Driving Sustainable Innovation: A Review of Data-Driven Technologies in Sustainable Business Model Innovation

  • Nadine Bachmann*
  • , Rainer Harms
  • , Katherine Gundolf
  • , Tamara Oukes
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

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 languageEnglish
Pages (from-to)819-847
Number of pages29
JournalBusiness Strategy and the Environment
Volume35
Issue number1
DOIs
Publication statusPublished - Jan 2026

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