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Robust Plans and Contingent Plans

Author

Listed:
  • Arnab Chakraborty
  • Nikhil Kaza
  • Gerrit-Jan Knaap
  • Brian Deal

Abstract

Problem: The practice of scenario planning is often too focused on developing a single preferred scenario and fails to adequately consider multiple uncertain futures. The U.S. Department of Housing and Urban Development recently awarded grants for scenario planning at regional and metropolitan scales that further promote this practice. However, a lack of systematic analysis of uncertainty limits the role of scenario planning. Purpose: The purpose of this article is to demonstrate how to incorporate uncertainty into large-scale scenario analysis and then use that framework to identify contingent and robust plans. Methods: We adapt the concepts of controllable internal options and uncontrollable external forces and consider their interactions in order to develop future scenarios and identify contingent and robust decisions. We then apply this technique using advanced econometric, land use, and transportation models developed for the Baltimore–Washington metropolitan region and its vicinity. Finally, based on the results of a hypothetical, yet plausible, exercise, we show how contingent and robust decisions can help local and regional governments develop contingent and robust plans. Results and conclusions: Scenarios developed as a combination of internal options and external forces allow us to identify a wider range of future impacts than in traditional metropolitan scenario planning. Robust plans support choices that offer benefits across scenarios. Contingent plans can be tailored to specific futures. Takeaway for practice: By providing a way to think systematically about uncertainty, scenario analysis promises to improve the efficacy of large-scale planning. Research support: This article was not directly supported by any outside agency, but support for the modeling system was provided by the following organizations: Maryland State Highway Administration, Maryland Department of Transportation, Maryland Department of Planning, U.S. Environmental Protection Agency, and Lincoln Institute of Land Policy.

Suggested Citation

  • Arnab Chakraborty & Nikhil Kaza & Gerrit-Jan Knaap & Brian Deal, 2011. "Robust Plans and Contingent Plans," Journal of the American Planning Association, Taylor & Francis Journals, vol. 77(3), pages 251-266.
    • Handle: RePEc:taf:rjpaxx:v:77:y:2011:i:3:p:251-266
    DOI: 10.1080/01944363.2011.582394
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    Citations

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    Cited by:

    1. Yexuan Gu & Brian Deal & Linda Larsen, 2018. "Geodesign Processes and Ecological Systems Thinking in a Coupled Human-Environment Context: An Integrated Framework for Landscape Architecture," Sustainability, MDPI, vol. 10(9), pages 1-24, September.
    2. Justice Mensah, 2020. "Improving Quality Management in Higher Education Institutions in Developing Countries through Strategic Planning," Asian Journal of Contemporary Education, Asian Economic and Social Society, vol. 4(1), pages 9-25, June.
    3. Lingli Li & Jinjie Wang & Chaoxian Yang & Chaofu Wei, 2021. "Implementation Process of General Land-Use Planning and Its Adjustment—A Case Study of Rongchang District in Chongqing, China," IJERPH, MDPI, vol. 18(11), pages 1-24, May.
    4. Rozanne Spijkerboer, "undated". "The use of scenario planning as a tool in US public spatial planning practice," NEURUS papers neurusp185, NEURUS - Network of European and US Regional and Urban Studies.
    5. Arnab Chakraborty, 2012. "Recognizing Uncertainty and Linked Decisions in Public Participation: A New Framework for Collaborative Urban Planning," Systems Research and Behavioral Science, Wiley Blackwell, vol. 29(2), pages 131-148, March.
    6. Pan, Meiyu (Melrose) & Wong, Stephen & Tainter, Francis & Woelfel, Steve & Ryan, Alyssa, 2024. "Integrating equity in transportation scenario planning: A systematic review," Transport Policy, Elsevier, vol. 145(C), pages 85-95.
    7. Rifat, Shaikh Abdullah Al & Liu, Weibo, 2022. "Predicting future urban growth scenarios and potential urban flood exposure using Artificial Neural Network-Markov Chain model in Miami Metropolitan Area," Land Use Policy, Elsevier, vol. 114(C).
    8. Erfani, Goran & Roe, Maggie, 2020. "Institutional stakeholder participation in urban redevelopment in Tehran: An evaluation of decisions and actions," Land Use Policy, Elsevier, vol. 91(C).
    9. Bev Wilson & Arnab Chakraborty, 2013. "The Environmental Impacts of Sprawl: Emergent Themes from the Past Decade of Planning Research," Sustainability, MDPI, vol. 5(8), pages 1-26, August.
    10. Marisa A Zapata & Nikhil Kaza, 2015. "Radical uncertainty: scenario planning for futures," Environment and Planning B, , vol. 42(4), pages 754-770, July.
    11. Zipan Cai & Bo Wang & Cong Cong & Vladimir Cvetkovic, 2020. "Spatial dynamic modelling for urban scenario planning: A case study of Nanjing, China," Environment and Planning B, , vol. 47(8), pages 1380-1396, October.
    12. Youjung Kim & Galen Newman & Burak Güneralp, 2020. "A Review of Driving Factors, Scenarios, and Topics in Urban Land Change Models," Land, MDPI, vol. 9(8), pages 1-22, July.
    13. Mercy Serwah Owusu Ansah & Emmanuel Oppong Peprah, 2022. "The Link between Stakeholder Engagement and Strategic Planning in the Ghana Forestry Sector: A Systematic Literature Review," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 6(5), pages 907-914, May.

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