About the Journal
Structural Equation Modelling and Multivariate Research (SEMMR)
Aims and Scope
Structural Equation Modelling and Multivariate Research (SEMMR) is dedicated to advancing knowledge in Structural Equation Modelling (SEM) and Partial Least Squares SEM (PLS-SEM). Our journal serves as a platform for the latest research, methodological innovations, and practical applications within this field. SEMMR aims to enhance both the theoretical understanding and practical application of SEM techniques across a variety of disciplines.
Focus Areas
Current Research: SEMMR publishes up-to-date studies that offer new insights into SEM and PLS-SEM, contributing to the ongoing development and refinement of these methodologies.
Methodological Innovations: We highlight papers that introduce novel methods or enhance existing SEM techniques, thereby advancing the technical aspects of structural equation modelling.
Applications: Our journal features practical applications of SEM in various fields, demonstrating how these techniques can address real-world problems and improve research outcomes.
Multidisciplinary Approach
SEMMR embraces a broad range of academic disciplines, reflecting the diverse applications of SEM. We welcome contributions from:
Artificial Intelligence (AI)
Tourism
Education
Marketing
Business
Economics
Econometrics
Psychology
Health
Sport
Sociology
Political Science
Gastronomy
By including research from these diverse fields, SEMMR showcases the versatility and relevance of SEM methodologies.
Types of Contributions
Theoretical Articles: These papers explore new theories, frameworks, or models in SEM and PLS-SEM. They contribute to academic discourse by presenting novel ideas that push the boundaries of current knowledge.
Applied Papers: These articles present innovative uses of SEM and PLS-SEM across various disciplines. They include practical case studies, empirical research, and methodological innovations that illustrate the effectiveness of SEM in solving complex problems.
Additional Content
In addition to research articles, SEMMR may feature:
Book Reviews: Reviews of recent publications that introduce new SEM and PLS-SEM software or discuss recent advancements in theory and practice.
Studies Using Multivariate Statistical Techniques: Research employing multivariate methods that complement or enhance SEM methodologies, offering broader insights into statistical analysis.
Objective
By bridging the gap between theoretical advancements and practical applications, SEMMR aims to foster a comprehensive understanding of structural equation modelling and its diverse uses. The journal serves as a vital resource for researchers, practitioners, and scholars, supporting the growth and development of SEM across multiple fields.
