The Influence Mechanism of Knowledge-Based Professionals' Core Value Identity on Creativity From the Perspective of the Knowledge Economy

Factors influencing women's entrepreneurial success: A multi-analytical approach

Women entrepreneurs are significant contributors to the economic development of any country and their role becomes more vital in improving the economic condition of developing countries. This highlights the important role of women-owned small and medium enterprises (SMEs) and their entrepreneurial success. Therefore, the current study extends the entrepreneurship literature by examining the effects of factors like personality traits (PT), motivation and commitment (MC), availability of financial resources (AFR), and government support (GS) on entrepreneurial success (ES) of women-owned SMEs. Using a purposive sampling technique data from 255 women-owned SMEs were collected. A multi-analytical approach was employed to analyze the data. The Structural equation modeling (SEM) results indicated that PT, MC, AFR, and GS have a direct effect of ES whereas MC also mediated the link between PT and ES, and the results reveal that in presence of MC the effects of PT on ES become more significant. SEM results revealed that PT and AFR are the most important factors related to entrepreneurial success. On the contrary, ANN analysis revealed that "motivation and commitment" is the most influencing factor. These findings can guide business practitioners and policymakers in the envisioned strategy formulation to encourage women entrepreneurs who can contribute to their country's sustainable economic growth.

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

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.