B2B growth and sales · Qualitative multiple-case study
Value creation in data-centric B2B platforms: A model based on multiple case studies
Ilaria Mancuso, Antonio Messeni Petruzzelli, Umberto Panniello (2024). Industrial Marketing Management.
Plain-English take
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.
How much weight to give this
3/5 Exploratory evidence; interpret cautiously
The 1–5 evidence-check score is a practical reading aid, not a formal peer review or a probability that a conclusion is true. It combines design strength (2 points), sample reporting (1), comparison/control clarity (1), and how much of the paper could be checked (1). Access affects how confidently this directory can assess a study, not the study's underlying quality. Blinding is reported separately because it is not relevant to every design.
Synthesis or analytical design addresses the question, but conclusions depend on included literature or model assumptions.
The accessible source does not report a usable sample size.
The comparison structure is limited or depends on the paper's model/context.
Firecrawl retrieved a full paper or full-text publisher page for this annotation.
Double-blind? Blinding was not established from the captured source; it may not apply to this study design.
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.
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.
This is a paraphrase of the source. Check the original paper for definitions, estimates, statistical uncertainty and analysis details.
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.
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.
Evidence access
Full text retrieved from publisher or linked open repository
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.
If only an abstract or metadata was available, the profile is limited to claims supported there. A paper's paywall does not change its evidentiary status, but it limits what we can substantiate from accessible text.