Strategic mechanism for enhanced sustainable practice performance in shipping organizations through big data analytics powered by artificial intelligence

Purpose This study aims to analyze the impact of big data analytics powered by artificial intelligence (AI–BDA) on the sustainable practice performance in shipping organizations and to establish a strategic mechanism to achieve sustainable management of the shipping industry. Design/methodology/approach We employed the organizational information processing theory (OIPT) and the knowledge-based view (KBV) as theoretical lenses to develop our research model. To empirically validate the hypotheses, we collected data from 182 shipping organizations and utilized a nine-tier hierarchical moderating regression model, complemented by a three-way interaction analysis. Findings AI-powered big data analytics can positively affect the sustainable practice performance of shipping organizations. Organizational flexibility can help achieve this effect, and interpartner resource sharing increases the impact intensity. Simultaneously, intellectual capital as a boundary condition can promote the moderating effects of organizational flexibility and interpartner resource sharing on the relationship between AI-powered big data analytics and the sustainable practice performance of shipping organizations. The results of qualitative triangulation largely support the quantitative analysis findings, while also highlighting potential issues related to data security and third-party service platforms. Originality/value The results provide theoretical and practical contributions to the research on the sustainable development of shipping and the application of AI-BDA and provide a new research direction by combining OIPT and KBV.