[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-115402-en":3,"doc-seo-115402-105":31,"detail-sidebar-cat-0-en-105":93},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},115402,962084926284,"Aurora","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Decision Analysis for Management Judgment - Paul Goodwin","A comprehensive introduction to decision analysis for management judgment, guiding readers through complex choices under multiple objectives, uncertainty, and risk. Covers value trees, SMART, alternatives such as AHP, and utility theory for both monetary and non-monetary attributes. Develops probability foundations, decision trees and influence diagrams, simulation and Monte Carlo methods, and Bayes’ theorem for revising judgments. Addresses heuristics and biases, elicitation of probabilities, structured risk management, group decision processes, resource allocation and negotiation, decision framing and cognitive inertia, and scenario planning combined with decision analysis, including AI decision-support.","Table of Contents  \nCover  \nTable of Contents  \nTitle Page  \nCopyright  \nDedication  \nForeword to First Edition  \nPreface  \nAccompanying website at www.wiley.com/go/goodwin6e  \n1 Introduction  \nComplex decisions  \nThe role of decision analysis  \nGood and bad decisions and outcomes  \nApplications of decision analysis  \nOur own consultancy-based case examples of scenario planning  \nOverview of the book  \nReferences  \n2 How people make decisions involving multiple objectives  \nHeuristics used for decisions involving multiple objectives  \nOther characteristics of decision-making involving multiple  \nobjectives  \nSummary  \nExercises  \nReferences  \n3 Decisions involving multiple objectives: SMART  \nBasic terminology  \nAn office location problem  \nAn overview of the analysis  \nConstructing a value tree  \nMeasuring how well the options perform on each attribute  \nDetermining the weights of the attributes  \nAggregating the benefits using the additive model  \nTrading benefits against costs  \nSensitivity analysis  \nTheoretical considerations  \nConflicts between intuitive and analytic results  \nSummary  \nExercises  \nReferences  \n4 Decisions involving multiple objectives: alternatives to SMART  \nSmarter  \nEven Swaps  \nEven Swaps versus SMART  \nThe analytic hierarchy process  \nPerforming AHP calculations by hand  \nThe axioms of theAHP  \nTheAHP versus SMART  \nMACBETH  \nSummary  \nExercises  \nReferences  \n5 Introduction to probability  \nOutcomes and events  \nApproaches to probability  \nMutually exclusive and exhaustive events  \nComplementary events  \nMarginal and conditional probabilities  \nIndependent and dependent events  \nThe multiplication rule  \nProbability trees  \nProbability distributions  \nExpected values  \nThe axioms of probability theory  \nSummary  \nExercises  \nReferences  \n6 Decision-making under risk  \nThe maximin criterion  \nThe expected monetary value criterion  \nLimitations of the EMV criterion  \nSingle-attribute utility  \nInterpreting utility functions  \nUtility functions for non-monetary attributes  \nThe axioms of utility  \nMore on utility elicitation  \nLimitations of applying utility  \nMulti-attribute utility  \nSummary  \nExercises  \nReferences  \n7 Decision trees and influence diagrams  \nConstructing a decision tree  \nDetermining the optimal policy  \nDecision trees and utility  \nDecision trees involving continuous probability distributions  \nAssessment of decision structure  \nEliciting decision-tree representations  \nSummary  \nExercises  \nReferences  \n8 Applying simulation to decision problems  \nMonte Carlo simulation  \nApplying simulation to a decision problem  \nApplying simulation to investment decisions  \nModeling dependence relationships  \nSummary  \nExercises  \nReferences  \n9 Revising judgments in light of new information  \nBayes’theorem  \nThe effect of new information on the revision of probability  \njudgments  \nApplying Bayes’theorem to a decision problem  \nAssessing the value of new information  \nSummary  \nExercises  \nReferences  \n10 Heuristics and biases in probability assessment  \nHeuristics and biases  \nThe representativeness heuristic  \nThe anchoring and adjustment heuristic  \nIs human probability judgment really so poor?  \nSummary  \nExercises  \nReferences  \n11 Methods for eliciting probabilities  \nIssues with verbal probability expressions  \nCoherence in probability judgments  \nTwo barriers to improving probability assessments through  \nlearning  \nPreparing for probability assessment  \nConsistency and coherence checks  \nAssessing the validity of probabilities  \nAssessing probabilities for very rare events  \nCommunicating probability estimates  \nSummary  \nExercises  \nReferences  \n12 Structured risk management  \nThe Two Valleys Company  \nSummary  \nExercises  \nReferences  \n13 Decisions involving groups of individuals  \nMathematical aggregation  \nAggregating judgments in general  \nAggregating probability judgments  \nAggregating preference judgments  \nUnstructured group processes  \nThe Delphi method  \nPrediction markets","cbCaiiezZvnqDJCB","https://ap.wps.com/l/cbCaiiezZvnqDJCB","pdf",7470069,6,1,645,"English","en",105,"# 1 Introduction\n# 2 How people make decisions involving multiple objectives\n# 3 Decisions involving multiple objectives: SMART\n# 4 Decisions involving multiple objectives: alternatives to SMART\n# 5 Introduction to probability\n# 6 Decision-making under risk\n# 7 Decision trees and influence diagrams\n# 8 Applying simulation to decision problems\n# 9 Revising judgments in light of new information\n# 10 Heuristics and biases in probability assessment\n# 11 Methods for eliciting probabilities\n# 12 Structured risk management\n# 13 Decisions involving groups of individuals\n# 14 Resource allocation and negotiation problems\n# 15 Decision framing and cognitive inertia\n# 16 Scenario planning: a way of dealing with uncertainty\n# 17 Combining scenario planning with decision analysis\n# 18 Alternative decision-support systems and the role of AI","[{\"question\":\"What is decision analysis used for in management judgment?\",\"answer\":\"It supports good decisions by structuring and analyzing complex choices, especially when multiple objectives, uncertainty, and risk affect outcomes.\"},{\"question\":\"How does SMART help with decisions involving multiple objectives?\",\"answer\":\"SMART builds a value tree, measures option performance on each attribute, assigns attribute weights, aggregates benefits, and uses methods like sensitivity analysis to explore trade-offs.\"},{\"question\":\"How are probabilities revised when new information becomes available?\",\"answer\":\"Bayes’ theorem updates probability judgments, and the approach also assesses the value of the new information for the decision.\"}]","Decision Analysis for Management Judgment - Paul Goodwin | PDF",1785472977,1625,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":88,"head_meta":90,"extra_data":92,"updated_unix":29},"decision-analysis-for-management-judgment-paul-goodwin","",{"@graph":37,"@context":87},[38,55,70],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/document/","Document",2,{"item":50,"name":12,"@type":44,"position":51},"https://docshare.wps.com/document/research-report/",3,{"item":53,"name":13,"@type":44,"position":54},"https://docshare.wps.com/document/decision-analysis-for-management-judgment-paul-goodwin/115402/",4,{"url":53,"name":13,"@type":56,"author":57,"headline":13,"publisher":59,"fileFormat":62,"inLanguage":24,"description":14,"dateModified":63,"datePublished":64,"encodingFormat":62,"isAccessibleForFree":65,"interactionStatistic":66},"DigitalDocument",{"name":9,"@type":58},"Person",{"url":42,"name":60,"@type":61},"DocShare","Organization","application/pdf","2026-08-17","2026-07-31",true,{"@type":67,"interactionType":68,"userInteractionCount":20},"InteractionCounter",{"@type":69},"ViewAction",{"@type":71,"mainEntity":72},"FAQPage",[73,79,83],{"name":74,"@type":75,"acceptedAnswer":76},"What is decision analysis used for in management judgment?","Question",{"text":77,"@type":78},"It supports good decisions by structuring and analyzing complex choices, especially when multiple objectives, uncertainty, and risk affect outcomes.","Answer",{"name":80,"@type":75,"acceptedAnswer":81},"How does SMART help with decisions involving multiple objectives?",{"text":82,"@type":78},"SMART builds a value tree, measures option performance on each attribute, assigns attribute weights, aggregates benefits, and uses methods like sensitivity analysis to explore trade-offs.",{"name":84,"@type":75,"acceptedAnswer":85},"How are probabilities revised when new information becomes available?",{"text":86,"@type":78},"Bayes’ theorem updates probability judgments, and the approach also assesses the value of the new information for the decision.","https://schema.org",{"og:url":53,"og:type":89,"og:title":13,"og:site_name":60,"og:description":14},"article",{"robots":91,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":94},[95,99,103,107,112,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":96,"show_sort_weight":97,"slug":98},"Story & Novel",90,"story-novel",{"id":48,"doc_module":4,"doc_module_name":47,"category_name":100,"show_sort_weight":101,"slug":102},"Literature",80,"literature",{"id":54,"doc_module":4,"doc_module_name":47,"category_name":104,"show_sort_weight":105,"slug":106},"Exam",70,"exam",{"id":108,"doc_module":4,"doc_module_name":47,"category_name":109,"show_sort_weight":110,"slug":111},5,"Comic",60,"comic",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":108,"slug":139},19,"General","general"]