Exploring how the ambidextrous leadership influences knowledge workers innovative behavior: a two stage SEM-ANN analysis

探究双元领导力如何影响知识型员工的创新行为:一项两阶段结构方程模型-人工神经网络分析

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Abstract

This study investigates the impact of ambidextrous leadership, which integrates transformational and transactional leadership styles, on the innovative behavior of knowledge workers. Grounded in theory of reciprocal determinism, it explores the mediating roles of perceived organizational support and self-efficacy, addressing gaps in the literature on leadership and innovation. Data were collected from 372 knowledge workers in China via an online survey, and analyzed using a two-stage methodology that combines Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess linear relationships and Artificial Neural Network (ANN) analysis to capture non-linear dynamics. The results indicate that ambidextrous leadership significantly enhances knowledge workers' innovative behavior through the mediating effects of perceived organizational support and self-efficacy, with a chain mediation effect underscoring the interplay between leadership, organizational support, and individual psychology. By integrating ambidextrous leadership with reciprocal determinism theory, this study enriches the theoretical understanding of leadership's role in fostering innovation and provides cross-cultural evidence of its applicability. The findings offer practical strategies for organizations to foster innovation by creating supportive environments and adopting adaptive leadership practices. Future research could explore longitudinal effects and investigate additional mediating or moderating variables to further deepen the understanding of leadership's impact on innovation.

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