How are foresight methods selected? 论文

2008foresight引用 423
Multi-Criteria Decision MakingCognitive Science and MappingSustainable Agricultural Systems Analysis

详细信息

发表期刊/会议
foresight
发表日期
2008-10-15
发表年份
2008

关键词

Multi-Criteria Decision MakingCognitive Science and MappingSustainable Agricultural Systems Analysis

摘要

Purpose This paper addresses a challenging topic, which in both academic and professional literatures has been widely discussed but mainly from one single angle – that is, how to select foresight methods. From that point of view researchers and consultants promote (even if unintentionally) the use of particular methods. Here the question of selection is raised from a different perspective: how are foresight methods selected? Design/methodology/approach The guiding “theory” is that a better understanding of the fundamental attributes of foresight methods and their linkages to the core phases of a foresight process, together with the identification of possible patterns in the selection of methods, will provide useful insights as to how the selection of methods is carried out. Findings So far the selection of foresight methods has been dominated by the intuition, insight, impulsiveness and – sometimes – inexperience or irresponsibility of practitioners and organisers. This paper reveals that the selection of foresight methods (even if not always coherent or systematic) is a multi‐factor process, and needs to be considered as such. Practical implications The results can be utilised by lecturers and students to describe and understand better the use of foresight methods, and by organisers of foresight (including practitioners) to better inform decisions during the design of (hopefully) more coherent methodological frameworks. Originality/value The paper combines practical concepts and frameworks (such as the Foresight Process and the Foresight Diamond) with innovative analyses to represent and visualise better the combination of methods in 886 case studies, for example introducing the Methods Combination Matrix (MCM) to examine the dynamics of a mix of methods.

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