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What is Structural Equation Modelling (SEM)

Chapter 7
Reshaping Entrepreneurial Education Within an Industry 4.0 Context
Structural Equation Modelling is a statistical approach utilized to scrutinize the relationships between observed and latent variables. Frequently applied in social sciences and other disciplines to assess and affirm intricate theoretical models, SEM enables researchers to explore both direct and indirect effects within a system of equations. This method provides insights into the fundamental structures of relationships in data.
Published in Chapter:
Mapping Research Gaps in Reported Skills Required for Women Entrepreneurs in Industry 4.0
Preeti Sharma (Sharda School of Business Studies, Sharda University, India), Apoorva Verma (Sharda University, India), and Aparajita Das Gupta (Amity University, India)
Copyright: © 2024 |Pages: 21
DOI: 10.4018/979-8-3693-0409-9.ch007
Abstract
The study suggests a theoretical framework that bridges the gap between the new entrepreneurship model and government policies required for women entrepreneurs. To test the suggested model and hypothesis, a survey of a sample of 289 women entrepreneurs (18-48) was conducted. Cronbach's alpha and a confirmatory factor analysis were used to determine the scale's reliability and validity. Structural equation modelling (SEM) was utilised to verify the given model and hypothesis. In this research, six hypotheses were tested, and it was found that the hypotheses were showing a direct relationship. Specifically, the result of SEM showed that the latent variables HC (human capital), SC (social capital), DMC (digital market competence), FL (financial literacy), TP (technological proficiency), and FTA (financial technological awareness) have direct relationship with the observed variable entrepreneur abilities (EA). This study fills this research gap.
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Chapter 10
A Statistical Analysis of Priority Factors for Local e-Government in a Developing Country: Case Study of Yogyakarta Local Government, Indonesia
A new concept employed in factor analysis and multivariate analysis in situations where the impact of multi-dimensional factors on a concept is being investigated.
Published in Chapter: A Statistical Analysis of Priority Factors for Local e-Government in a Developing Country: Case Study of Yogyakarta Local Government, Indonesia; From: Handbook of Research on E-Government in Emerging Economies: Adoption, E-Participation, and Legal Frameworks
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Chapter 123
Telecommunications Subscriber's Satisfaction and Loyalty: The Impact of Contractual Switching Cost, Price Fairness, and Brand Image
A general term to explain a family of statistical methods and procedures to assess a conceptual or theoretical model including confirmatory factor analysis, path analysis, and exploratory factor analysis.
Published in Chapter: Telecommunications Subscriber's Satisfaction and Loyalty: The Impact of Contractual Switching Cost, Price Fairness, and Brand Image; From: Encyclopedia of E-Commerce Development, Implementation, and Management
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Chapter 40
Knowledge Sharing Mediating Information Technology Student Innovation
Permits the researcher to statistically model and test complex phenomena.
Published in Chapter: Knowledge Sharing Mediating Information Technology Student Innovation; From: Handbook of Research on Modern Educational Technologies, Applications, and Management
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Chapter 3
Role of Human Resources, Production Process, and Flexibility on Commercial Benefits From AMT Investments
Statistical technique for building and testing statistical models, which are often causal models. It is a hybrid technique that encompasses aspects of confirmatory factor analysis, path analysis and regression analysis.
Published in Chapter: Role of Human Resources, Production Process, and Flexibility on Commercial Benefits From AMT Investments; From: Optimizing Current Strategies and Applications in Industrial Engineering
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Chapter 2
Application of ISM in the Manufacturing Sector
SEM is a multivariate statistical analysis technique that is usually utilised for the analysis of structural relationships. It is usually regarded as an amalgamation of multiple regression and factor analysis and is used to assess the structural relationships that tend to exist between the latent constructs and the variables used to measure these latent constructs.
Published in Chapter: Application of ISM in the Manufacturing Sector; From: Multi-Criteria Decision Analysis in Management
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