|
on Technology and Industrial Dynamics |
| By: | Ascione, Grazia Sveva |
| Abstract: | Much of the literature emphasizes the relationship between interdisciplinarity and the Sustainable Development Goals (SDGs), which are seen as closely linked and highly interdisciplinary. Therefore, innovation related to the SDGs is expected to be technologically diverse, especially when it emanates from academia, where teams of researchers collaborate to create innovation for the benefit of society. However, research on innovation for the SDGs is still in its infancy due to a lack of comprehensive quantitative analysis about its characteristics and a lack of consideration of potentially relevant actors, such as universities. This paper aims to make a threefold contribution to the existing literature by analyzing USPTO patent data from 2006 to 2020. First, we develop a novel method for tagging SDGs-related patents using an unsupervised natural language processing (NLP) approach. Starting from an initial list of keywords, we build an extended dictionary of keywords for each SDG based on the patent text by combining the TF-IDF method with a vector representation of the patent text and SDGs keywords. Second, we analyze innovation related to the SDGs, focusing particularly on the contribution of universities. Third, we compare the diversity of SDGs and non-SDGs patents using the Rao-Stirling index. Our results show that patents related to the SDGs are on the rise, but the trend is more pronounced for universities, where the majority of innovation production revolves around SDG 3 (good health and well-being). Moreover, the rise in SDGs patents seems to be led not only by green technologies, but mainly by high technologies. Eventually, the empirical results point in two directions. On the one hand, SDGs related patents are more diverse than their counterparts across almost all technology sectors. However, if we consider university patents only, there is a diversity premium only for a few SDGs, namely SDG 2, SDG 3, and SDG 15. |
| Keywords: | echnological diversity; University patents; Interdisciplinarity; SDGs; United States |
| JEL: | O3 O34 |
| Date: | 2023–10–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:119452&r=tid |
| By: | Antea Barišić; Mahdi Ghodsi (The Vienna Institute for International Economic Studies, wiiw); Robert Stehrer (The Vienna Institute for International Economic Studies, wiiw) |
| Abstract: | This paper advances the literature on the impacts of new technologies on labour markets, focusing on wage and labour income shares. Using a dataset from 32 countries and 38 industries, we analyse the effects of new technologies – proxied by patents, information and communication technology (ICT) capital usage, and robot intensity – on average wages and labour income shares over time. Our results indicate a positive correlation between patents and wage levels along with a minor negative impact on labour income shares, suggesting that technology rents are not fully passed on to labour. Robot intensity is positively associated with labour income shares, while ICT capital has an insignificant effect. These effects persist over time and are reinforced by global value chain (GVC) linkages. Our conclusions align with recent research indicating that new technologies have a generally limited impact on wages and labour income shares. |
| Keywords: | Robot adoption, ICT investment, new technologies, GVC, wages, labour income shares |
| JEL: | C13 C23 F14 F16 O33 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:wii:wpaper:240&r=tid |
| By: | Nicolas Ameye; Jacques Bughin; Nicolas van Zeebroeck |
| Abstract: | This paper studies the diffusion of artificial intelligence (AI) within firms, from exploration to local adoption to full-scale exploitation. The optimal timing of technology adoption represents a balance between preempting the risk of competition and time needed to acquire necessary complements, to ensure a successful return on investment. We formulate and test the idea that this balance changes along the adoption curve from experimentation to exploitation. We first model the decision of a firm facing Cournot competition to explore then exploit AI and assess the role of a variety of internal complements (technological and organizational) as well as competitive rivalry in these processes. Based on this theoretical model, a reduced form model of internal diffusion of AI is then estimated. Three results emerge: (1) rivalry triggers a competitive technology race that prevails in the exploitation more than in the exploration phase; (2) direct AI complements (such as machine learning) favor both adoption and exploitation, while indirect complements (such as cloud and big data) matter more for the experimentation than for the exploitation phase; (3) organizational complements are important for exploiting AI at scale, while technological ones drive exploration and adoption more than exploitation. |
| Keywords: | Artificial Intelligence, Adoption, Exploitation, Diffusion, Competition, Complements |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:ict:wpaper:2013/368095&r=tid |
| By: | Katrin Hussinger (DEM, Université du Luxembourg); Wunnam Issah (University of Leicester School of Business, UK) |
| Abstract: | This paper shows that the American Inventor’s Protection Act, which introduced the disclosure of patent applications after 18 months, i.e. before a grant decision is taken and, hence, before it is known whether the respective technology receives legal protection, is associated with a reduction of family firms’ research and development (R&D) investment. This suggests that early disclosure of patent applications is perceived as a threat to family firms’ innovation activity and discourages their R&D investment. This finding deserves our attention because family firms account for a large share of the U.S. economy and a reduction of their R&D investment can have long-term consequences. |
| Keywords: | R&D investments, AIPA, Family firms, Socio-emotional wealth (SEW) |
| JEL: | O30 O34 O38 G32 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:luc:wpaper:23-17&r=tid |
| By: | Haarburger, Richard; Stemmler, Henry |
| Abstract: | This paper studies how automation technology affects market power in the global economy. We develop a theoretical model in which firms' markups are endogenous to factor input choices based on technology levels, but are also affected by technology adoption of other domestic and foreign firms. In an empirical analysis, we find that market power, measured as the markup of price over marginal cost, declines on average with higher levels of automation. However, there is substantial heterogeneity, with firms in the highest revenue and markup quintile gaining market power. Moreover, we find that exposure to foreign automation increases competition in the local market. |
| Keywords: | Automation, Markups, Robots, Market Concentration |
| JEL: | O33 F41 F12 D43 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:esprep:281378&r=tid |
| By: | Koski, Heli; Fornaro, Paolo |
| Abstract: | Abstract This study investigates the impact of firm-level investments in data assets on productivity growth during the COVID-19 pandemic, utilizing matched employer-employee data of 13, 609 Finnish firms for 2015–2020. Our estimation results indicate that firms with greater pre-pandemic investments in software and database assets and ICT experienced significantly higher labor productivity growth in the first year of the pandemic. Notably, these positive effects are predominantly observed in the service sector, while manufacturing companies did not exhibit statistically significant impacts. Furthermore, our analysis highlights that large service companies with greater investments in data assets demonstrated higher labor productivity growth than their counterparts. We also identify a noteworthy complementarity between a firm’s investments in ICT and databases and employees’ skills, as measured by education level. Interestingly, our empirical findings underscore that firms investing more in data, databases and ICT were statistically significantly more likely to belong to the productivity frontier of their industry. |
| Keywords: | Data assets, Digitalization, Productivity, Growth, Resilience, Pandemics |
| JEL: | D22 L25 O33 |
| Date: | 2024–01–16 |
| URL: | http://d.repec.org/n?u=RePEc:rif:wpaper:113&r=tid |
| By: | Aghion, Philippe; Bergeaud, Antonin; Gigout, Timothee; Lequien, Matthieu; Malitz, Marc |
| Abstract: | We examine the effect of entry by French firms into a new export market on the dynamics of their patents' citations received from that destination. Applying a difference-in-differences identification strategy with a staggered treatment design, we show that: (i) entering a new foreign market has a significant impact on the long-run flow of citations; (ii) the impact is mostly driven by the extensive margin; (iii) inventors in destination countries patent mostly in products that do not directly compete with those of the exporting firm; (iv) the spillover intensity decreases with the technological distance between the exporting firm and the destination. |
| Keywords: | international trade; spillover; innovation; patent |
| JEL: | O33 O34 O40 F10 F14 |
| Date: | 2023–11–15 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:121291&r=tid |
| By: | Pinkus, David (Department of Economics, Copenhagen Business School); Pozzoli, Dario (Department of Economics, Copenhagen Business School); Schneider, Cédric (Department of Economics, Copenhagen Business School) |
| Abstract: | We use a unique database on domestic pension fund investment to analyze the re-lationship between pension fund investment and innovation within Danish firms. We find a significant positive association between pension fund investment and various measures of innovation, including green technologies for climate change mitigation and adaptation. However, this relationship is much weaker in highly competitive indus-tries, suggesting that pension funds encourage innovation by monitoring and holding managers accountable. Our analysis also shows that pension funds foster innovation by providing stable long-term capital. Overall, our study highlights the important role of pension funds in driving firm innovation, particularly by reducing managerial slack and by supplying stable, long-term capital. |
| Keywords: | Pension Fund Investment; Innovation; R&D |
| JEL: | J24 J60 L20 |
| Date: | 2024–01–17 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:cbsnow:2024_001&r=tid |
| By: | Patricia Crifo (École polytechnique, CREST and E4C, France and CIRANO, Canada) |
| Abstract: | This paper examines why a growth process relying on both green innova tion and green human capital may be responsible for higher inequality within and between skills. We propose a theoretical framework and derive some em pirical observations using data from more than 2000 companies in 21 OECD countries in 2022. We discuss the policy implications of this analysis in light of the COVID-19 pandemic, which has led many governments to place green investment at the heart of their recovery plans. |
| Keywords: | Environment, Skill Supply, Innovation-driven Growth |
| JEL: | O33 Q50 J24 |
| Date: | 2024–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:crs:wpaper:2024-02&r=tid |
| By: | Andrea Roventini |
| Abstract: | This work presents the evolutionary growth theory, which studies the drivers and patterns of technological change and production together with the (imperfect) mechanisms of coordination among a multitude of firms. This requires to studies economies as complex evolving systems, i.e. as ecologies populated by heterogenous agents whose out-of-equilibrium local market interactions lead to the emergence of some collective order at higher level of aggregation, while the system continuously evolves. Accordingly a multi-country multi-industry agent-based model is introduced, where the restless competition of firms in international markets lead to the emergence of growth and persistent income divergence among countries. Moreover, each economy experiences a structural transformation of its productive structure during the development process. Such dynamics results from firm-level virtuous (or vicious) cycles between knowledge accumulation, trade performances, and growth dynamics. The model also accounts for a rich ensemble of empirical regularities at macro, meso and micro levels of aggregation. Finally, the model is employed to assess different strategies that laggard countries can adopt to catch up with leaders. Results show that in absence of government interventions, laggards will continue to fall behind. On the contrary, industrial policies can successfully drive international convergence among countries. |
| Keywords: | Endogenous growth, structural change, technology-gaps, industrial policies, evolutionary economics, agent-based models |
| Date: | 2024–01–30 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2024/02&r=tid |
| By: | Julien Gosse; Chris CM Forman; Nicolas van Zeebroeck |
| Abstract: | Today’s world is profoundly transformed by two major revolutions. The first one is related to the sustainability transition, while the other relates to the digital transformation of our economies and societies. Recently, regions such as Europe have put the integration between these two transformations high on their agenda. A term was coined for it: the twin transition. In a nutshell, the twin transition aims at leveraging the potential of technologies such as Cloud technologies, Internet of Things (IoT) and Artificial Intelligence (AI) to tackle the sustainability transition. |
| Keywords: | Digital Transformation, Environmental Management, Sustainability Practices, Green ICT, ICT for Green |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:ict:wpaper:2013/368092&r=tid |
| By: | Luca Zamparelli (Department of Social and Economic Sciences, Sapienza University of Rome, Italy) |
| Abstract: | This paper investigates alternative ways of introducing technological progress in heterodox theories of economic growth. We model technical change as: i) exogenous and costless; ii) a positive externality of capital accumulation, the wage share or the employment rate; iii) endogenous and costly. We implement these formalizations in Classical growth theories, where investments coincide with full capacity savings, and Keynesian theories where capital accumulation is demand constrained. We also distinguish between abundant and inelastic labor market closures. We discuss the outcomes of these models in terms of long-run growth, functional income distribution and employment. |
| Keywords: | Technical change, heterodox growth models, R&D, factor income shares, employment |
| JEL: | D24 E25 D33 O30 O41 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:new:wpaper:2404&r=tid |
| By: | Cortes, Patricia (Boston University); Feng, Ying (National University of Singapore); Guida-Johnson, Nicolás (Pontificia Universidad Javeriana); Pan, Jessica (National University of Singapore) |
| Abstract: | We examine the differential effects of automation on the labor market and educational outcomes of women relative to men over the past four decades. Although women were disproportionately employed in occupations with a high risk of automation in 1980, they were more likely to shift to high-skill, high-wage occupations than men in over time. We provide a causal link by exploiting variation in local labor market exposure to automation attributable to historical differences in local industry structure. For a given change in the exposure to automation across commuting zones, women were more likely than men to shift out of routine task-intensive occupations to high-skill, high wage occupations over the subsequent decade. The net effect is that initially routine-intensive local labor markets experienced greater occupational gender integration. College attainment among younger workers, particularly women, also rose signicantly more in areas more exposed to automation. We propose a model of occupational choice with endogenous skill investments, where social skills and routine tasks are q-complements, and women have a comparative advantage in social skills, to explain the observed patterns. Supporting the model mechanisms, areas with greater exposure to automation experienced a greater movement of women into occupations with high social skill (and high cognitive) requirements than men. |
| Keywords: | automation, gender, occupational segregation, gender skill gap |
| JEL: | J16 J24 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16695&r=tid |
| By: | Samira Bakkali; Michele Cincera; Nicolas van Zeebroeck |
| Abstract: | This paper investigates the relationship between ICT and international R&D collaborations among 19 OECD countries from 2000 to 2015. More specifically, it looks at the impact of broadband penetration on the number of international co-inventions measured through patents. Poisson and Negative binomial regression models are employed for estimation. The results reveal a non-linear association between broadband access and international R&D collaborations, characterized by an inverted U-shaped curve. Additionally, the insights show that broadband penetration increased the concentration of existing and new collaboration ties. Subsequent analysis is undertaken, splitting the overall country-pairs sample into seven technology areas using the OST7 classification. Consistent with the overall findings, Electronics, Instruments, Chemicals, and Pharma exhibit the same inverted U-shaped relationship. However, the relationship is non-significant for Industrial and Mechanical Processes, while Civil engineering displays a positive linear association. These results also underline how crucial it is to consider particular technology areas when assessing how technology adoption affects international R&D collaboration. |
| Keywords: | Broadband penetration, International R&D Collaboration, Negative Binomial |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:ict:wpaper:2013/368096&r=tid |
| By: | Silvia Massini (Manchester Institute of Innovation Research, The University of Manchester); Mabel Sanchez Barrioluengo (Manchester Institute of Innovation Research, The University of Manchester); Xiaoxiao Yu (Manchester Institute of Innovation Research, The University of Manchester); Reza Salehnejad (Manchester Institute of Innovation Research, The University of Manchester) |
| Abstract: | Advanced digital technologies (DTs) such as AI, Big Data, Cloud Computing, 3D printing, IoT, and Robotics are known for their potential to be pervasive and generate disruptive change. Despite this, there is limited evidence regarding the factors that motivate or hinder technology adoption. This study, based on an original survey of firms in Greater Manchester, aims to shed light on the determinants of DT adoption, including underlying motivations, potential barriers, and skills deficits. Additionally, it explores the influence of digitalisation and skills on firms‘ performance. Our results suggest that while different DTs are at varying stages of technology diffusion, they are characterised by complementarity and are often jointly adopted. Furthermore, the adoption of DTs in SMEs and younger firms, coupled with the presence of appropriate (digital and non-digital) skills, constitutes a pivotal synergy that significantly influences firms' productivity levels. |
| Keywords: | Digital transformation, Adoption, Skills, Motivations, Barriers, Productivity, Firms |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:bdj:smioir:2024-01&r=tid |