Explaining the Quantitative Model of High-Performance Work Systems in the Healthcare Sector of Ardabil Province through Structural Equations

This study was done with the aim of providing high performance work systems.

The method of this quantitative research was correlational and descriptive, and quantitative method was used to provide a model of high-performance work systems. The statistical population of the research in the quantitative part is made up of health workers of Ardabil province, and a sample size of 358 people was selected through the Morgan-Jersey table. The validity of the tool was confirmed through the advice and guidance of the supervisors, and the reliability of the tool was also confirmed through the calculation of Cronbach's alpha coefficient above 0.7. In order to analyze the data, descriptive statistics were used to describe the conditions and demographic indicators, and inferential statistics were used to quantitatively analyze the model from confirmatory factor analysis in the form of SPSS25 and Lisrel 8.8 software. Statistical analysis was conducted on 25 categories and 85 subcategories (causal conditions including 4 components, background category 4 components, intervention category 4 components, main core 5 components, strategies 4 components and consequences 4 themes) which formed the conceptual framework of the research.

According to the findings, it can be said that the current proposed model can improve the model measurement of high-performance work systems. The results of the confirmatory factor analysis with the observed factor loadings for all categories and themes which are more than 0.3 which are within the acceptable range, and the significant T-value test which is greater than 1.96, show the fit of the structural model.

The confirmation of the theoretical model and the results of the structural model also showed that the research variables with path coefficient and T-value have a positive effect on each other, finally, other indicators of the fit of the structural model also helped to confirm the quantitative and conceptual model. At the end, suggestions were presented.