• Journal of Information Technology Services
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• v.10 no.2
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• pp.203-221
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• 2011

The purpose of this study is to investigate the applications of Structural Equation Modeling(SEM) into MIS area in recent years. Two methodologies, Lisrel and PLS, are adopted for the method comparison. A research model, based upon TAM(Technology Acceptance Model) is used for the analysis of the data set of a previous study. The research model includes six research variables that are composed of twenty-eight question items. 272 data are used for data analyses through Lisrel v.8.72 and Visual PLS v.1.04. This study shows the statistical results of Lisrel are the same to those of PLS. The contribution of this study can be suggested as the followings; (1) A theoretical comparison of two methodologies is shown, (2) A statistical analysis is done at a real-situated data set, and (3) Several implications are suggested.

• Asia Marketing Journal
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• v.3 no.2
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• pp.1-20
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• 2001

본 연구는 리즈렐을 이용한 자료 분석에서 실제적으로 발생할 수 있는 문제점과 유의해야 할 사항을 실증자료를 이용하여 고찰하기 위한 것이다. 분석자료는 수도권에 소재하고 있는 보험판매영업소에서 판매활동을 하고 있는 328명의 보험판매원의 조직시민 행동(organizational citizenship behaviors, OCB)에 영향을 미치는 선행변수를 파악하기 위해 수집된 자료를 이용하였다. LISREL 적용상의 유의사항으로는 구성 개념과 지표간의 관계 및 구성 개념간의 관계, 좋은 참조변수 지정의 중요성, χ² 검정 적용상의 유의사항, 식별되지 않은 모델과 관련한 유의사항, 초기설정치의 제공과 수용하기 어려운 해와 관련한 유의사항, 모델 탐색시의 유의사항, 공분산행렬로 분석하지 않고 상관 행렬로 분석하는 경우의 문제점, 표본크기 확인과 분석에 선택된 변수 지정의 중요성, 전반적인 적합도에 의한 모델의 검정, 결과 해석과 보고시의 유의사항을 다루고 있다. 이어서, LISREL에 있어서의 모수 유의성 검정상의 문제점에 대해 고찰하고 있으며, LISREL의 유용성과 한계점에 대해서도 다루고 있다.

• Journal of Korean Society of Rural Planning
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• v.5 no.2 s.10
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• pp.56-65
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• 1999

Recently, new concept and paradigm of 'Environmentally-Friendliness' is taking a growing interest in environmental planning and design. This study is to establish the evaluation model for environmentally-friendliness of 'Tourism Farms' in rural areas by LISREL structural equation model. A questionnaire survey was conducted for deputy manager group and expert group. As the Result of LISREL structural equation model, the environmentally-friendliness of tourism farms is composed of three categories. First, conservation of global environment (Low Impact), second, friendliness to surrounding nature(High Contact), and third, environmental health and amenities (Health & Amenity). Five indicators, such as (1)saving of energy and water resource, (2)reduction and reuse of garbage, (3)natural purification of sewage disposal, (4)utilization of natural energy, (5)campaign and education programs of environmentally-friendliness, were affecting the first category, i.e., conservation of global environment(Low Impact). Friendliness to surrounding nature (High Contact) is affected by 3 indicators, (1)contact to nature and diverse green areas, (2)water intimate & contact areas, (3)natural ecology observation by biotope. Finally, the dimension of environmental health and amenity is affected by 3 indicators, (1)nature affinity by farming experience, (2)environmental-friendliness of soil & crops by organic farming, (3) campaign and education programs of environmentally-friendliness. Total coefficient of determination of the structural equation model by LISREL was 0.897, which showed high explanatory power.

• Journal of Applied Reliability
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• v.2 no.1
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• pp.33-45
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• 2002

We investigate into some problems related to Corruption Perception Index(CPI). Delphi method is a popular for obtaining CPI; it is a mean of systematically collecting and progressively refining information provided by a group of selected experts in order to obtaining the weight values of questionnaires. However, Delphi method hold low aspect, to some extent, for it is solely dependent upon the judgment of a few professionals. In this paper, we propose the measurement model for X in LISREL as alternative for gaining the weight values of questionnaires. We use the 1999 Seoul ACI(Anti- Corruption Index) for empirical study.

• Journal of The Korean Association For Science Education
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• v.17 no.3
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• pp.301-311
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• 1997

The purpose of this study is to construct a structural equation model and to analyze causal relationships among variables related to attitudes to science using structural equation modeling(SEM) with LISREL VII. The sample consisted of 483 10th grade boys from a general high school in Pusan, Korea. The questionnaires (ABC-attitude scale: affection, behavioral intention, cognition scale of attitude towards science) were developed by the researcher through a pilot study. And other instruments have modified previous ones. Five instruments were used in this study: GALT(group assessment of logical thinking), MTSlS(modified test of science inquiry skill), ABC-attitude scale, MSAS(modified scientific attitude scale), CSAT(common science achievement test). Structural equation modeling with LISREL VII($J\ddot{o}reskog$ & $S\ddot{o}rbom,$ 1993) was employed to estimate the causal inferences about hypothesized relationships among observed data sets. Three competing models consisted of five latent variable(scientific thinking ability, science inquiry skill, attitude towards science, scientific attitude, science achievement) - lP(inquiry preceding) model, AP(attitude preceding) model and AM(attitude mediating) model - were developed. Among these competing models, IP model satisfied the observed data sets. The causal relationships among "attitudes to science" and other latent variables were reliably identified. According to the results of the present study, science inquiry skill was the most significant variable that can predict science achievement. But scientific thinking ability has not directly influenced science achievement. This study suggests that inquiry based teaching-learning processes should be offered to students for improvement of science achievement. At the same time, it seems to be important to develop positive attitude towards science. Understanding of relationships among variables related to attitudes to science will be helpful to the development of science curriculum and to the design of science teaching and learning process. LISREL has been recognized as a useful approach in testing a SEM. However, in this study, LISREL approach was estimated as much more useful method for research design.

• Proceedings of the Korean Association for Survey Research Conference
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• 2001.06a
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• pp.3-11
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• 2001

본 연구에서는 델파이 방법에 의한 1999년 서울시 반부패지수를 검토하고, 5대 민생취약부분 중 위생분야 조사자료를 토대로 하여 LISREL 측정 모형에 의한 반부패지수 산출 절차를 논의하며, 두 분석결과를 비교한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.978-984
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• 2018

Structural equation modeling is pointing to statistical procedures that simultaneously perform path analysis and confirmatory factor analysis. Today, this statistical procedure is an essential tool for researchers in the social sciences. There are as AMOS, LISREL and PLS representative tools that can perform structural equation modeling analysis. AMOS provides a convenient graphical user interface for beginners to use. PLS has the advantage of not having a constraint on normal distribution as well as a graphical user interface. Therefore, we compared and analyzed the three most commonly used tools (applications) in social sciences. Based on structural equation modeling, confirmatory factor analysis was performed using the IBM AMOS Ver. 23, the LISREL 8.70 and the SmartPLS 2.0. The comparative results show that LISREL has the highest explanatory power of dependent variables than other analytical tools. The path coefficients and T-values presented by the analysis results showed similar results for all three analysis tools. This study suggests practical and theoretical implications based on the results.

• Health Policy and Management
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• v.4 no.2
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• pp.58-76
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• 1994

In order to study factors affecting the use of the ambulatory physician services. Andersen's model for health utilization was modified by adding the health behavior component and examined with three different approaches. Three different approaches were the multiople regression model, logistic regression model, and LISREL model. For multiple regression, dependent variable was reported illness-related visits to a physician during past one year and independent variables are variaous variables measuring predisposing factor, enabling factor, need factor and health behavior. For the logistic regression, dependent variable was visit or no-visit to a physician during past one year and independent variables were same as the multiple regression analysis. For the LISREL, five endogenous variables of health utiliztion, predisposing factor, enabling factor, need factor, and health behavior and 20 exogeneous variables which measures five endogenous variables were used. According to the multiple regression analysis, chronic illness, health status, perceived health status of the need factor; residence, sex, age, marital status, education of the predisposing factor ; health insurance, usual source for medical care of enabling factor were the siginificant exploratory variables for the health utilization. Out of the logistic regression analysis, health status, chronic illness, residence, marital status, education, drinking, use of health aid were found to be significant exploratory variables. From LISREL, need factor affect utilization most following by predisposing factor, enabling factor and health behavior. For LISREL model, age, education, and residence for predisposing factor; health status, chronic illess, and perceived health status for need factor; medical insurance for enabling factor; and doing any kind of health behavior for the health behavior were found as the significant observed variables for each theoretical variables.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.131-134
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• 2018

Structural equation modeling is pointing to statistical procedures that simultaneously perform path analysis and confirmatory factor analysis. Today, this statistical procedure is an essential tool for researchers in the social sciences. There are as (AMOS, LISREL and PLS) representative tools that can perform structural equation modeling analysis. AMOS provides a convenient graphical user interface for beginners to use. PLS has the advantage of not having a constraint on normal distribution as well as a graphical user interface. Therefore, we compared and analyzed the three most commonly used tools in social sciences. This study suggests practical and theoretical implications based on the results.

• Journal of Korean Society of Forest Science
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• v.97 no.3
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• pp.255-265
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• 2008

This study is aiming at providing the useful information for successful implementation of the forest resource promotion policy through analyzing the impacting factors and their relationships on policy accomplishment and policy effectiveness in executing the forest resource promotion policy. Interview survey was conducted on the stake-holders such as government officers and civilians who have direct or indirect influences on the establishment and execution of the forest resource promotion policy. The forest resource promotion policy was heuristically analyzed by using the LISREL (Linear Structural RELations) Model. The policy accomplishments of forest resource promotion significantly showed the positive relations with the suitability of problem recognition, the suitability of policy decision-making and rationality of policy execution, while the degree of policy support and the policy accomplishments were having significant impacts upon the policy effectiveness. Since the path coefficients between the latent variables and observed variables and among the latent variables mostly showed the positive relations significantly, the forest resource promotion policy was evaluated very successful in terms of policy accomplishments and policy effectiveness.