The DOI matches its Crossref record.
Managing Open Innovation
Abstract
OVERVIEW:Industrial innovation is becoming more open, requiring changes in how firms manage innovation. External sources of knowledge become more prominent, while external channels to market also offer greater promise. This complicates the evaluation of early-stage technology projects, which often involve significant technical and market uncertainty. In such circumstances, companies need to “play poker” as well as chess. Measurement errors (false positives, false negatives) are likely to arise from judgments about the commercial potential of early-stage projects. Most companies' policies consciously limit “false positives” in assessing a project's commercial potential, but few companies take steps to manage the risk of “false negatives.” New metrics may help a firm focus more upon external sources of innovation to enhance its business model, and enable the firm to salvage value from false negatives that otherwise would be lost.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Teece, D., Peteraf, M., & Leih, S. (2016) · California Management Review · doi:10.1525/cmr.2016.58.4.13 · Cited by 2,317
The role of open innovation in developing an entrepreneurial support ecosystem
Pustovrh, A., Rangus, K., & Drnovšek, M. (2020) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2019.119892 · Cited by 156
Competing in Advanced Manufacturing: The Need for Improved Growth Models and Policies
Tassey, G. (2014) · Journal of Economic Perspectives · doi:10.1257/jep.28.1.27 · Cited by 122
Metadata
- Authors
- Chesbrough, H.
- Venue
- Research-Technology Management
- Publisher
- Informa UK Limited
- Published
- 2004-01
- Volume
- 47
- Issue
- 1
- Pages
- 23-26
- ISSN
- 0895-6308 (ISSN-L)
- 1930-0166
- OpenAlex
- W205729765
- Cited by
- 629
- References
- 0
- FWCI
- 24.98
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.