Research on the Pathway of the Impact of Organizational Ambidextrous Learning on Business Sustainable Development Performance under Machine Learning Algorithms

As organizations navigate the dynamic and complex landscape of today's business environment, the need for continual adaptation to facilitate sustainable development becomes increasingly evident. In this context, organizational ambidexterity - the capability to explore new opportunities while exploiting existing competencies - emerges as a vital strategy for corporations to maintain sustainable growth. This study leverages machine learning algorithms to gather and synthesize data, utilizing a Bayesian network model to predict the influence of organizational ambidexterity on corporate sustainability performance. The empirical findings reveal that ambidextrous learning within an organization has a favorable impact on its sustainable development performance. These insights will not only enrich our comprehension of the inherent relationship between organizational learning and corporate sustainability, but also hold substantial practical implications for businesses striving to enhance their ambidextrous learning capabilities and implement effective sustainability strategies.