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What is Structural Equation Model

Social Reflections of Human-Computer Interaction in Education, Management, and Economics
Structural equation modeling is a multivariate statistical analysis technique that is used to analyze structural relationships. This technique is the combination of factor analysis and multiple regression analysis, and it is used to analyze the structural relationship between measured variables and latent constructs.
Published in Chapter:
The Impact of Attitudes Toward Artificial Intelligence on Job Performance
Funda Hatice Sezgin (Istanbul University-Cerrahpasa, Turkey)
DOI: 10.4018/979-8-3693-3033-3.ch005
Abstract
The perception of artificial intelligence among employees is increasingly relevant as artificial intelligence technologies become more prevalent in the workplace. A positive perception of artificial intelligence can lead to improved job performance, as employees may be more willing to embrace and utilize artificial intelligence technologies to enhance their work. Conversely, a negative perception of artificial intelligence can hinder job performance, as employees may resist or feel threatened by artificial intelligence technologies. This study aims to examine the association between attitudes to artificial intelligence and job performance among 500 academicians employed in universities in Istanbul, using structural equation modeling. The findings of the analysis indicate a statistically significant positive relationship (β=0.412, p<0.01) between artificial intelligence and job performance. It is necessary to emphasize the importance of making academics' attitudes towards artificial intelligence positive.
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A Research on Hedonic and Utilitarian Consumption Behavior of Young Consumers on Big Discount Days
It is a multivariate statistical analysis technique that is used to analyze structural relationships.
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The Relationship Between Sustainable Leadership and Organizational Identification in Universities
Structural equation modeling is a multivariate statistical analysis technique that is used to analyze structural relationships. This technique is the combination of factor analysis and multiple regression analysis, and it is used to analyze the structural relationship between measured variables and latent constructs.
Full Text Chapter Download: US $37.50 Add to Cart
The Impact of Leadership on Learning Outcomes: A Study on Effective Leadership Style for Principals in Vocational Colleges
Is a series of statistical methods used in non-experimental data that allow complex relationships between one or more independent variables and one or more dependent variables.
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Tourist Satisfaction Analysis Through Structural Equation Models
Parametric statistical technique that allows one to test, within a given collection of data, whether a theoretical model related to a complex set of measurable and latent can be verified at the population level.
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