Uncertainty in Strategic Decision Making: Analysis, Categorization, Causation and Resolution

✍ Scribed by Richard J. Arend

• Publisher: Palgrave Macmillan
• Year: 2024
• Tongue: English
• Leaves: 466
• Category: Library

✦ Synopsis

Knight (1921) defines uncertainty as an informational market failure that, while being detrimental to most existing businesses, presents possible profitable opportunities for others. This book builds upon that classic work by providing an analysis of the alternative approaches to strategic decision-making under such uncertainty. It covers what uncertainty is, why it is important, and what connections it has to business and related fields, culminating in a new and comprehensive typology and a valuable guide for how to appropriately address various types of uncertainties, even under AI.

It clarifies the current terminological and categorical confusion about ‘unknowns’ while complementing the mathematical, probability-based approaches that treat uncertainty as ‘knowable’ (i.e., as risk). It corrects the mistaken approaches that treat ‘unknowables’ as ‘shapeable’ or ‘discoverable’. This book widens the perspective for viewing uncertainty, in terms of its impacts across humanity, byoffering a shrewder understanding of what roles uncertainties play in human activity. It will appeal to academics across business, economics, philosophy, and other disciplines looking for approaches to apply, test, and hone for dealing with decision-making under uncertainty.

✦ Table of Contents

Acknowledgments
Contents
List of Figures
List of Tables
1 Overview of This Book on Strategic Decision-Making Under Uncertainty
Why This Book on Uncertainty?
Notable Takes on Uncertainty
Further Preliminaries
More Notable Takes on Uncertainty
Uncertainty as Good or Bad or Both?
Examples of the Bads of Uncertainty
Examples of the Goods of Uncertainty
Effective Management of Uncertainty
Our Perspective (Business-Based, Applying Western/Democratic Values)
Delineation from Risk (and Probability)
Hence, Non-Mathematicalness
The Heterogeneity of Uncertainty
Decision-Making and Knowns
Creating the Decision-Making Model
Complications
Big Questions
Philosophy of Science
Goals
Resistance (…Is Eventually Futile)
Why This Book Now
Plan of Analysis
References
2 Confusion over Uncertainty in Decision-Making
Why Clarity Is Important
What Confusion Exists
What Terms Are Confused
Sources of Confusion
How to Unconfuse
References
3 Definitions of Uncertainty (for Decision-Making)
Why Definitional Precision Is Important
Classic Definitions
Uncertainty as the Inability to Assign Probabilities
Uncertainty as Unknown Cause-and-Effect Relationships
Uncertainty-as-Unpredictability
Knight’s Definition of Uncertainty
Ellsberg’s Definition of Ambiguity
Alternative Definitions of Uncertainty
Uncertainty as Unknowability
Uncertainty as Novelty
Uncertainty as Non-Optimizability
Uncertainty as Doubt
Contrasts to Full Information
The Amount of Uncertainty Question
The Epistemological Question
References
4 Sources of Uncertainty (in Decision-Making)
Why the Causes of Uncertainties are Important
Reminder—How a Cause’s Symptoms Can Manifest in a Decision to Make it Non-Optimizable
Sources of Uncertainty Related to the Problem Itself
Sources in the Problem Characteristics
Novelty/Uniqueness
Complexity of Phenomena
Non-linear Dynamic Systems and Chaos
Ill-Defined Problems
Relationships with Time
Other (Pointed) Issues
Sources in the Problem’s External Context (Exogenous to the Decision-Maker)
New Technology
The Inherent Randomness of Nature
Luck [as Randomness for Humans]
Inconsistent (Often Rivalrous) External Human Behaviors
Dynamic Aspects of Inconsistent External Human Behaviors (as Unpredictable Reactions)
Conflicting External Reports
Sources in the Problem’s Internal Context (Endogenous to the Decision-Maker)
Change and Its Consequences (Inside)
Communications Issues
Personal Artefacts and Choices
Biases and Errors in Statistical Analysis
Blissful Ignorance and Dangerous Implicit Assumptions
Limits of Analysis
General Limits to Problem Analysis
Laws and Regulations
Measurement Error
Computational Limits over Current Facts
Mathematical Limits
System-atic Errors
Incomplete Modeling
Empirical Non-Verifiability
Organizational Limits to Problem Analysis
Lack of Investigatory Time
Lack of Other Investigatory Resources
Human Limits
Lack of Control
Individual Limits to Problem Analysis
Lack of Expertise
Epistemic Issues/Decision-Maker Weakness
References
5 Span of Effects of Uncertainty (in Decision-Making)
The Impacts of Uncertainty
Impacts on Entities
On Survival
On Feelings
On Challenges
On Organization
On Compensation for Experiencing Uncertainty
On Rational Behaviors and Choices
Impacts on Entity Reactions
On Behaviors to Reduce or Accept Uncertainty
On Behaviors to Explore or Exploit Uncertainty
Impacts on Understanding
Impacts on Theorizing
Impacts on Lab Studies
Impacts on Communications and Measures
References
6 Negative Effects of Uncertainty (on Decision-Making)
Costly Uncertainties
Negative Effects of Uncertainty
Drivers of Negative Effects
Contexts for Negative Effects
Dealing with Negative Effects
References
7 Positive Effects of Uncertainty (on Decision-Making)
The Existential Positive Effects of Uncertainty
Uncertainty as a Signal of Potential Rewards
Conceptual Benefits from Uncertainty
Real Benefits from Uncertainty
Conditions for Benefits
Who Benefits
References
8 Optimal Uncertainty (in Decision-Making)
Why a Goldilocksian ‘Amount’ of Uncertainty Can Exist
At What Level of Analysis?
For What Ends?
How to Generate It
References
9 Measures of Uncertainty (in Decision-Making)
The Importance of Measuring Uncertainty and Its Characteristics
Approaches to Measurement
Practical Measures
Conceptual Measures
Immeasurability
References
10 Multi-Dimensionality of Uncertainty
Why Uncertainty Is Multi-Dimensional
Which Dimensions?
Bases for These Dimensions
Dealing with Multi-Dimensionality
References
11 Uncertainty’s Connections to Entrepreneurship
Why Uncertainty Connects to Entrepreneurship
Which Uncertainties and Activities?
Drivers of the Entrepreneurship Connection
The Context of the Entrepreneurship Connection
Managing the Entrepreneurship Connection
References
12 Uncertainty’s Connections to Strategy
Why Uncertainty Connects to Strategy
Uncertainty and Theories of the Firm (and of Firm Rents)
Top Management’s Focus on Uncertainty
Uncertainty and Contracting
Deeper into Uncertainty
Drivers of the Strategy Connection
The Context of the Strategy Connection
Uncertainties and Activities
Managing the Strategy Connection
References
13 Uncertainty’s Connections to Creativity, Art, and Music
Connecting Uncertainty to Creativity
Connecting Uncertainty to Art and Music
Why the Connections Exist
Philosophical Questions Raised
References
14 Uncertainty’s Connections to Spirituality/Religion
Connecting Uncertainty to Spirituality and Religion
Connecting Spirituality to Decision-Making under Uncertainty
Importance of Uncertainty in Religion
Drivers of Uncertainty in Religion
Offering Some Balance
References
15 Uncertainty’s Connections to Curiosity, Neurobiology, and Evolution
Connecting Uncertainty to Curiosity
Connecting Uncertainty to Neurobiology
Connecting Uncertainty to Cognition
Connecting Uncertainty to Evolution
Drivers of the Connections
Philosophical Implications
References
16 Past Failures to Engage with Uncertainty
Identifying the Failures to Engage
Drivers of the Failures
Why Probability-Based Approaches Fail
How That Failure Extends to Subjective Expected Utility
Alternatives
References
17 A New Typology of Uncertainty (for Decision-Making)
Introduction to a New Typology
Reminders About the Main Assumption and Definition
The Plan for This Chapter
Past Uncertainty Types and Labels
Incomplete Information
Knightian Uncertainty
Ellsbergian Ambiguity
Ignorance
Aleatory Uncertainty
Unknown Unknowns
Equivocality
Vagueness
Epistemic Uncertainty
Other Potential Types
The New Primary Typology
Cleaning Up the Minor Issues Involved
The Relevant Secondary Typology
Step One—Assessing the Background Facts
State Uncertainty/ Uncertainty about the Present Reality
Uncertainty about the Past
Step Two—Understanding the Goals
Step Three—Identifying the Stakeholders
Step Four—Recognizing All Possible Relevant Options/Choices
Step Five—Identifying All Possible Outcomes (Relevant to the Choices)
Step Six—Calculating the (Monetary) Payoffs of the Outcomes
Step Seven—Considering the Ethics and Values of the Outcomes [separated from Goals]
Step Eight—Calculating the (Overall) Worth of the Outcomes [Utilities]
Step Nine—Assigning Probabilities to the Uncontrollable Outcome-Affecting Events
Step Ten—Including Any Timing Issues Involved in the Process
Step Eleven—Applying the Relevant Constraints
A Line of Demarcation in the Decision-Making Process
Step Twelve—Identifying the Dynamic Links in the Extended Process
Step Thirteen—Assessing the Dynamics of Competition
Unknown Effects on Rival Targets
Unknown Responses of Targets
Unknown Target Intensions
Unknown Target Decision Constraints
A Tertiary Typology
Dimensions of Specifying What Is Uncertain
Dimensions of Specifying Why the Uncertainty Exists
Dimensions of Specifying Where the Uncertainty Exists
Revisiting a Selection of Uncertainty Sources to Highlight the Separation from Types
Measurement Uncertainty
Model Uncertainty
Environmental Uncertainty
Endogenous Uncertainty and Knowable Unknowns
Supplement on Knightian Uncertainty Issues
Knight’s Model as a Theory of Rents
The Three Dangers of the Knightian Model
The Premise Danger
The Implication Danger
The Definition Danger
Discussion
References
18 Best Treatments and Approaches to Uncertainty Types (in Decision-Making)
Introduction to Uncertainty Treatment
Part One—Treating the Treatable Uncertainties
Bucket One—Uncovering Unknowns via Discovery, Search, and Monitoring
Bucket Two—Uncovering Unknowns via Experimentation, Experience, Analysis, and Modeling
Experimentation
Sensemaking and Modeling
Experience and Alertness
Inference from Big Data
Other Active Learning Approaches
Bucket Three—Uncovering Unknowns via Influencing the Outcome Through Social Construction and Preemption
Bucket Four—Uncovering Unknowns via Scenarios and Simulations
Bucket Five—Uncovering Unknowns via Adapting to Outcomes Through Flexibility, Options and Robustness
Bucket Six—Uncovering Unknowns via Sharing the Burden with Cooperation and Insurance, or Through Diversification
Part Two—Addressing the Untreatable Uncertainties (the Unknown-and-Unknowables)
A Shift in Mentality
The Four Approaches
Bucket A-One—Addressing the Untreatable by Bearing the Irreducible Uncertainty
Bucket A-Two—Addressing the Untreatable by Changing the Goal
Heuristics in General
Conditions for Heuristic Use
Dangers of Heuristics
Types and Examples of Heuristics
Acting ‘As If’ the Unknown Is Known
Acting on the Knowns Alone
Altering the Knowns to Reduce Harms
Modeling What Is Known
Applying Information-Gap Theory
Bucket A-Two-Plus—Addressing the Untreatable by Changing the Goal to a Relative One
Bucket A-Three—Addressing the Untreatable by Changing the Focal Entity
Playing No-Regrets, Conservative Moves
Following Available Standard Procedures and Norms
Expressing Dissatisfaction or Doubt
Ignoring, Suppressing, or Denying the Uncertainty
Trying to Delay the Decision or Action
Avoiding the Uncertainty
Bucket A-Four—Addressing the Untreatable by Altering the Game
Part Three—Processing Issues in Decision Uncertainty Treatment/Approach
The Awareness of Uncertainties
Prioritization
Context Matters—Big and Small
The Costs of Addressing Uncertainties
Combining Approaches
On the Offense—Creating Uncertainties
References
19 Conclusions of the Analysis of Uncertainty (as Everything)
Summary
Implications
Philosophical and Scientific Issues
Future Work
(Almost) Final Thoughts
References
20 Supplement on the Impact of Artificial Intelligence on Uncertainty
Why This Supplement (Now)?
Summary of AI’s Impacts on Uncertainties
The Relevant Impact of AI Itself
AI the Good
AI the Bad
The Uncertainties in the AI Box
Mitigating Those (Treatable) Internal AI Uncertainties
Estimating Those Uncertainties in AI
Main Implications
Wrapping IT Up—the Real and the F.ai.k
References
Uncertainty Literature
Index