Open AccessWhat about Data-Driven Business Models? Mapping the Literature and Scoping Future Avenues
Author(s) -
Maria Vincenza Ciasullo,
Raffaella Montera,
Emilia Romeo
Publication year - 2021
Publication title -
international journal of business and management
Language(s) - English
Resource type - Journals
eISSN - 1833-8119
pISSN - 1833-3850
DOI - 10.5539/ijbm.v16n8p1
Subject(s) - systematic review , extant taxon , intersection (aeronautics) , business model , phenomenon , knowledge management , management science , data science , computer science , business , marketing , political science , engineering , epistemology , philosophy , medline , evolutionary biology , law , biology , aerospace engineering
The paper aims to perform an assessment of the literature at the intersection of data and business models, examining the extent to which the data-driven business model (DDBM) is considered in the current literature and how it is characterised in terms of approaches, benefits and barriers. A systematic literature review (SRL) of the available body of knowledge on these topics was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. The SRL reveals limited but rapidly growing coverage of the cutting-edge phenomenon on the part of scientific studies. In problematising the extant literature, competitive, cultural and strategic approaches are proposed together with the relative enablers fostering the adoption of each approach. Benefits and barriers to the implementation of a DDBM are also discussed across technical, organisational and financial dimensions. The insights derived from a critical review of the DDBM literature point out gaps, which may itself inform future research and theory development in this area, as well as support practitioners’ decision-making on the datatisation of business models.