nep-ino New Economics Papers
on Innovation
Issue of 2023‒03‒27
seven papers chosen by
Uwe Cantner
University of Jena

  1. Measuring Science and Innovation Linkage Using Text Mining of Research Papers and Patent Information By MOTOHASHI Kazuyuki; KOSHIBA Hitoshi; IKEUCHI Kenta
  2. The transition of brown regions: A matter of timing? By Stefano Basilico; Nils Grashof
  3. Schumpeterian Growth, Price Rigidities, and the Business Cycles By Adil Mahroug; Alain Paquet
  4. Similarities and Differences in the Adoption of General Purpose Technologies By Ajay K. Agrawal; Joshua S. Gans; Avi Goldfarb
  5. Does constructive feedback improve idea quality in idea contests? Exploring the role of hierarchy and feedback overlap By Mathias Boënne; Bart Leten; Walter Van Dyck
  6. The Science of Startups: The Impact of Founder Personalities on Company Success By Paul X. McCarthy; Xian Gong; Fabian Stephany; Fabian Braesemann; Marian-Andrei Rizoiu; Margaret L. Kern
  7. Robots and Workers: Evidence from the Netherlands By Daron Acemoglu; Hans R. A. Koster; Ceren Ozgen

  1. By: MOTOHASHI Kazuyuki; KOSHIBA Hitoshi; IKEUCHI Kenta
    Abstract: In this study, the text information of academic papers published by Japanese authors (about 1.7 million papers) and patents filed with the Japan Patent Office (about 12.3 million patents) since 1991 are used for analyzing the inter-relationship between science and technology. Specifically, a distributed representation vector using the title and abstract of each document is created, then neighboring documents to each are identified using the cosine similarity. A time trend and sector specific linkages within science and technology are identified by using the count of neighbor patents (papers) for each paper (patent). It is found that the science intensity of inventions (the number of neighbor papers for patents) increases over time, particularly for university/PRI patents and university-industry collaboration patents over the 30 years studied. As for university/PRI patents, the institutional reforms for the science sector (government laboratory incorporation in 2001 and national university incorporation in 2004) contributed to the interactions between science and technology. In contrast, the technology intensity of science (the number of neighbor patents by paper) decreases over time. It is also found that the technology intensity of life science papers is rather low, although they have a significant impact on subsequent patents. However, there are some scientific fields which are affected by technological developments, so that the state of science and innovation interactions is heterogenous across the fields.
    Date: 2023–03
  2. By: Stefano Basilico (University of Bremen, Faculty of Business Studies and Economics, and Gran Sasso Science Institute, Social Sciences); Nils Grashof (Friedrich Schiller University Jena, Faculty of Economics and Business Administration)
    Abstract: Green innovations aim to improve and reduce the environmental impact of economic activities. Thus far, research focus on the positive trajectories of green transition. Recent studies focus also on the speed of transition and on its effects on economic outcomes. Continuing in this direction we focus on brown regions (i.e. specialized in fossil-fuel technologies) and the challenges that they face to become sustainable. Taking as example German Labour Market Regions we identify brown regions and measure their transition using an innovative approach based on Social Network Analysis and Knowledge Spaces. We find that the earlier a region transitioned to green technologies, the better it is for both its social and economic outcomes. Our findings imply that the transition of brown regions has effects on socio-economic outcomes not yet accounted for in the sustainability transition literature.
    Keywords: green transition, green technologies, knowledge spaces, network embeddedness, socio-economic development
    JEL: O32 O33 R11
    Date: 2023–03–09
  3. By: Adil Mahroug (University of Quebec in Montreal); Alain Paquet (University of Quebec in Montreal)
    Abstract: Embedding Schumpeterian innovation within a New Keynesian DSGE model matters for the likelihood of innovating when making endogenous decisions about investments in R&D and the path of the technological frontier. This feature brings new challenges at the modeling and simulation stages with implications for the interactions between Schumpeterian innovation and price rigidities, and between business cycle and growth. The interplay of innovation with optimal price setting in the intermediate sector spells out how the technological frontier advances, and how more innovation leads to more price flexibility despite the existence of nominal rigidities. With a reasonable calibration, key moments and comovements of macroeconomic variables are consistent with their observed counterparts. The Schumpeterian features of the model play a role on the cyclical impacts of various standard shocks and that of a knowledge-spillover shock. Moreover, different combinations of steady-state innovation probability and extent of knowledge spillovers, for the same steady-state growth rate of the economy, have important welfare implications in consumption equivalent terms.
    Keywords: Schumpeterian endogenous growth, Innovation, Business cycles, New Keynesian dynamic stochastic general equilibrium (DSGE) model, nominal price rigidity and flexibility.
    JEL: E32 E52 O31 O33 O42
    Date: 2021–11
  4. By: Ajay K. Agrawal; Joshua S. Gans; Avi Goldfarb
    Abstract: Economic models provide little insight into when the next big idea and its associated productivity dividend will come along. Once a general purpose technology (GPT) is identified, the economist’s toolkit does provide an understanding when firms will adopt a new technology and for what purpose. The focus of the literature has been on commonalities across each type of GPT. This focus is natural, given that the goal of the literature has been to identify generalizable insights across technologies. Broadly, this literature emphasizes heterogeneity in co-invention costs across firms. Each GPT, however, provides a distinct benefit. Steam provided a new power source. The internet facilitated communication. The differences between GPTs are important for understanding adoption patterns. Using the examples of the internet and artificial intelligence, we discuss how both co-invention costs and distinct benefits determine the adoption of technology. For both technologies, we demonstrate that discussions of the impact of a GPT on productivity and growth need to emphasize the benefits as well as the costs. The goal of this paper is therefore to link the literature on co-invention costs with an understanding of the distinct benefits of each GPT.
    JEL: O33 O4
    Date: 2023–02
  5. By: Mathias Boënne; Bart Leten; Walter Van Dyck
    Abstract: To fuel the innovation process with high-quality ideas, firms are increasingly soliciting ideas from their employee workforce and involving them in idea contests. During an idea contest employees suggest ideas on a firm-internal, digital idea platform. Once submitted, idea holders can receive constructive feedback from colleagues on their ideas – which has been advanced as positive instrument for stimulating idea improvement and idea quality. Examining three firm-internal, multi-staged idea contests that generated 395 ideas from a global management consulting firm, we examine under what conditions constructive feedback positively influences idea quality. We focus on the hierarchical roles of feedback providers and receivers and the role of feedback overlap (which indicates whether feedback focuses on similar issues). We find that the effect of constructive feedback on idea quality is larger when feedback providers have a higher hierarchical rank, but that this effect does not depend on the hierarchical rank of feedback recipients. Further, we show that (partial) feedback overlap strengthens idea quality. Our results generate new insights for both idea contributing employees and innovation managers about the important role of managing feedback during idea contests.
    Date: 2023–03–07
  6. By: Paul X. McCarthy; Xian Gong; Fabian Stephany; Fabian Braesemann; Marian-Andrei Rizoiu; Margaret L. Kern
    Abstract: Startup companies solve many of today's most complex and challenging scientific, technical and social problems, such as the decarbonisation of the economy, air pollution, and the development of novel life-saving vaccines. Startups are a vital source of social, scientific and economic innovation, yet the most innovative are also the least likely to survive. The probability of success of startups has been shown to relate to several firm-level factors such as industry, location and the economy of the day. Still, attention has increasingly considered internal factors relating to the firm's founding team, including their previous experiences and failures, their centrality in a global network of other founders and investors as well as the team's size. The effects of founders' personalities on the success of new ventures are mainly unknown. Here we show that founder personality traits are a significant feature of a firm's ultimate success. We draw upon detailed data about the success of a large-scale global sample of startups. We found that the Big 5 personality traits of startup founders across 30 dimensions significantly differed from that of the population at large. Key personality facets that distinguish successful entrepreneurs include a preference for variety, novelty and starting new things (openness to adventure), like being the centre of attention (lower levels of modesty) and being exuberant (higher activity levels). However, we do not find one "Founder-type" personality; instead, six different personality types appear, with startups founded by a "Hipster, Hacker and Hustler" being twice as likely to succeed. Our results also demonstrate the benefits of larger, personality-diverse teams in startups, which has the potential to be extended through further research into other team settings within business, government and research.
    Date: 2023–02
  7. By: Daron Acemoglu; Hans R. A. Koster; Ceren Ozgen
    Abstract: We estimate the effects of robot adoption on firm-level and worker-level outcomes in the Netherlands using a large employer-employee panel dataset spanning 2009-2020. Our firm-level results confirm previous findings, with positive effects on value added and hours worked for robot-adopting firms and negative outcomes on competitors in the same industry. Our worker-level results show that directly-affected workers (e.g., blue-collar workers performing routine or replaceable tasks) face lower earnings and employment rates, while other workers indirectly gain from robot adoption. We also find that the negative effects from competitors' robot adoption load on directly-affected workers, while other workers benefit from this industry-level robot adoption. Overall, our results highlight the uneven effects of automation on the workforce.
    JEL: D63 E22 E23 E24 J24 O33
    Date: 2023–03

This nep-ino issue is ©2023 by Uwe Cantner. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.