Abstract
Many companies use data-driven technologies to drive sustainable business model innovation (BMI), yet often face challenges in doing so effectively. However, the literature at the intersection of data-driven and sustainable BMI remains conceptually dispersed, limiting theoretical progress and practical application. To consolidate the literature, we combine a systematic literature review with bibliometric coupling to conceptualize data-driven sustainable BMI. First, we identify five distinct research streams—digital platforms, circular economy, smart manufacturing and supply chains, blockchain, and servitization—which reflect diverse technological pathways to transform traditional business models into sustainable ones. Second, we develop a dynamic capabilities-based process model that explains how companies can achieve this transformation by orchestrating data-driven and sustainable capabilities across the initiation, ideation, integration, and implementation phases of BMI. This study advances theoretical understanding and provides practical guidance on how data-driven technologies can enable positive environmental, social, and economic outcomes.
| Original language | English |
|---|---|
| Pages (from-to) | 819-847 |
| Number of pages | 29 |
| Journal | Business Strategy and the Environment |
| Volume | 35 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 8 Decent Work and Economic Growth
-
SDG 12 Responsible Consumption and Production
Keywords
- bibliometrics
- business model innovation
- data-driven technology
- dynamic capability
- sustainability
- systematic literature review
Fingerprint
Dive into the research topics of 'Driving Sustainable Innovation: A Review of Data-Driven Technologies in Sustainable Business Model Innovation'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver