cross-impact analysis

Designed by

Michael Braito

Marianne Penker

CROSS-IMPACT ANALYSIS for

KNOWLEDGE INTEGRATION

Put here your name, details of the workshop, etc.

Outline

1. Sustainable development by Knowledge

Integration

2. Knowledge Integration – Why and how?

3. The CROSS-IMPACT Analysis

Theoretical introduction

4. The Cross-Impact Analysis (Step 1 – 3)

Step 1: Defining the boundaries

Step 2: Identifying the driving forces

Step 3: Analysing the driving forces

participatory process

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by Michael Braito, Marianne Penker 2

Thinking of tomorrow for a sustainable development!

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The delegates at the RIO+20 acknowledged the importance of strengthening transdisciplinary cooperation in order to enhance sustainable development. by Michael Braito, Marianne Penker 3

Why is this so crucial for sustainable development?

1. Each discipline is important!

2. Concentrating on one subject is failing in seeing other aspects.

3. Learning from each other …

4. … to recognize the big picture.

Sustainable development can only be reached if human beings work together.

KNOWLEDGE INTEGRATION

• Decisions in the field of sustainable development have to be taken in the context of uncertain and incomplete knowledge.

• A systematic integration of a range of research-informed judgments, expertise from different disciplines and experiencebased knowledge is often the best way forward.

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Methods of Knowledge Integration

• In interdisciplinary research and transdisciplinary knowledge

“integration, the focus of the dialogue process is on a research question and the process aims to enable the formation of a combined judgment between the participants, with that judgment being informed by the best research evidence” (McDonald et al. 2009).

• Several methods for dialogue/participatory processes exist (see

McDonald et al. 2009), for instance:

– Citizens’ jury,

– Conference,

– Delphi technique,

– Open space technology,

– CROSS-IMPACT ANALYSIS

.

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KNOWLEDGE

INTEGRATION

WHY and HOW!?

The complexity of today and tomorrow

Our world, our socio-economic system is changing rapidly and unpredictable.

A number of issues follow their own future path, but at the same time, they interact not only with each other but with any number of … macroeconomic regulatory

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The problem of limited points of views

• To analyse complex systems we reduce the complexity.

• In doing this, we tend to stop gathering detail and select one path forward that seems the most likely one.

macroeconomic regulatory

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Knowledge Integration – dealing with unknowns/uncertainties

• Integrating knowledge from different disciplines helps “to sketch a broad spectrum of possible development options” (Penker and

Wytrzens 2005) .

• “A necessary adjunct to complexity is uncertainty” (Bammer 2006, 98) .

Knowledge Integration by the Cross-Impact Analysis supports to:

• capture the uncertainties,

• highlight the issues that may have a significant impact on others, and

• to study the relationships between these critical issues.

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The

CROSS-IMPACT ANALYSIS

CROSS-IMPACT ANALYSIS I

“Cross-Impact methods are mostly used for analytical tasks which do not allow the use of theory-based computational models due to their disciplinary heterogeneity and the relevance of system knowledge, but on the other hand are too complex for a purely argumentative systems analysis” (Weimer-Jehle 2005, 334) .

“This is a technique […], taking into account the causality among relevant events, based on experts’ judgments” (Hayashi 2006, 1064)

.

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CROSS-IMPACT ANALYSIS II

Fields of application

• If the problem requires cross discipline analysis

• If a system/research question can only be analysed qualitatively

Systematic approach

• Assessing the interdependencies of the driving forces in pairs

• Production of a Cross-Impact matrix as a system description

(Weimer-Jehle 2010, 1)

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AIMS of the CROSS-IMPACT ANALYSIS

• Knowledge Integration (explicit scientific knowledge and implicit local knowledge)

• Following the approach of ‘intuitive logics ’ (Jungermann and Thuring 1987)

See the sense of complexity and ambiguity in terms of possibility and plausibility.

• Exploring the interrelationships between multiple factors in terms of cause/effect and chronology

Realise that the possibilities are not unlimited.

• Not predicting the future, but understanding the present

• Developing an information framework for decision making

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AIM of System Intervention

• Initiate a process of understanding (future is unpredictable and unknown).

• Highlight and understand possibilities for action (despite partial uncertainty).

• Enhance openness for new ways instead of moving always on the worn-out paths.

• Exercise to deal with the unknown, the unforeseeable.

• Identify different interests, assessments, expectations.

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Three steps for system analysis

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STEP 1

Defining the boundaries

Boundaries of the analysed system

• Set the objectives.

• Define boundaries and establish focus.

• The objectives for the exemplary project should include the following:

1. Thematic framework,

2. Time horizon, and

3. Geographical scope of the project/system.

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STEP 2

Identifying the driving forces

What are ‘driving forces’?

• Driving forces are attributes of a system which are most relevant at the present and cause changes in the system state over time

(e.g. social, economic, environmental, political, and technological).

• Main key factors facing the research topic

• Driving forces are NOT PROBLEMS

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• Changes in society, politics, technology etc. are often the symptoms of more fundamental transformations.

• Driving forces are indicating change, but should not indicate direction or dimension.


Methods to identify driving forces I

Identification of a MAXIMUM of 10-12 driving forces

Different methods exist:

• Systemic picture (all together or as a “World Café”)

• Brainstorming/Brainwriting by using cards

• etc.

Leading question:

Which factors are influencing the present and might have a significant impact on the development of the exemplary system/ research question?

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Methods to identify driving forces II

Systemic picture

(all together or as a “World Café”)

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Methods to identify driving forces III

Brainstorming/Brainwriting by using cards

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Feedback

Integrate scientific knowledge with participants’ knowledge

• Literature research

• Empirical research

– Field work

– Interviews

– Delphi Method

– etc.

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STEP 3

Analysing the driving forces

Analysis of the driving forces by the


1. The Cross-Impact

MATRIX

2. The Cross-Impact

GRID

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What is the impact/influence of DF1 on DF2, …?

Impact on from

DF 1

DF 2

DF 3

DF 4

Passive sum PS

DF 1 DF 2

0

1

3

4

3

1

3

7

DF 3

1

7

3

3

DF 4

1

2

2

5

Active sum AS

4

7

7

5

0 = no or weak impact

If DF 1 changes strongly,

impact on DF 2 is very weak

1 = weak or timely delayed impact


impact on DF 2 is very weak

2 = medium impact


impact on DF 2 is medium

3 = strong or very strong impact


impact on DF 2B is strong or very strong

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Identify the most active/passive driving forces

Active respectively impulsive driving

forces (high AS and low PS) the driving force has more impact on other driving forces and is less influenced by other driving forces. Such driving forces are called effective “levers” or “switches” if they are controllable driving forces which can be steered.

Reactive respectively passive driving forces

(high PS and low AS) the driving force is more influenced by other driving forces and has got less impact on other driving forces. These driving forces are good indicators for the observation of a situation.

Critical respectively dynamic driving

forces (high AS and high PS) the driving force is influenced strongly by other driving forces but has a high impact on other driving forces as well. These driving forces are linked to other driving forces and have to be kept in focus.

Buffering respectively slow driving forces

(low AS and low PS) the driving force hardly influences other driving forces and other driving forces have low impact on the driving force itself.

These driving forces are hardly linked with other driving forces but rather isolated.

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The Cross-Impact GRID

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System analysis

Discussion of the most actively impacting and most passively influenced driving forces.

Critical assessment by using the initial reasons for the different judgements.

Key questions

• How do the driving forces interact?

• What impact do they have on other forces?

• Where and how can we intervene?

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Enjoy integrating knowledge

References

Bammer, G., 2006. Integration and Implementation Sciences: Building a New Specialisation. In Perez,

P. and Batten, D (eds.). Complex Science for a Complex World. Australia: ANU E Press, The

Australian National University Australia. 95-107.

Blanninga, R.W. and Reinig B.A., 1999. Cross-impact analysis using group decision support systems: an application to the future of Hong Kong. Futures. 31. 39–56.

Hayashi, A., Tokimatsu, K., Yamamoto, H. and Mori, S., 2006. Narrative scenario development based on cross-impact analysis for the evaluation of global-warming mitigation options. Applied Energy,

83, 1062–1075.

Jungermann, H. and Thuring, M. 1987. The use of mental models for generating scenarios. In Wright,

G. and Ayton, P. (eds.), Judgmental Forecasting. London: Wiley.

Maack, J. 2001. Scenario Analysis: A Tool for Task Managers.

McDonald, D., Bammer, G. and Deane, P., 2009. Research IntegratIon using dialogue methods.

Australia: ANU E Press, The Australian National University Australia.

Penker, M. and Wytrzens, H.K., 2005. Scenario for the Austrian food chain in 2020 and its landscape impacts. Landscape and Urban Planning. 71. 175-189.

Weimer-Jehle, W. 2005. Cross-impact balances: A system-theoretical approach to cross-impact analysis. Technological Forecasting & Social Change, 73, 334–361.

Weimer-Jehle, W. 2010. Introduction to qualitative systems and scenario analysis using cross-impact balance analysis. Stuttgart, ZIRN.

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Institute for Sustainable Economic Development

Department of Economics and Social Sciences

BOKU University of Natural Resources and Life Sciences, Vienna

Feistmantelstr. 4, 1180 Vienna, Austria http://www.wiso.boku.ac.at/2797.html?&L=1

Michael Braito

Expertise

• Environmental economics and environmental policy

• Sustainable development

• Rural development

• Optimisation and valuation of managerial processes

• Analysis and economic valuation of societal processes

Marianne Penker

Expertise

• Rural development

• Implementation Research

• Property Rights

• Rural Governance

• Landscape Governance

• Conservation and Environmental Policy

cross-impact analysis

KNOWLEDGE INTEGRATION

participatory process

Thinking of tomorrow for a sustainable development!

KNOWLEDGE

INTEGRATION

WHY and HOW!?

The