nep-ino New Economics Papers
on Innovation
Issue of 2020‒10‒12
eight papers chosen by
Uwe Cantner
University of Jena

  1. The Emergence of Knowledge Production in New Places By Christopher R. Esposito; ;
  2. Latent Technology as an Outcome of R&D By Cunningham, James; Link, Albert
  3. "In knowledge we trust: learning-by-interacting and the productivity of inventors" By Matteo Tubiana; Ernest Miguelez; Rosina Moreno
  4. Technology evolution in the global automotive industry: a patent-based analysis By Alessandra Perri; Daniela Silvestri; Francesco Zirpoli
  5. Unleashing Innovative Power. Solving cognitive, social and geographic distance issues with informal institutional proximity By Cathrin Sollner; Dirk Fornahl;
  6. Bridging Technologies in the Regional Knowledge Space: Measurement and Evolution By Stefano Basilico; Holger Graf
  7. Labor Supply and Automation Innovation By Alexander M. Danzer; Carsten Feuerbaum; Fabian Gaessler
  8. When robots do (not) enhance job quality: The role of innovation regimes By Damiani, Mirella; Pompei, Fabrizio; Kleinknecht, Alfred

  1. By: Christopher R. Esposito; ;
    Abstract: This article studies how new locations emerge as advantageous places for the creation of ideas. Analysis of a novel patent-based dataset that traces the flow of knowledge between inventions and across time reveals that inventors initiate knowledge production in new places through a three-stage process. In the first stage, about 50 years before knowledge production in a region reaches an appreciable volume, local inventors begin to experiment with a few promising ideas developed in other places. In the second stage, inventors use the promising ideas developed elsewhere to create a large number of highly impactful inventions locally. In the third stage, inventors source high-impact ideas from their local environs and produce an even larger number of inventions, albeit of lower quality. Overall knowledge production in regions peaks in this third stage, but novelty and the potential for future knowledge growth decline.
    Keywords: Regional development, innovation, knowledge transmission, agglomeration
    JEL: O33 R12
    Date: 2020–09
  2. By: Cunningham, James (Northumbira University); Link, Albert (University of North Carolina at Greensboro, Department of Economics)
    Abstract: This paper focuses on a situation in which a firm decides to sell its non-commercialized technology to another firm rather than commercialize it (a latent entrepreneurial firm), and the other firm then adopts the appearance of an emergent entrepreneur. Using U.S. project data from firms funded through the U.S. Small Business Innovation Research (SBIR) program, we find using a qualitative choice model that firms that do not commercialize their newly developed SBIR-funded technology have a greater probability of selling their technology to another firm than do firms that do commercialize. We also identify other covariates with the probability that such a firm will sell their technology.
    Keywords: Latent entrepreneurship; Emergent entrepreneurship; SBIR; Commercialization;
    JEL: O32 O33 O38
    Date: 2020–09–29
  3. By: Matteo Tubiana (University of Bergamo); Ernest Miguelez (GREThA UMR CNRS 5113 - Université de Bordeaux); Rosina Moreno (AQR-IREA Research Group, University of Barcelona. Department of Econometrics, Statistics and Applied Economics. Av. Diagonal 690, 08034 Barcelona, Spain)
    Abstract: Innovation rarely happens through the actions of a single person. Innovators source their ideas while interacting with their peers, at different levels and with different intensities. In this paper, we exploit a dataset of disambiguated inventors in European cities to assess the influence of their interactions with co-workers, organizations’ colleagues, and geographically co-located peers, to understand if the different levels of interaction influence their productivity. Following inventors’ productivity over time and adding a large number of fixed effects to control for unobserved heterogeneity, we uncover critical facts, such as the importance of city knowledge stocks for inventors’ productivity, with firm knowledge stocks and network knowledge stocks being of smaller importance. However, when the complexity and quality of knowledge is accounted for, the picture changes upside down and closer interactions (individuals’ co-workers and firms’ colleagues) become way more important.
    Keywords: Inventors, Productivity, Stock of knowledge, Interactions. JEL classification: O18, O31, O33, O52, R12.
    Date: 2020–09
  4. By: Alessandra Perri (Department of Management, Università Ca' Foscari Venice); Daniela Silvestri (Department of Management, Università Ca' Foscari Venice); Francesco Zirpoli (Department of Management, Università Ca' Foscari Venice)
    Abstract: This study explores the evolution of the knowledge base of the automotive industry. Over the last decades, the industry has experienced major changes. New and originally unrelated fields have increasingly become relevant shaping over time the knowledge base of the industry. Using data on patent families granted in the period 1990-2014, we map the knowledge base of the automotive industry by reconstructing and analyzing the patenting portfolio of the top firms operating in this industry. The analysis documents exploration in new technical fields as well as persistence in industry-specific technical areas, pointing to the relevance of core competences that might be difficult to accumulate for industry outsiders.
    Keywords: knowledge base evolution, automotive industry, patent analysis
    JEL: L62 O34
    Date: 2020–09
  5. By: Cathrin Sollner; Dirk Fornahl;
    Abstract: Literature nowadays claims that innovation is no longer an only ‘one-organization-show’ but that more and more organizations conduct innovative activities in collaboration. To collaborate successfully, cognitive, social, geographic and institutional distances have to be bridged. Especially interesting is the moderating impact of informal institutions, as being at the basis of every human interaction. However, an extensive investigation is still missing. Therefore, the present research makes a first step in closing this research gap, revealing that informal institutional distances are like a diverse puzzle not to be underestimated, as each of the dimensions has different effects on different forms of distances.
    Keywords: research collaboration; informal institutional distance; proximity interactions; patent quality
    JEL: D91 R11 R12
    Date: 2020–09
  6. By: Stefano Basilico (Friedrich Schiller University Jena, Faculty of Economics and Business Administration); Holger Graf (Friedrich Schiller University Jena, Faculty of Economics and Business Administration)
    Abstract: The concept of Bridging Technologies (BTs) refers to technologies which are important for the regional knowledge base by connecting different fields and thereby enabling technological development. We provide analytical tools to identify BTs and study their evolution over time. We apply these tools on several levels. Our findings indicate that large patenting regions are not necessarily the ones that embed most new technologies in their Knowledge Space (KS). Our findings reveal that the German KS became less dependent on important technologies, such as transport, machinery and chemicals over the period 1995-2015. Changes in the German KS in terms of the development of new BTs are due to a regionally dispersed process rather than driven by single regions.
    Keywords: Knowledge Spaces, Network Analysis, Bridging Technology, Revealed Relatedness, GPT, Centrality
    JEL: O33 O34 R11
    Date: 2020–09–10
  7. By: Alexander M. Danzer (KU Eichstaett-Ingolstadt, IZA Bonn, CReAM, CESifo); Carsten Feuerbaum (KU Eichstaett-Ingolstadt , Max Planck Institute); Fabian Gaessler (Max Planck Institute)
    Abstract: While economic theory suggests substitutability between labor and capital, little evidence exists regarding the causal effect of labor supply on inventing labor-saving technologies. We analyze the impact of exogenous changes in regional labor supply on automation innovation by exploiting an immigrant placement policy in Germany during the 1990s and 2000s. Difference-in-differences estimates indicate that one additional worker per 1,000 manual and unskilled workers reduces automation innovation by 0.05 patents. The effect is most pronounced two years after immigration and confined to industries containing many low-skilled workers. Labor market tightness and external demand are plausible mechanisms for the labor-innovation nexus.
    Keywords: Labor supply, automation, innovation, patents, labor market tightness, quasi-experiment
    JEL: O31 O33 J61
    Date: 2020–07
  8. By: Damiani, Mirella; Pompei, Fabrizio; Kleinknecht, Alfred
    Abstract: Whether robots have a positive or negative impact on job quality and wages depends on the dominant innovation regime in an industry. In an innovation regime with a high cumulativeness of knowledge, i.e. if accumulation of (tacit) knowledge from experience (embodied by workers) is important for innovation, robots enhance the probability that workers will get permanent (other than temporary) contracts and they earn higher wages. The opposite holds for industries with a low-cumulativeness regime when innovation depends mainly on general (and generally available) knowledge. Our results emerge from multi-level estimates of two countries (Italy and Germany), combining sectoral data on robot use with person-level data on properties of workers. Our results imply that previous studies tended to find weak effects of robotization as they did not control for innovation regimes. An implication for European industrial policy is that the hiring of more flexible personnel (and shorter job tenures) that has become popular in the period of supply-side economics is likely to have a negative impact on the productive use of robot technology in industries with a high cumulativeness of knowledge, and less so in low-cumulativeness industries. Unqualified pleas for labour market deregulation can have a problematic impact on technology and should be reconsidered.
    Keywords: robots, quality of work, innovation regimes, knowledge cumulativeness
    JEL: J3 J5 M5 O3
    Date: 2020–09–21

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