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Leveraging AI for geo-economic decisions: navigating the nexus between business process management, knowledge management and business intelligence practices

A. Pal et al.

Business Process Management Journal2026https://doi.org/10.1108/bpmj-06-2025-0865article
AJG 2ABDC B
Weight
0.50

Abstract

Purpose The purpose of this study is to explore how artificial intelligence (AI), integrated with business process management (BPM), knowledge management (KM) and business intelligence (BI), can optimize decision-making in geo-economic contexts, utilizing the resource-based view (RBV) theory. Design/methodology/approach Data were gathered from over 280 professionals representing listed information technology companies in northern India using a structured questionnaire. Convenience sampling was employed for data collection. The measurement and structural models were tested using partial least squares structural equation modeling (PLS-SEM). Findings AI adoption significantly improves BI, BPM and KM practices though it has no direct effect on geo-economic decision-making (GEDM). BPM, however, strongly drives both GEDM and KM, positioning it as a key strategic enabler. Mediation analysis shows that BI and BPM partially transmit AI's influence on organizational decision-making. Originality/value The research provides a new perspective on how AI can be combined with BPM, KM and BI in GEDM. This approach provides insight into how a network of interconnected resources leverages organizational capabilities – a contribution with new insight for leveraging performance in complex, dynamic global environments, particularly through the application of RBV theory to create value.

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https://doi.org/https://doi.org/10.1108/bpmj-06-2025-0865

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@article{a.2026,
  title        = {{Leveraging AI for geo-economic decisions: navigating the nexus between business process management, knowledge management and business intelligence practices}},
  author       = {A. Pal et al.},
  journal      = {Business Process Management Journal},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/bpmj-06-2025-0865},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.