Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 8

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

The possibilities and limits of trade secrets to protect data shared between firms in agricultural and food sectors

Radauer, Alfred, Searle, Nicola, Bader, Martin A.·2023·World Patent Information
DOI 10.1016/j.wpi.2023.102183
Open this paper in CoChat — free account

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.wpi.2023.102183

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Figures

Image 1
CC-BY · From the PDF
Fig. 1 Firm Data-Sharing Decision Tree
Fig. 1 Firm Data-Sharing Decision TreeCC-BY · From the PDF
Fig. 4 Expanded firm data-sharing decision tree.
Fig. 4 Expanded firm data-sharing decision tree.CC-BY · From the PDF

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.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

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

Cites

Show all 1 references

Research works printed but not linked: 40

  1. Klerkx, 2019, A review of social science on digital agriculture, smart farming and agriculture 4.0: new contributions and a future research agenda, NJAS - Wageningen J. Life Sci., 90
  2. Wiseman, 2019, Farmers and their data: an examination of farmers' reluctance to share their data through the lens of the laws impacting smart farming, NJAS - Wageningen J. Life Sci., 90–91
  3. Friedman, 1991, Some economics of trade secret law, J. Econ. Perspect., 5, 61, 10.1257/jep.5.1.61 · DOI
  4. Teece, 1986, Profiting from technological innovation: implications for integration, collaboration, licensing and public policy, Res. Pol., 15, 285, 10.1016/0048-7333(86)90027-2 · DOI · Paper page
  5. Png, 2017, Secrecy and patents: theory and evidence from the uniform trade secrets act, Strat. Sci., 2, 176, 10.1287/stsc.2017.0035 · DOI
  6. Holgersson, 2013, Patent management in entrepreneurial SMEs: a literature review and an empirical study of innovation appropriation, patent propensity, and motives, R&d Manage., 43, 21, 10.1111/j.1467-9310.2012.00700.x · DOI
  7. Bonakdar, 2017, Capturing value from business models: the role of formal and informal protection strategies, Int. J. Technol. Manag., 73, 151, 10.1504/IJTM.2017.083073 · DOI
  8. Cuthbertson, 2022, Digital services and competitive advantage: strengthening the links between RBV, KBV, and innovation, J. Bus. Res., 152, 168, 10.1016/j.jbusres.2022.07.030 · DOI
  9. Broring, 2010, Developing innovation strategies for convergence-Is' open innovation'imperative?, Int. J. Technol. Manag., 49, 272, 10.1504/IJTM.2010.029421 · DOI
  10. Clancy, 2017, Intellectual property rights and the ascent of proprietary innovation in agriculture, Ann. Rev. Res. Econ., 9, 53, 10.1146/annurev-resource-100516-053524 · DOI
  11. Reichman, 1997, Intellectual property rights in data, Va. Law Rev., 50, 49
  12. Koščík, 2017, Database authorship and ownership of sui generis database rights in data-driven research, International Review of Law, Comput. Technol., 31, 43
  13. Sadowski, 2019, When data is capital: datafication, accumulation, and extraction, Big Data Soc., 6, 10.1177/2053951718820549 · DOI · Paper page
  14. Levine, 2018, Why do startups use trade secrets, Notre Dame Law Rev., 94, 751
  15. Arora, 2016, The paradox of openness revisited: collaborative innovation and patenting by UK innovators, Res. Pol., 45, 1352, 10.1016/j.respol.2016.03.019 · DOI
  16. Arundel, 1998, What percentage of innovations are patented? empirical estimates for European firms, Res. Pol., 27, 127, 10.1016/S0048-7333(98)00033-X · DOI
  17. Klein, 2020, Secrecy, the patent puzzle and endogenous growth, Eur. Econ. Rev., 126, 10.1016/j.euroecorev.2020.103445 · DOI
  18. Kwon, 2012, Patent races with secrecy, J. Ind. Econ., 60, 499, 10.1111/j.1467-6451.2012.00482.x · DOI
  19. Dass, 2020, Intellectual property protection and financial markets: patenting versus secrecy, Rev. Finance, 25, 669, 10.1093/rof/rfaa033 · DOI
  20. Gallié, 2012, French firms' strategies for protecting their intellectual property, Res. Pol., 41, 780, 10.1016/j.respol.2011.12.008 · DOI
  21. Chang, 2012, Service regime: an empirical analysis of innovation patterns in service firms, Technol. Forecast. Soc. Change, 79, 1569, 10.1016/j.techfore.2012.05.017 · DOI
  22. Leiponen, 2009, If you cannot block, you better run: small firms, cooperative innovation, and appropriation strategies, Res. Pol., 38, 1478, 10.1016/j.respol.2009.06.003 · DOI
  23. Wang, 2021, Information asymmetry and the inefficiency of informal ip strategies within employment relationships, Technol. Forecast. Soc. Change, 162, 10.1016/j.techfore.2020.120335 · DOI
  24. King, 2007, Disentangling interfirm and intrafirm causal ambiguity: a conceptual model of causal ambiguity and sustainable competitive advantage, Acad. Manag. Rev., 32, 156, 10.5465/amr.2007.23464002 · DOI
  25. Ritala, 2015, Knowledge sharing, knowledge leaking and relative innovation performance: an empirical study, Technovation, 35, 22, 10.1016/j.technovation.2014.07.011 · DOI
  26. James, 2013, How firms capture value from their innovations, J. Manag., 39, 1123
  27. Appleyard, 1996, How does knowledge flow? Interfirm patterns in the semiconductor industry, Strat. Manag. J., 17, 137, 10.1002/smj.4250171112 · DOI
  28. Ferrell, 2016, Legal issues on the farm data frontier, Part I: managing first-degree relationships in farm data transfers, Drake J. Agric. Law, 21, 13
  29. Azevedo, 2018, Non-compete covenants, litigation and garden leaves, J. Bus. Res., 88, 197, 10.1016/j.jbusres.2018.03.020 · DOI
  30. Zaheer, 1998, Does trust matter? Exploring the effects of inter-organizational and inter-personal trust on performance, Organ. Sci., 9, 141, 10.1287/orsc.9.2.141 · DOI · Paper page
  31. Gambetta, 2000, Can we trust trust, Trust: Making and breaking cooperative relations, 13, 213
  32. Ellixson, 2019, Legal and economic implications of farm data: ownership and possible protections, Drake J. Agric. Law, 24, 49
  33. van der Burg, 2021, Trust in farm data sharing: reflections on the EU code of conduct for agricultural data sharing, Ethics Inf. Technol., 23, 185, 10.1007/s10676-020-09543-1 · DOI
  34. Perkmann, 2015, Open data partnerships between firms and universities: the role of boundary organizations, Res. Pol., 44, 1133, 10.1016/j.respol.2014.12.006 · DOI
  35. Richter, 2019, The data sharing economy: on the emergence of new intermediaries, IIC - Int. Rev. Intellect. Property and Competition Law, 50, 4
  36. Krattiger, 2007, vol. 1
  37. Ebneyamini, 2018, Toward developing a framework for conducting case study research, Int. J. Qual. Methods, 17, 10.1177/1609406918817954 · DOI
  38. Miles, 1979, Qualitative data as an attractive nuisance: the problem of analysis, Adm. Sci. Q., 24, 590, 10.2307/2392365 · DOI
  39. Smith, 2018, Creating FAIR and open data ecosystems for agricultural programmes, Gates Open Res., 2, 42
  40. Radauer, 2010, Elements of good practice for providers of publicly funded patent information services for SMEs–Selected and amended results of a benchmarking exercise, World Patent Inf., 32, 237, 10.1016/j.wpi.2009.09.003 · DOI

Cited by

Metadata

Authors
Radauer, A., Searle, N., & Bader, M. A.
ORCID
Radauer, Alfred
Venue
World Patent Information
Publisher
Elsevier BV
Published
2023-06
Volume
73
Pages
102183
ISSN
0172-2190
DOI
10.1016/j.wpi.2023.102183
Cited by
8
References
1
Language
en
Licence

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