دانلود مقاله ISI انگلیسی شماره 26266
عنوان فارسی مقاله

آیا شرکت ها تجارت کردن بین کمیت و کیفیت اختراعات خود روبرو هستند؟

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
26266 2013 8 صفحه PDF سفارش دهید محاسبه نشده
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عنوان انگلیسی
Do firms face a trade-off between the quantity and the quality of their inventions?
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Research Policy, Volume 42, Issue 5, June 2013, Pages 1072–1079

کلمات کلیدی
عملکرد نوآوری - کیفیت اختراع - مقدار اختراع - انفجار ثبت اختراع - گرایش به حق ثبت اختراع - بهره وری تحقیقات
پیش نمایش مقاله
پیش نمایش مقاله آیا شرکت ها تجارت کردن بین کمیت و کیفیت اختراعات خود روبرو هستند؟

چکیده انگلیسی

This paper presents evidence that firms face a trade-off between the quantity and the quality of their research output. The econometric analysis uses survey data on patent applicants at the European Patent Office and addresses the identification problem caused by differences in firms’ propensity to patent. The existence of a trade-off emphasizes the need to take the quality of research output into account when assessing research productivity. It also raises questions about the optimal quantity–quality mix that firms should target.

مقدمه انگلیسی

An important topic in the economic and management of innovation literature is the study of firms’ research productivity (e.g. Henderson and Cockburn, 1996, Penner-Hahn and Shaver, 2005 and Girotra et al., 2010). Research productivity is the quality-constant measure of the efficiency at which inputs to the innovation process are converted into output. The quantity of output is the number of inventions created and it is often proxied with the number of patents, as imperfect a proxy as it is (Griliches, 1990). The quality of output is more difficult to define and, a fortiori, to measure. Following Lanjouw and Schankerman (2004), the quality of output encompasses both the technological and economic value of inventions. The existing research has mostly focused on the determinants of the quantity of inventions created, with quality considerations usually relegated to the background. Yet, the quality dimension is just as critical to the understanding of research productivity as the quantity dimension. Little is known about the relationship between the quantity of inventions created and their quality, in particular with respect to a potential trade-off between these two dimensions. For any given level of research inputs, it seems obvious that an increase in the number of inventions created would be associated with inventions of lower average value. This is not necessarily the case, however. For one thing, some otherwise comparable firms may be more productive than others due to a better use of IT resources, more appropriate contracting and management practices, or more skilled researchers. For another, it is difficult to target a quality level due to the uncertain nature of the innovation process. A firm investing all its resources in a risky but promising project may end up with a limited output of low value. And further, dynamics of the invention process itself may affect the quantity/quality trade-off. For instance, Fleming (2001) shows that inventors’ experimentation with new components and combinations leads to less success on average, but it also increases the variability of success that can lead to breakthrough inventions. To the best of our knowledge, the existence of a trade-off has yet to be shown. Only a handful of studies have looked at the hypothesis of a trade-off and none has come up with conclusive evidence. A first group of studies has tested the hypothesis using firm-level patent data. Lanjouw and Schankerman (2004) regress the number of patents per dollar invested in R&D on an index that captures the mean quality of patent applications for a panel of U.S. firms. Within-firm regressions provide no support for the hypothesis, while between-firm regressions provide only weak support. Sørensen and Stuart (2000) provide an indirect test of the hypothesis. Applying organizational theory, they argue that firm age should be positively associated with the rate of innovation, but negatively associated with how influential the innovations are. They find strong evidence that firm age increases the rate of (patented) inventions, but only weak evidence on the impact of firm age on patent quality. A second group of studies uses patent data at the inventor level. Mariani and Romanelli (2007) use data from the PatVal-EU survey of inventors to test whether the quantity of patents produced affects their average value as measured by patent indicators. They find a positive effect of the quantity of patents on the average quality using forward citations but no effect using a composite value indicator. Gambardella et al. (2011) propose a related test of the hypothesis. The authors also use data from the PatVal-EU survey of inventors but rely on a self-assessed measure of value. They find a negative relationship between the number of inventions and the average value of the patents in the portfolio, but the effect is not statistically significant.1 A limitation of existing studies is that they rely on patent data but do not address the confounding effect of the propensity to patent. Were the decision to patent an invention independent of its value, the trade-off would easily be estimated with patent data. One would simply regress the number of patents against average patent value. A negative coefficient would signal a trade-off. However, since the marginal value of inventions patented is likely to decrease with the propensity to patent (defined as the proportion of inventions patented), a negative correlation between patent quantity and patent quality would not be evidence of a trade-off. The objective of this paper is to test whether innovative firms face a trade-off between the quantity and the quality of their inventions (holding research inputs constant). An attempt to address the identification problem caused by heterogeneous patent propensities is a distinguishing feature of this study. We put forward an empirical model that links the average quality of inventions with the average quality of patent applications and adopt an instrumental variable approach to account for differences in the propensity to patent. The econometric analysis uses cross-sectional survey data on patent applicants at the European Patent Office (EPO) and finds evidence of a trade-off between invention quantity and quality, as measured by the patent family size. The existence of a trade-off has profound implications for the economics of science and the management of innovation. It stresses the need to take the quality of inventions into account to properly assess – and to study the determinants of – the productivity of research spending. It also raises questions regarding the optimal quantity–quality mix that firms should target. The paper is organized as follows. Section 2 introduces the empirical framework and the data is presented in Section 3. Section 4 presents the econometric results and the final section discusses the implications of the findings.

نتیجه گیری انگلیسی

This paper tests whether firms face a trade-off between the quantity and the quality of their inventions. The empirical test is not trivial because inventions are usually observed at the point of patent application. Since the marginal value of inventions patented is likely to decrease with the propensity to patent, a negative correlation between patent quantity and patent quality would not necessarily be evidence of a trade-off. The empirical analysis addresses the identification problem caused by heterogeneous patent propensities across firms by using an instrumental variable approach. Using survey data on applicants at the EPO, we find that firms with a higher rate of invention also have inventions of lower average value as measured by the patent family size. Important implications for the economics of science and the management of innovation follow from the present findings. First, the existence of a trade-off suggests that a higher number of inventions, and a fortiori patent applications, per unit of research input is not necessarily associated with a higher research productivity. Researchers should strive to take the quality of inventions into account to properly assess – and to study the determinants of – the productivity of research spending. However, this task is particularly difficult because the propensity to patent truncates the innovative output that can be observed. The propensity to patent is usually not observed by researchers and, even if it is, appropriate instrument to account for it may not be available. Second, the existence of a trade-off implies that firms should be very cautious in setting their quantity target, as this may affect the average quality of their inventions. This decision is not only important in a static context but may also have far-reaching consequences. We know from previous research that the quality of available knowledge determines the potential for future inventions because the invention process is cumulative and because existing knowledge enhances the absorptive capacity of the firm (Cohen and Levinthal, 1990). Hence, firms that trade invention quality for immediate research output may undermine their knowledge base and consequently compromise their long-term innovation capabilities. If considered in a broader context, the results provide an insight into the patent ‘explosion’. It is well documented that patent offices worldwide are facing a rise in patenting rates, together with a drop in patent quality (e.g. van Pottelsberghe and van Zeebroeck, 2008). Two broad explanations can be proposed to account for the increase in patent filings. Because only a fraction of inventions are patented, a rise in patent rates could reflect either an increase in the propensity to patent–patent/invention ratio – or a real increase in invention rates – invention/R&D ratio. Although it is generally believed that the current boom in patent applications is the result of an increase in firms’ propensity to use the patent system (Hall, 2005, Encaoua et al., 2006 and de Rassenfosse and van Pottelsberghe, 2012), the question of whether co-occurring changes in the organization of science may explain these stylized facts has received little attention (to the notable exception of Kortum and Lerner, 1999). In particular, the culture in corporate research labs is reported to be more driven by business imperatives than before, resulting in an increase in applied R&D projects with immediate returns, at the expense of long-term and riskier endeavors (see e.g. Rosenbloom and Spencer, 1996, Ernst, 1998, Coombs and Georghiou, 2002 and Varma, 2000). The results presented in this paper are consistent with the second explanation of the patent explosion. It is shown that an increase in the rate of inventions spurred, for instance, by a shift towards more applied R&D projects, can lead to a decrease in the average quality of inventions. Clearly, some firms operating in today's context, of a market-oriented and results-driven approach to technology generation, may have traded quality for quantity. Although this observation is not sufficient to infer that the boom in patent applications is driven by a genuine increase in the quantity of research output; it does suggest that it may be an additional explanation, together with the observed increase in the propensity to patent. Interestingly, the changes in the nature of R&D may also have increased the incentives to patent, since applied projects are presumably easier to imitate. To conclude, we note that the empirical analysis is silent on the determinants of the quantity–quality decision and the factors that mitigate the trade-off. Although this has the advantage of not constraining the econometric analysis, it also raises more questions than it answers. Such questions require an analysis of their own and it is hoped that future research will contribute to improving our understanding in this area. For instance, it would be interesting to study the extent to which the optimal quantity–quality mix depends on firms’ and industry (e.g. complex vs. discrete) characteristics. Similarly, the impact of the quantity–quality choice on the returns to innovation and the innovation potential is unclear, and represent opportunities for further research.

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