Collaboration exploitation and exploration: does a proactive search strategy matter?
Scientometrics, ISSN: 1588-2861, Vol: 126, Issue: 10, Page: 8295-8329
2021
- 3Citations
- 25Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Although one school of thought in the university-industry interactive literature is that universities learn from prior collaboration, we posit that any potential knowledge learning effects depend on the type of collaboration. Our empirical findings confirm that the use of collaboration exploitation, exploration and balancing strategy of ambidexterity all improve a university’s innovation. We also posit that proactive searching allows universities to leverage their collaboration exploitation and exploration. In contrast, when universities combine ambidexterity with a proactive search strategy, the negative consequences for university innovation become more pronounced. To test this integrative model of U-I collaboration, we leverage a unique and detailed longitudinal dataset on the 110 top U.S. research universities and the top 200 R&D performing firms to account for a large share of research papers published in the U.S. in the last 19 years. Poisson and negative binomial regression models are used to test the hypotheses in panel data of 2090 university-year cases. We find support for our theoretical model.
Bibliographic Details
Springer Science and Business Media LLC
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