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on Innovation |
| By: | Robert M Yawson |
| Abstract: | Models on innovation, for the most part, do not include a comprehensive and end-to-end view. Most innovation policy attention seems to be focused on the capacity to innovate and on input factors such as R&D investment, scientific institutions, human resources and capital. Such inputs frequently serve as proxies for innovativeness and are correlated with intermediate outputs such as patent counts and outcomes such as GDP per capita. While this kind of analysis is generally indicative of innovative behaviour, it is less useful in terms of discriminating causality and what drives successful strategy or public policy interventions. This situation has led to the developing of new frameworks for the innovation system led by National Science and Technology Policy Centres across the globe. These new models of innovation are variously referred to as the National Innovation Ecosystem. There is, however, a fundamental question that needs to be answered: what elements should an innovation policy include, and how should such policies be implemented? This paper attempts to answer this question. |
| Date: | 2021–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2106.15479&r= |
| By: | Ugo Fratesi (Polytechnic University of Milan); Carlo Gianelle (European Commission - JRC); Fabrizio Guzzo (European Commission - JRC) |
| Abstract: | The objective of this report is to provide an account of how and to what extent the Smart Specialisation approach to regional innovation policy has been implemented in practice. The analysis explores how policy measures implemented under the Thematic Objective 1 “Strengthening research, technological development and innovation” of national and regional Operational Programmes, co-financed by the European Regional Development Fund, have incorporated key Smart Specialisation principles during the 2014-2020 programming period. We identify three main design principles of Smart Specialisation and translate them into three research hypotheses characterized in ways that can be tested empirically.We find that the Smart Specialisation strategies under scrutiny mostly apply a limited portfolio of traditional, supply-side instruments. All things considered, there is limited evidence of the implementation of a truly selective intervention logic aimed to support in a dedicated way different investment priorities. We observe quite pervasive support to the establishment of a critical mass of individual and collaborative entrepreneurial initiatives in all the Smart Specialisation areas, while support to the formation and strengthening of stakeholder communities is only present in a very few territories. We find positive although not widespread evidence of the introduction of novel elements in the design of some instruments; this points to a tentative break with tradition and path dependency which is in line with the spirit of Smart Specialisation. Policy implications for the future development and evolution of European regional innovation policy are derived. |
| Keywords: | regional innovation policy, Smart Specialisation, policy instruments, implementation measures |
| JEL: | O25 O30 R12 R58 |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc123821&r= |
| By: | Tristan L. Botelho; Daniel Fehder; Yael Hochberg |
| Abstract: | Entrepreneurship is thought to be a key driver of economic growth. While there are myriad forms of entrepreneurship, ranging from self-employment to small and medium size enterprises to technology- and innovation-driven startups, recent research provides evidence that the relationship between entrepreneurship and economic growth is driven not by overall quantity of new firm entry, but rather by a small subset of high-growth startups that are primarily categorized as innovation-driven. This paper provides a survey of the growing literature on the economics of such innovation-driven entrepreneurship. We begin by distinguishing between the various forms of entrepreneurship, which are often confounded in both theory and empirical work. We lay out the current state of knowledge, and describe the challenges faced by researchers in the field, particularly around measurement, data and identification. We conclude with an overview of the major open questions and directions for future research in the area. |
| JEL: | O0 O3 |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:28990&r= |
| By: | S, Minkyu. |
| Abstract: | How does firm innovation respond to changing trade environments? This paper investigates this question using the matched administrative datasets for UK firms' R&D expenditures and their trade exposures between 2002 and 2011. I find a strong adverse impact of import competition from China on UK firms' R&D, which is supportive of the `Schumpeterian hypothesis'. There is no evidence that the improved access to Chinese inputs for individual firms offset this negative competition channel. Increased export demand, by contrast, significantly stimulates firms' innovation efforts. Our results also reveal heterogeneity in the R&D responses depending on the firms' initial conditions: First, more productive British firms raise their R&D spending by much more in response to increased foreign demand. Second, exporters reduce R&D by less than non-exporters in the face of the rising Chinese competition. These findings together imply that innovation of purely domestic and less profitable firms was most hurt by globalization, leading to a widening productivity gap across firms. |
| Keywords: | R&D, Chinese competition, Firm-level trade |
| JEL: | F14 F60 O31 |
| Date: | 2021–07–08 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:2151&r= |
| By: | SCHROECKER Doris; WILLE Angelo; SENTIS Pauline; TUEBKE Alexander (European Commission - JRC); HERNANDEZ GUEVARA Hector (European Commission - JRC); GRASSANO Nicola (European Commission - JRC); DIODATO Dario (European Commission - JRC); COMPANO Ramon (European Commission - JRC); CSEFALVAY Zoltan; GEORGAKAKI Aliki (European Commission - JRC); LETOUT Simon (European Commission - JRC); PASIMENI Francesco (European Commission - JRC) |
| Abstract: | This first pilot ‘industrial technology prospect report’ aims to provide an insight into the state of play on R&I in low-carbon industry technologies, which are key for emissions reductions in energy-intensive industries, such as steel, cement and chemicals, covered by the upcoming EU low-carbon industrial alliance20. It concentrates on the maturity of relevant technologies and their potential to help industry reach the EU climate targets. It provides an overview of relevant production costs in industrial sectors, potential cost reductions through new technology and insights into current public and private sector R&D investment and related patenting developments. The report also provides a snapshot of green R&I development and patents in EU regions. This report is the outcome of a model of cooperation between services that will help to provide a strong evidence base to inform future roadmaps supporting R&I in industrial ecosystems and alliances. The approach will be further developed in other areas through and greater involvement of the European Institute for Innovation and Technology (EIT) in analysing the territorial dimension of R&I. the exploitation of existing analytical capacities, targeted use of Horizon Europe results and greater involvement of the European Institute for Innovation and Technology (EIT) in analysing the territorial dimension of R&I. |
| Keywords: | Energy Intensive Industries, Research & Development, Innovation, Technology Roadmap |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc125684&r= |
| By: | Naudé, Wim (University College Cork); Bray, Amy (Zindi); Lee, Celina (Zindi) |
| Abstract: | In this paper, we study the crowdsourcing of innovation in Africa through a data science contest on an intermediated digital platform. We ran a Machine Learning (ML) contest on the continent's largest data science contest platform, Zindi. Contestants were surveyed on their motivations to take part and their perceptions about AI in Africa. In total, 614 contestants submitted 15,832 entries, and 559 responded to the accompanying survey. From the findings, we answered several questions: who take part in these contests and why? Who is most likely to win? What are contestants' entrepreneurial aspirations in deploying AI? What are the obstacles they perceive to the greater diffusion of AI in Africa? We conclude that crowdsourcing of AI via data contest platforms offers a potential mechanism to alleviate some of the constraints in the adoption and diffusion of AI in Africa. Recommendations for further research are made. |
| Keywords: | crowdsourcing, innovation, data science, artificial intelligence, Africa |
| JEL: | O31 O33 O36 O55 |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp14545&r= |