(), Anders Broström
() and Chiara Franzoni
Ali Mohammadi: CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology, Postal: CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology, SE-100 44 Stockholm, Sweden
Anders Broström: CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology, Postal: CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology, SE-100 44 Stockholm, Sweden
Chiara Franzoni: Politecnico di Milano, Postal: Department of Management, , Economics and Industrial Engineering, , Via Raffaele Lambruschini 4/b, , Milan Italy 20156
Abstract: In this paper, we study how workforce composition is related to firm’s radical innovation. Previous studies have argued that teams composed by individuals with diverse background are able to perform more information processing and make a deeper use of the information, which is important to accomplish complex tasks. We suggest that this argument can be extended to the level of the aggregate workforce of high technology firms. Our theoretical interest is focused on the extent to which insights from the literatures on science and invention can be applied to firms’ abilities to achieve radical innovation. In particular, we argue that having a set of employees with greater ethnical and higher education diversity is associated with superior radical innovation performance. Using a sample of 3,888 Swedish firms, we find that greater workforce ethnic diversity is positively correlated to the share of a firm’s turnover generated by radical innovation, while it is neutral to incremental innovation. Greater diversity in terms of higher educational disciplinary background of the workforce is positively correlated to the share of turnover generated by both radical and incremental innovation. Contrary to our hypothesis, we also find that having more external collaborations reduces the importance of a workforce with a diverse disciplinary background, while the importance of ethnic diversity is hold unchanged. Our findings hold after using alternatives measures of dependent and independent variables, alternative sample sizes, and alternative estimation techniques including panel data, and structural equation modeling for simultaneous estimation of diversity, R&D intensity and external search.
36 pages, June 29, 2015
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