Forthcoming articles

International Journal of Foresight and Innovation Policy

International Journal of Foresight and Innovation Policy (IJFIP)

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International Journal of Foresight and Innovation Policy (2 papers in press)

Regular Issues

  • FISHBONE DIAGRAM FOR TECHNOLOGICAL ANALYSIS AND FORESIGHT   Order a copy of this article
    by Mario Coccia 
    Abstract: Fishbone diagram is a graphical technique to show the several causes of a specific event. Fishbone diagram is applied here as a novel graphical representation to identify, explore and analyse the source and evolution of innovation and especially General Purpose Technologies (GPTs). Firstly, the study here shows the driving forces of GPTs, such as: higher democratization, high investment in R&D, etc. Secondly, these drivers of GPTs and in gen-eral of new technology are represented with fishbone diagram for the technological analysis. Some examples are given by applying the Fishbone diagram to specific GPTs, such as steam engine and Information and Communication Technologies (ICTs). Overall, then, fishbone diagram seems to be an appropriate and general technique of graphical representation for the technological analysis and foresight of path-breaking innovation in society.
    Keywords: Fishbone Diagram; General Purpose Technology; Technological Foresight; Sources of Innovation; Technological Evolution; New Technology; Technological Analysis.

  • Innovation Networks: An agent-based model
    by Juan Gabriel Brida, Sergio Palomeque 
    Abstract: This study develops an Agent Based Model which seeks to analyse the innovation network of an economic sector that is intensive in highly trained human resources. This sector is composed by agents that face a restriction to the incorporation of new capital, and have the possibility to choose the proportion of its available capital devoted to each of the two available goods. These agents have a menu of three strategies to seek to innovate, and thus increase their productivity. The adjustment of these strategies is done endogenously and results in a process that determines the structure of the innovation network. The consideration of public policies in the system leads to the conclusion that the effect of policies depends heavily on the specific population to which they are directed. These results are manifested both in the performance of the system and in the network structure that emerges from the evolution of the model. Acknowledgments: A preliminary version of this work was presented at the Workshop “Economic Dynamics: Theory and applications”, UdelaR - Montevideo (Uruguay), 23 -25 November 2016, the XXVIII EAEPE Conference, Manchester- UK; the X MEIDE Conference Montevideo - Uruguay and the XXXVIII Sunbelt Conference, Utrecht - Netherlands. Detailed comments of an anonymous referee on an earlier draft have been extremely helpful. Our research was supported by CSIC-UDELAR (project ‘Grupo de investigación en Dinámica Económica’; ID 881928 and Programa de iniciación a la investigación ID 261).
    Keywords: Agent Based Models, Network Innovation, Complex Systems, Public Policies