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Björheden Rolf, PhD.

Development of Bioenergy from Forest Biomass – a Case Study of Sweden and Finland

volume: 38, issue: 2

Multi-Criteria Decision Analysis (MCDA) in Forest Operations – an Introductional Review

volume: 40, issue: 1

Decision making in forestry is very complex and requires consideration of trade-offs among
economic, environmental, and social criteria. Different multi-criteria decision analysis
(MCDA) methods have been developed for structuring and exploring the decision-making
process of such problems. Although MCDA methods are often used for forest management
problems, they are rarely used for forest operation problems. This indicates that scholars and
practitioners working with forest operations are either unaware of MCDA methods, or see no
benefit in using these methods. Therefore, the prime objective of this review was to make
MCDA methods more intelligible (compared with current level of understanding) to novice
users within the field of forest operations. For that purpose, basic ideas as well as the strengths
and limitations of selected MCDA methods are presented. The second objective was to review
applications of MCDA methods in forest operations. The review showed that MCDA applications
are suitable for forest operation problems on all three planning levels – strategic, tactical,
and operational – but with least use on the operational level. This is attributed to: 1) limited
availability of temporally relevant and correct data, 2) lack of time (execution of MCDA
methods is time consuming), and 3) many operational planning problems are solved with
regards to an economic criterion, with other criteria serving more as frames. However, with
increased importance of environmental and social aspects, incorporating MCDA methods into
the decision-making process on the operational planning horizon (e.g., by developing MCDAbased
guidelines for forestry work) is essential.

Publishers:
Copublishers:

Web of Science Impact factor (2023): 2.7
Five-years impact factor: 2.3

Quartile: Q1 - Forestry

Subject area

Agricultural and Biological Sciences

Category/Quartile

Forestry/Q1