Potential surprise theory as a theoretical foundation for scenario planning

Article


Derbyshire, J. 2017. Potential surprise theory as a theoretical foundation for scenario planning. Technological Forecasting and Social Change. 124, pp. 77-87. https://doi.org/10.1016/j.techfore.2016.05.008
TypeArticle
TitlePotential surprise theory as a theoretical foundation for scenario planning
AuthorsDerbyshire, J.
Abstract

Despite some recent progress, scenario planning’s development as an academic discipline remains constrained by the perception it is solely a practical tool for thinking about the future, with limited theoretical foundations. The paper addresses this issue by showing that G. L. S. Shackle’s ‘Potential Surprise Theory’ (PST) contains much that can lend theoretical support to scenario planning - especially its use of plausibility rather than probability, and its focus on potential extreme outcomes. Moreover, PST and scenario planning share the same ontology, viewing the future as constructed by the imagination of individuals. Yet, under PST, while the future is imagined and, therefore, subjective, individuals nevertheless seek to identify the ‘best’ option through a deductive process of elimination. PST therefore assists in overcoming the divide between the constructivist and deductivist perspectives in scenario planning as it employs both. Finally, the paper shows that theoretically underpinning scenario planning with PST would place it at the heart of contemporary debates on decision making under uncertainty taking place in economics and other fields, enhancing its status and profile as a discipline.

Research GroupCentre for Enterprise, Environment and Development Research (CEEDR)
LanguageEnglish
PublisherElsevier
JournalTechnological Forecasting and Social Change
ISSN0040-1625
Publication dates
Online04 Jun 2016
Print01 Nov 2017
Publication process dates
Deposited11 May 2016
Accepted09 May 2016
Output statusPublished
Publisher's version
License
Accepted author manuscript
License
Digital Object Identifier (DOI)https://doi.org/10.1016/j.techfore.2016.05.008
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