Journal: Journal of Evolutionary Economics

Abbreviation

J Evol Econ

Publisher

Springer

Journal Volumes

ISSN

1432-1386
0936-9937

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Publications1 - 10 of 10
  • Research and development as an initiator of fixed capital investment
    Item type: Journal Article
    Spescha, Andrin; Wörter, Martin (2021)
    Journal of Evolutionary Economics
    This paper investigates the causal relationship between firms’ R&D expenditures and their investments in fixed capital. It argues that a firm’s R&D expenditures lead to inventions that in turn trigger investments in fixed capital, as the manufacturing of newly invented goods or services requires the creation of additional production capacities. Using firm-level panel data ranging from 1990 to 2014, the paper applies a 2SLS approach to uncover the direction of causality between R&D expenditures and fixed capital investment. To obtain exogenous instruments, the paper exploits shocks to i) technological opportunities and ii) innovative sales of capital goods industries. The results reveal that firms’ R&D expenditures cause subsequent investments in fixed capital, while there is no evidence of the reverse effect. An increase in R&D expenditures of 1% leads to an increase in fixed capital investments between 0.4% and 0.6%. Therefore, increasing R&D expenditures may not only be valuable for long-term economic growth but also, via fixed capital investment, provide the economy with positive stimuli in times of prolonged stagnation. (© 2020 Springer).
  • Quantifying knowledge exchange in R&D networks: A data-driven model
    Item type: Journal Article
    Vaccario, Giacomo; Tomasello, Mario V.; Tessone, Claudio J.; et al. (2018)
    Journal of Evolutionary Economics
  • Patterns in management research on artificial intelligence: A longitudinal analysis using structural topic modeling
    Item type: Journal Article
    Dahlke, Johannes; Ebersberger, Bernd (2025)
    Journal of Evolutionary Economics
    The field of management research on applied artificial intelligence (AI) is growing rapidly as the technology is maturing in industrial applications. Due to the nascent state of the scientific discourse, it is hard to discern thematic focal points or how well managerial and technical topics are integrated. Based on 10,036 publications over 25 years, we map the topic landscape of AI-related management research, longitudinal patterns of topics, and structural changes of topic networks and research communities. Our model identifies 71 unique topics, indicating a strong but myopic focus on technological capabilities and applications. The lagged response to technological paradigm shifts indicates a double pacing problem. Network structures of thematic research communities reveal increased centralization and interconnections, suggesting the field's role in transferring basic AI research to industrial implementation. However, topics in technology management of AI seem to be separated from recent advances in AI. We propose mechanisms to foster an integrative discourse on applied AI that allows management research to act as a sense-giving institution. This includes focusing on fundamental technological characteristics instead of applications and strengthening the role of journals as discourse intermediaries.
  • How do different motives for R&D cooperation affect firm performance?
    Item type: Journal Article
    Arvanitis, Spyros (2012)
    Journal of Evolutionary Economics
  • Knowledge integration between technical change and strategy making
    Item type: Journal Article
    Brusoni, Stefano; Cassi, Lorenzo; Tuna, Simge (2021)
    Journal of Evolutionary Economics
    This paper looks at the different strategies that two of the tire industry’s most prominent players, Pirelli and Michelin, deployed to exploit a radical process innovation: robotized, modular manufacturing. This paper argues that Pirelli, originally the technological follower, could develop a more nuanced, complex and ultimately successful strategy thanks to its superior knowledge integration capabilities. Empirically, we examine the structural characteristics and evolution of inventors’ networks in the two companies to reveal their knowledge integration capabilities. We apply the cohesive blocking method developed by White and Harary (Sociol Methodol 31(1):305–359, 2001) to argue that Pirelli, while relying on comparable skills in terms of technical fields, leveraged a more connected, cohesive and structured skills than Michelin. On this basis, it could develop and deploy a more complex strategy that better fit the characteristics of the new process technology. Pirelli’s knowledge network structure enhanced its knowledge integration capabilities and allowed for a more efficient fit between technology and strategy.
  • The spatial component of R&D networks
    Item type: Journal Article
    Scholl, Tobias; Garas, Antonios; Schweitzer, Frank (2018)
    Journal of Evolutionary Economics
  • Industry diversity and its impact on the innovation performance of firms
    Item type: Journal Article
    Wörter, Martin (2009)
    Journal of Evolutionary Economics
  • Equity dynamics in bargaining without information exchange
    Item type: Journal Article
    Nax, Heinrich (2015)
    Journal of Evolutionary Economics
  • Competition, R&D and Innovation: Testing the inverted-U in a simultaneous system
    Item type: Journal Article
    Peneder, Michael; Wörter, Martin (2014)
    Journal of Evolutionary Economics
    To address the relationship between innovation and competition we jointly estimate the opportunity, production, and impact functions of innovation in a simultaneous system. Based on Swiss micro-data, we apply a 3-SLS system estimation. The findings confirm a robust inverted-U relationship, in which a rise in the number of competitors at low levels of initial competition increases the firm’s research effort, but at a diminishing rate, and the research effort ultimately decreases at high levels of competition. When we split the sample by firm types, the inverted-U shape is steeper for creative firms than for adaptive ones. The numerical solution indicates three particular configurations of interest: (i) an uncontested monopoly with low innovation; (ii) low competition with high innovation; and (iii) a ‘no innovation trap’ at very high levels of competition. The distinction between solution (i) and (ii) corresponds to Arrow’s positive effect of competition on innovation, whereas the difference between outcomes (ii) and (iii) captures Schumpeter’s positive effect of market power on innovation. Simulating changes of the exogenous variables, technology potential, demand growth, firm size and exports have a positive impact on innovation, while foreign ownership has a negative effect, and higher appropriability has a positive impact on the number of competitors.
  • An evolutionary explanation of the value premium puzzle
    Item type: Journal Article
    Hens, Thorsten; Lensberg, Terje; Schenk-Hoppe, Klaus Reiner; et al. (2011)
    Journal of Evolutionary Economics
Publications1 - 10 of 10