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on Innovation |
| By: | Serenella Caravella; Francesco Crespi; Giacomo Cucignatto; Dario Guarascio |
| Abstract: | This work sheds new light on the Photovoltaic Supply Chain (PVSC), providing fresh evidence on structural dependencies (SDs) and (asymmetrically distributed) technological capabilities. Bridging the perspectives of 'technological sovereignty' and 'strategic autonomy', a number of contributions are provided. First, we carry out a fine-grained mapping of the PVSC, combining trade and patent data. Second, we assess the long-term evolution of trade and technological hierarchies, documenting processes of polarization and growing SDs. Third, we zoom-in on critical PV areas (i.e. products and related technologies), providing a 'strategic intelligence' activity which may prove useful for tailoring trade, industrial and innovation policies. Fourth, we explore the relationship between technological specialization and productive capabilities showing that, in the upstream segment, reinforcing the former may help mitigating SDs. |
| Keywords: | Technological sovereignty; Strategic dependency; Photovoltaic industry; Trade; Patents. |
| Date: | 2023–09–14 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2023/32&r=ino |
| By: | Petralia, Sergio; Kemeny, Thomas; Storper, Michael |
| Abstract: | Tacit knowledge – ideas that cannot readily be meaningfully and completely communicated – has long been considered a precursor to scientific and technological advances. Using words and phrases found in the universe of USPTO patents 1940-2020, we propose a new method of measuring tacit knowledge and its progressive codification. We uncover a discontinuity in the production of highly tacit technologies. Before 1980, highly- and less-tacit inventions are evenly distributed among inventors, organizations, scientific domains and subnational regions. After 1980, inventors of highly tacit patents become relatively rare, and increasingly concentrated in domains and locations. The economic payoffs to tacit knowledge also change, as it starts unequally rewarding high-income workers. This suggests a role for tacit knowledge in contributing to the rise in income inequality since 1980. |
| JEL: | J1 |
| Date: | 2023–09–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:120154&r=ino |
| By: | Joseph Engelberg; Runjing Lu; William Mullins; Richard R. Townsend |
| Abstract: | We document political sentiment effects on US inventors. Democratic inventors are more likely to patent (relative to Republicans) after the 2008 election of Obama but less likely after the 2016 election of Trump. These effects are 2-3 times as strong among politically active partisans and are present even within firms over time. Patenting by immigrant inventors (relative to non-immigrants) also falls following Trump’s election. Finally, we show partisan concentration by technology class and firm. This concentration aggregates up to more patenting in Democrat-dominated technologies (e.g., Biotechnology) compared to Republican-dominated technologies (e.g., Weapons) following the 2008 election of Obama. |
| JEL: | D72 J24 M5 O31 |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:31619&r=ino |
| By: | Kugelberg, Susanna (Copenhagen Business School); Borrás, Susana (Copenhagen Business School) |
| Abstract: | This paper is a teaching case study written for educational purposes. The case brings forward a real-life situation of an organization that is engaged in the exciting but also risky journey of implementing a green innovation at a large scale. The case is written in a way that allows students to reflect and think about the organizational and leadership challenges and opportunities involved. The teacher can activate these reflections in the context of various possible theoretical and analytical frameworks, in a number of possible different courses. The case is about Exergi, the main utility company producing district heating in Stockholm. After successfully transitioning from coal to bio-energy sources, since 2020 Exergi has embarked on a new and far more ambitious venture: Bioenergy Carbon Capture and Storage (BECCS). This technology captures CO2 emissions from biomass combustion and stores them, potentially resulting in negative emissions. BECCS plays a central role in IPCC mitigation pathways and Exergi has recognized an opportunity, but venturing into this uncharted territory presents numerous challenges. BECCS is a new and untested technology at an industrial scale, requiring substantial investments, and a market for selling carbon removal certificates (CRC) that does not exist yet. Though promising for reaching net zero targets in time, the viability of BECCS for Exergi depends on a supportive regulatory framework, cross-border cooperation, and the creation of a CRC market. To navigate these challenges, Exergi relies on creating an innovative organizational culture as well as mobilizing external stakeholders. Hence, CEO Anders Egelrud has hired individuals with entrepreneurial mindsets, and sought external expertise as well as creating strong networks and communication approach. Yet, some internal tensions have also come to the fore, due to the rapid internal dynamics. Overall, Exergi's transition from coal to BECCS reflects the commitment to sustainable practices by an incumbent, and its willingness to size new opportunities. The company's success driving this transformation forward hinges on many events coming together, both external and internal to the firm. |
| Keywords: | climate mitigation; green transitions; eco-innovation; sustainability; capacity; dynamic capabilities; utilities; energy; incumbent; district heating; Sweden; Stockholm; carbon capture; bioenergy; biomass; leadership; net zero; climate neutrality; transformative innovation |
| JEL: | O31 O33 O38 O44 Q01 Q16 Q55 Q58 |
| Date: | 2023–09–11 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:lucirc:2023_007&r=ino |
| By: | Annamaria Conti; Vansh Gupta; Jorge Guzman; Maria P. Roche |
| Abstract: | Open source is key to innovation, but we know little about how to incentivize it. In this paper, we examine the impact of a program providing monetary incentives to motivate innovators to contribute to open source. The Sponsors program was introduced by GitHub in May 2019 and enabled organizations and individuals alike to reward developers for their open source work on the platform. To study this program, we collect fine-grained data on about 100, 000 GitHub users, their activities, and sponsorship events. Using a difference-in-differences approach, we document two main effects. The first is that developers who opted into the program, which does not entail receiving a financial reward, increased their output after the program's launch. The second is that the actual receipt of sponsorship has a long-lasting negative effect on innovation, as measured by new repository creation, regardless of the amount of money received. We estimate a similar decline in other community-oriented tasks, but not in coding effort. While the program’s net effect on users’ innovative output appears to be positive, our study shows that receiving an extrinsic reward may crowd out developers' intrinsic motivation, diverting their effort away from community and service-oriented activities on open source. |
| JEL: | J24 L86 O3 O31 O36 |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:31668&r=ino |
| By: | Erdem Dogukan Yilmaz; Tim Meyer; Milan Miric |
| Abstract: | Online innovation communities are an important source of innovation for many organizations. While contributions to such communities are typically made without financial compensation, these contributions are often governed by licenses such as Creative Commons that may prevent others from building upon and commercializing them. While this can diminish the usefulness of contributions, there is limited work analyzing what leads individuals to impose restrictions on the use of their work. In this paper, we examine innovators imposing restrictive licenses within the 3D-printable design community Thingiverse. Our analyses suggest that innovators are more likely to restrict commercialization of their contributions as their reputation increases and when reusing contributions created by others. These findings contribute to innovation communities and the growing literature on property rights in digital markets. |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2309.00536&r=ino |
| By: | Ådne Cappelen; Pierre Mohnen; Arvid Raknerud; Marina Rybalka (Statistics Norway) |
| Abstract: | This paper revisits the estimation of private returns to R&D. In an extension of the standard approach, we allow for endogeneity of production decisions, heterogeneity of R&D elasticities, and asymmetric treatment of intramural and extramural R&D. Our empirical analyses are based on an extended Cobb-Douglas production function that allows for firms with zero R&D capital, which is especially useful for studying firms’ transition from being R&D-non—active to becoming R&D-active. Using a large panel of Norwegian firms observed in the period 2001-2018, we estimate the average private net return to be in the range 0-5 percent across a variety of model specifications if we treat intra- and extramural R&D symmetrically. If in compliance with the Frascati manual, we treat intramural R&D as investment and extramural R&D as intermediate input, the estimated net return increases to 5-10 percent. |
| Keywords: | Returns to R&D; Intramural R&D; Extramural R&D; Capitalization of R&D; Dynamic panel data models; GMM |
| JEL: | C33 C52 D24 O38 |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:ssb:dispap:1005&r=ino |
| By: | Antonella Biscione (CESPIC, Catholic University “Our Lady of Good Counsel”); Chiara Burlina (“Marco Fanno” Department of Economics and Management, University of Padova); Raul Caruso (Department of Economic Policy and CSEA, Università Cattolica del Sacro Cuore, CESPIC Catholic University “Our Lady of Good Counsel”) |
| Abstract: | Training has generally been linked to firm’s innovation propensity, but evidence remains sparse on the role of different typologies of training for firms in transition economies. Using a unique sample from the World Bank Enterprise Surveys (wave 2018-2020), we test the effect of training programs on innovation in 27 countries of Eastern Europe and Central Asia. We test several definitions of training, and our results show that both product and process innovations benefit from all the proposed activities. To validate our findings, we employ a specific instrumental variable approach by applying the Lewbel’s special regressor technique, whose outcome confirms our baseline results. Our contribution is twofold: first, we exploit a new database for transition countries that fill the gap in the literature on training programs also in these economies; second, for a policy perspective, we highlight the need to invest and promote training to boost innovation capacity of firms in these countries to reach the level of developed economies. |
| Keywords: | Transition Economies; Innovation; Training |
| JEL: | O14 O32 P27 P36 |
| Date: | 2023–01 |
| URL: | http://d.repec.org/n?u=RePEc:pea:wpaper:1020&r=ino |
| By: | Asuamah Yeboah, Samuel |
| Abstract: | This systematic review explores the dynamic relationship between Foreign Direct Investment (FDI)-driven entrepreneurial ecosystems and the United Nations' Sustainable Development Goals (SDGs). FDI is recognized as a potent catalyst for global development, and its alignment with specific SDGs can create a transformative impact across various domains. By strategically harnessing FDI, countries can accelerate their progress towards achieving the SDGs and building a more inclusive and equitable future. The study identifies several key SDGs where FDI-driven entrepreneurial ecosystems play a pivotal role: SDG 1: No Poverty: FDI fosters economic growth, generates employment opportunities, and enhances labour productivity, consequently alleviating poverty. It contributes to improving wages, human capital development, and overall well-being. SDG 8: Decent Work and Economic Growth: FDI-supported ecosystems promote inclusive economic growth by creating jobs and enhancing working conditions. They boost local productivity, induce employment, and stimulate consumption. SDG 9: Industry, Innovation, and Infrastructure: FDI brings technological innovation, knowledge transfer, and advanced infrastructure, fostering innovation and enhancing local business competitiveness. SDG 10: Reduced Inequality: FDI empowers marginalized communities, enabling them to access resources, markets, and global networks, thus reducing inequality. SDG 17: Partnerships for the Goals: FDI-driven partnerships between foreign corporations and local startups leverage expertise, resources, and networks to collectively achieve various SDGs. Such collaborations aim to align with the principles and objectives of SDG 17. SDG 4: Quality Education: Multinational corporations' involvement in FDI can lead to educational initiatives, skill development programs, and technology transfers that enhance educational quality. SDG 13: Climate Action: FDI-driven innovation results in sustainable technologies, cleaner production processes, and environmental solutions contributing to climate action. SDG 16: Peace, Justice, and Strong Institutions: FDI promotes transparency, accountability, and ethical business practices, strengthening institutions and contributing to a stable business environment. SDG 5: Gender Equality: FDI-supported startups empower women entrepreneurs, enhance gender diversity in the workforce, and create opportunities for women's economic participation. SDG 11: Sustainable Cities and Communities: FDI-driven entrepreneurial ecosystems contribute to urban development through smart technologies, sustainable infrastructure, and innovative solutions. SDG 7: Affordable and Clean Energy: FDI plays a critical role in the adoption of clean energy technologies, supporting the transition to renewable energy sources. |
| Keywords: | Poverty Alleviation, Economic Growth, Innovation, Inequality Reduction, Partnerships, Quality Education, Climate Action, Strong Institutions, Gender Equality, Sustainable Urban Development, Clean Energy Adoption. |
| JEL: | F21 F23 O31 O32 O33 O38 O40 O41 O43 O44 O57 |
| Date: | 2023–07–20 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:118519&r=ino |
| By: | Daron Acemoglu; Philippe Aghion; Lint Barrage; David Hémous |
| Abstract: | We investigate the short- and long-term effects of a natural gas boom in an economy where energy can be produced with coal, natural gas, or clean sources and the direction of technology is endogenous. In the short run, a natural gas boom reduces carbon emissions by inducing substitution away from coal. Yet, the natural gas boom discourages innovation directed at clean energy, which delays and can even permanently prevent the energy transition to zero carbon. We formalize and quantitatively evaluate these forces using a benchmark model of directed technical change for the energy sector. Quantitatively, the technology response to the shale gas boom results in a significant increase in emissions as the US economy is pushed into a “fossil-fuel trap” where long-run innovations shift away from renewables. Overall, the shale gas boom reduces our measure of social welfare under laissez-faire, whereas, combined with carbon taxes and more generous green subsidies, it could have increased welfare substantially. |
| JEL: | O30 O41 O44 Q33 Q43 Q54 Q55 |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:31657&r=ino |
| By: | Oschinski, Matthias |
| Abstract: | We assess the impact of artificial intelligence (AI) on Germany’s labour market applying the methodology on suitability for machine learning (SML) scores established by Brynjolfsson et al., (2018). However, this study introduces two innovative approaches to the conventional methodology. Instead of relying on traditional crowdsourcing platforms for obtaining ratings on automatability, this research exploits the chatbot capabilities of OpenAI's ChatGPT. Additionally, in alignment with the focus on the German labor market, the study extends the application of SML scores to the European Classification of Skills, Competences, Qualifications and Occupations (ESCO). As such, a distinctive contribution of this study lies in the assessment of ChatGPT's effectiveness in gauging the automatability of skills and competencies within the evolving landscape of AI. Furthermore, the study enhances the applicability of its findings by directly mapping SML scores to the European ESCO classification, rendering the results more pertinent for labor market analyses within the European Union. Initial findings indicate a measured impact of AI on a majority of the 13, 312 distinct ESCO skills and competencies examined. A more detailed analysis reveals that AI exhibits a more pronounced influence on tasks related to computer utilization and information processing. Activities involving decision-making, communication, research, collaboration, and specific technical proficiencies related to medical care, food preparation, construction, and precision equipment operation receive relatively lower scores. Notably, the study highlights the comparative advantage of human employees in transversal skills like creative thinking, collaboration, leadership, the application of general knowledge, attitudes, values, and specific manual and physical skills. Applying our rankings to German labour force data at the 2-digit ISCO level suggests that, in contrast to previous waves of automation, AI may also impact non-routine cognitive occupations. In fact, our results show that business and administration professionals as well as science and engineering associate professionals receive relatively higher rankings compared to teaching professionals, health associate professionals and personal service workers. Ultimately, the research underscores that the overall ramifications of AI on the labor force will be contingent upon the underlying motivations for its deployment. If the primary impetus is cost reduction, AI implementation might follow historical patterns of employment losses with limited gains in productivity. As such, public policy has an important role to play in recalibrating incentives to prioritize machine usefulness over machine intelligence. |
| Keywords: | Generative AI, Labour, Skills Suitability for Machine Learning, German labour market, ESCO |
| JEL: | A1 J0 |
| Date: | 2023–08–14 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:118300&r=ino |
| By: | Commander, Simon (IE Business School, Altura Partners); Estrin, Saul (London School of Economics) |
| Abstract: | Much of the debate about Asia's economic success has focussed on the respective roles of the market and state. It has been argued that industrial policy has helped address market failures and achieve critical coordination of development planning and process. Yet, starkly contrasting market and state ignores the way that both have been closely intertwined. Indeed, across the different economic and political systems in Asia, a common feature has emerged in which government and big, diversified and mostly family-owned business groups work in close connection to support their mutual interests. Through such ties, Asia has found a solution to many of the problems of economic development by a different type of coordination. Whilst highly effective in a phase of extensive growth, such connections carry less beneficial consequences. Not least, the accumulation of market power and the restraint of competition that result from preferential ties between business groups and political power. At the same time, the lock-hold of business groups limits growth in the formal economy, in employment whilst also stoking inequality. Further, as Asia searches for greater innovation to drive progress, such close ties are far more likely to stand in the way, deterring new entrants and holding back the creation of more broad-based innovation. Breaking down the entrenched power of connected business groups will require new policies that address head-on the distortions that these connections create. These include measures to deter recourse to the business group format itself. |
| Keywords: | Asia growth, industrial policy, business groups |
| JEL: | L5 L22 O25 O53 |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izapps:pp202&r=ino |