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on Innovation |
| By: | Annette Becker (Technical University of Munich, TUM School of Management, Dept. of Economics & Policy); Hanna Hottenrott (Technical University of Munich, TUM School of Management, Dept. of Economics & Policy; K.U.Leuven, Dept. of Managerial Economics, Strategy and Innovation; Centre for European Economic Research (ZEW)); Anwesha Mukherjee (Technical University of Munich, TUM School of Management, Dept. of Economics & Policy) |
| Abstract: | Corporate research and development constitutes one of the main sources of innovation. Recent research, however, discusses a decline in corporate research and its implications for technological progress. The contribution of this study is to model research & development (R&D) decisions in an R&D investment model that allows the analysis of firms’ engagement in research (R) as compared to development (D) activities. The model predicts higher investments in both activities for larger firms, but it also shows that research intensity, i.e. the R-share in R&D, declines with firm size. We test these propositions using data of R&D-active firms over the period from 2000 to 2015. Results from panel model estimations that account for unobserved heterogeneity across firms show that larger firms invest indeed more in both research and development whereas the relative focus on research decreases with firm size. In addition, the empirical results suggest that, since the returns to research decline with firm size, specialization maximizes productivity. We discuss policy implications based on these findings. |
| Keywords: | Corporate Research, R&D, Firm Size, Comparative Advantage, Productivity, Innovation Policy |
| JEL: | C14 C30 O31 O38 |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:aiw:wpaper:03&r=all |
| By: | Ugur, Mehmet (Institute of Political Economy, Governance, Finance and Accountability, University of Greenwich); Vivarelli, Marco (UNU-MERIT, Maastricht University, Department of Economic Policy, Universita Cattolica del Sacro Cuore, and IZA, Bonn) |
| Abstract: | We review the theoretical underpinnings and the empirical findings of the literature that investigates the effects of innovation on firm survival and firm productivity, which constitute the two main channels through which innovation drives growth. We aim to contribute to the ongoing debate along three paths. First, we discuss the extent to which the theoretical perspectives that inform the empirical models allow for heterogeneity in the effects of R&D/innovation on firm survival and productivity. Secondly, we draw attention to recent modelling and estimation effort that reveals novel sources of heterogeneity, non-linearity and volatility in the gains from R&D/innovation, particularly in terms of its effects on firm survival and productivity. Our third contribution is to link our findings with those from prior reviews to demonstrate how the state of the art is evolving and with what implications for future research. |
| Keywords: | Innovation, R&D, Survival, Productivity |
| JEL: | O31 O32 O33 O40 |
| Date: | 2020–09–03 |
| URL: | http://d.repec.org/n?u=RePEc:unm:unumer:2020038&r=all |
| By: | Josh Lerner; Ramana Nanda |
| Abstract: | Venture capital is associated with some of the most high-growth and influential firms in the world. Academics and practitioners have effectively articulated the strengths of the venture model. At the same time, venture capital financing also has real limitations in its ability to advance substantial technological change. Three issues are particularly concerning to us: 1) the very narrow band of technological innovations that fit the requirements of institutional venture capital investors; 2) the relatively small number of venture capital investors who hold, and shape the direction of, a substantial fraction of capital that is deployed into financing radical technological change; and 3) the relaxation in recent years of the intense emphasis on corporate governance by venture capital firms. While our ability to assess the social welfare impact of venture capital remains nascent, we hope that this article will stimulate discussion of and research into these questions. |
| JEL: | G24 O31 |
| Date: | 2020–07 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:27492&r=all |
| By: | Alexandra Palm (TIK, University of Oslo) |
| Abstract: | How does mobile phone use affect subjective well-being, and what are the implications of this for responsible research and innovation (RRI)? Previous studies generally find negative associations between mobile phone use and users’ well-being. This paper presents novel evidence of this question based on a new survey dataset for a large representative sample of Norwegian adults. The paper highlights three findings. First, the intensity of mobile phone use per se is not significantly associated with subjective well-being. Second, communication features of mobile phones such as private phone calls and text messaging are positively associated with subjective well-being. Third, network and communication applications (e.g. Facebook, Instagram, Twitter) are negatively associated with the subjective well-being of young adults. The paper discusses implications of these empirical results in terms of RRI, arguing that policy makers and industry actors should consider individual users’ well-being as a central dimension to assess objectives and impacts of innovation processes in digital technologies. |
| Date: | 2020–08 |
| URL: | http://d.repec.org/n?u=RePEc:tik:inowpp:20200823&r=all |
| By: | Joshua S. Gans; Michael Kearney; Erin L. Scott; Scott Stern |
| Abstract: | A central premise of research in the strategic management of innovation is that start-ups are able to leverage emerging technological trajectories as a source of competitive advantage. But, if the potential for a technology is given by the fundamental character of a given technological trajectory, then why does entrepreneurial strategy matter? Or, put another way, if the evolution of technology is largely shaped by the strategic choices entrepreneurs make, then why do technological trajectories exhibit systematic patterns such as the Technology S-curve? Taking a choice-based perspective, this paper illuminates the choices confronting a start-up choosing their technology by resolving the paradox of the Technology S-curve through a reformulation of the foundations of the Technology S-curve. Specifically, we reconceptualize the Technology S-curve not as a technological given but as an envelope of potential outcomes reflecting differing strategic choices by the entrepreneur in exploration versus exploitation. Taking this lens, we are able to clarify the role of technological uncertainty on start-up strategy, the impact of constraints on technological evolution, and how technology choice is shaped by the possibility of imitation. Our findings suggest that staged exploration may stall innovation as a result of the replacement effect, increasing the strategic importance of commitment. |
| JEL: | O31 |
| Date: | 2020–07 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:27489&r=all |
| By: | R. Church; J. C. Duque; D. E. Restrepo |
| Abstract: | In this paper, we propose a spatially constrained clustering problem belonging to the family of "p-regions" problems. Our formulation is motivated by the recent developments of economic complexity on the evolution of the economic output through key interactions among industries within economic regions. The objective of this model consists in aggregating a set of geographic areas into a prescribed number of regions (so-called innovation ecosystems) such that the resulting regions preserve the most relevant interactions among industries. We formulate the p-Innovation Ecosystems model as a mixed-integer programming (MIP) problem and propose a heuristic solution approach. We explore a case involving the municipalities of Colombia to illustrate how such a model can be applied and used for policy and regional development. |
| Date: | 2020–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2008.05885&r=all |
| By: | Cesare Righi; Timothy Simcoe |
| Abstract: | Continuations allow inventors to claim technology developed after the original filing date of their patent, leading to concerns about inadvertent infringement and hold-up. We use the link between patents and standards created by the disclosure of standard essential patents (SEPs) to analyze the relationship between standard publication - a key observable milestone in technology development - and continuations. More than half of the SEPs in our data are filed after standard publication. Consistent with opportunistic behavior by patentees, there is a large increase in continuations immediately after standard publication. Keywords in the claims of SEPs linked to the same standard also become more similar after that standard is published. |
| JEL: | K11 L15 O34 |
| Date: | 2020–08 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:27686&r=all |
| By: | Colombo, Stefano; Filippini, Luigi; Sen, Debapriya |
| Abstract: | We consider a patent licensing game with a capacity constrained innovator. We show that when the constraint is strong (weak), the patentee prefers licensing by means of a fixed fee (unit royalty). In the case of a two-part tariff, the innovator charges a positive fixed fee if and only if the constraint is strong enough. |
| Keywords: | Patent licensing; capacity constraint; Cournot duopoly |
| JEL: | D43 D45 L24 |
| Date: | 2020–08–28 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:102653&r=all |
| By: | Nancy Stokey |
| Abstract: | The importance of new technologies derives from the fact that they spread across many different users and uses, as well as different geographic regions. The diffusion of technological improvements, across producers within a country and across international borders, is critical for long run growth. This paper looks at some evidence on adoption patterns in the U.S. for specific innovations, reviews some evidence on the diffusion of new technologies across international boundaries, and looks at two theoretical frameworks for studying the two types of evidence. One focuses on the dynamics of adoption costs, the other on input costs. |
| JEL: | O14 O33 |
| Date: | 2020–07 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:27466&r=all |