Cross-Impact Balances (CIB) for Scenario Analysis: Fundamentals and Implementation

Acknowledgments
Contents
Abbreviations
List of Figures
List of Tables
Chapter 1: Introduction to CIB
References
Chapter 2: The Application Field of CIB
2.1 Scenarios
2.2 Scenarios and Decisions
2.3 Classifying CIB
References
Chapter 3: Foundations of CIB
3.1 Descriptors
3.2 Descriptor Variants
3.2.1 Completeness and Mutual Exclusivity of the Descriptor Variants
3.2.2 The Scenario Space
3.2.3 The Need for Considering Interdependence
3.3 Coping with Interdependence: The Cross-Impact Matrix
3.4 Constructing Consistent Scenarios
3.4.1 The Impact Diagram
3.4.2 Discovering Scenario Inconsistencies Using Influence Diagrams
3.4.3 Formalizing Consistency Checks: The Impact Sum
3.4.4 The Formalized Consistency Check at Work
3.4.5 From Arrows to Rows and Columns: The Matrix-Based Consistency Check
3.4.6 Scenario Construction
3.5 How to Present CIB Scenarios
3.6 Key Indicators of CIB Scenarios
3.6.1 The Consistency Value
Descriptor Consistency Values
Scenario Consistency Values
Nonconsideration of Autonomous Descriptors
Inconsistency Scale
Global Inconsistency
3.6.2 The Consistency Profile
Consistency Profile and Scenario Stability
Consistency Profile and Judgment Uncertainty
3.6.3 The Total Impact Score
3.7 Data Uncertainty
3.7.1 Estimating Data Uncertainty
3.7.2 Data Uncertainty and the Robustness of Conclusions
3.7.3 Other Sources of Uncertainty
References
Chapter 4: Analyzing Scenario Portfolios
4.1 Structuring a Scenario Portfolio
4.1.1 Perspective A: If-Then
4.1.2 Perspective B: Order by Performance
4.1.3 Perspective C: Portfolio Mapping
Scenario Axes
Using Scenario Axes Diagrams in CIB Analysis
Special form of the Scenario Axes Diagram: Probability vs. Effect
4.2 Revealing the Whys and Hows of a Scenario
4.2.1 How to Proceed
4.2.2 The Scenario-Specific Cross-Impact Matrix
4.3 Ex Post Consistency Assessment of Scenarios
4.3.1 Intuitive Scenarios
4.3.2 Reconstructing the Descriptor Field
4.3.3 Preparing the Cross-Impact Matrix
4.3.4 CIB Evaluation
4.4 Intervention Analysis
4.4.1 Analysis Example: Interventions to Improve Water Supply
4.4.2 The Cross-Impact Matrix and its Portfolio
4.4.3 Conducting an Intervention Analysis
Compilation of the Intervention Options
Testing a Proposed Intervention: E1
Testing a Proposed Intervention: A2
Robustness Check
Side Effect Control
Alternative Forms of Intervention Analysis
4.4.4 Surprise-Driven Scenarios
4.5 Expert Dissent Analysis
4.5.1 Classifying Dissent
4.5.2 Rule-Based Decisions
4.5.3 The Sum Matrix
Consensus and Dissent in the Matrix Ensemble
Evaluation of the Sum Matrix
Significance of Inconsistencies in Sum Matrices
Sum Matrix Construction in the Case of Nonuniform Rating Scales
Sum Matrix vs. Mean Value Matrix
Summary: Interpreting the Sum Matrix
4.5.4 Delphi
4.5.5 Ensemble Evaluation
Step 1: Individual Evaluation of the Expert Matrices
Step 2: Compiling the Ensemble Table
Step 3: Analyzing the Ensemble Table
Sensitivity Analysis
4.5.6 Group Evaluation
Step 1: Identification of the Key Dissent
Step 2: Grouping the Matrices Along the Key Dissent
Step 3: Group Sum Matrix Building and Evaluation
Comparing the Results of the Group Evaluation and the Ensemble Evaluation
4.6 Storyline Development
4.6.1 Strengths and Weaknesses of CIB-Based Storyline Development
4.6.2 Preparation of the Scenario-Specific Cross-Impact Matrix
4.6.3 Storyline Creation
4.7 Basic Characteristics of a CIB Portfolio
4.7.1 Number of Scenarios
Scenario Counts in Practice
Sparse Matrices: A Prerequisite for Large Scenario Portfolios
Frequency Distribution of the Inconsistency Value
4.7.2 The Presence Rate
4.7.3 The Portfolio Diversity
The Distance Table
Measuring Portfolio Diversity
Typical Diversity Scores
References
Chapter 5: What if Challenges in CIB Practice
5.1 Insufficient Number of Scenarios
5.2 Too Many Scenarios
5.2.1 Statistical Analysis
Interpreting the Frequency Data
Requirements for a Probabilistic Interpretation of Frequency Data
5.2.2 Diversity Sampling
5.2.3 Positioning Scenarios on a Portfolio Map
Method Comparison
5.2.4 Further Procedures
Cluster Analysis
Correspondence Analysis
5.3 Monotonous Portfolio
5.3.1 Unbalanced Judgment Sections
5.3.2 Unbalanced Columns
5.4 Bipolar Portfolio
5.4.1 Causes of Bipolar Portfolios
5.4.2 Special Approaches for Analyzing Bipolar Portfolios
Single Intervention
Dual Interventions
5.5 Underdetermined Descriptors
5.6 Essential Vacancies
5.6.1 Resolving Vacancies by Expanding the Portfolio
5.6.2 Cause Analysis
5.7 Context-Dependent Impacts
References
Chapter 6: Data in CIB
6.1 About Descriptors
6.1.1 Explanation of Term
6.1.2 Descriptor Types
Formal Typology: Classification by Interdependence Type
Content-Oriented Typology: Classification by Roles in Terms of Content
6.1.3 Methodological Aspects
Completeness of the Descriptor Field
Number of Descriptors
Aggregation Level
Documentation
6.2 About Descriptor Variants
6.2.1 Explanation of Term
6.2.2 Types of Descriptor Variants
State Descriptors Versus Trend Descriptors
Descriptor Variants: Scales of Measurement
Descriptor Variant Classification According to Occurrence in the Portfolio
6.2.3 Methodological Aspects
Definition
Completeness
Mutual Exclusivity
Absence of Overlap
6.2.4 Designing the Descriptor Variants
Gradation of the Descriptor Variants
Range of the Descriptor Variants: Conservative Scenarios vs. Extreme Scenarios
Plausibility of Descriptor Variants
6.3 About Cross-impacts
6.3.1 Explanation of Term
6.3.2 Methodological Aspects
Rating Interval
Empty Judgment Sections and the Omission of Very Weak Influences
Ensuring Coding Quality: Avoid Coding Indirect Influences
What Are Indirect Influences?
Why Is It a Problem to Code Indirect Influences in the Matrix Together with Direct Influences?
Implementation Hints
Ensuring Coding Quality: Avoiding Inverse Coding
Ensuring Coding Quality: Balancing Positive and Negative Cross-impacts
Comparability as a Criterion for the Coding Style
Conventions to Ensure Comparability of Cross-impact Ratings
``Standardization´´ as a Strict but also Restrictive Instrument to Balance Positive and Negative Cross-impacts
Ensuring Coding Quality: Calibrating Strength Ratings
Ensuring Coding Quality: Sign Errors and Double Negations
Ensuring Coding Quality: Predetermined Descriptors
Phantom Variants as a Cause of Bias
Ensuring Coding Quality: Absolute Cross-impacts
Avoiding Conflicts Between Absolute Cross-impacts
6.3.3 Data Uncertainty
6.4 About Data Elicitation
6.4.1 Self-Elicitation
Examples
6.4.2 Literature Review
Descriptor Screening
Descriptor Variants
Cross-impact Data
Coding Literature Quotations: An Example from Practice
Assessment
Examples
6.4.3 Expert Elicitation (Written/Online)
Descriptor Screening
Descriptor Ranking
Descriptor Variants
Cross-impact Data
Partitioning the Matrix for Expert Elicitation
Assessment
Examples
6.4.4 Expert Elicitation (Interviews)
Descriptor/Variant Screening
Cross-impact Data
Assessment
Examples
6.4.5 Expert Elicitation (Workshops)
Descriptor Screening
Descriptor Ranking
Cross-impact Data
Assessment
Number of Participants
Time Management
General Recommendations
Pretest
Combining Elicitation Methods
Iteration and Scenario Validation
Examples
6.4.6 Use of Theories or Previous Research as Data Collection Sources
Assessment
Examples
References
Chapter 7: CIB at Work
7.1 Iran Nuclear Deal
7.2 Energy and Society
7.3 Public Health
7.4 IPCC Storylines
References
Chapter 8: Reflections on CIB
8.1 Interpretations
8.1.1 Interpretation I (Time-Related): CIB in Scenario Analysis
8.1.2 Interpretation II (Unrelated to Time): CIB in Steady-State Systems Analysis
8.1.3 Interpretation III: CIB in Policy Design
8.1.4 Classification of CIB as a Qualitative-Semiquantitative Method of Analysis
8.2 Strengths of CIB
8.2.1 Scenario Quality
8.2.2 Traceability of the Scenario Consistency
8.2.3 Reproducibility and Revisability
8.2.4 Complete Screening of the Scenario Space
8.2.5 Causal Models
8.2.6 Knowledge Integration and Inter- and Transdisciplinary Learning
8.2.7 Objectivity
8.2.8 Scenario Criticism
8.3 Challenges and Limitations
8.3.1 Time Resources
8.3.2 Aggregation Level and Limited Descriptor Number
8.3.3 System Boundary
8.3.4 Limits to the Completeness of Future Exploration
8.3.5 Discrete-Valued Descriptors and Scenarios
8.3.6 Trend Stability Assumption
8.3.7 Uncertainty and Residual Subjectivity in Data Elicitation
8.3.8 Context-Sensitive Influences
8.3.9 Consistency as a Principle of Scenario Design
8.3.10 Critical Role of Methods Expertise
8.3.11 CIB Does Not Study Reality but Mental Models of Reality
8.4 Unsuitable Use Cases: A Checklist
8.5 Alternative Methods
References
Appendix: Analogies
Physics
Network Analysis
Game Theory
Glossary
Cross-impact matrix (in the context of CIB)
Portfolio (in CIB)
Scenarios (in the context of CIB)
Index