steps methods #8 mcm

STEPS Pathways Methods

PART 8

Multicriteria Mapping (MCM) - an illustrative example

Professor Andy Stirling

Co-director, STEPS Centre

www.steps-centre.org

www.sussex.ac.uk/spru

www.multicriteria-mapping.org

An Example: Multicriteria Mapping (MCM)

choose

options

MCM: what goes in

choose

options

MCM: what goes in

MCM: choosing options

choose

options

MCM: what goes in

define

criteria

MCM: defining criteria

choose

options

define

criteria

assess

scores

MCM: what goes in

choose

options

define

criteria

assess

scores

option 1

option 2

option 3

option 4

performance

CRITERION A

MCM: what goes in

choose

options

define

criteria

assess

scores

explore

uncertainty

MCM: what goes in

option 1

option 2

option 3

option 4

CRITERION A

performance

choose

options

define

criteria

assess

scores

explore

uncertainty

A

B

C

MCM: what goes in

MCM: assessing scores

choose

options

define

criteria

assess

scores

assign

weights

explore

uncertainty

performance

option 1

option 2

option 3

option 4

OVERALL RANKINGS

MCM: what goes in

choose

options

define

criteria

assess

scores

assign

weights

explore

uncertainty

performance

option 1

option 2

option 3

option 4

OVERALL RANKINGS

MCM: what goes in

choose

options

define

criteria

assess

scores

assign

weights

explore

uncertainty

performance

option 1

option 2

option 3

option 4

consider

ranks OVERALL RANKINGS

MCM: what goes in

MCM: assigning weights http://mcm.dabdev.net/projects/ec4cc0623c5f4bf09acd1febec66e5f6/engage/engagements/eadd5a2094cf419d86cd4dd99223f03e/#weights

choose

options

define

criteria

assess

scores

assign

weights

explore

uncertainty

performance

option 1

option 2

option 3

option 4

consider

ranks OVERALL RANKINGS

MCM: what goes in

O

C

S

U

W

R

From MCM sessions to opening up deliberation

From MCM sessions to opening up deliberation

From MCM sessions to opening up deliberation

group-based

elicitation or

deliberation

From MCM sessions to opening up deliberation

wider

stakeholder

deliberation

From MCM sessions to opening up deliberation

general diversity heuristic

ij (dij)α.(pi.pj)

β

Mapping Diversities SEG

Dancing with the quantification devil… what isn’t counted, doesn’t count!

Yoshizawa, Suzuki, et al

Rafols, Porter and Leydesdorff (2010)

Diversity in Scientometrics

Scientometrics of disciplinarity & directionality in research & innovation

narrow

broad

closing down opening up

expert /

analytic

participatory /

deliberative

citizen’s juries

decision

analysis

participatory

rural appraisal

stakeholder

negotiation

q-method

sensitivity

analysis

deliberative

mapping do-it-yourself

panels

open

space

cost-benefit

analysis

risk

assessment

interactive

modelling

structured

interviews

interpretive

participant

observation

multi-site

ethnographic-

methods

citizen’s juries

consensus

conference

open

hearings

dissenting

opinions

multi-criteria

mapping

scenario

workshops

Building Repertoires (from Dynamic Sustainabilities)

For “opening up new political spaces”

contending

histories

spot-the-

narrative

industry

NGOs

qualitative picture of framings, focusing

structured as ‘optimistic’ or ‘pessimistic’ expectations

(as well as: option/criteria definitions; transcript ‘nuggets’)

MCM: what comes out

optimistic assumptions about

technical operation

pessimistic view of how option

is likely to perform in practice

All annotations and discussion transcripts

entered and processed in database

Also detailed text ‘reports’ for selected parameters

rich body of background data

concerning ‘framings’ of options by perspectives

MCM: what comes out

uncertainties by option

rich body of background data

concerning ‘framings’ of options by perspectives

MCM: what comes out

A

B

C

D

uncertainties by option

rich body of background data

concerning ‘framings’ of options by perspectives

MCM: what comes out

A

B

C

D

uncertainties by perspective

academics

industry

government

NGOs

uncertainties by option

rich body of background data

concerning ‘framings’ of options by perspectives

MCM: what comes out

A

B

C

D

uncertainties by perspective

academics

industry

government

NGOs

scores for particular issues

A

B

C

D

uncertainties by option

rich body of background data

concerning ‘framings’ of options by perspectives

MCM: what comes out

A

B

C

D

uncertainties by perspective

academics

industry

government

NGOs

weights by issue for perspectives scores for particular issues

A

B

C

D

economics

health

environment

equity

academics

industry

government

NGOs

uncertainties by option

rich body of background data

concerning ‘framings’ of options by perspectives

MCM: what comes out

A

B

C

D

uncertainties by perspective

academics

industry

government

NGOs

weights by issue for perspectives scores for particular issues

A

B

C

D

economics

health

environment

equity

academics

industry

government

NGOs

improved services

altruistic donation

presumed consent

xenotransplantation

embryonic stem cells

healthier living

low performance high

MCM Results: an example from health policy

women’s panel (BC1)

improved services

altruistic donation

presumed consent

xenotransplantation

embryonic stem cells

healthier living

low performance high

MCM Results: an example from health policy

women’s panel (BC1)

improved services

altruistic donation

presumed consent

xenotransplantation

embryonic stem cells

healthier living

men’s panel (BC1)

low performance high

MCM Results: an example from health policy

women’s panel (BC1)

improved services

altruistic donation

presumed consent

xenotransplantation

embryonic stem cells

healthier living

improved services

altruistic donation

presumed consent

xenotransplantation

embryonic stem cells

healthier living

women’s panel (C2D) men’s panel (C2D)

men’s panel (BC1)

low performance high

MCM Results: an example from health policy

Risks and benefits of different agricultural strategies

under assumptions of selection of UK expert policy advisers (1999)

organic

environmental

intensive

GM + labelling

GM + monitoring

GM + voluntary controls

low performance high

MCM Results: an example from GM food

Risks and benefits of different agricultural strategies

under assumptions of selection of UK expert policy advisers (1999)

organic

environmental

intensive

GM + labelling

GM + monitoring

GM + voluntary controls

GOVERNMENT

organic

environmental

intensive

GM + labelling

GM + monitoring

GM + voluntary controls

low performance high

MCM Results: an example from GM food

Risks and benefits of different agricultural strategies

under assumptions of selection of UK expert policy advisers (1999)

organic

environmental

intensive

GM + labelling

GM + monitoring

GM + voluntary controls

GOVERNMENT INDUSTRY

organic

environmental

intensive

GM + labelling

GM + monitoring

GM + voluntary controls

low performance high

MCM Results: an example from GM food

Risks and benefits of different agricultural strategies

under assumptions of selection of UK expert policy advisers (1999)

organic

environmental

intensive

GM + labelling

GM + monitoring

GM + voluntary controls

GOVERNMENT INDUSTRY

organic

environmental

intensive

GM + labelling

GM + monitoring

GM + voluntary controls

PUBLIC INTEREST

low performance high

MCM Results: an example from GM food