Decision analysis has become widely recognized as an important process for translating science into management actions. With climate change and other systemic threats as driving forces in creating environmental and engineering problems, there is a great need for understanding decision making frameworks through a case-study based approach. Management of environmental and engineering projects is often complicated and multidisciplinary in scope and nature, thus issues that arise can be difficult to solve analytically. Multi-Criteria Decision Analysis: Case Studies in Engineering and the Environment provides detailed description of MCDA methods and tools and illustrates their applications through case studies focused on sustainability and system engineering applications.

New in the Second Edition:

Given the novelty and inherent applicability of this decision-making framework to the environmental and engineering fields, a greater number of teaching tools for this topic need to be made available. This book provides those teaching tools, covering the breadth of the applications of MCDA methodologies with clear explanations of the MCDA process. The case studies are implemented in the DECERNS software package, allowing readers to experiment and explore and to understand the full process by which environmental managers assess these problems.

This book is a great resource for professionals and students seeking to learn decision analysis techniques and apply similar frameworks to environmental and engineering projects

Decision analysis has become widely recognized as an important process for translating science into management actions. With climate change and other systemic threats as driving forces in creating environmental and engineering problems, there is a great need for understanding decision making frameworks through a case-study based approach. Management of environmental and engineering projects is often complicated and multidisciplinary in scope and nature, thus issues that arise can be difficult to solve analytically. Multi-Criteria Decision Analysis: Case Studies in Engineering and the Environment provides detailed description of MCDA methods and tools and illustrates their applications through case studies focused on sustainability and system engineering applications.

New in the Second Edition:

Given the novelty and inherent applicability of this decision-making framework to the environmental and engineering fields, a greater number of teaching tools for this topic need to be made available. This book provides those teaching tools, covering the breadth of the applications of MCDA methodologies with clear explanations of the MCDA process. The case studies are implemented in the DECERNS software package, allowing readers to experiment and explore and to understand the full process by which environmental managers assess these problems.

This book is a great resource for professionals and students seeking to learn decision analysis techniques and apply similar frameworks to environmental and engineering projects

A multidisciplinary approach to problem-solving in community-based organizations using decision models and operations research applications

A comprehensive treatment of public-sector operations research and management science, Decision Science for Housing and Community Development: Localized and Evidence-Based Responses to Distressed Housing and Blighted Communities addresses critical problems in urban housing and community development through a diverse set of decision models and applications. The book represents a bridge between theory and practice and is a source of collaboration between decision and data scientists and planners, advocates, and community practitioners.

The book is motivated by the needs of community-based organizations to respond to neighborhood economic and social distress, represented by foreclosed, abandoned, and blighted housing, through community organizing, service provision, and local development. The book emphasizes analytic approaches that increase the ability of local practitioners to act quickly, thoughtfully, and effectively. By doing so, practitioners can design and implement responses that reflect stakeholder values associated with healthy and sustainable communities; that benefit from increased organizational capacity for evidence-based responses; and that result in solutions that represent improvements over the status quo according to multiple social outcome measures. Featuring quantitative and qualitative analytic methods as well as prescriptive and exploratory decision modeling, the book also includes:

Decision Science for Housing and Community Development: Localized and Evidence-Based Responses to Distressed Housing and Blighted Communities is an ideal textbook for upper-undergraduate and graduate-level courses in decision models and applications; humanitarian logistics; nonprofit operations management; urban operations research; public economics; performance management; urban studies; public policy; urban and regional planning; and systems design and optimization. The book is also an excellent reference for academics, researchers, and practitioners in operations research, management science, operations management, systems engineering, policy analysis, city planning, and data analytics.

A multidisciplinary approach to problem-solving in community-based organizations using decision models and operations research applications

A comprehensive treatment of public-sector operations research and management science, Decision Science for Housing and Community Development: Localized and Evidence-Based Responses to Distressed Housing and Blighted Communities addresses critical problems in urban housing and community development through a diverse set of decision models and applications. The book represents a bridge between theory and practice and is a source of collaboration between decision and data scientists and planners, advocates, and community practitioners.

The book is motivated by the needs of community-based organizations to respond to neighborhood economic and social distress, represented by foreclosed, abandoned, and blighted housing, through community organizing, service provision, and local development. The book emphasizes analytic approaches that increase the ability of local practitioners to act quickly, thoughtfully, and effectively. By doing so, practitioners can design and implement responses that reflect stakeholder values associated with healthy and sustainable communities; that benefit from increased organizational capacity for evidence-based responses; and that result in solutions that represent improvements over the status quo according to multiple social outcome measures. Featuring quantitative and qualitative analytic methods as well as prescriptive and exploratory decision modeling, the book also includes:

Decision Science for Housing and Community Development: Localized and Evidence-Based Responses to Distressed Housing and Blighted Communities is an ideal textbook for upper-undergraduate and graduate-level courses in decision models and applications; humanitarian logistics; nonprofit operations management; urban operations research; public economics; performance management; urban studies; public policy; urban and regional planning; and systems design and optimization. The book is also an excellent reference for academics, researchers, and practitioners in operations research, management science, operations management, systems engineering, policy analysis, city planning, and data analytics.

This book combines the quantitative decision-informing techniques of management science and operations research with the data-centric techniques found throughout the world of analytics. The material uses only standard Excel spreadsheet features and functions for creating models. Using a step-by-step approach, readers learn a unified architecture for sensitivity, scenario, simulation, decision, and optimization analysis. Spreadsheets with numerous screenshots support visual, hands-on learning (and provide some surprising innovations). Special influence diagrams and non-intimidating but accurate terminology help explain the logic of the models and calculations. Well-structured chapters include guideposts, enrichment, and curated links to valuable external resources. Readers are encouraged to own their learning and think about future trajectories for themselves and the field. This book helps all readers quickly learn tools and concepts to use right away and to expand throughout a career. The book includes access to a companion website featuring workbooks and other valuable materials to support learning.

Decision analysis has become widely recognized as an important process for translating science into management actions. With climate change and other systemic threats as driving forces in creating environmental and engineering problems, there is a great need for understanding decision making frameworks through a case-study based approach. Management of environmental and engineering projects is often complicated and multidisciplinary in scope and nature, thus issues that arise can be difficult to solve analytically. Multi-Criteria Decision Analysis: Case Studies in Engineering and the Environment provides detailed description of MCDA methods and tools and illustrates their applications through case studies focused on sustainability and system engineering applications.

New in the Second Edition:

Given the novelty and inherent applicability of this decision-making framework to the environmental and engineering fields, a greater number of teaching tools for this topic need to be made available. This book provides those teaching tools, covering the breadth of the applications of MCDA methodologies with clear explanations of the MCDA process. The case studies are implemented in the DECERNS software package, allowing readers to experiment and explore and to understand the full process by which environmental managers assess these problems.

This book is a great resource for professionals and students seeking to learn decision analysis techniques and apply similar frameworks to environmental and engineering projects

Decision analysis has become widely recognized as an important process for translating science into management actions. With climate change and other systemic threats as driving forces in creating environmental and engineering problems, there is a great need for understanding decision making frameworks through a case-study based approach. Management of environmental and engineering projects is often complicated and multidisciplinary in scope and nature, thus issues that arise can be difficult to solve analytically. Multi-Criteria Decision Analysis: Case Studies in Engineering and the Environment provides detailed description of MCDA methods and tools and illustrates their applications through case studies focused on sustainability and system engineering applications.

New in the Second Edition:

Given the novelty and inherent applicability of this decision-making framework to the environmental and engineering fields, a greater number of teaching tools for this topic need to be made available. This book provides those teaching tools, covering the breadth of the applications of MCDA methodologies with clear explanations of the MCDA process. The case studies are implemented in the DECERNS software package, allowing readers to experiment and explore and to understand the full process by which environmental managers assess these problems.

This book is a great resource for professionals and students seeking to learn decision analysis techniques and apply similar frameworks to environmental and engineering projects

A multidisciplinary approach to problem-solving in community-based organizations using decision models and operations research applications

A comprehensive treatment of public-sector operations research and management science, Decision Science for Housing and Community Development: Localized and Evidence-Based Responses to Distressed Housing and Blighted Communities addresses critical problems in urban housing and community development through a diverse set of decision models and applications. The book represents a bridge between theory and practice and is a source of collaboration between decision and data scientists and planners, advocates, and community practitioners.

The book is motivated by the needs of community-based organizations to respond to neighborhood economic and social distress, represented by foreclosed, abandoned, and blighted housing, through community organizing, service provision, and local development. The book emphasizes analytic approaches that increase the ability of local practitioners to act quickly, thoughtfully, and effectively. By doing so, practitioners can design and implement responses that reflect stakeholder values associated with healthy and sustainable communities; that benefit from increased organizational capacity for evidence-based responses; and that result in solutions that represent improvements over the status quo according to multiple social outcome measures. Featuring quantitative and qualitative analytic methods as well as prescriptive and exploratory decision modeling, the book also includes:

Decision Science for Housing and Community Development: Localized and Evidence-Based Responses to Distressed Housing and Blighted Communities is an ideal textbook for upper-undergraduate and graduate-level courses in decision models and applications; humanitarian logistics; nonprofit operations management; urban operations research; public economics; performance management; urban studies; public policy; urban and regional planning; and systems design and optimization. The book is also an excellent reference for academics, researchers, and practitioners in operations research, management science, operations management, systems engineering, policy analysis, city planning, and data analytics.

A multidisciplinary approach to problem-solving in community-based organizations using decision models and operations research applications

A comprehensive treatment of public-sector operations research and management science, Decision Science for Housing and Community Development: Localized and Evidence-Based Responses to Distressed Housing and Blighted Communities addresses critical problems in urban housing and community development through a diverse set of decision models and applications. The book represents a bridge between theory and practice and is a source of collaboration between decision and data scientists and planners, advocates, and community practitioners.

The book is motivated by the needs of community-based organizations to respond to neighborhood economic and social distress, represented by foreclosed, abandoned, and blighted housing, through community organizing, service provision, and local development. The book emphasizes analytic approaches that increase the ability of local practitioners to act quickly, thoughtfully, and effectively. By doing so, practitioners can design and implement responses that reflect stakeholder values associated with healthy and sustainable communities; that benefit from increased organizational capacity for evidence-based responses; and that result in solutions that represent improvements over the status quo according to multiple social outcome measures. Featuring quantitative and qualitative analytic methods as well as prescriptive and exploratory decision modeling, the book also includes:

Decision Science for Housing and Community Development: Localized and Evidence-Based Responses to Distressed Housing and Blighted Communities is an ideal textbook for upper-undergraduate and graduate-level courses in decision models and applications; humanitarian logistics; nonprofit operations management; urban operations research; public economics; performance management; urban studies; public policy; urban and regional planning; and systems design and optimization. The book is also an excellent reference for academics, researchers, and practitioners in operations research, management science, operations management, systems engineering, policy analysis, city planning, and data analytics.

This book combines the quantitative decision-informing techniques of management science and operations research with the data-centric techniques found throughout the world of analytics. The material uses only standard Excel spreadsheet features and functions for creating models. Using a step-by-step approach, readers learn a unified architecture for sensitivity, scenario, simulation, decision, and optimization analysis. Spreadsheets with numerous screenshots support visual, hands-on learning (and provide some surprising innovations). Special influence diagrams and non-intimidating but accurate terminology help explain the logic of the models and calculations. Well-structured chapters include guideposts, enrichment, and curated links to valuable external resources. Readers are encouraged to own their learning and think about future trajectories for themselves and the field. This book helps all readers quickly learn tools and concepts to use right away and to expand throughout a career. The book includes access to a companion website featuring workbooks and other valuable materials to support learning.