Structural equation modeling the use of a risk assessment instrument in child protective services
Decision Support Systems
Decision support systems unfrastructure: The root problems of the management of changing IT
Decision Support Systems
Network Models and Optimization: Multiobjective Genetic Algorithm Approach
Network Models and Optimization: Multiobjective Genetic Algorithm Approach
Expert Systems with Applications: An International Journal
Sequential Approximate Multiobjective Optimization Using Computational Intelligence
Sequential Approximate Multiobjective Optimization Using Computational Intelligence
International Journal of Information Management: The Journal for Information Professionals
Hi-index | 12.05 |
Many studies have attempted to specify alternative model configurations as fitting empirical data with the aid of structural equation modeling (SEM) method. However, significant path searching between constructs has increased in difficulty and complexity. One way to enhance modeling efficiency is evolutionary optimization by genetic algorithm (GA). This study applies the project management (PM) knowledge possessed by construction personnel and uses techniques, tools, and skills (TTS) to explore the causal relationship between TTS usage and construction engineering project performance (PP). A questionnaire survey is used to empirically measure the effectiveness of PM TTS on PP. The research framework is first defined by hypotheses supported by the literature. The GA is then applied to the model fitting process to optimize the structural paths. Analytical results show that evolutionary optimization for singular and multiple goodness of fit effectively searches the SEM specifications. By using GA in SEM procedure, researchers can perform automated specification searches to find the best empirical model fit to the data.