Unpacking novelty: university vs. industry publications and field-effects of industry publishing
Novelty in academia is important for both scientific and technological breakthroughs. While publishing scientific articles is primarily a university-driven activity, industry also regularly indulges in publishing scientific articles in academia as a part of R&D efforts by firms. As an “outsider” to publishing in academia, industry is driven by its own experiences while pursuing scientific research and can bring novelty to academic knowledge. At the same time, the outsider position of industry scientists can also lead to legitimacy problems and discourage the publication of novel knowledge because academics in a field may not accept the new ideas put forth by industry. Further, the industry is often secretive in revealing its knowledge in scientific publications, which can impede novelty in industry-authored publications. In this paper, our initial research question focuses on determining whether the university or the industry generates a larger number of novel publications, and which of these entities’ publications exhibit a higher level of novelty. Industry involvement in publishing can impact the novelty of university-authored publications. Further, the extent of industry participation in publishing scientific papers varies across different fields of scientific research. Our second research question explores the relationship between the extent of industry participation in publishing within a specific field and the degree of novelty in the scientific publications emerging from that field. Using 928,787 publications in STEM fields from MAG for scientific articles published in the year 2017, we find that industry-authored publications are less novel than university-authored publications. We also find that the novelty of publications is less in fields with high industry involvement in publishing than in those with low industry involvement in publishing. Our findings remain consistent across various econometric methods, measures, and subsets of data.
Unpacking novelty: university vs. industry publications and field-effects of industry publishing
Novelty in academia is important for both scientific and technological breakthroughs. While publishing scientific articles is primarily a university-driven activity, industry also regularly indulges in publishing scientific articles in academia as a part of R&D efforts by firms. As an “outsider” to publishing in academia, industry is driven by its own experiences while pursuing scientific research and can bring novelty to academic knowledge. At the same time, the outsider position of industry scientists can also lead to legitimacy problems and discourage the publication of novel knowledge because academics in a field may not accept the new ideas put forth by industry. Further, the industry is often secretive in revealing its knowledge in scientific publications, which can impede novelty in industry-authored publications. In this paper, our initial research question focuses on determining whether the university or the industry generates a larger number of novel publications, and which of these entities’ publications exhibit a higher level of novelty. Industry involvement in publishing can impact the novelty of university-authored publications. Further, the extent of industry participation in publishing scientific papers varies across different fields of scientific research. Our second research question explores the relationship between the extent of industry participation in publishing within a specific field and the degree of novelty in the scientific publications emerging from that field. Using 928,787 publications in STEM fields from MAG for scientific articles published in the year 2017, we find that industry-authored publications are less novel than university-authored publications. We also find that the novelty of publications is less in fields with high industry involvement in publishing than in those with low industry involvement in publishing. Our findings remain consistent across various econometric methods, measures, and subsets of data.