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SciVal Metric: Academic-Corporate Collaboration
Last updated on November 15, 2024
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Academic-Corporate Collaboration in SciVal indicates the degree of collaboration between academic and corporate affiliations: to what extent are this entity’s publications co-authored across the academic and corporate, or industrial, sectors?
A publication either exhibits academic-corporate collaboration, or it does not. This assignment is made based on the sector assigned to the Institution in SciVal.
The metric looks at a publication level and considers any publication with an Academic - Corporate Collaboration which has:
- more than 1 author
- includes at least 1 affiliation mapped to an Academic Organization
- at least 1 affiliation mapped to a Corporate Organization - these affiliations can be from other co-authors of the paper, it does not need to be from an author of the institution you are looking at.
This metric calculates the Citations per Publication for collaborative and non-collaborative papers. Academic-Corporate Collaboration is a:
- Collaboration metric
- “Power Metric” when the “Total value” option is selected, but not when the “Percentage” option is selected
- Investigate the degree of collaboration between the academic and corporate sectors within a data set
- Benchmark the cross-sector collaboration of entities of different sizes, but in related disciplines, such as large and small research teams, or large and small Centers of Excellence:
- It is advised to select the 'Percentage' option when comparing entities of different sizes, to normalize for this variable.
- Showcase extensive collaboration between academia and industry that may underpin a set of Scholarly Output
- Investigate collaborative activity very early in a new strategy, or for an early-career researcher, since the affiliation data underlying this metric does not require time to accumulate to reliable levels in the same way as citation data does
- Look at publishing activity in a way that is difficult to manipulate
- Benchmarking the extent of Academic-Corporate Collaboration of entities in different disciplines:
- The opportunity or desire to collaborate outside the sector may differ, such as between econometrics and drug discovery, or the philosophy of science and toxicology.
- It is not advisable to use this metric to compare entities in distinct disciplines without accounting for these differences.
- When comparing entities made up of a mixture of disciplines, such as an Institution or Country, it is advised to apply the Subject Area filter to focus on one field that is common between all the entities.
- Entities are small and there may be gaps in their output within the Scopus coverage:
- A single missing publication from a small data set may have a significant negative impact on apparent cross-sector partnerships, whereas the effect of 1 or a few missing publication(s) from a large data set may be acceptable.
- The only way to account for this is to be vigilant, particularly when looking at small data sets such as an early-career researcher, or to limit the use of Academic-Corporate Collaboration to comparing larger data sets in which potential gaps in the database coverage likely have a similar effect on all entities being viewed and do not invalidate the comparison.
- Investigating activity in a discipline with focus outside the interest of industry, such as history:
- It is not advised to use this metric in such a situation.
- Academic-Corporate Collaboration Impactopens in new tab/window, which calculates the Citations per Publication for publications with and without academic-corporate collaboration, and indicates how beneficial this cross-sector collaboration is with respect to citation impact
- The set of all other “Power Metrics” whose value tend to increase as the entity becomes bigger: Scholarly Output, Subject Area Count, Scopus Source Title Count, Citation Count, Cited Publications (“Total value”), Number of Citing Countries, Collaboration (“Total value”), Outputs in Top Citation Percentiles (“Total value”), Publications in Top Journal Percentiles (“Total value”), and h-indices
- The set of all other “time-independent metrics” which provide useful, reliable information immediately upon publication and do not rely on the passing of time for useful data to accumulate: Scholarly Output, Subject Area Count, Scopus Source Title Count, Collaboration, and Publications in Top Journal Percentiles
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