Platforms · Qualitative multiple-case study
Value creation in data-centric B2B platforms: A model based on multiple case studies
Industrial Marketing Management · 2024
Summary
Clients, providers, and enablers relate through data acquisition and manipulation. Governance mechanisms and boundary resources (including APIs, SDKs, connectivity devices, interfaces, rulesets and data-sharing agreements) support transactions, complementary applications, data-driven matching/network effects, new data-enabled business models, and faster/better decisions. The model distinguishes transactional and innovation behaviors and mechanisms of value creation. For a founder, use this as a question to test in your own context, not a universal playbook.
For your marketing
Possible founder application
Treat this as evidence for the specific b2b growth and sales question studied. Compare the setting and sample to your company before changing a growth decision; use a local experiment where the paper does not match your context.
Reported result
What the study found
Clients, providers, and enablers relate through data acquisition and manipulation. Governance mechanisms and boundary resources (including APIs, SDKs, connectivity devices, interfaces, rulesets and data-sharing agreements) support transactions, complementary applications, data-driven matching/network effects, new data-enabled business models, and faster/better decisions. The model distinguishes transactional and innovation behaviors and mechanisms of value creation.
Research question
What the authors investigated
Who manages data in data-centric B2B platforms, what data-acquisition/manipulation activities do they perform, and how are those relationships governed to create value?
Design
Multiple-case analysis with coding and cross-case comparison of three data-centric B2B platforms; the paper develops a model from the cases.
Sample and setting
Three industrial B2B platforms: Siemens MindSphere, Airbus Skywise, and Eni Open-es. The source specifies three cases but does not report a respondent sample size.
Scope and transfer
Limitations to keep in view
Only three incumbent platforms in industrial productive environments were studied; generalizability to other sectors, SMEs/start-ups, and other platform configurations is uncertain. The study is qualitative, does not test the model quantitatively, focuses on value creation rather than value capture, and excludes platforms where data are only transacted.
Research sources
Publisher full text provides the exact bibliographic record, abstract, explicit research questions, case-method section, findings, and a named limitations/future-research section. Evidence strength: strong (full publisher text). Correction notices were not separately verified in this collection; consult the current publisher record before applying the findings.