Churning of R&D Personnel and Innovation

Abstract

Die Dis cus si on Pape rs die nen einer mög lichst schnel len Ver brei tung von neue ren For schungs arbei ten des ZEW. Die Bei trä ge lie gen in allei ni ger Ver ant wor tung der Auto ren und stel len nicht not wen di ger wei se die Mei nung des ZEW dar.Dis cus si on Papers are inten ded to make results of ZEW research prompt ly avai la ble to other eco no mists in order to encou ra ge dis cus si on and sug gesti ons for revi si ons. The aut hors are sole ly respon si ble for the con tents which do not neces sa ri ly repre sent the opi ni on of the ZEW.Download this ZEW Discussion Paper from our ftp server:ftp://ftp.zew.de/pub/zew-docs/dp/dp10032.pdf Non-technical SummaryThis paper investigates the effect of mobility among a firm's R&D personnel on its innovation performance.Since knowledge created within an R&D department of a firm is largely embodied in the person of the individual researcher, firms might gain access to external knowledge via hiring new staff. Consequently, innovation should be enhanced. However, firms may suffer from a simultaneous outflow of R&D workers.Our empirical analysis falls back on theories developed by Jovanovic (1979) and Cooper (2001). According to these theories, labor mobility increases the employer-employee matching quality within the R&D department (Jovanovic, 1979). Moreover, as long as the R&D knowledge of a leaving worker can be still used by the worker's former employer, overall labor mobility results in net inflows of R&D knowledge and thus should stimulate innovation (Cooper, 2001).To disentangle the effects of net gains or losses in R&D personnel and replacements within the R&D department is the major aim of this study. We employ, besides net growth in R&D personnel, churning as a measure for R&D worker mobility. Churning depicts the number of workers which are replaced by new ones, i.e. it is an employment-neutral measure of labor turnover. Furthermore, we distinguish between different types of innovations, namely between process and product innovations as well as between market and product-range novelties.Using two sets of bivariate probit regressions, we estimate various knowledge production functions. Labor mobility is found to enhance innovation performance up to a certain threshold. Interestingly, this threshold differs between the types of innovation. The optimal amount of churning among R&D works is lower for process innovations than for product innovations. This result is intuitive since process innovation will require much more firm-specific knowledge and less external knowledge. Our regressions further indicate that a positive effect of labor mobility on innovation performance depends crucially on the appropriability regime. If R&D knowledge is characterized by rivalry in its application, i.e. it is non-duplicative, the threshold up to which a positive effect of labor mobility can be observed is considerably lower. Das Wichtigste in Kürze

The Productivity Effects of Worker Replacement in Young Firms

“…While some studies report a negative linear relationship between labor turnover and productivity (Baron et al, 2001;Yanadori and Kato, 2007;Shaw et al, 2005;Huselid, 1995), other studies report evidence of an inverted u-shape (Glebbeek and Bax, 2004;Müller and Peters, 2010), attenuated negative shapes (Shaw et al 2005, or no significant direct relationship at all Siebert and Zubanov, 2009;Arthur, 1994;Guthrie, 2001;McElroy et al, 2001).…”

“…Accordingly, I divide the churning rate by two to get a measure for a firm's proportion of replaced employees that is easy to interpret at the firm level. A comparable measure has been used by Albaek and Sorensen (1998), as well as by Müller and Peters (2010).…”

Innovation Systems in Small Catching-Up Economies

“…Thus, while previous studies looked at the links with knowledge spillovers through mobility and productivity, we are able to analyze the direct link to innovation activities. Thus, our study seems to be one of the fi rst to match CIS data with external data on labor mobility at the fi rm level (for others, see e.g., Müller and Peters 2010 ) . The worker fl ow indicators calculated are included as independent variables in the knowledge production function (innovation output equation) and production function together with other inputs (various knowledge sourcing variables, innovation expenditures, etc.).…”

“…However, both the productivity and profi tability of the hiring fi rm increased when workers working previously in R&D jobs were hired into non-R&D activities. Müller and Peters ( 2010 ) , as opposed to several other studies, analyze not the impact of new employees, but that of labor churning, that is, the percentage of workers who are replaced by new ones. By estimating empirically the knowledge production function for product and process innovations, a nonlinear relationship between churning and innovation was found.…”

“…Labor mobility is also needed to improve the quality of the match between the employee and the fi rm, as the quality of matching could be evaluated only after the job match has been formed (Müller and Peters 2010 The Impact of Interfi rm Labor Mobility on Innovation: Evidence from Job Search Portal Data Jaan Masso , Raul Eamets , Pille Mõtsmees , and Kaia Philips worker (employee) mobility is that the mobility of workers is one of the most important sources of knowledge fl ows or knowledge spillovers between fi rms (Arrow 1962 ;). While, in principle, knowledge could also be diffused through other means (patents, licenses, product competition, and product announcements), employee mobility is necessary for the large part of knowledge that is tacit (c.f.…”