Enhancing Horizon Scanning by utilizing pre-developed scenarios: analysis of current practice and specification of a process improvement to aid the identification of important 'weak signals'

Article


Rowe, E., Wright, G. and Derbyshire, J. 2017. Enhancing Horizon Scanning by utilizing pre-developed scenarios: analysis of current practice and specification of a process improvement to aid the identification of important 'weak signals'. Technological Forecasting and Social Change. 125, pp. 224-235. https://doi.org/10.1016/j.techfore.2017.08.001
TypeArticle
TitleEnhancing Horizon Scanning by utilizing pre-developed scenarios: analysis of current practice and specification of a process improvement to aid the identification of important 'weak signals'
AuthorsRowe, E., Wright, G. and Derbyshire, J.
Abstract

This paper documents the Intuitive Logics scenario planning process and its relationship with horizon scanning activity in order to evaluate the separate and joint usefulness of these methods for anticipating the future. The specific objectives of this paper are to: (i) identify and differentiate scenario planning and horizon scanning methodologies (ii) discuss & evaluate their analytic underpinnings, and (iii) critically appraise their separate and combined value and effectiveness in relation to enhancing organizational preparedness for the future. Our analysis culminates with specifications to (iv) enhance the identification of ’weak signals’ in Horizon Scanning by utilizing a systematically broadened range of both negatively-valenced and positively-valenced scenario storylines.

Research GroupCentre for Enterprise, Environment and Development Research (CEEDR)
LanguageEnglish
PublisherElsevier
JournalTechnological Forecasting and Social Change
ISSN0040-1625
Publication dates
Online23 Aug 2017
Print01 Dec 2017
Publication process dates
Deposited08 Aug 2017
Accepted01 Jul 2017
Output statusPublished
Publisher's version
License
Accepted author manuscript
License
Digital Object Identifier (DOI)https://doi.org/10.1016/j.techfore.2017.08.001
Permalink -

https://repository.mdx.ac.uk/item/871y5

  • 12
    total views
  • 5
    total downloads
  • 2
    views this month
  • 1
    downloads this month

Export as