Maximizing CSR impact: Leveraging artificial intelligence and process optimization for sustainability performance management

持续性 企业社会责任 过程(计算) 业务 过程管理 计算机科学 生态学 生物 操作系统
作者
Ali Khan,Khalid Mehmood,Ahsan Ali
出处
标识
DOI:10.1002/csr.2832
摘要

Abstract This study, which is anchored to Resource‐Based View (RBV) theory, explores the relationship between artificial intelligence (AI), process optimization, organizational flexibility, and sustainability performance in organizational settings. Leveraging the RBV framework's focus on internal resources as sources of competitive advantage, this research seeks to clarify how AI adoption, process optimization, and organizational flexibility foster sustainable growth. SPSS PROCESS Macro was used to analyze the data from 288 organizations. The findings derived from the empirical data, this study verify the positive relationships between AI and process optimization as well as AI and sustainability performance, revealing the strategic nature of AI as a resource to improve operational effectiveness and environmental responsibility. Further, our results indicate the mediating role of process optimization and the moderating effect of organizational flexibility in determining the link between AI and sustainability outcomes. Moreover, results confirmed the indirect effects of AI on sustainability performance via process optimization under the boundary conditions of the organizational flexibility. These findings add to the developing literature of sustainable operational practices and provide practical suggestions that might be useful for the practitioners aiming at using AI driven by organizational capabilities to deliver sustainability performance.
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