Decision Analysis for Management Judgment

Höfundar: Paul Goodwin; George Wright (Útgáfa: 6)
Decision Analysis for Management Judgment

Kaup valmöguleikar

APPLYING DECISION ANALYSIS FOR EFFECTIVE MANAGEMENT JUDGMENT ACROSS DIVERSE FIELDS Sound decision-making is essential for success in today’s complex organizational environments. Now in its sixth edition, Decision Analysis for Management Judgment provides students and professionals with the tools and insights needed to make informed, rational choices in the face of uncertainty. Written for managers and students without advanced mathematical training, this leading textbook clearly explains a wide range of decision analysis techniques while addressing the psychological biases and pitfalls that often undermine judgment.

Throughout the text, authors Paul Goodwin and George Wright combine behavioral insights with practical analytical tools, bridging the gap between foundational theory and real-world practice. Presenting complex concepts in a clear, accessible style suitable for both students and professionals, Decision Analysis for Management Judgment is an invaluable resource for anyone tasked with evaluating alternatives, anticipating future scenarios, and balancing multiple objectives in professional contexts.

It is ideal for upper-level undergraduate, MBA, and executive education courses in decision analysis, management judgment, strategic planning, and environmental planning. NEW TO THIS EDITION: Introduces the role of artificial intelligence in decision-making, highlighting benefits, limitations, and future potential Provides a step-by-step guide to applying the Intuitive Logics method of scenario planning Demonstrates a streamlined approach for integrating scenario planning with multi-attribute decision analysis New practical examples illustrating successful applications of decision analysis and scenario planning Includes the latest psychological research on multi-attribute decision-making and behavioral “nudges” Incorporates the SPIES method for estimating probability distributions and expands coverage of the Delphi method with recommendations for robust implementation Adds Cooke’s Classical Method for aggregating expert probability judgments and discusses the success of superforecasters WILEY ADVANTAGE: Provides a reader-friendly introduction to decision analysis without requiring advanced mathematical knowledge Integrates behavioral insights to address psychological biases that can undermine managerial judgment Covers a wide range of qualitative and quantitative decision analysis techniques applicable to real-world problems Applies concepts to diverse contexts, including business, public administration, and environmental planning Encourages active learning through end-of-chapter exercises that reinforce understanding and critical thinking Supports flexible teaching approaches with a companion website containing additional exercises, case studies, quizzes, and simulations.

Nánar um bókina

Útgefandi
Wiley Global Education US
ISBN
9781394362479
Print ISBN
9781394362554
Format
ePub
Útgáfa
6
Höfundar
Paul Goodwin; George Wright
Tungumál
English
Útgefið
2026-02-13
Prent takmörkun á líftíma
100
Prent takmörkun
10
Afritunar takmörkun
2

Kaflar

  • Cover
  • Table of Contents
  • Title Page
  • Copyright
  • Dedication
  • Foreword to First Edition
  • Preface
  • Accompanying website at www.wiley.com/go/goodwin6e
  • 1 Introduction
  • Complex decisions
  • The role of decision analysis
  • Good and bad decisions and outcomes
  • Applications of decision analysis
  • Our own consultancy-based case examples of scenario planning
  • Overview of the book
  • References
  • 2 How people make decisions involving multiple objectives
  • Heuristics used for decisions involving multiple objectives
  • Other characteristics of decision-making involving multiple objectives
  • Summary
  • Exercises
  • References
  • 3 Decisions involving multiple objectives: SMART
  • Basic terminology
  • An office location problem
  • An overview of the analysis
  • Constructing a value tree
  • Measuring how well the options perform on each attribute
  • Determining the weights of the attributes
  • Aggregating the benefits using the additive model
  • Trading benefits against costs
  • Sensitivity analysis
  • Theoretical considerations
  • Conflicts between intuitive and analytic results
  • Summary
  • Exercises
  • References
  • 4 Decisions involving multiple objectives: alternatives to SMART
  • Smarter
  • Even Swaps
  • Even Swaps versus SMART
  • The analytic hierarchy process
  • Performing AHP calculations by hand
  • The axioms of the AHP
  • The AHP versus SMART
  • MACBETH
  • Summary
  • Exercises
  • References
  • 5 Introduction to probability
  • Outcomes and events
  • Approaches to probability
  • Mutually exclusive and exhaustive events
  • Complementary events
  • Marginal and conditional probabilities
  • Independent and dependent events
  • The multiplication rule
  • Probability trees
  • Probability distributions
  • Expected values
  • The axioms of probability theory
  • Summary
  • Exercises
  • References
  • 6 Decision-making under risk
  • The maximin criterion
  • The expected monetary value criterion
  • Limitations of the EMV criterion
  • Single-attribute utility
  • Interpreting utility functions
  • Utility functions for non-monetary attributes
  • The axioms of utility
  • More on utility elicitation
  • Limitations of applying utility
  • Multi-attribute utility
  • Summary
  • Exercises
  • References
  • 7 Decision trees and influence diagrams
  • Constructing a decision tree
  • Determining the optimal policy
  • Decision trees and utility
  • Decision trees involving continuous probability distributions
  • Assessment of decision structure
  • Eliciting decision-tree representations
  • Summary
  • Exercises
  • References
  • 8 Applying simulation to decision problems
  • Monte Carlo simulation
  • Applying simulation to a decision problem
  • Applying simulation to investment decisions
  • Modeling dependence relationships
  • Summary
  • Exercises
  • References
  • 9 Revising judgments in light of new information
  • Bayes’ theorem
  • The effect of new information on the revision of probability judgments
  • Applying Bayes’ theorem to a decision problem
  • Assessing the value of new information
  • Summary
  • Exercises
  • References
  • 10 Heuristics and biases in probability assessment
  • Heuristics and biases
  • The representativeness heuristic
  • The anchoring and adjustment heuristic
  • Is human probability judgment really so poor?
  • Summary
  • Exercises
  • References
  • 11 Methods for eliciting probabilities
  • Issues with verbal probability expressions
  • Coherence in probability judgments
  • Two barriers to improving probability assessments through learning
  • Preparing for probability assessment
  • Consistency and coherence checks
  • Assessing the validity of probabilities
  • Assessing probabilities for very rare events
  • Communicating probability estimates
  • Summary
  • Exercises
  • References
  • 12 Structured risk management
  • The Two Valleys Company
  • Summary
  • Exercises
  • References
  • 13 Decisions involving groups of individuals
  • Mathematical aggregation
  • Aggregating judgments in general
  • Aggregating probability judgments
  • Aggregating preference judgments
  • Unstructured group processes
  • The Delphi method
  • Prediction markets
  • Decision conferencing
  • Summary
  • Exercises
  • References
  • 14 Resource allocation and negotiation problems
  • Modeling resource-allocation problems
  • The main stages of the analysis
  • Identifying the possible strategies for each region
  • Sensitivity analysis
  • Negotiation models
  • An illustrative problem
  • Practical applications
  • Summary
  • Exercises
  • References
  • 15 Decision framing and cognitive inertia
  • Creativity in problem solving
  • How people frame decisions
  • Solving the wrong problem
  • Get hooked on complexity – overlooking simple options
  • Imposing imaginary constraints and false assumptions on the range of options
  • Sensitivity to reference points
  • Mental accounting and the narrow bracketing of decisions
  • Inertia in strategic decision-making
  • Non-rational escalation of commitment
  • How people react to a threat
  • Rethinking decisions
  • Studies in the psychological laboratory and cognitive inertia: a synthesis
  • Summary
  • Exercises
  • Appendix
  • References
  • 16 Scenario planning: a way of dealing with uncertainty
  • Scenario construction: the Intuitive Logics method
  • Case study of a scenario intervention in the English National Health Service
  • Case study of an unsuccessful scenario-planning intervention
  • Conclusion
  • Exercises
  • References
  • 17 Combining scenario planning with decision analysis
  • Main stages of the approach
  • Illustrative case study
  • Strengths and limitations of MINIMOD
  • Having a checklist of key objectives
  • Other approaches
  • Summary
  • Exercises
  • References
  • 18 Alternative decision-support systems and the role of AI
  • Statistical models of judgment
  • Snap decisions and decision analysis: why not trust our initial intuitions?
  • Designing decisions so that people make the ‘best’ choice
  • The role of artificial intelligence in aiding decisions
  • Some final words of advice
  • Summary
  • References
  • Suggested answers to selected questions
  • Chapter 2
  • Chapter 3
  • Chapter 4
  • Chapter 5
  • Chapter 6
  • Chapter 7
  • Chapter 8
  • Chapter 9
  • Chapter 11
  • Chapter 14
  • Chapter 17
  • Index
  • End User License Agreement