IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v111y2016icp164-175.html
   My bibliography  Save this article

Towards robust technology roadmapping: How to diagnose the vulnerability of organisational plans

Author

Listed:
  • Lee, Changyong
  • Kim, Juram
  • Lee, Sungjoo

Abstract

While technology roadmapping has been the subject of many previous studies, a general lack of attention to the issues of uncertainty exists, thus leading to difficulties in consensus-building in the follow-up activity phase of technology roadmapping. To counter this, we propose a systematic approach to diagnosing the vulnerability of organisational plans against complex future conditions. For this, first, field anomaly relaxation (FAR) is employed to generate and evaluate future scenarios in a structured manner. Second, analytic network process (ANP) is used to measure the ripple impacts of activities on organisational plans by considering the interaction between activities. Lastly, a vulnerability assessment map is developed to provide a comprehensive and balanced view of organisational plans. The systematic process and quantitative outcomes the proposed approach offers will assist robust technology roadmapping in the face of growing uncertainties associated with the future. A case study of the organisational plan for developing home security systems is presented.

Suggested Citation

  • Lee, Changyong & Kim, Juram & Lee, Sungjoo, 2016. "Towards robust technology roadmapping: How to diagnose the vulnerability of organisational plans," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 164-175.
    • Handle: RePEc:eee:tefoso:v:111:y:2016:i:c:p:164-175
    DOI: 10.1016/j.techfore.2016.06.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162516301317
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2016.06.022?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. Margherita Pagani, 2009. "Roadmapping 3G mobile TV : Strategic thinking and scenario planning through repeated cross-impact handling," Post-Print hal-02313094, HAL.
    2. Lee, Changyong & Song, Bomi & Park, Yongtae, 2015. "An instrument for scenario-based technology roadmapping: How to assess the impacts of future changes on organisational plans," Technological Forecasting and Social Change, Elsevier, vol. 90(PA), pages 285-301.
    3. T Ritchey, 2006. "Problem structuring using computer-aided morphological analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(7), pages 792-801, July.
    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. Chakraborty, Swagata & Nijssen, Edwin J. & Valkenburg, Rianne, 2022. "A systematic review of industry-level applications of technology roadmapping: Evaluation and design propositions for roadmapping practitioners," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    2. Kheybari, Siamak & Rezaie, Fariba Mahdi & Farazmand, Hadis, 2020. "Analytic network process: An overview of applications," Applied Mathematics and Computation, Elsevier, vol. 367(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. de Alcantara, Douglas Pedro & Martens, Mauro Luiz, 2019. "Technology Roadmapping (TRM): a systematic review of the literature focusing on models," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 127-138.
    2. Cho, Yonghee & Yoon, Seong-Pil & Kim, Karp-Soo, 2016. "An industrial technology roadmap for supporting public R&D planning," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 1-12.
    3. Panula-Ontto, Juha, 2019. "The AXIOM approach for probabilistic and causal modeling with expert elicited inputs," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 292-308.
    4. Cheng, M.N. & Wong, Jane W.K. & Cheung, C.F. & Leung, K.H., 2016. "A scenario-based roadmapping method for strategic planning and forecasting: A case study in a testing, inspection and certification company," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 44-62.
    5. Panula-Ontto, Juha & Luukkanen, Jyrki & Kaivo-oja, Jari & O'Mahony, Tadhg & Vehmas, Jarmo & Valkealahti, Seppo & Björkqvist, Tomas & Korpela, Timo & Järventausta, Pertti & Majanne, Yrjö & Kojo, Matti , 2018. "Cross-impact analysis of Finnish electricity system with increased renewables: Long-run energy policy challenges in balancing supply and consumption," Energy Policy, Elsevier, vol. 118(C), pages 504-513.
    6. Saba Sareminia & Alireza Hasanzadeh & Shaaban Elahi & Gholamali Montazer, 2019. "Developing Technology Roadmapping Combinational Framework by Meta Synthesis Technique," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(02), pages 1-36, April.
    7. Amankwah-Amoah, Joseph, 2016. "Emerging economies, emerging challenges: Mobilising and capturing value from big data," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 167-174.
    8. Cheng, Yu & Huang, Lucheng & Ramlogan, Ronnie & Li, Xin, 2017. "Forecasting of potential impacts of disruptive technology in promising technological areas: Elaborating the SIRS epidemic model in RFID technology," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 170-183.
    9. Soon Goo Hong & DonHee Lee, 2023. "Development of a citizen participation public service innovation model based on smart governance," Service Business, Springer;Pan-Pacific Business Association, vol. 17(3), pages 669-694, September.
    10. Kemp-Benedict, Eric & Carlsen, Henrik & Kartha, Sivan, 2019. "Large-scale scenarios as ‘boundary conditions’: A cross-impact balance simulated annealing (CIBSA) approach," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 55-63.
    11. Basma Hamrouni & Abdelhabib Bourouis & Ahmed Korichi & Mohsen Brahmi, 2021. "Explainable Ontology-Based Intelligent Decision Support System for Business Model Design and Sustainability," Sustainability, MDPI, vol. 13(17), pages 1-28, September.
    12. Ram, Camelia, 2020. "Scenario presentation and scenario generation in multi-criteria assessments: An exploratory study," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    13. Raele, Ricardo & Boaventura, João Mauricio Gama & Fischmann, Adalberto Américo & Sarturi, Greici, 2014. "Scenarios for the second generation ethanol in Brazil," Technological Forecasting and Social Change, Elsevier, vol. 87(C), pages 205-223.
    14. Hansen, Christoph & Daim, Tugrul & Ernst, Horst & Herstatt, Cornelius, 2016. "The future of rail automation: A scenario-based technology roadmap for the rail automation market," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 196-212.
    15. Lee, Changyong, 2021. "A review of data analytics in technological forecasting," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    16. Yuskevich, Ilya & Hein, Andreas Makoto & Amokrane-Ferka, Kahina & Doufene, Abdelkrim & Jankovic, Marija, 2021. "A metamodel of an informational structure for model-based technology roadmapping," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    17. Yu, Xiang & Zhang, Ben, 2019. "Obtaining advantages from technology revolution: A patent roadmap for competition analysis and strategy planning," Technological Forecasting and Social Change, Elsevier, vol. 145(C), pages 273-283.
    18. Jannie Coenen & Rob van der Heijden & Allard C. R. van Riel, 2019. "Making a Transition toward more Mature Closed-Loop Supply Chain Management under Deep Uncertainty and Dynamic Complexity: A Methodology," Sustainability, MDPI, vol. 11(8), pages 1-27, April.
    19. Hussain, M. & Tapinos, E. & Knight, L., 2017. "Scenario-driven roadmapping for technology foresight," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 160-177.
    20. J S Edwards & B Ababneh & M Hall & D Shaw, 2009. "Knowledge management: a review of the field and of OR's contribution," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 114-125, May.

    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:111:y:2016:i:c:p:164-175. 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.