شناخت نوآوری: تجزیه و تحلیل پایداری برای شرکت های تولیدی اسپانیایی
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|2381||2013||13 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Research Policy, Volume 42, Issue 2, March 2013, Pages 340–352
This study focuses on the persistence of innovation in a panel of Spanish manufacturing firms for the period 1990–2008. In particular, we analyse whether persistence in firms’ innovation activities over time is the result of previous experience, the dynamic capabilities of the firm or industry-market related characteristics. We find that R&D (input) and innovation (output) are highly persistent at the firm level. After controlling for unobserved heterogeneity and initial conditions and by using a dynamic random effects probit, we conclude that there are similar determinants of persistence in R&D and innovative activities. Among external/environmental factors, market dynamism affects R&D and innovation. Regarding firm specific characteristics, size and outsourcing also have a positive impact on both processes. Past innovative behaviour is clearly more decisive in explaining the current state of R&D and innovation activities than external factors or firm-level heterogeneity.
In recent years, analyses of the relationship between innovation and industrial dynamics have generated a wide array of theoretical and empirical contributions. Progress in new econometric packages and the availability of large panel data sets at the firm level have allowed researchers to identify some stylised facts and empirical regularities related to the high within-industry heterogeneity in innovation (Malerba, 2007). This heterogeneity is due, among other things, to differences in the ability to innovate. As Dosi (1997) notes, heterogeneity in innovation across firms indicates the presence of particular capabilities and implies that even when firms perform the same activities, they can do so in different ways. In this sense, substantial research efforts have been devoted to examining persistence in innovation (Cefis, 2003, Malerba et al., 1997, Peters, 2009 and Raymond et al., 2010), showing that ‘innovation is not a purely random phenomenon driven by small shocks, but it implies systematic heterogeneity across firms…’ (Cefis and Orsenigo, 2001, p. 1156). Additionally, several studies empirically address the propensity of firms to innovate. Innovative activity has been proxied by input (R&D effort) and output measures (patents or the number of innovations). This paper provides the first dynamic approach to innovation persistence, focusing on both perspectives.1 We estimate that there will be a strong (and positive) relationship between input (R&D) and output (final innovation), but R&D spending does not necessarily ensure that innovation occurs. Engaging and persisting in R&D primarily depends on firm-level decisions, but the results (final innovations) are affected by other external factors such as market dynamism and the competitive environment. This paper examines the dynamics of innovation and R&D decisions in Spanish manufacturing using firm-level data for the period 1990–2008. Its first aim is to analyse persistence in R&D and innovation to clarify the role played by past behaviour in the innovation process. Second, we attempt to determine whether there are differences in the effects of the explanatory variables on the probabilities of being an innovator and engaging in R&D activities. Thus, the goal is to discover the factors that are effectively driving the observed differences in these probabilities. More particularly, we attempt to answer two related sets of questions. First, are R&D and innovation persistent at the firm level? Do significant differences exist between the persistence of R&D and the persistence of innovation? Second, what is the relationship between R&D and innovation? Are the factors that influence these decisions similar? What is more relevant in the innovation process, state dependence or firms’ unobserved heterogeneity? This paper contributes to the literature in several ways. First, we study persistence in innovation over time using R&D (input) and innovation (output) panel data on Spanish manufacturing firms. To the best of our knowledge, there are no other studies that directly consider both types of measures to study persistence in innovation. To do so, we use a dynamic random effects probit model proposed by Wooldridge (2005) that accounts for the initial conditions of the dependent variables. We also estimate Transition Probability Matrices and Survival Functions in innovation and R&D to detect whether persistent innovators coexist with persistent R&D performers. Finally, we broaden the current literature by including new variables in specifications based on the evolutionary theory of persistence in innovation (Le Bas and Latham, 2005). The paper is organised as follows. First, we review the relevant literature on the dynamics and persistence of innovation and introduce a conceptual framework based on the evolutionary approach for analysing the relationship between R&D and innovation. Second, we describe the data and estimate transition probabilities to investigate R&D and innovation persistence. Third, to analyse the determinants of and persistence in R&D and final innovations, we estimate a random-effects dynamic probit and an alternative specification based on the Wooldridge correction. The main results of the model are presented in Section 4. Finally, we discuss the results of the research and draw some conclusions.
نتیجه گیری انگلیسی
This study examines firm innovative persistence, accounting for both the innovation inputs (R&D) and outputs (process and product innovations) of a representative sample of Spanish manufacturing companies between 1990 and 2008. The availability of longitudinal, firm-level panel data allows us to consider the dynamic features of R&D decisions and innovation and focus on the roles of persistence and individual unobserved heterogeneity of firms. In estimating the dependence of past innovation performance, we introduce lagged dependent variables as explanatory terms and use a new econometric methodology to control for the initial conditions and unobserved heterogeneity: a random effects dynamic probit model based on Wooldridge's proposal (2005). We find that innovation input and output are highly persistent at the firm level. Persistence or true state dependence occurs when a firm that has invested in R&D or innovates in the current year engages in R&D or innovates again in the next period. Past experience, either in innovation or in R&D activities, is an incentive to remain an R&D performer or an innovator. Nevertheless, persistence is higher in R&D activities than in innovations. Approximately 90% of firms with R&D activities in t−1 have R&D in t. The corresponding percentage is approximately 70% for innovation. In fact, past innovative behaviour is clearly more decisive in explaining the current state of R&D and innovation activities than external factors or differences in firm-level characteristics. These results suggest that the persistence of innovation could be an important source of competitive advantage for most innovative firms. Additionally, non-innovators and minor innovators face barriers to engaging in the innovation process with respect to major and persistent innovators. In line with the initial hypothesis, the drivers of the innovation process play a similar role in both R&D and innovation. R&D and innovation are related and they follow a feedback process. As we expected, output (innovation) is primarily explained by input (R&D), and current R&D is conditioned by the innovation experience of the firm. In broad terms, there are more similarities than differences in the impacts of environmental factors on R&D and innovation. Regarding the drivers of innovation, market dynamism is the only external factor decisive for engaging in R&D and obtaining innovations. Market changes only explain innovation. Similarly, regarding firm-specific characteristics, only size and outsourcing have positive impacts in both cases, while being an exporter is only decisive in explaining the R&D decision. Including initial conditions is important, but the coefficients of the random effects probit model are not significantly different from those in the Wooldridge correction. If we focus on the averaged-time effects, being a persistent innovator (measured by an averaged-time innovation variable) is a significant factor that contributes to increasing the probability of engaging in R&D. Furthermore, these results suggest that the innovation history of a firm is crucial for understanding R&D persistence. For the rest of the explanatory variables, the signs of the coefficients associated with each of the time-averaged variables are, in broad terms, the same as the signs of the coefficients associated with the corresponding year-specific variables. The results are of considerable interest for public policy targeting R&D and innovation. The empirical evidence suggests a plausible argument for permanent R&D incentives to strengthen the impact of the policy on persistence in innovative activities (Guellec and Van Pottelsberghe de la Potterie, 2003). Government agencies or other institutions could provide incentives to engage in R&D, but persistence in the innovation process requires stability in R&D over time to produce persistent and stable innovators. This policy measure would promote competition and improve performance and would help non-R&D firms or occasional performers with long-term schemes in particular. It would also contribute to the entry of new innovators and greater stability in innovation for incumbent firms in the industry. As mentioned above, our analysis shows high persistence in innovative activities. This path could be explained by the existence of sunk costs, learning effects or dynamic economies of scale. Furthermore, we have increased the understanding of the determinants of persistence. These results are supported by the theory of ‘dynamic capabilities’, in which innovative performance is generated by systematic and continuous processes of accumulation of resources and competencies over time (Teece and Pisano, 1994 and Teece et al., 1997); the ‘resource and competence’ theory of the firm (Freiling, 2004), where internal resources are essential for understanding the innovation process; and, the ‘industrial organisation’ framework because the evidence demonstrates the influence of market structure and industry-specific factors in the innovation process (Geroski et al., 1997). Although further research is needed to investigate firm heterogeneity and the ‘creative accumulation’ process of innovation (Schumpeter Mark II hypothesis), our study is an attempt to analyse persistence and understand innovation in a globalised environment based on the ‘evolutionary theory of the firm’ (Le Bas and Latham, 2005).