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| Effect of the Diversity of Scientific Teams on Disruptive Innovation in Academia: A Case Study in the Field of Artificial Intelligence |
| Tang Xuli1, Li Xin2 |
1.School of Information Management, Central China Normal University, Wuhan 430079
2.School of Medicine and Health Management, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430030 |
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Abstract Although disruptive innovation in academia has become a new engine for technological progress and economic development, few researchers have studied the factors that affect disruptive innovation in academia. In this study, we take scientific teams as the research object and systematically analyze the effect of diversity in scientific teams on disruptive innovations in academia from three perspectives: social category, information, and behavior willingness. First, we collected collaboration papers on artificial intelligence (AI) published between 1950 and 2019 from the Microsoft Academic Graph. We extracted and represented author characteristics using topic model and text mining to compute the diversity indicators of scientific teams. Additionally, we measured disruptive innovation at the article level using the disruptive index. Then, the correlation analysis and ordinary least squares (OLS) regression analysis were used to eliminate the diversity indicators unrelated to disruptive innovation in academia. Finally, coarsened exact matching was used to explore the causal relationships between the diversity of scientific teams and disruptive innovation in academia. The results show that in the field of AI, the topic diversity and nation diversity of scientific teams have a significant causal relationship with disruptive innovation in academia. The degree of disruptive innovation in academia will decline 8.776%-19.000% when the topic diversity of scientific teams increases; it will also decline 5.493%-7.693% when the nation diversity increases. In addition, the results also show that there is no causal relationship between the diversity of behavior willingness of a scientific team and the degree of disruptive innovation in academia in the field of AI.
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Received: 16 November 2021
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