Aligning Yemeni Smes with SDGs: The Role of Innovation Self-Efficacy and Knowledge Sharing on Project Success

Objective: This study explores the interplay between Knowledge Sharing (KSH), Innovation Self-Efficacy (ISE), and Project Success (PS) within Yemeni manufacturing small and medium-sized enterprises (SMEs). It focuses on analyzing how KSH and ISE influence PS, with a particular emphasis on the mediating effect of ISE in the relationship between KSH and PS. Theoretical Framework: This section outlines the key concepts and theories that form the foundation of the research. Social Cognitive Theory (SCT) and the Knowledge-Based View (KBV) are highlighted as the primary frameworks, offering a robust understanding of how ISE and KSH influence PS, especially in resource-limited contexts such as Yemen. Method: Data were collected from 355 project managers and supervisors of manufacturing SMEs using a survey-based quantitative approach across four regions in Yemen. The suggested hypotheses were evaluated through Partial Least Squares Structural Equation Modeling (PLS-SEM). Results and Discussion: The findings show that KSH significantly impacts PS, and ISE partially mediates this relationship. Thus, promoting KSH practices and ISE is crucial for improving project outcomes, especially in resource-limited settings. Future research should examine contextual factors like organizational culture, leadership styles, and external influences to better understand how relationships vary across different industries and regions. Research Implications: Practitioners should focus on fostering a culture of KSH and boosting ISE to achieve better project outcomes. SMEs in challenging environments, like Yemen, can leverage these insights to overcome obstacles and enhance their competitiveness. Originality/Value: This study provides a theoretical and empirical basis for examining the relationship between KSH, ISE, and PS in Yemeni SMEs. It emphasizes the vital role of human and knowledge resources in project success and offers practical recommendations for maximizing these resources in resource-limited settings.