A Performance Key Features Analysis Model Based on Corporate Sustainability Micro-foundation and Machine Learning: An Empirical Study of the Fast Fashion Manufacturing Industry.

Organizations pursuing sustainable development need unique dynamic capabilities for complex business environments. Organizational dynamic capabilities are built on various forms of employee behaviors, thus possessing distinct individual micro-foundations. Job performance is a manifestation of an employee's behaviors aligned with organizational goals. Studying individual micro-foundations enhances the understanding of building organizational sustainability dynamic capabilities through their impact on job performance. This study collected multidimensional variables influencing job performance in the fashion manufacturing industry. By integrating machine learning techniques and ensemble variable selection methods, an analytical model was developed to identify key performance features. The empirical results revealed the top five key variables influencing job performance: previous year performance, tenure, age, interpersonal atmosphere, and hope. The study further explores these crucial variables and provides improvement recommendations for HR activities within the case company. These suggestions aim to facilitate a swift response to environmental changes and promote the development of dynamic capabilities for organizational sustainability. [ABSTRACT FROM AUTHOR]