IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v141y2019icp289-304.html
   My bibliography  Save this article

The theory of technological parasitism for the measurement of the evolution of technology and technological forecasting

Author

Listed:
  • Coccia, Mario

Abstract

How to measure the evolution of technology in order to predict innovations that grow rapidly? This study suggests a new perspective based on the theory of technological parasitism, which can measure and assess the dynamics of technological evolution for technological forecasting. In particular, the evolution of technology is modelled here in terms of interaction between a host technology (system) and a parasitic technology (subsystem). The coefficient of evolutionary growth of the model here indicates the evolution of parasitic technology in relation to host technology, suggesting the evolutionary pathway of overall system of technology over time (i.e., underdevelopment, growth and development). This approach is illustrated with realistic examples using empirical data of of product and process technologies: farm tractor, freight locomotive, electricity generation and smartphone technology. Overall, then, the proposed model, based on the theory of technological parasitism, can be useful for bringing a new perspective to explain and generalize properties of the evolution of technology and predict which innovations are likely to evolve rapidly in society.

Suggested Citation

  • Coccia, Mario, 2019. "The theory of technological parasitism for the measurement of the evolution of technology and technological forecasting," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 289-304.
  • Handle: RePEc:eee:tefoso:v:141:y:2019:i:c:p:289-304
    DOI: 10.1016/j.techfore.2018.12.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S004016251830581X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2018.12.012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Daim, Tugrul U. & Yoon, Byung-Sung & Lindenberg, John & Grizzi, Robert & Estep, Judith & Oliver, Terry, 2018. "Strategic roadmapping of robotics technologies for the power industry: A multicriteria technology assessment," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 49-66.
    2. Hall, Bronwyn H. & Jaffe, Adam B., 2018. "Measuring Science, Technology, and Innovation: A Review," Annals of Science and Technology Policy, now publishers, vol. 2(1), pages 1-74, March.
    3. Mario Coccia, 2018. "Optimization in R&D intensity and tax on corporate profits for supporting labor productivity of nations," The Journal of Technology Transfer, Springer, vol. 43(3), pages 792-814, June.
    4. Farmer, J. Doyne & Lafond, François, 2016. "How predictable is technological progress?," Research Policy, Elsevier, vol. 45(3), pages 647-665.
    5. Georgy Levit & Uwe Hossfeld & Ulrich Witt, 2011. "Can Darwinism be “Generalized” and of what use would this be?," Journal of Evolutionary Economics, Springer, vol. 21(4), pages 545-562, October.
    6. Béla Nagy & J Doyne Farmer & Quan M Bui & Jessika E Trancik, 2013. "Statistical Basis for Predicting Technological Progress," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-7, February.
    7. Sandén, Björn A. & Hillman, Karl M., 2011. "A framework for analysis of multi-mode interaction among technologies with examples from the history of alternative transport fuels in Sweden," Research Policy, Elsevier, vol. 40(3), pages 403-414, April.
    8. Mario COCCIA, 2018. "Theorem of not independence of any technological innovation," Journal of Economics Bibliography, KSP Journals, vol. 5(1), pages 29-35, March.
    9. Giovanni Dosi, 2000. "Sources, Procedures, and Microeconomic Effects of Innovation," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 2, pages 63-114, Edward Elgar Publishing.
    10. Magee, C.L. & Basnet, S. & Funk, J.L. & Benson, C.L., 2016. "Quantitative empirical trends in technical performance," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 237-246.
    11. Coccia, Mario, 2018. "A Theory of the General Causes of Long Waves: War, General Purpose Technologies, and Economic Change," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 287-295.
    12. Geoffrey M. Hodgson, 2002. "Darwinism in economics: from analogy to ontology," Journal of Evolutionary Economics, Springer, vol. 12(3), pages 259-281.
    13. Coccia, Mario, 2015. "General sources of general purpose technologies in complex societies: Theory of global leadership-driven innovation, warfare and human development," Technology in Society, Elsevier, vol. 42(C), pages 199-226.
    14. Christian Schubert, 2014. "“Generalized Darwinism” and the quest for an evolutionary theory of policy-making," Journal of Evolutionary Economics, Springer, vol. 24(3), pages 479-513, July.
    15. William D. Nordhaus, 1996. "Do Real-Output and Real-Wage Measures Capture Reality? The History of Lighting Suggests Not," NBER Chapters, in: The Economics of New Goods, pages 27-70, National Bureau of Economic Research, Inc.
    16. Watanabe, Chihiro & Kanno, Genryo & Tou, Yuji, 2012. "Inside the learning dynamism inducing the resonance between innovation and high-demand consumption: A case of Japan's high-functional mobile phones," Technological Forecasting and Social Change, Elsevier, vol. 79(7), pages 1292-1311.
    17. Timothy F. Bresnahan & Robert J. Gordon, 1996. "The Economics of New Goods," NBER Books, National Bureau of Economic Research, Inc, number bres96-1.
    18. Chun-Chieh Wang & Hui-Yun Sung & Mu-Hsuan Huang, 2016. "Technological evolution seen from the USPC reclassifications," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 537-553, May.
    19. J. W. Stoelhorst, 2008. "The explanatory logic and ontological commitments of generalized Darwinism," Journal of Economic Methodology, Taylor & Francis Journals, vol. 15(4), pages 343-363.
    20. Richard Nelson, 2006. "Evolutionary social science and universal Darwinism," Journal of Evolutionary Economics, Springer, vol. 16(5), pages 491-510, December.
    21. Hodgson, Geoffrey M. & Knudsen, Thorbjorn, 2006. "Why we need a generalized Darwinism, and why generalized Darwinism is not enough," Journal of Economic Behavior & Organization, Elsevier, vol. 61(1), pages 1-19, September.
    22. Carranza, Juan Esteban, 2010. "Product innovation and adoption in market equilibrium: The case of digital cameras," International Journal of Industrial Organization, Elsevier, vol. 28(6), pages 604-618, November.
    23. Ulrich, Karl, 1995. "The role of product architecture in the manufacturing firm," Research Policy, Elsevier, vol. 24(3), pages 419-440, May.
    24. Wright, Gavin, 1997. "Towards a More Historical Approach to Technological Change," Economic Journal, Royal Economic Society, vol. 107(444), pages 1560-1566, September.
    25. Rosenberg, Nathan, 1969. "The Direction of Technological Change: Inducement Mechanisms and Focusing Devices," Economic Development and Cultural Change, University of Chicago Press, vol. 18(1), pages 1-24, Part I Oc.
    26. Pistorius, C. W. I. & Utterback, J. M., 1997. "Multi-mode interaction among technologies," Research Policy, Elsevier, vol. 26(1), pages 67-84, March.
    27. Geoffrey Hodgson & Thorbjørn Knudsen, 2008. "In search of general evolutionary principles: Why Darwinism is too important to be left to the biologists," Journal of Bioeconomics, Springer, vol. 10(1), pages 51-69, April.
    28. Coccia, Mario, 2012. "Driving forces of technological change in medicine: Radical innovations induced by side effects and their impact on society and healthcare," Technology in Society, Elsevier, vol. 34(4), pages 271-283.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kanungo, Rama Prasad & Gupta, Suraksha & Patel, Parth & Prikshat, Verma & Liu, Rui, 2022. "Digital consumption and socio-normative vulnerability," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    2. Coccia, Mario, 2020. "Deep learning technology for improving cancer care in society: New directions in cancer imaging driven by artificial intelligence," Technology in Society, Elsevier, vol. 60(C).
    3. Mirzadeh Phirouzabadi, Amir & Savage, David & Blackmore, Karen & Juniper, James, 2020. "The evolution of dynamic interactions between the knowledge development of powertrain systems," Transport Policy, Elsevier, vol. 93(C), pages 1-16.
    4. Ghazinoory, Sepehr & Nasri, Shohreh & Afshari-Mofrad, Masoud & Taghizadeh Moghadam, Negin, 2023. "National Innovation Biome (NIB): A novel conceptualization for innovation development at the national level," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    5. Alam, Gazi Mahabubul & Asimiran, Soaib, 2021. "Online technology: Sustainable higher education or diploma disease for emerging society during emergency—comparison between pre and during COVID-19," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    6. Mario Coccia, 2021. "Evolution and structure of research fields driven by crises and environmental threats: the COVID-19 research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9405-9429, December.
    7. Shi, Baisheng & Wang, Hao, 2023. "An AI-enabled approach for improving advertising identification and promotion in social networks," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    8. Koopo Kwon & Sungchan Jun & Yong-Jae Lee & Sanghei Choi & Chulung Lee, 2022. "Logistics Technology Forecasting Framework Using Patent Analysis for Technology Roadmap," Sustainability, MDPI, vol. 14(9), pages 1-30, April.
    9. Daehyoun Choi & Hind R’bigui & Chiwoon Cho, 2021. "Candidate Digital Tasks Selection Methodology for Automation with Robotic Process Automation," Sustainability, MDPI, vol. 13(16), pages 1-18, August.
    10. Godart, Frédéric & Pistilli, Luca, 2024. "The multifaceted concept of disruption: A typology," Journal of Business Research, Elsevier, vol. 170(C).
    11. Lee, Changyong, 2021. "A review of data analytics in technological forecasting," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    12. Liu, Jun & Chang, Huihong & Forrest, Jeffrey Yi-Lin & Yang, Baohua, 2020. "Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    13. Coccia, Mario, 2019. "Why do nations produce science advances and new technology?," Technology in Society, Elsevier, vol. 59(C).
    14. Candiani, Juan Antonio & Gilsing, Victor & Mastrogiorgio, Mariano, 2022. "Technological entry in new niches: Diversity, crowding and generalism," Technovation, Elsevier, vol. 116(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mario Coccia, 2019. "Technological Parasitism," Papers 1901.09073, arXiv.org.
    2. Christian Schubert, 2009. "Darwinism in Economics and the Evolutionary Theory of Policy-Making," Papers on Economics and Evolution 2009-10, Philipps University Marburg, Department of Geography.
    3. Coccia, Mario, 2020. "Deep learning technology for improving cancer care in society: New directions in cancer imaging driven by artificial intelligence," Technology in Society, Elsevier, vol. 60(C).
    4. Zhang, Guanglu & McAdams, Daniel A. & Shankar, Venkatesh & Darani, Milad Mohammadi, 2017. "Modeling the evolution of system technology performance when component and system technology performances interact: Commensalism and amensalism," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 116-124.
    5. Singh, Anuraag & Triulzi, Giorgio & Magee, Christopher L., 2021. "Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description," Research Policy, Elsevier, vol. 50(9).
    6. Spagano, Salvatore, 2021. "Generalized Darwinism: An Auxiliary Hypothesis," MPRA Paper 108829, University Library of Munich, Germany.
    7. Jan Schnellenbach, 2015. "Does classical liberalism imply an evolutionary approach to policy-making?," Journal of Bioeconomics, Springer, vol. 17(1), pages 53-70, April.
    8. Dosi, Giovanni & Grazzi, Marco & Mathew, Nanditha, 2017. "The cost-quantity relations and the diverse patterns of “learning by doing”: Evidence from India," Research Policy, Elsevier, vol. 46(10), pages 1873-1886.
    9. Rahmeyer Fritz, 2013. "Schumpeter, Marshall, and Neo-Schumpeterian Evolutionary Economics: A Critical Stocktaking," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 233(1), pages 39-64, February.
    10. Sylvie Geisendorf, 2009. "The economic concept of evolution: self-organization or Universal Darwinism?," Journal of Economic Methodology, Taylor & Francis Journals, vol. 16(4), pages 377-391.
    11. Fritz Rahmeyer, 2010. "A Neo-Darwinian Foundation of Evolutionary Economics. With an Application to the Theory of the Firm," Discussion Paper Series 309, Universitaet Augsburg, Institute for Economics.
    12. Anuraag Singh & Giorgio Triulzi & Christopher L. Magee, 2020. "Technological improvement rate estimates for all technologies: Use of patent data and an extended domain description," Papers 2004.13919, arXiv.org.
    13. Ríos-Núñez, Sandra M. & Coq-Huelva, Daniel & García-Trujillo, Roberto, 2013. "The Spanish livestock model: A coevolutionary analysis," Ecological Economics, Elsevier, vol. 93(C), pages 342-350.
    14. Thomas Grebel, 2011. "Innovation and Health," Books, Edward Elgar Publishing, number 14375.
    15. Triulzi, Giorgio & Alstott, Jeff & Magee, Christopher L., 2020. "Estimating technology performance improvement rates by mining patent data," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    16. Mario Coccia, 2017. "Disruptive technologies and competitive advantage of firms in dynamic markets," IRCrES Working Paper 201704, CNR-IRCrES Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY - former Institute for Economic Research on Firms and Growth - Torino (TO) ITALY.
    17. Liu, Jun & Chang, Huihong & Forrest, Jeffrey Yi-Lin & Yang, Baohua, 2020. "Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    18. Heinrich, Torsten, 2016. "The Narrow and the Broad Approach to Evolutionary Modeling in Economics," MPRA Paper 75797, University Library of Munich, Germany.
    19. Georgy Levit & Uwe Hossfeld & Ulrich Witt, 2011. "Can Darwinism be “Generalized” and of what use would this be?," Journal of Evolutionary Economics, Springer, vol. 21(4), pages 545-562, October.
    20. Mario Coccia, 2018. "Measurement of the evolution of technology: A new perspective," Papers 1803.08698, arXiv.org.

    More about this item

    Keywords

    Measurement of technology; Technometrics; Technological evolution; Technological change; Coevolution; Nature of technology; Host technology; Parasitic technology; Technological parasitism; Technological innovation; Technological forecasting; Technology assessment; Technological progress;
    All these keywords.

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:141:y:2019:i:c:p:289-304. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.