1. CROSS-IMPACT ANALYSIS for
by Michael Braito, Marianne Penker
Designed by
Michael Braito
Marianne Penker
CROSS-IMPACT ANALYSIS for
KNOWLEDGE INTEGRATION
Analysing a complex question/system should follow a systematic process to integrate disperse knowledge.
Put here your name,
details of the workshop,
etc.

2. by Michael Braito, Marianne Penker
Outline
Sustainable development by Knowledge Integration
Knowledge Integration – Why and how?
The CROSS-IMPACT Analysis
Theoretical introduction
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
by Michael Braito, Marianne Penker

3. by Michael Braito, Marianne Penker
Thinking of tomorrow for a sustainable development!
Starting point to underline the importance of knowledge integration, in order to enhance sustainable development.
The delegates at the RIO+20 acknowledged the importance of strengthening transdisciplinary cooperation in order to enhance sustainable development.
by Michael Braito, Marianne Penker

4. Why is this so crucial for sustainable development?
by Michael Braito, Marianne Penker
Why is this so crucial for sustainable development?
Each discipline is important!
Concentrating on one subject is failing in seeing other aspects.
Learning from each other …
… 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 experience- based knowledge is often the best way forward.
Explain, why we have to think transdisciplinary.
Sustainable development can only be reached, if …
Knowledge Integration (KI) is a way to think globally.
KI is the process of fitting our ideas – our theories of “how-the-world-works" – together into a coherent structure.
“Research integration is the process of improving the understanding of real-world problems by synthesising relevant knowledge from diverse disciplines and stakeholders” (McDonald et al. 2009).
by Michael Braito, Marianne Penker

5. Methods of Knowledge Integration
by Michael Braito, Marianne Penker
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.
Problems:
Isolated disciplinary knowledge
Uncertainty and unknowns
Not enough time to do all research necessary to inform decision makers
Solution:
Expert assessment based on inter- and transdisciplinary Knowledge Integration
by Michael Braito, Marianne Penker

6. KNOWLEDGE INTEGRATION WHY and HOW!?
by Michael Braito, Marianne Penker
KNOWLEDGE INTEGRATION WHY and HOW!?
The next section is used to:
Introduce the challenges we face when integrating knowledge from different disciplines, in order to think of tomorrow,
Show the need of thinking of tomorrow.

7. The complexity of today and tomorrow
by Michael Braito, Marianne Penker
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 …
macro-economic
political
rural
etc.
ecological
techno-logical
social
regulatory
regional
Complexity has many dimensions, including an extensive array of factors, with both linear and nonlinear connections and interdependencies and a range of relevant political, cultural, disciplinary and sectoral perspectives. In addition, geographical and temporal scales can be huge (Bammer 2006, 98).
by Michael Braito, Marianne Penker

8. 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.
macro-economic
political
rural
ecological
techno-logical
social
regulatory
regional
etc.
These limited points of views may become a straitjacket, not allowing us to see the big picture.
by Michael Braito, Marianne Penker

9. Knowledge Integration – dealing with unknowns/uncertainties
by Michael Braito, Marianne Penker
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.
“A necessary adjunct to complexity is uncertainty. In dealing with any complex issue or problem, there will always be many unknowns, including facts, causal and associative relationships, and effective interventions. Some unknowns result from resource limitations on research and some result from methodological limitations, while some things are simply unknowable” (Bammer 2006, 98).
“The unknowns are compounded by constant change, occurring on many fronts including biological evolution (for example, the development of new communicable diseases); scientific, technological and economic developments; changes in international relations; and manifold intended and unintended consequences of local, national and international policy and programs” (Bammer 2006, 98).
The main information available to deal with this uncertainty is the personal judgement of practitioners and experts (Penker and Wytrzens 2005).
by Michael Braito, Marianne Penker

10. The CROSS-IMPACT ANALYSIS
by Michael Braito, Marianne Penker
The CROSS-IMPACT ANALYSIS
The Cross-Impact method was originally developed by Theodore Gordon and Olaf Helmer in The method resulted from a simple question: can forecasting be based on perceptions about how future events may interact?
Cross-Impact Analysis “[…] is particularly used when conducting analyses which, owing to their disciplinary heterogeneity and the relevance of ‘soft’ system knowledge, do not permit the application of quantitative prognosis models and yet remain too complex for intuitive systems analysis“ (Weimer-Jehle 2010, 1).

11. 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).
We know from experience that most events and developments are in some way related to other events and developments.
by Michael Braito, Marianne Penker

12. 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)
by Michael Braito, Marianne Penker

13. AIMS of the CROSS-IMPACT ANALYSIS
by Michael Braito, Marianne Penker
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.
Summary of the main aims of Knowledge Integration by using the Cross-Impact Analysis:
It helps to raise awareness of future problems.
It helps to develop a common definition of desirable factors.
It allows discussions between different social groups regarding obstacles in the way towards a future worth living.
It allows to identify and discuss the differences and similarities of problems and solutions as perceived by different groups of participants.
It supports attempts to work out solutions together.
Not predicting the future, but understanding the present
Developing an information framework for decision making
by Michael Braito, Marianne Penker

14. AIM of System Intervention
by Michael Braito, Marianne Penker
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.
by Michael Braito, Marianne Penker

15. Three steps for system analysis
by Michael Braito, Marianne Penker
Three steps for system analysis
The participatory process to implement the Cross-Impact Analysis follows three steps.
by Michael Braito, Marianne Penker

16. CROSS-IMPACT ANALYSIS STEP 1 Defining the boundaries
by Michael Braito, Marianne Penker
CROSS-IMPACT ANALYSIS STEP 1 Defining the boundaries
Step 1 is prepared by the trainee in advance, in order to start immediately with identifying the driving forces (to start the Knowledge Integration process).

17. Boundaries of the analysed system
by Michael Braito, Marianne Penker
Boundaries of the analysed system
Set the objectives.
Define boundaries and establish focus.
The objectives for the exemplary project should include the following:
AIM of STEP 1:
Setting the objectives is the essential starting point for Knowledge Integration, in order to define boundaries and establish the focus of the exemplary system.
The objectives of the example must be clearly stated and agreed with the participants.
IMPLEMENTATION in the workshop:
Prepare the example in advance – the topic.
Explain that normally this crucial step should be done with all participants together.
Assure that all participants have a common understanding of the example.
Thematic framework,
Time horizon, and
Geographical scope of the project/system.
by Michael Braito, Marianne Penker

18. CROSS-IMPACT ANALYSIS STEP 2 Identifying the driving forces
by Michael Braito, Marianne Penker
CROSS-IMPACT ANALYSIS STEP 2 Identifying the driving forces
The preparatory step for carrying out the Cross-Impact Analysis is collecting and choosing the most important factors which have a significant direct or indirect influence on the system (Weimer-Jehle 2005, 338).

19. What are ‘driving forces’?
by Michael Braito, Marianne Penker
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
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.
This first step can be crucial to the success of the exercise. Any driving force for the system not included, will be completely excluded from the study.
Example of driving forces for the research question of “Migration”:
Labour market,
Housing market,
Life-style,
Infrastructure,
Accessibility,
etc.
by Michael Braito, Marianne Penker

20. Methods to identify driving forces I
by Michael Braito, Marianne Penker
Methods to identify driving forces I
Identification of a MAXIMUM of 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?
Decision on the right method to identify the driving forces depends on the number/characteristics of the participants.
by Michael Braito, Marianne Penker

21. Methods to identify driving forces II
by Michael Braito, Marianne Penker
Methods to identify driving forces II
Systemic picture
(all together or as a “World Café”)
Drawing a systemic picture is another brainstorming method that helps participants to see the complexity of the related topic.
The leading question is placed in the middle of the poster. Each participant suggests driving forces and the group decides (led by the moderator) where to place this driving force. Some driving forces are interrelated and can be linked with others. As a result the group gets a picture of the underlying system.
For the “World Café” see:
by Michael Braito, Marianne Penker

22. Methods to identify driving forces III
by Michael Braito, Marianne Penker
Methods to identify driving forces III
Brainstorming/Brainwriting
by using cards
Brainstorming encourages participants, in pairs or groups, to make large numbers of suggestions about driving forces with no restrictions on the extent to which creativity and imagination can be applied. These suggestions can then be collated, combined, expanded, refined and prioritised as appropriate.
Brainwriting is a similar technique to Brainstorming. Participants work in small groups. Questions are posed and individuals generate as many suggestions of driving forces as possible. Those suggestions are then passed on to the next person who uses them as a trigger for their own ideas. You can use plain paper or flip charts on the wall to collect the answers, with each sheet or chart collecting.
by Michael Braito, Marianne Penker

23. by Michael Braito, Marianne Penker
Feedback
Integrate scientific knowledge with participants’ knowledge
Literature research
Empirical research
Field work
Interviews
Delphi Method
etc.
After the small group work the trainee gives feedback to the whole group. He/she is doing this by giving his/her input from scientific knowledge.
Reduce the number of driving forces by discussing them with the participants to a feasible number of maximum 8 driving forces.
The inclusion of driving forces that are not pertinent can complicate the analysis unnecessarily. Since the number of driving forces pair interactions to be considered is equal to n2-n (where n is the number of driving forces), the number of interactions to be considered increases rapidly as the number of driving forces increases.
Brainstorm about the driving forces and agree upon the impact and likelihood of each driver. Consider that each driving force might follow a single, certain as well as multiple, uncertain paths in the future.
Discussion:
Use a blank poster/flip chart to summarise the groups’ results.
Ask the groups if they have different/more driving forces.
The result is a comprehensive list of driving forces.
by Michael Braito, Marianne Penker

24. CROSS-IMPACT ANALYSIS STEP 3 Analysing the driving forces
by Michael Braito, Marianne Penker
CROSS-IMPACT ANALYSIS STEP 3 Analysing the driving forces
The next step consists of developing a matrix containing judgments which express the influence of each descriptor on each one of the other descriptors (Weimer-Jehle 2005, 339).

25. Analysis of the driving forces by the CROSS-IMPACT ANALYSIS
by Michael Braito, Marianne Penker
Analysis of the driving forces by the CROSS-IMPACT ANALYSIS
The Cross-Impact MATRIX
The Cross-Impact GRID
“Analysing the driving forces needs a various of different knowledge and requires transdisciplinary thinking. It is a logical exercise based on rigorously thinking through the forces and trends already noted and identifying the ones that are most important for the decision” (Maack 2001, 71).
In this workshop the Cross-Impact Analysis is used. The core consists of the Cross-Impact MATRIX, which allows to construct the Cross-Impact GRID.
Other methods to analyse DFs exist:
Ranking1
Controllability
Relevance/Uncertainty-Matrix2
In another module designed by the authors (SCENARIO PROCESS) methods 1 and 2 are presented.
by Michael Braito, Marianne Penker

26. What is the impact/influence of DF1 on DF2, …?
from
DF 1
DF 2
DF 3
DF 4
Active sum AS 3 1 7 2 5 4
Passive sum PS
DF = Driving force
Each participant is judging by himself about the impact of each driving force to the others. Alternatively filling out the Cross-Impact sheet is possible to be done in small groups of 2-3 participants.
The diagonal of the Cross-Impact matrix is left empty because the above stated Cross-Impact question is senseless for diagonal elements.
As Blanninga and Reining (1999, 39) state, there are two possible problems when conducting this method with a group or experts:
“First, in some political environments people may be reluctant to discuss the events openly. Second, the subjective probability estimates may violate the laws of probability theory … .”
Therefore, each participant should get the possibility to judge about the cross-impact of each driving force anonymously.
Use the excel-file Cross Impact Analysis (Template) and print one empty sheet for each participant or each small group in advance.
0 = no or weak impact
If DF 1 changes strongly, impact on DF 2 is very weak
1 = weak or timely delayed impact
2 = medium impact
If DF 1 changes strongly, impact on DF 2 is medium
3 = strong or very strong impact
If DF 1 changes strongly, impact on DF 2B is strong or very strong
by Michael Braito, Marianne Penker

27. 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.
After collecting all Cross-Impact sheets, transfer all numbers of the participants to the worksheets of the excel-file. Use for each participant one worksheet in the excel-file.
As a result the excel-file shows in the first two worksheet (CIA-mean, CIA-standard deviation) the mean values as well as the standard deviation of all participants.
Show the results either by using the beamer or by printing the worksheets at the venue.
Interpretation of the Cross-Impact MATRIX:
The colour highlights those parts, where participants’ judgment was different (high standard deviation). Discuss the reasons of different judgments with the participants. Be aware, that each opinion is as important and right as any other.
by Michael Braito, Marianne Penker

28. by Michael Braito, Marianne Penker
The Cross-Impact GRID
Interpretation of the Cross-Impact GRID
The most interesting driving forces are those in the right upper corner  flexible variables. They are actively influencing the system as well as they are passively influenced by the other driving forces of the system.
The active variables are the most important driving forces in case you want to influence the system. Manipulating those driving forces may have a significant impact on the system.
The passive variables are good indicators for the system and show if the system is functioning well or not.
The inflexible variables are buffering the system, they are not influencing other driving forces as well as they are not very much influenced by others.
by Michael Braito, Marianne Penker

29. by Michael Braito, Marianne Penker
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?
The discussion of the system has not to follow a certain path!
The trainee may decide from time to time, which kind of discussion he/she prefers (depends on the participants, on the nature of Knowledge Integration etc.)
Suggestions:
Ask participants to give explicit reasons for their judgments. So “… differences between the participant judgments become obvious and can be discussed and that even for experienced participants a new point of view can be created and their understanding of the system can be consolidated” (Weimer-Jehle 2005, 339).
In sound cases judgements may be revised.
Once checked and if necessary improved, the Cross-Impact matrix is analysed again.
Discuss and interpret with the group the results and formulate them in terms of the aims defined at the outset and make recommendations concerning their application (Weimer-Jehle 2010, 7).
by Michael Braito, Marianne Penker

30. Enjoy integrating knowledge

31. by Michael Braito, Marianne Penker
References
Bammer, G., 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
Blanninga, R.W. and Reinig B.A., Cross-impact analysis using group decision support systems: an application to the future of Hong Kong. Futures –56.
Hayashi, A., Tokimatsu, K., Yamamoto, H. and Mori, S., 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 The use of mental models for generating scenarios. In Wright, G. and Ayton, P. (eds.), Judgmental Forecasting. London: Wiley.
Maack, J Scenario Analysis: A Tool for Task Managers.
McDonald, D., Bammer, G. and Deane, P., Research IntegratIon using dialogue methods. Australia: ANU E Press, The Australian National University Australia.
Penker, M. and Wytrzens, H.K., Scenario for the Austrian food chain in 2020 and its landscape impacts. Landscape and Urban Planning
Weimer-Jehle, W Cross-impact balances: A system-theoretical approach to cross-impact analysis. Technological Forecasting & Social Change, 73, 334–361.
Weimer-Jehle, W Introduction to qualitative systems and scenario analysis using cross-impact balance analysis. Stuttgart, ZIRN.
by Michael Braito, Marianne Penker

32. 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
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