• 지식경영연구
• /
• 제13권4호
• /
• pp.55-69
• /
• 2012

This paper developed measurement indices for intellectual capital of public R&D organizations and investigated causal relationships among the components. We developed 10 measurement factors and 37 indicators and confirmed the reliability of these measurements. We offered an alternative to the existing model for searching causal relationships. From our survey research, using the structural equation model, we found a new relationship. In contrast to the existing model, we found a cycling relationship among three variables: human capital causes structural capital, structural capital causes relational capital, and relational capital causes human capital.

• 대한인간공학회지
• /
• 제22권2호
• /
• pp.1-13
• /
• 2003

In general, causal relationship for theoretical concepts is hypothesized based on precedent studies and tested by a structural equation model. However, when theoretical backgrounds are scarce or absent, the causal relationship is hypothesized operatively by the purpose and scope of research and tested by overall goodness-of-fit indices such as GFI and RMR. Such a causal relationship can't be most appropriate statistically because it is selected as specific relationship from researcher's view among possible causal relationships. Therefore, this study is to propose a procedure for identifying the causal relationship that produces the best GFI among possible causal relationships for theoretical concepts.

• 한국도로학회논문집
• /
• 제14권6호
• /
• pp.121-129
• /
• 2012

PURPOSES : Traffic accidents at intersections have been increased annually so that it is required to examine the causations to reduce the accidents. However, the current existing accident models were developed mainly with non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal complicated causations for traffic accidents, though they are right choices to study randomness and non-linearity of accidents. Therefore, to reveal the complicated causations of traffic accidents, this study used structural equation methods(SEM). METHODS : SEM used in this study is a statistical technique for estimating causal relations using a combination of statistical data and qualitative causal assumptions. SEM allow exploratory modeling, meaning they are suited to theory development. The method is tested against the obtained measurement data to determine how well the model fits the data. Among the strengths of SEM is the ability to construct latent variables: variables which are not measured directly, but are estimated in the model from several measured variables. This allows the modeler to explicitly capture the unreliability of measurement in the model, which allows the structural relations between latent variables to be accurately estimated. RESULTS : The study results showed that causal factors could be grouped into 3. Factor 1 includes traffic variables, and Factor 2 contains turning traffic variables. Factor 3 consists of other road element variables such as speed limits or signal cycles. CONCLUSIONS : Non-linear regression models can be used to develop accident predictions models. However, they lack to estimate causal factors, because they select only few significant variables to raise the accuracy of the model performance. Compared to the regressions, SEM has merits to estimate causal factors affecting accidents, because it allows the structural relations between latent variables. Therefore, this study used SEM to estimate causal factors affecting accident at urban signalized intersections.

• 한국간호교육학회지
• /
• 제11권2호
• /
• pp.161-168
• /
• 2005

Purpose: The purposes are to identify the factors that influence work-based stressor experienced by clinical nurses and to provide a perceived causal structural model among these factors. Method: Data was collected and analyzed in 2 steps to apply a perceived causal structure : network analysis which was developed by Kelley(1983). Results: 1. The extracted causes from qualitative data were identified 10 categories ; over loaded work, relative feelings of deprived, inefficient duty schedule, negative attitudes of patient, burden of extra affair, inadequate administrative support, negative attitudes of physician, conflict with other personnels in hospital, lack of professional knowledge and skill, nursing service marketing burden. 2. Construction of the perceived causal structural model ; 1) The most central cause is over loaded work and the distal causes were inadequate administrative support, lack of professional knowledge and skill in the systems of causation. 2) The causes that have a number of outgoing link were over loaded work, inadequate administrative support, negative attitudes of physician. 3) The cause that have a number of incoming link was relative feelings of deprived. Conclusion: The network suggests that the first centre cause was related on over loaded work.

• 동아시아식생활학회지
• /
• 제17권1호
• /
• pp.136-142
• /
• 2007

This study measured the causal relationships among tourist-perceived sacrifice, service quality, service value, and behavioral intention of employee's service. A total of 224 questionnaires were completed. The equation model was used to measure the causal effect. The results demonstrated that the structural analysis result for the data was an excellent model fit. The influences of perceived value and service quality on service value were statistically significant. As expected, service quality and service value had significant effects on behavioral intention. Moreover, overall service quality played a mediating role in the relationship between perceived sacrifice and service value. Service value played a mediating role in the relationship between service quality and behavioral intention.

• 한국생활과학회지
• /
• 제16권5호
• /
• pp.1031-1040
• /
• 2007

The purpose of this study was to assess the causal relationships of attitude toward fish eating, health involvement, convenience, fish consumption and age. A total of 235 questionnaires were completed. Structural equation model was used to assess the causal relationships among constructs. Results of the study demonstrated that the structural equation analysis result for the data also indicated excellent model fit. The influences of age on health involvement and convenience were statistically significant. The influences of health involvement on attitude toward fish eating and fish consumption behavior were statistically significant. The influence of convenience on fish consumption behavior were statistically significant. Moreover, the age had a significant indirect effect on attitude toward fish eating through health involvement. The age also had a significant indirect effect on fish consumption behavior through convenience.

• 응용통계연구
• /
• 제32권2호
• /
• pp.173-185
• /
• 2019

과학적 연구에서 핵심적인 연구 주제 또는 가설은 대부분 인과적 질문(causal question)을 포함한다. 예를 들어, 전염병 예방을 위한 치료법의 효과 연구, 특정 정책의 시행으로 인한 효용(utility)의 평가에 대한 연구, 특정 사용자를 대상으로 노출된 광고의 종류에 따른 광고의 효과성에 대한 연구는 모두 인과 관계(causal relationship)의 추론이 요구된다. 이러한 인과 관계를 다루는 통계적 인과 추론(statistical causal inference)의 주요 관심사 중 하나는 모집단에 일종의 개입(정책 혹은 처치)을 적용한 후 개입의 효과를 정확하게 추정하는 것이다. 인과 추론은 임상실험과 정책결정에서 주로 이용되었으나, 이른바 빅데이터 시대의 도래로 가용한 관측자료가 폭발적으로 증가하였고 이로 인하여 인과 추론에 대한 잠재적 응용가치와 수요가 지속적으로 증가하고 있다. 하지만 가용한 대부분의 자료는 임의실험 기반의 자료와 달리 개입이 임의로 분배되지 않은 비실험 관측자료이다. 따라서, 본 논문은 비실험 관측자료로부터 개입의 효과를 추정하기 위한 인과 추론의 핵심 개념과 최근의 연구동향을 소개하고자 한다. 이를 위하여 본문에서는 먼저 개입의 효과를 Neyman-Rubin의 잠재 결과(potential outcome) 모형으로 나타내고, 개입의 효과를 추정하는 여러 접근법 중 특히 성향점수(propensity score) 기반 추정법과 회귀모형 기반 추정법을 중점적으로 소개한다. 최근 연구동향으로는 (1) 평균 효과 크기 추정을 넘어선 개인별 효과 크기의 추정, (2) 효과크기 추정에 있어서 자료 규모의 증대로 인한 차원의 저주가 야기하는 난제들과 이에 대한 해결방안들, (3) 복합적 인과관계를 반영하기 위한 Pearl의 구조적 인과 모형(structural causal model) 및 잠재 결과 모형과의 비교의 3가지 주제로 구분하여 소개한다.

• 보건행정학회지
• /
• 제8권1호
• /
• pp.52-96
• /
• 1998

To find causal factors and improvement plans of organizational commitment of public servants in urban health centers, a hypothetical causal model, which included 2 endogenous variables(organizational commitment & organizational satisfaction) and 15 exogenous variables, was constructed. Exogenous variables consisted of individual factors (sex, age, education, job-grade, and annual salary), psychological variables(pride for organization, extrinsic motivation, intrinsic motivation and support of supervisor) ad structural variables(formalization, centralization, communication, job-conflict, job-decision, and workload). In the hypothetical causal model, organizational commitment was supposed to be effect variable, and organizational satisfaction was presumed to be intervening variable to mediate between organizational commitment and exogenous variables. For data collection, cross-sectional self-administered questionnaire survey was conducted to 1,295 public servants from 32 urban health centers nationwide. The survey responses were from 934, 72.1% of subjects. But 756 responses(58.4%) were analyzed because of excluding ones with missing values. The hypothetical causal model was fitted by covariance structural analysis with maximum likelihood method. Main results were as follows: (1) The fitted causal model accounted for 33 and 55 percent of total variance of organizational commitment and organizational satisfaction of public servants, respectively. (2) In order of effect size, pride for organization, supervisor support, communication, extrinsic motivation and centralization had an indirect effect effect on organizational commitment through organizational satisfaction. However, the effect of centralization was negative. (3) Pride for organiztion, intrinsic motivation, organizational satisfaction, job-conflict, supervisor support, communication, age, centralization, annual salar and extrinsic motivation had indirect or direct effects on organizational commitment in order of effect size. Among them, effects of job-conflict and centraldization were negative. In conclusion, these results suggested that organizational commitment of public servants in urban health centers could be enhanced by pride for organization, intrinsic and extrinsic motivations, prevention of job-conflict and excess centralization, supervisor support and active communication. Especially, pride for organization and intrinsic motivation were expected to play the most important role.

• 산업경영시스템학회지
• /
• 제38권2호
• /
• pp.101-107
• /
• 2015

Modern football has transformed into a scientific football based on data. With this trend, various methods for tactics studies and outcome prediction have been developed on the perspective of data analysis. In this paper, we propose a structural equation model for football game. We analyze critical factors that affect to the winning of game except psychological parts and the causal relationship between latent variables and observed variables is statistically verified through the proposed structural equation model. The results show that the Passing ability and the Ball possession affect to the Attack ability, and consequently it has a positive impact on the winning of game.

• Asia pacific journal of information systems
• /
• 제7권2호
• /
• pp.225-266
• /
• 1997

A Causal Transition Model of the IT impact on organization is proposed. The model is based upon the premise that the IT impact is a multi-phase, multi-realm phenomenon, and that the IT impact in one organizational realm logically transpires to another realm, thus forming complex causal webs among them. Two exploratory research studies, the one qualitative and the other quantitative, were conductea to validate the model in a setting involving major structural reorganization of the organizations' IT function. The research results provide support for the general theory structure of the model. The findings include: ⅰ) the IT impact manifests on multiple organizational realms, with different degrees of strength, ⅱ) the impact on the realms follow a particular causal transition path among them, and ⅲ) the IT impact manifests on and through the information processing aspect of work. The results, however, indicate that people's perception of the IT impact is strongly mitigated by the IT relevance of work, and that the organization is affected as much by the structural arrangement surrounding and accompanying the IT as by the technology itself, suggesting that the IT impact is an organizational phenomenon as well as a technological phenomenon. The implications of the research results are discussed at the end.