{"id":170091,"date":"2024-10-19T10:27:28","date_gmt":"2024-10-19T10:27:28","guid":{"rendered":"https:\/\/pdfstandards.shop\/product\/uncategorized\/asce-quantitativeriskmanagementdecision-2017\/"},"modified":"2024-10-25T02:37:30","modified_gmt":"2024-10-25T02:37:30","slug":"asce-quantitativeriskmanagementdecision-2017","status":"publish","type":"product","link":"https:\/\/pdfstandards.shop\/product\/publishers\/asce\/asce-quantitativeriskmanagementdecision-2017\/","title":{"rendered":"ASCE QuantitativeRiskManagementDecision 2017"},"content":{"rendered":"

Quantitative Risk Management and Decision Making in Construction introduces valuable techniques for weighing and evaluating alternatives in decision making with a focus on risk analysis for identifying, quantifying, and mitigating risks associated with construction projects. Singh addresses such topics as probabilistic cost estimating, contingency analysis, cause-effect diagrams, FAST diagrams, and decision trees, and explains the tools available to quantify risks such as payoff matrices, Bayes\u2019 theorem, matrix analysis, and analytical hierarchy process. Finally, Singh shows how the information gained from analysis can be applied to mitigate risks using a risk-analysis card game, by monitoring performance, and by managing inventory. Intended for graduate and upper-level undergraduate students, each topic is accompanied by numerous examples, drawings, and exercises to illustrate and reinforce these concepts. In addition, the common techniques can be executed by business and construction managers for practical construction risk assessment.<\/p>\n

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PDF Pages<\/th>\nPDF Title<\/th>\n<\/tr>\n
1<\/td>\nCover <\/td>\n<\/tr>\n
3<\/td>\nOther Titles of Interest <\/td>\n<\/tr>\n
5<\/td>\nCopyright <\/td>\n<\/tr>\n
8<\/td>\nContents <\/td>\n<\/tr>\n
16<\/td>\nPreface <\/td>\n<\/tr>\n
20<\/td>\n1. Risk Management Planning
1.1 Introduction <\/td>\n<\/tr>\n
21<\/td>\n1.2 Risk Identification <\/td>\n<\/tr>\n
22<\/td>\n1.2.1 Risk Recognition
1.2.2 Risk Categorization <\/td>\n<\/tr>\n
24<\/td>\n1.3 Risk Assessment and Analysis
1.3.1 Qualitative Risk Analysis <\/td>\n<\/tr>\n
27<\/td>\n1.3.2 Quantitative Risk Analysis
1.3.2.1 Value Assignment <\/td>\n<\/tr>\n
28<\/td>\n1.3.2.2 Simulation
1.3.2.3 Probabilistic Techniques <\/td>\n<\/tr>\n
29<\/td>\n1.3.2.4 Discrete Events
1.4 Risk Control <\/td>\n<\/tr>\n
30<\/td>\n1.4.1 Risk Reduction <\/td>\n<\/tr>\n
31<\/td>\n1.4.2 Risk Distribution <\/td>\n<\/tr>\n
32<\/td>\n1.4.3 Risk Acceptance <\/td>\n<\/tr>\n
33<\/td>\n1.5 Risk Allocation <\/td>\n<\/tr>\n
34<\/td>\n1.6 Risk Monitoring
1.7 Risk Planning <\/td>\n<\/tr>\n
35<\/td>\n1.8 Summary <\/td>\n<\/tr>\n
36<\/td>\n1.9 Exercises <\/td>\n<\/tr>\n
37<\/td>\nReferences <\/td>\n<\/tr>\n
38<\/td>\n2. Probabilistic Cost Analysis
2.1 Introduction <\/td>\n<\/tr>\n
39<\/td>\n2.2 Triangular (Three-Point) Estimates <\/td>\n<\/tr>\n
40<\/td>\n2.3 Cost Items (Work Packages
2.4 Work Package Cost Fluctuations
2.5 Price Probability <\/td>\n<\/tr>\n
41<\/td>\n2.6 Triangular Distribution <\/td>\n<\/tr>\n
42<\/td>\n2.7 Requesting Prices <\/td>\n<\/tr>\n
43<\/td>\n2.8 Background
2.9 Probability Evaluation by Triangular Distribution <\/td>\n<\/tr>\n
46<\/td>\n2.10 Probabilities of Project Cost <\/td>\n<\/tr>\n
47<\/td>\n2.11 Cumulative Probability of Project Costs <\/td>\n<\/tr>\n
48<\/td>\n2.12 Finding the Bid Price <\/td>\n<\/tr>\n
51<\/td>\n2.13 Additional Perspectives
2.13.1 The Owner\u2019s Perspective
2.13.2 Guaranteed Maximum Price (GMP <\/td>\n<\/tr>\n
52<\/td>\n2.13.3 Contractor\u2019s Risk Transfer and Subcontractor\u2019s Risk
2.14 Summary <\/td>\n<\/tr>\n
53<\/td>\n2.15 Exercises
2.16 Acknowledgments <\/td>\n<\/tr>\n
54<\/td>\nReferences <\/td>\n<\/tr>\n
56<\/td>\n3. Contingency Analysis and Allocation
3.1 Introduction: Contingency Cost Management <\/td>\n<\/tr>\n
57<\/td>\n3.2 Contingency Cost Process Overview <\/td>\n<\/tr>\n
58<\/td>\n3.2.1 Contingency Cost Allocation Methodology
3.3 Critical Cost
3.3.1 Identifying Critical Work Packages <\/td>\n<\/tr>\n
60<\/td>\n3.3.2 Handling Noncritical Work Packages
3.3.3 Criticality Rule Examples <\/td>\n<\/tr>\n
61<\/td>\n3.4 Monte Carlo Simulation
3.4.1 Creating the Monte Carlo Slab <\/td>\n<\/tr>\n
62<\/td>\n3.4.2 Generating Random Numbers <\/td>\n<\/tr>\n
63<\/td>\n3.5 Cumulative Probability Profile <\/td>\n<\/tr>\n
64<\/td>\n3.6 Contingency Allocation <\/td>\n<\/tr>\n
65<\/td>\n3.7 Drawdown Curve <\/td>\n<\/tr>\n
68<\/td>\n3.8 Summary
3.9 Exercises <\/td>\n<\/tr>\n
70<\/td>\nReferences <\/td>\n<\/tr>\n
72<\/td>\n4. Cause-and-Effect Diagrams
4.1 Introduction
4.2 Kaoru Ishikawa <\/td>\n<\/tr>\n
73<\/td>\n4.3 Applications of Cause-and-Effect Diagrams <\/td>\n<\/tr>\n
75<\/td>\n4.4 Types of Cause-and-Effect Diagrams
4.4.1 Drawing the Dispersion Analysis Type of Cause-and-Effect
\n Diagram <\/td>\n<\/tr>\n
78<\/td>\n4.4.2 Drawing the Cause Enumeration Type of Cause-and-Effect
\n Diagram <\/td>\n<\/tr>\n
79<\/td>\n4.4.3 Drawing the Production Process Classification Type of
\n Cause-and-Effect Diagram
4.5 Example Problems <\/td>\n<\/tr>\n
80<\/td>\n4.5.1 Example 1: Dispersion Analysis Type <\/td>\n<\/tr>\n
83<\/td>\n4.5.2 Example 2: Production Process Classification Type <\/td>\n<\/tr>\n
84<\/td>\n4.5.3 Example 3: Cause Enumeration type <\/td>\n<\/tr>\n
89<\/td>\n4.6 Exercises
References <\/td>\n<\/tr>\n
90<\/td>\n5. Function Analysis System Technique\u2014Structuring Uncertainty
5.1 Introduction <\/td>\n<\/tr>\n
91<\/td>\n5.2 Background of the Functional Analysis System
\n Technique (FAST <\/td>\n<\/tr>\n
92<\/td>\n5.3 Function Analysis <\/td>\n<\/tr>\n
93<\/td>\n5.3.1 Defining Function <\/td>\n<\/tr>\n
97<\/td>\n5.3.2 Classifying Functions
5.3.2.1 Basic Functions
5.3.2.2 Secondary Functions <\/td>\n<\/tr>\n
98<\/td>\n5.3.2.3 Higher-Order and Lower-Order Functions
5.3.2.4 Assumed Functions <\/td>\n<\/tr>\n
99<\/td>\n5.3.2.5 All-Time Functions
5.3.2.6 Dependent and Independent Functions
5.3.2.7 Critical Path
5.3.2.8 Analyzing Functions <\/td>\n<\/tr>\n
100<\/td>\n5.4 Function Analysis System Technique and Value Methodology
5.4.1 The How\u2013Why Concept <\/td>\n<\/tr>\n
102<\/td>\n5.4.2 When Logic <\/td>\n<\/tr>\n
103<\/td>\n5.4.3 And\/Or Logic
5.4.4 FAST Procedure Tree <\/td>\n<\/tr>\n
110<\/td>\n5.5 Conclusion
5.6 Exercises <\/td>\n<\/tr>\n
112<\/td>\nReferences <\/td>\n<\/tr>\n
114<\/td>\n6. Decision Trees
6.1 Objective
6.2 Introduction
6.2.1 Understanding the Potential and Limits of Decision
\n Trees <\/td>\n<\/tr>\n
115<\/td>\n6.2.1.1 Marketing Problem <\/td>\n<\/tr>\n
117<\/td>\n6.3 Diagram Breakdown <\/td>\n<\/tr>\n
119<\/td>\n6.4 Example Problems
6.4.1 Example 1: Application in Construction Engineering <\/td>\n<\/tr>\n
123<\/td>\n6.4.2 Example 2: Application in Fundraising <\/td>\n<\/tr>\n
130<\/td>\n6.4.3 Example 3: Application in Insurance <\/td>\n<\/tr>\n
136<\/td>\n6.5 Review
6.6 Exercises <\/td>\n<\/tr>\n
138<\/td>\n7. Payoff Matrix
7.1 Introduction
7.2 Method <\/td>\n<\/tr>\n
140<\/td>\n7.3 Example Problem 1: Increasing Monthly Profits <\/td>\n<\/tr>\n
141<\/td>\n7.4 Answer to Example Problem 1
7.4.1 Determining Decision Alternatives
7.4.2 Determining States of Nature <\/td>\n<\/tr>\n
142<\/td>\n7.4.3 Determining Maximin
7.4.4 Determining Maximax <\/td>\n<\/tr>\n
143<\/td>\n7.4.5 Determining Minimax Regret <\/td>\n<\/tr>\n
144<\/td>\n7.4.6 Expected Monetary Value
7.4.7 Expected Opportunity Loss <\/td>\n<\/tr>\n
145<\/td>\n7.4.8 Decision Tree Approach <\/td>\n<\/tr>\n
146<\/td>\n7.5 Example Problem 2: Limiting Decision Costs
7.6 Answer to Example Problem 2
7.6.1 Setting up a Payoff Table <\/td>\n<\/tr>\n
147<\/td>\n7.6.2 Determining Minimax
7.6.3 Determining Minimin <\/td>\n<\/tr>\n
148<\/td>\n7.6.4 Determining Minimax Regret <\/td>\n<\/tr>\n
149<\/td>\n7.6.5 EMV <\/td>\n<\/tr>\n
150<\/td>\n7.7 Example Problem 3: Qualitative Decision Making
7.8 Answer to Example Problem 3
7.8.1 Maximin <\/td>\n<\/tr>\n
151<\/td>\n7.8.2 Maximax
7.8.3 Minimax Regret <\/td>\n<\/tr>\n
152<\/td>\n7.8.4 EMV <\/td>\n<\/tr>\n
153<\/td>\n7.9 Importance of the Payoff Matrix <\/td>\n<\/tr>\n
154<\/td>\n7.10 Exercises <\/td>\n<\/tr>\n
156<\/td>\n8. Bayes\u2019 Theorem
8.1 Introduction
8.2 What is Bayes\u2019 Theorem <\/td>\n<\/tr>\n
157<\/td>\n8.3 Criticism and Advantages
8.4 Derivation of Bayes\u2019 Theorem from First Principles
8.4.1 Events and Sample Space <\/td>\n<\/tr>\n
159<\/td>\n8.4.2 Conditional Probability and Dependence <\/td>\n<\/tr>\n
160<\/td>\n8.4.3 Bayes\u2019 Theorem Derived from Conditional Probability <\/td>\n<\/tr>\n
162<\/td>\n8.5 Logic of Prior\/Posterior Probabilities and Tree Diagrams <\/td>\n<\/tr>\n
164<\/td>\n8.6 Examples and Sample Exercises: Applications of Bayes\u2019 Theorem <\/td>\n<\/tr>\n
165<\/td>\n8.6.1 Example 1: Contractor Performance Information <\/td>\n<\/tr>\n
168<\/td>\n8.6.2 Example 2: Defective Parts at a Firearms Manufacturer <\/td>\n<\/tr>\n
172<\/td>\n8.7 Exercises <\/td>\n<\/tr>\n
179<\/td>\n8.8 Conclusion <\/td>\n<\/tr>\n
180<\/td>\nReferences <\/td>\n<\/tr>\n
182<\/td>\n9. Matrix Analysis
9.1 Introduction
9.2 Criteria <\/td>\n<\/tr>\n
183<\/td>\n9.3 Alternatives\/Activities <\/td>\n<\/tr>\n
184<\/td>\n9.4 Weights <\/td>\n<\/tr>\n
185<\/td>\n9.5 Scores <\/td>\n<\/tr>\n
186<\/td>\n9.6 Case Study 1: Construction Site Preparation <\/td>\n<\/tr>\n
188<\/td>\n9.7 Case Study 2: Selection of an Engineering College <\/td>\n<\/tr>\n
190<\/td>\n9.8 Case Study 3: Selecting Solar Panels <\/td>\n<\/tr>\n
191<\/td>\n9.9 Case Study 4: Bid Analysis <\/td>\n<\/tr>\n
193<\/td>\n9.10 Discussion
9.11 Exercises <\/td>\n<\/tr>\n
194<\/td>\nReferences <\/td>\n<\/tr>\n
196<\/td>\n10. MCDM and the Analytic Hierarchy Process
10.1 Introduction
10.2 The Analytic Hierarchy Process (AHP <\/td>\n<\/tr>\n
197<\/td>\n10.3 Users of AHP <\/td>\n<\/tr>\n
198<\/td>\n10.4 AHP Approaches\u2014The Deductive Approach and the Systems
\n Approach
10.5 Weighting Criteria <\/td>\n<\/tr>\n
199<\/td>\n10.6 Structuring a Problem
10.7 Cross Tabulation <\/td>\n<\/tr>\n
201<\/td>\n10.8 Criteria Ranges
10.8.1 Ranges by Rank <\/td>\n<\/tr>\n
202<\/td>\n10.8.2 Range Between 0 and 1 <\/td>\n<\/tr>\n
203<\/td>\n10.8.3 Weighting the Criteria <\/td>\n<\/tr>\n
204<\/td>\n10.9 Comparison Matrix
10.9.1 Pairwise Comparison <\/td>\n<\/tr>\n
206<\/td>\n10.9.2 Geometric Mean <\/td>\n<\/tr>\n
207<\/td>\n10.9.3 Largest Eigenvalue
10.9.4 Consistency Index <\/td>\n<\/tr>\n
208<\/td>\n10.9.5 Random Index and Consistency Ratio <\/td>\n<\/tr>\n
209<\/td>\n10.9.6 Sensitivity Analysis
10.10 AHP Advantage and Critiques <\/td>\n<\/tr>\n
210<\/td>\n10.11 Conclusion
10.12 Exercises <\/td>\n<\/tr>\n
211<\/td>\nReferences <\/td>\n<\/tr>\n
212<\/td>\n11. Project Planning\u2014The OOPS Game
11.1 Introduction
11.2 Origins
11.3 How to Play the OOPS Game <\/td>\n<\/tr>\n
214<\/td>\n11.3.1 OOPS Game Example <\/td>\n<\/tr>\n
216<\/td>\n11.4 OOPS Game Analysis
11.4.1 Reducing the Scope of Analysis <\/td>\n<\/tr>\n
219<\/td>\n11.4.2 Approach of the Analysis <\/td>\n<\/tr>\n
221<\/td>\n11.5 Results of Analysis
11.5.1 All Scores <\/td>\n<\/tr>\n
222<\/td>\n11.5.2 All-BUILD Strategy
11.5.3 All PLAN Strategies <\/td>\n<\/tr>\n
224<\/td>\n11.6 Analysis of Data <\/td>\n<\/tr>\n
228<\/td>\n11.6.1 Lowest-Mean-Cost Strategy of 6T0 through 6T6 Strategies <\/td>\n<\/tr>\n
229<\/td>\n11.6.2 BUILD When Probability of Success is Greater than
\n 50% (P > 0.5 <\/td>\n<\/tr>\n
232<\/td>\n11.6.3 BUILD When the Probability of Success is Greater than
\n or Equal to 50% (P = 0.5 <\/td>\n<\/tr>\n
233<\/td>\n11.6.4 Varying the Threshold for Attempting to BUILD <\/td>\n<\/tr>\n
235<\/td>\n11.6.5 Choosing PLAN in the Beginning <\/td>\n<\/tr>\n
236<\/td>\n11.7 Conclusion <\/td>\n<\/tr>\n
237<\/td>\n11.8 Exercises <\/td>\n<\/tr>\n
238<\/td>\n12. Tracking Performance through Control Charts
12.1 Introduction
12.2 The History of Control Charts <\/td>\n<\/tr>\n
239<\/td>\n12.3 Causes of Process Variation <\/td>\n<\/tr>\n
240<\/td>\n12.4 Run and Control Charts, Upper Control Limit and
\n Lower Control Limit, and Six Sigma
12.5 Control Chart Concepts <\/td>\n<\/tr>\n
242<\/td>\n12.6 Variable Control Charts <\/td>\n<\/tr>\n
247<\/td>\n12.7 Attribute Control Charts <\/td>\n<\/tr>\n
248<\/td>\n12.7.1 The p Chart <\/td>\n<\/tr>\n
254<\/td>\n12.7.2 The np Chart <\/td>\n<\/tr>\n
256<\/td>\n12.7.3 The c Chart <\/td>\n<\/tr>\n
257<\/td>\n12.7.4 The u Chart <\/td>\n<\/tr>\n
258<\/td>\n12.8 Control Chart Analysis <\/td>\n<\/tr>\n
261<\/td>\n12.9 Summary, Analysis, and Conclusion <\/td>\n<\/tr>\n
262<\/td>\n12.10 Exercises <\/td>\n<\/tr>\n
265<\/td>\nReferences <\/td>\n<\/tr>\n
268<\/td>\n13. Economic Order Quantity for Inventory Control
13.1 Introduction
13.2 Costs Associated with Carrying Inventory
13.2.1 Ordering Costs <\/td>\n<\/tr>\n
269<\/td>\n13.2.2 Carrying Costs <\/td>\n<\/tr>\n
271<\/td>\n13.2.3 Total Inventory Cost
13.3 Economic Order Quantity <\/td>\n<\/tr>\n
272<\/td>\n13.3.1 Derivation of EOQ <\/td>\n<\/tr>\n
273<\/td>\n13.3.2 Assumptions of the EOQ Model <\/td>\n<\/tr>\n
274<\/td>\n13.4 EOQ Example
13.5 Reorder Point <\/td>\n<\/tr>\n
275<\/td>\n13.5.1 Case where L \u00d7 S < EOQ <\/td>\n<\/tr>\n
276<\/td>\n13.5.2 Case where L \u00d7 S > EOQ
13.6 Sensitivity of EOQ Model <\/td>\n<\/tr>\n
277<\/td>\n13.7 Average Inventory
13.8 Weaknesses of the EOQ Model <\/td>\n<\/tr>\n
278<\/td>\n13.9 Safety Stock <\/td>\n<\/tr>\n
279<\/td>\n13.9.1 Setting the Safety Stock Level <\/td>\n<\/tr>\n
280<\/td>\n13.10 EOQ with Back-Ordering <\/td>\n<\/tr>\n
283<\/td>\n13.10.1 Back-Ordering Example
13.11 Ordering with Quantity Discounts <\/td>\n<\/tr>\n
284<\/td>\n13.11.1 Quantity Discounts Example <\/td>\n<\/tr>\n
285<\/td>\n13.12 Exercises <\/td>\n<\/tr>\n
286<\/td>\nReferences <\/td>\n<\/tr>\n
288<\/td>\nAppendix 1 Case Study for a Risk Plan: Kapi\u2018olani Boulevard
A1.1 Introduction
A1.2 Background <\/td>\n<\/tr>\n
289<\/td>\nA1.3 Risk Management
A1.3.1 Roundabout at Kapi\u2018olani Boulevard and Ward Avenue <\/td>\n<\/tr>\n
291<\/td>\nA1.4 Risk Identification
A1.4.1 Risk Identification for the Roundabout at Kapi\u2018olani
\n Boulevard and Ward Avenue <\/td>\n<\/tr>\n
292<\/td>\nA1.5 Risk Assessment <\/td>\n<\/tr>\n
294<\/td>\nA1.5.1 Risk Assessment for the Roundabout at Kapi\u2018olani
\n Boulevard and Ward Avenue <\/td>\n<\/tr>\n
295<\/td>\nA1.6 Risk Analysis <\/td>\n<\/tr>\n
296<\/td>\nA1.6.1 Risk Analysis for the Roundabout at Kapi\u2018olani
\n Boulevard and Ward Avenue <\/td>\n<\/tr>\n
297<\/td>\nA1.7 Risk Mitigation and Planning <\/td>\n<\/tr>\n
298<\/td>\nA1.8 Risk Allocation <\/td>\n<\/tr>\n
300<\/td>\nA1.9 Risk Monitoring and Updating
A1.9.1 Risk Monitoring and Updating for the Roundabout at
\n Kapi\u2018olani Boulevard and Ward Avenue
A1.10 General Discussion <\/td>\n<\/tr>\n
301<\/td>\nA1.11 Case-Study Problem <\/td>\n<\/tr>\n
303<\/td>\nReferences <\/td>\n<\/tr>\n
304<\/td>\nAppendix 2 Example Contingency Fund Evaluation Problem
A2.1 Steps to Solution <\/td>\n<\/tr>\n
312<\/td>\nIndex <\/td>\n<\/tr>\n
320<\/td>\nAbout the Author <\/td>\n<\/tr>\n<\/table>\n","protected":false},"excerpt":{"rendered":"

Quantitative Risk Management and Decision Making in Construction<\/b><\/p>\n\n\n\n\n
Published By<\/td>\nPublication Date<\/td>\nNumber of Pages<\/td>\n<\/tr>\n
ASCE<\/b><\/a><\/td>\n2017<\/td>\n321<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"featured_media":170094,"template":"","meta":{"rank_math_lock_modified_date":false,"ep_exclude_from_search":false},"product_cat":[2660],"product_tag":[],"class_list":{"0":"post-170091","1":"product","2":"type-product","3":"status-publish","4":"has-post-thumbnail","6":"product_cat-asce","8":"first","9":"instock","10":"sold-individually","11":"shipping-taxable","12":"purchasable","13":"product-type-simple"},"_links":{"self":[{"href":"https:\/\/pdfstandards.shop\/wp-json\/wp\/v2\/product\/170091","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pdfstandards.shop\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/pdfstandards.shop\/wp-json\/wp\/v2\/types\/product"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/pdfstandards.shop\/wp-json\/wp\/v2\/media\/170094"}],"wp:attachment":[{"href":"https:\/\/pdfstandards.shop\/wp-json\/wp\/v2\/media?parent=170091"}],"wp:term":[{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/pdfstandards.shop\/wp-json\/wp\/v2\/product_cat?post=170091"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/pdfstandards.shop\/wp-json\/wp\/v2\/product_tag?post=170091"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}