The role of AI capabilities and entrepreneurial competency in SME performance: the mediating role of strategic intelligence

Artificial Intelligence Adoption and Sustainable Business Performance: The Mediating Role of Innovation Capability

This study investigates how AI adoption enhances organizational innovation capability and, in turn, improves economic, environmental, and social dimensions of business performance, and links digital transformation with sustainability outcomes.

GenAI, Leadership, and Entrepreneurial Orientation: The Mediating Role of Knowledge Management Capability

This study examines how generative artificial intelligence use and knowledge-oriented leadership influence entrepreneurial orientation through the mediating role of knowledge management capability in postsecondary education institutions . Despite the growing interest in artificial intelligence and entrepreneurship, prior research has predominantly focused on individual-level outcomes, while the organizational mechanisms that translate technological and leadership inputs into entrepreneurial behavior remain insufficiently understood. Addressing this gap, the present study adopts a capability-based perspective grounded in the knowledge-based view. A quantitative research design was employed. Data were collected from 387 academic staff members across 25 colleges in Kazakhstan using a structured questionnaire. The proposed model was tested using partial least squares structural equation modeling (PLS-SEM), enabling the assessment of both direct and indirect relationships among the constructs. The results indicate that knowledge-oriented leadership exerts a strong positive effect on knowledge management capability, which in turn significantly enhances entrepreneurial orientation. Generative AI use demonstrates both a direct effect on entrepreneurial orientation and an indirect effect through knowledge management capability, suggesting a complementary mediation mechanism. The findings further reveal that the impact of GenAI is contingent upon its integration into organizational knowledge processes rather than its isolated or ad-hoc use. The study contributes to the literature by providing a capability-based explanation of how technological and leadership factors jointly shape entrepreneurial orientation at the organizational level. It extends prior research by moving beyond individual-level perspectives and highlighting the central role of knowledge management capability as a transformation mechanism. From a practical standpoint, the findings suggest that educational institutions should prioritize the development of structured knowledge processes and leadership practices that support knowledge sharing and application when implementing GenAI initiatives. Such an approach enhances the sustainability and consistency of entrepreneurial behavior within knowledge-intensive environments.

Artificial Intelligence in Supporting Strategic Decision-Making and Its Impact on Organizational Performance

AI capability is a new strategic capability in the organization that goes beyond operational efficiency and can support the quality strategic decision-making, sustainable performance of an organization, and high decision quality. Though AI capability is evolving, current research remains disparate in how to transform an AI capability to a organizational value with the role of governance, leadership, and organizations capability. To solve this, in this study, a integrated conceptual framework grounded in the theory of resource-based view(RBV), dynamic capabilities theory(DCT) and the AI Governance literature is developed and empirically tested. In the model, the sequential relation between AI capability, AI governance, strategic decision quality, organizational agility, and organizational performance was proposed and the moderating role of digital leadership was examined. An explanatory sequential mixed-methods research design was used. The empirical analysis includes two phases. In the first phase, a cross-sectional survey of 446 senior executives and strategic decision makers of public and private organizations was conducted to empirically test the proposed integrated model using Partial Least Squares Structural Equation Modeling (PLS-SEM). In the second phase, qualitative data from 30 semi-structured interviews with senior executives was collected to gain a deep understanding of AI governance, digital leadership and organizational agility practices. Multi-group analysis further revealed differences in the proposed relationships for public and private organizations. Findings revealed that AI capability not only significantly strengthens the AI governance, and consequently the strategic decision quality, but it also improve the organizational agility, resulting in improved performance. Furthermore, digital leadership has a positive effect on reinforcing the association between AI governance and the strategic decision quality. Overall, this study integrates the technology capability, the organizational capability and the leadership capability to establish an AI-enabled strategic decision-making and performance management framework, and provides strategic insights for organizations that aim to realize greater value from their AI investments.

Integrating Learning and Strategy to Enhance SME Performance in Indonesia

This study examines the integration of learning orientation and business strategy in driving the entrepreneurial orientation — specifically innovativeness, proactiveness, and risk-taking — of small and medium-sized enterprises (SMEs) in Indonesia. Grounded in the Resource-Based View (RBV) theory, this research addresses a key gap by investigating how learning and strategy mediate the relationship between entrepreneurial behaviors and firm performance. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) and a survey of 300 SME entrepreneurs, the study finds that learning orientation and business strategy significantly influence firm performance, collectively explaining 51.3 % of the variance. The results demonstrate the pivotal role of innovation, proactive behaviors, and risk-taking in enhancing SME competitiveness and growth. Furthermore, the study highlights the importance of continuous learning and strategic adaptability in helping SMEs navigate Indonesia's dynamic market environment. These findings provide new theoretical insights into the mechanisms driving firm performance and offer practical implications for SME managers and policymakers aiming to foster entrepreneurial growth in emerging economies. This research contributes to the literature by exploring the unique interplay between learning, strategy, and entrepreneurship within the Indonesian context.

The Impact of Artificial Intelligence (AI) Adoption on Employee Competence and Organizational Performance : The Moderating Role of Digital Leadership

Artificial Intelligence Capabilities and Strategic Performance of Manufacturing Firms in Nigeria

This study examined the effect of artificial intelligence (AI) capabilities on the strategic performance of manufacturing firms in Nigeria. The study was motivated by the increasing importance of AI technologies in enhancing organizational competitiveness, operational efficiency, and decision-making. Specifically, the study investigated the influence of machine learning capability, predictive analytics capability, intelligent automation capability, and data management capability on strategic performance. The study was anchored on the Resource-Based View (RBV) theory and adopted a survey research design. Data were collected from managers and supervisors of selected manufacturing firms in Nigeria using a structured questionnaire. Descriptive statistics, correlation, and multiple regression analyses were employed for data analysis. The findings revealed that machine learning capability, predictive analytics capability, intelligent automation capability, and data management capability significantly and positively influence the strategic performance of manufacturing firms. The study concludes that AI capabilities constitute valuable strategic resources that enhance competitiveness, adaptability, and long-term organizational success. The study recommends increased investment in AI infrastructure, employee digital skills development, and data analytics systems to improve strategic outcomes in the Nigerian manufacturing sector.