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