers' satisfaction. Among economic variables, the degree of keeping wholesalers' payment date have greater influence on the degree of licenced dealers' satisfaction, and licenced dealers' faculty being able to send good fish in quality have greater influence on the degree of wholesaler's satisfaction than other variables. In short, licenced dealers make great account of wholesalers' payment, and wholesalers make great account of licenced dealers' faculty being able to send good fish in quality in dealing relationship. Second, noneconomic variables have more relevance to the degree of dependence in both sides than economic variables. This means that noneconomic variables as well as economic variables can be a factor to keep up the dealing relationship. Third, the degree of satisfaction and dependence have influence on performance in both sides. In the licenced dealers' side, the degree of dependence have greater influence on performance than the degree of satisfaction, on the other hand, in wholesalers' side, the degree of satisfaction have greater influence on performance than the degree of dependence. This means that wholesalers can easily substitute their dealing partner for another licenced dealer comparatively.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.141-149
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• 2008

Recently we frequently analyze multivariate data with quite large number of variables. In such data sets, virtually duplicated variables may exist simultaneously even though they are conceptually distinguishable. Duplicate variables may cause problems such as the distortion of principal axes in principal component analysis and factor analysis and the distortion of the distances between observations, i.e. the input for cluster analysis. Also in supervised learning or regression analysis, duplicated explanatory variables often cause the instability of fitted models. Since real data analyses are aimed often at multiple purposes, it is necessary to reduce the number of variables to a parsimonious level. The aim of this paper is to propose a practical algorithm for selection of a subset of variables from a given set of p input variables, by the criterion of minimum trace of partial variances of unselected variables unexplained by selected variables. The usefulness of proposed method is demonstrated in visualizing the relationship between selected and unselected variables, in building a predictive model with very large number of independent variables, and in reducing the number of variables and purging/merging categories in categorical data.

• Journal of the Korean Statistical Society
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• v.11 no.2
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• pp.88-93
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• 1982

A local limit theorem for large deviations for the i.i.d. random variables was given by Richter (1957), who used the saddle point method of complex variables to prove it. In this paper we give an alternative form of local limit theorem for large deviations for the i.i.d. random variables which is essentially equivalent to that of Richter. We prove the theorem by more direct and heuristic method under a rather simple condition on the moment generating function (m.g.f.). The theorem is proved without assuming that $E(X_i)=0$.

• Journal of the Korean Statistical Society
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• v.29 no.3
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• pp.315-318
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• 2000

In this note we use the Poisson Summation Formula to generalize a result of Harris and Park (1994) on lattice distributions induced by uniform (0,1) random variables to those generated by random variables with step functions as their probability functions.

• Journal of the Korean Institute of Landscape Architecture
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• v.20 no.2
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• pp.18-26
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• 1992

The purpose of this study is to suggest a method for identifying target markets of potential urban park users by their sociodemographic variables. Data was classified into(ⅰ) users vs. nonusers ; (ⅱ) of chosen three urban parks ; or(ⅲ) users of each urban park then analyzed by discriminant analysis. The results showed that linear combination of selected sociodemographic variables could be used for identifying target markets in some cases. In general, season and sex were the most powerful discriminant variables. But the other cases were not satisfactory. The weak points of this study due to adapting secondary data for analysis were discussed.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.206-211
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• 1998

In audio techniques calculation of digital filters is accelerated considerably by use of wave variables instead of voltages and currents. The suitability of wave variables for digital simulation of power converters was investigated and the results are reported in this paper. The original method is described briefly, modelling of switches and diode rectifiers is presented, examples are given and the features of the method are discussed.