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The intelligence advantage: unlocking business model innovation through supply chain knowledge networks

Matilda Obodua Lartey et al.

Benchmarking: an international journal2026https://doi.org/10.1108/bij-07-2025-0676article
AJG 1ABDC B
Weight
0.50

Abstract

Purpose Due to growing pressure, organizations are forced to introduce new ways of creating and capturing value. Thus, many organizations deploy business model innovation (BMI) to generate competitiveness. Knowledge-based view and dynamic capability view (DCV) were used as theoretical lenses in this study. We examined how supply chain intelligence (SCI) influences BMI through sensing capability (SC) and data-driven decision-making (DDDM) as moderator. Design/methodology/approach The model was tested on 150 multinational manufacturing companies (MMNCs) in Ghana. Variance-based structural equation modeling (partial least squares structural equation modelling [PLS-SEM]) was used for the analyses. Findings The results revealed that customer intelligence and supplier intelligence are directly associated with all BMI dimensions. The findings further showed that competitor intelligence indirectly affects all BMI dimensions. Sensing capability partially mediated the SCI–BMI relationship. DDDM did not exert a moderating influence. Practical implications Firms should prioritize investments in SCI as it has shown the greatest effect on BMI. Sensing capability demonstrates notable effectiveness and plays a supportive role rather than leading innovative efforts. Originality/value By focusing on MMNCs in Ghana, we validate a novel framework by providing empirical evidence on the effects of SCI dimensions on BMI. Furthermore, we analyzed the role of SC and DDDM in the relationship. Thus, we extend theory and offer key insights into how SCI enhances BMI.

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https://doi.org/https://doi.org/10.1108/bij-07-2025-0676

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@article{matilda2026,
  title        = {{The intelligence advantage: unlocking business model innovation through supply chain knowledge networks}},
  author       = {Matilda Obodua Lartey et al.},
  journal      = {Benchmarking: an international journal},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/bij-07-2025-0676},
}

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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.