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An instrument for scenario-based technology roadmapping: How to assess the impacts of future changes on organisational plans

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  • Lee, Changyong
  • Song, Bomi
  • Park, Yongtae

Abstract

Scenario-based technology roadmapping offers a strong capability for strategic planning to respond to increasingly volatile environments. However, previous studies cannot guide organisations towards making robust decisions against complex future conditions since they remain conceptual and rely solely on graphical mapping tools. To counter this, we propose a systematic approach to making scenario-based technology roadmapping more robust by adding the ability to assess the impacts of future changes on organisational plans. At the heart of the suggested approach is a Bayesian network that can examine uncertainty inherent in future changes and ripple impacts resulting from interdependence among activities. The proposed approach is designed to be executed in three discrete steps: defining a roadmap topology and causal relationships via qualitative and quantitative modelling; assessing the impacts of future changes on organisational plans via current state analysis and sensitivity analysis; and finally managing plans and activities via development of plan assessment map and activity assessment map. A case study of photovoltaic cell technology is presented to show the feasibility of our method. We believe the systematic process and quantitative outcomes the suggested approach offers can facilitate responsive technology planning in the face of future uncertainties.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:tefoso:v:90:y:2015:i:pa:p:285-301
    DOI: 10.1016/j.techfore.2013.12.020
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    References listed on IDEAS

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    1. Baesens, Bart & Verstraeten, Geert & Van den Poel, Dirk & Egmont-Petersen, Michael & Van Kenhove, Patrick & Vanthienen, Jan, 2004. "Bayesian network classifiers for identifying the slope of the customer lifecycle of long-life customers," European Journal of Operational Research, Elsevier, vol. 156(2), pages 508-523, July.
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    4. Shin, Juneseuk & Park, Yongtae, 2007. "Building the national ICT frontier: The case of Korea," Information Economics and Policy, Elsevier, vol. 19(2), pages 249-277, June.
    5. Lee, Changyong & Cho, Yangrae & Seol, Hyeonju & Park, Yongtae, 2012. "A stochastic patent citation analysis approach to assessing future technological impacts," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 16-29.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. repec:eee:tefoso:v:138:y:2019:i:c:p:127-138 is not listed on IDEAS
    7. Amankwah-Amoah, Joseph, 2016. "Emerging economies, emerging challenges: Mobilising and capturing value from big data," MPRA Paper 85625, University Library of Munich, Germany.

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