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Work Force Composition and Innovation: How Diversity in Employees’ Ethnical and Disciplinary Backgrounds Facilitates Knowledge Re-combination

Ali Mohammadi (), Anders Broström and Chiara Franzoni ()
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Chiara Franzoni: Politecnico di Milano, Postal: Department of Management, , Economics and Industrial Engineering, , Via Raffaele Lambruschini 4/b, , Milan Italy 20156

No 413, Working Paper Series in Economics and Institutions of Innovation from Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies

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.

Keywords: Ethnic diversity; Education diversity; External search; Radical innovation (search for similar items in EconPapers)
JEL-codes: J15 J24 J61 O32 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2015-06-29
New Economics Papers: this item is included in nep-cse, nep-dem, nep-eur, nep-hrm, nep-ino, nep-lab, nep-sbm and nep-ure
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