Identifying the factors affecting strategic decision-making ability to boost the entrepreneurial performance: A hybrid structural equation modeling – artificial neural network approach

Abstract

This study builds a conceptual model of strategic decision-making ability that leads to entrepreneurial performance (EP) based on the two-system decision-making theory and logical analysis. An empirical approach using structural equation modeling – artificial neural network (SEM-ANN) was performed to describe the linear and nonlinear relationships in the proposed model. The empirical results reveal that strategic decision-making abilities are affected by five factors: attention, memory, thinking, emotion, and sentiment, and whose influence mechanisms and degrees are varied. Results also describe that these abilities have a positive effect on overall EP. Therefore, results suggest that businesses’ strategic decision-making is usually strengthened when entrepreneurs have a clear understanding of these influencing elements, and the interaction between them leads to improved performance.