Process innovations and firm productivity growth

Barrachina, María Engracia Rochina; Máñez, Juan A.; Sanchís-Llopis, Juan A.

doi:10.1007/s11187-008-9110-5

Cited by 56 publications

(32 citation statements)

References 35 publications

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“…However, a general limitation of most of these studies is that their analyses are restricted to manufacturing firms based on the Encuesta sobre Estrategias Empresariales dataset (ESEE) 3 . Among the most recent papers employing this database we find Vivero (2002), Huergo and Moreno (2004), Huergo and Jaumandreu (2004), Rodríguez-Fernández (2002, 2008), Rodríguez-Fernández and Maté-García (2006), Rochina-Barrachina et al (2010) and Casiman et al (2010), to name but a few. By contrast, only a few papers have carried out a joint analysis of both manufacturing and service sectors, most notably Segarra-Blasco (2010) and Segarra-Blasco and Teruel (2011) who analyse the case of Catalonia using data from the fourth Community Innovation Survey (CIS4).…”

Section: Previous Literaturementioning

confidence: 89%

Innovation spillovers and firm performance: micro evidence from Spain (2004–2009)

2015

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This article analyses the impact that R&D expenditures and intra-and inter-industry externalities have on the performance of Spanish firms. Despite the extensive literature studying the relationship between innovation and productivity, there are far fewer studies in this particular area examining the importance of sectoral externalities, especially focused on Spain. One novelty of this study, conducted for the industrial and service sectors, is that we also consider the technology level of the sector in which the firm operates and firm size. The database used is the Technological Innovation Panel (PITEC). It comprises 9,985 firms over the period 2004-2009 and has been used infrequently for studies of this type. The Olley and Pakes (1996) estimator is adopted in order to account for both simultaneity and selection biases providing consistent estimates. The results suggest that, unlike previous studies, R&D expenditures do not have a direct impact on firm performance. By contrast, spillovers do. In particular, intra-industry externalities present a positive and significant effect in low-tech and large firms. Inter-industry externalities, however, present an ambiguous effect and there appears to be no specific pattern of behaviour associated with technology level or firm size.

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Section: Previous Literaturementioning

confidence: 89%

Innovation spillovers and firm performance: micro evidence from Spain (2004–2009)

2015

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“…Moreover, they can form a link back to their previous employer to channel knowledge to their new firm, e.g. by keeping in contact with former colleagues (Reinau 2011), or when both employers cooperate (Somaya et al 2008). For this reason, employees are sometimes specifically forbidden to gain employment within the same sector after leaving a firm (Bishara and Westermann-Behaylo 2012).…”

Section: The Literaturementioning

confidence: 99%

“…This also goes for poaching behaviour, where firms know of specific knowledge employees supposedly carry (e.g. Reinau 2011). A conscious strategy on the part of a firm to use new human capital for innovations is simply one way to arrive at the possible benefit of labour mobility, indistinguishable from the effect of employees hired for other reasons.…”

Section: Endogeneitymentioning

confidence: 99%

Innovation through new blood

Smit

2017

Ann Reg Sci

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We model the influence of employee mobility on the transmission of knowledge between firms, assuming human capital to be an important influence on service innovation and firm productivity. To this end, we follow individual workers as they move from firm to firm, controlling for knowledge characteristics ('absorptive capacity') of the firm and for regional effects (agglomeration and urbanization). We measure the amount and variety of such flows, and we find statistically significant results; yet the impact of new employees on innovation and productivity seems to come more from the diversity of source firms than from the number of new employees, and effects differ markedly between small and larger firms. JEL Classification

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“…Rochina-Barrachina et al (2010), in contrast, use non-parametric methods. In their article, firms which undertake process innovation are compared to those which do not by comparing their cumulative distribution functions of productivity levels.…”

Section: Literature Reviewmentioning

confidence: 99%

“…They estimated models for both the manufacturing and service sector, with the following results: product innovation is significant in the service sector, but process innovation does not have any significant relationship with service sector productivity. Notes: "+ " indicates the relationship is positive "-" indicates the relationship is negative NS indicates the relationship was analyzed, but is not significant Source: Suriñach et al 2011;Rochina-Barrachina et al 2010;Evangelista and Vezzani 2010;Griffith et al 2006;Mairesse and Robin 2009;Janz et al 2004;Polder et al 2010;Masso and Vahter 2012. A related paper about the relationship between productivity and innovation in the Estonian service sector has been written by Masso and Vahter (2012). They also consider four types of innovation and divide the service sector into sub-sectors.…”

Section: Literature Reviewmentioning

confidence: 99%