Journal of Quantitative Research: PLS and Predictive Analytics focuses on the advancement and application of quantitative research methods, particularly Partial Least Squares (PLS) and predictive analytics, across multidisciplinary fields. The journal publishes studies that rigorously explore theoretical, methodological, and empirical issues with high relevance to academics, practitioners, and policymakers.

The scope of the journal includes, but is not limited to:

1. PLS-SEM Applications – Structural equation modeling, measurement model evaluation, model validation, and reliability analysis.
2. Predictive Analytics – Development and application of predictive models in business, finance, management, social sciences, health, technology, and education.
3. Methodological Innovations – New techniques, tools, and approaches in quantitative research and data analysis.
4. Empirical Studies – Research using quantitative data, simulation, or case studies that demonstrate practical implications.
5. Multidisciplinary Integration – Studies that apply PLS and predictive analytics in interdisciplinary contexts to address complex real-world problems.

The journal encourages submissions that contribute to improving data-driven decision making, enhancing predictive accuracy, and advancing the understanding of complex phenomena through robust quantitative approaches.