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Despite the widespread recognition of the significance of entrepreneurial innovations in driving financial success and building firms' competitive advantage, there is a lack of empirical investigation into their impact on organizations. This research paper aims to address this gap by exploring how entrepreneurial innovations can contribute to firms' competitive advantage and the mediating role of entrepreneurial thinking in this relationship. To answer these research questions, this paper utilizes the resource-based view (RBV) of the firm and the dynamic capabilities view (DCV).

The study employed a quantitative research design, and survey data were collected from 102 chief executive officers (CEOs) of Jordanian manufacturing companies in various industries. Structural equation modeling was used to test the hypothesized relationships.

The findings of this study suggest that there is a positive and significant impact of entrepreneurial innovation and thinking on the competitive advantage of firms. The authors also found that entrepreneurial thinking positively mediates this relationship. This study’s results support the RBV and DCV perspectives, which suggest that firms need to leverage unique resources and capabilities and develop dynamic capabilities to achieve a sustained competitive advantage.

The significance of this study lies in its contribution to the literature on the relationship between entrepreneurial innovation, thinking and competitive advantage. While previous research has explored these concepts separately, this study integrates them into a comprehensive framework that highlights the mediating role of entrepreneurial thinking in the relationship between entrepreneurial innovation and competitive advantage.

This study investigates the profound impact of artificial intelligence (AI) capabilities on decision-making processes and organizational performance, addressing a crucial gap in the literature by exploring the mediating role of decision-making speed and quality.

Drawing upon resource-based theory and prior research, this study constructs a comprehensive model and hypotheses to illuminate the influence of AI capabilities within organizations on decision-making speed, decision quality, and, ultimately, organizational performance. A dataset comprising 230 responses from diverse organizations forms the basis of the analysis, with the study employing a partial least squares structural equation model (PLS-SEM) for robust data examination.

The results demonstrate the pivotal role of AI capabilities in shaping organizational decision-making processes and performance. AI capability significantly and positively affects decision-making speed, decision quality, and overall organizational performance. Notably, decision-making speed is a critical factor contributing significantly to enhanced organizational performance. The study further uncovered partial mediation effects, suggesting that decision-making processes partially mediate the relationship between AI capabilities and organizational performance through decision-making speed.

This study contributes to the existing body of literature by providing empirical evidence of the multifaceted impact of AI capabilities on organizational decision-making and performance. Elucidating the mediating role of decision-making processes advances our understanding of the complex mechanisms through which AI capabilities drive organizational success.