My Account Log in

1 option

Decision science for housing and community development : localized and evidence-based responses to distressed housing and blighted communities / Michael P. Johnson, Jeffrey M. Keisler, Senay Solak, David A. Turcotte, Armagan Bayram, Rachel Bogardus Drew.

Van Pelt Library HN90.C6 J64 2016
Loading location information...

Available This item is available for access.

Log in to request item
Format:
Book
Author/Creator:
Johnson, Michael P., 1964- author.
Series:
Wiley series in operations research and management science
Language:
English
Subjects (All):
Community development--United States--Decision making.
Community development.
Urban renewal--United States--Decision making.
Urban renewal.
Housing rehabilitation--United States--Decision making.
Housing rehabilitation.
Decision making.
United States.
Physical Description:
xxxvi, 374 pages ; 25 cm.
Place of Publication:
Hoboken, New Jersey : John Wiley & Sons, Inc., [2016]
Contents:
1 Introduction: Community-Based Organizations, Neighborhood-Level Development, and Decision Modeling 1
1.1 Challenges and Opportunities for Housing and Community Development in the US 1
1.2 Community Development in the United States 6
1.3 Big Data, Analytics and Community Development 9
1.4 The Foreclosure Crisis: Problem, Impacts, and Responses 11
1.5 Community-Based Operations Research: A Novel Approach to Support Local Development 13
1.6 Why This Book Now? 19
1.7 Book Description 21
1.8 Conclusion 24
Section 1 Policy and Practice in Foreclosed Housing and Community Development 27
2 Foreclosed Housing Crisis and Policy and Planning Responses 29
2.1 Roots of the Foreclosed Housing Crisis 29
2.2 Impacts of the Crisis 32
2.2.1 Foreclosure Rates 33
2.2.2 Home Equity and Wealth 34
2.2.3 Health, Education, and Household Mobility 36
2.2.4 Disamenities and Spillover Effects 37
2.2.5 Market-Level Consequences 38
2.3 Responses to the Crisis 39
2.4 Effectiveness of Foreclosure Responses 41
2.5 Opportunities for Decision Modeling Responses to the Foreclosed Housing Crisis 43
3 Community Partners and Neighborhood Characteristics 45
3.1 Introduction 45
3.2 Methodology 46
3.2.1 Data Gathering Summary 46
3.2.2 Triangulation 47
3.2.3 Analysis 48
3.3 Selection of Cases 49
3.4 Case 1: The Neighborhood Developers 50
3.4.1 Organization Type and Mission 50
3.4.2 Organization Service Area and Population 55
3.4.3 Organization Engagement with Foreclosure Crisis 55
3.4.4 Organization Technical Capacity and Familiarity with Project's Analytic Methods 58
3.5 Case 2: Coalition for a Better Acre 59
3.5.1 Organization Type and Mission 59
3.5.2 Organization Service Area and Population Demographics 59
3.5.3 Organization Engagement with Foreclosure Crisis 61
3.5.4 Organization Technical Capacity and Familiarity with Project's Analytic Methods 62
3.6 Case 3: Codman Square Neighborhood Development Corporation 63
3.6.1 Organization Type and Mission 63
3.6.2 Organization Service Area and Population Demographics 63
3.6.3 Organization Engagement with Foreclosure Crisis 64
3.6.4 Organization Technical Capacity and Familiarity with Project's Analytic Methods 67
3.7 Case 4: Twin Cities Community Development Corporation 67
3.7.1 Organization Type and Mission 67
3.7.2 Organization Service Area and Population Demographics 68
3.7.3 Organization Engagement with Foreclosure Crisis 68
3.7.4 Organization Technical Capacity and Familiarity with Project's Analytic Methods 70
3.8 Case Contrast and Discussion 71
3.8.1 Role of Community Partners 71
3.8.2 Adaptation of Case Study Theory for Our Project 73
3.9 Conclusion 74
4 Analytic Approaches to Foreclosure Decision Modeling 75
4.1 Introduction 75
4.2 Analysis of Community Partners and their Service Areas 81
4.3 Localized Foreclosure Response 94
4.4 Opportunities for Research-Based Analytic Responses to Foreclosures 97
4.5 Solution Design for Community Development using Community-Based Operations Research 102
4.6 Where Do We Go From Here? 104
Section 2 Values, Metrics and Impacts for Decision Modeling 107
5 Value-Focused Thinking: Defining, Structuring and Using CDC Objectives in Decision Making 109
5.1 Introduction 109
5.1.1 Overview 109
5.1.2 Values and Objectives in Decisions 109
5.1.3 Values and Objectives in Community-Based Organization/CDC Decisions 110
5.1.4 Utility Functions and Decision Making 111
5.1.5 Multiattribute Utility Functions 112
5.1.6 Value-Focused Thinking 114
5.1.7 VFT as Soft OR and Problem Structuring Method 115
5.1.8 The Resource Allocation Decision Frame 115
5.1.9 Plan 118
5.2 Methods 118
5.2.1 Linear Additive Assumption 118
5.2.2 Defining the Mathematical Model as a Set of Linear Equations 119
5.2.3 Structuring 120
5.2.4 Obtaining Inputs 122
5.3 Cases 123
5.3.1 Simulated CDC 123
5.3.2 Codman Square Neighborhood Development Corporation 130
5.3.3 Twin Cities Community Development Corporation 138
5.4 Common and Contingent Objectives for CDCs 143
5.5 Lessons for Applying VFT to CBOs 151
6 Characteristics of Acquisition Opportunities: Strategic Value 153
6.1 Introduction 153
6.2 Problem Description 155
6.2.1 Policy Motivation 155
6.2.2 Theoretical Foundations 157
6.3 Model Development 159
6.3.1 Sets and Indexes 159
6.3.2 Parameters and Functions 160
6.3.3 Individual Resident Frame 160
6.3.4 CDC Frame 161
6.4 Case Study: The Neighborhood Developers 162
6.4.1 Site Description 162
6.4.2 Model Computations 166
6.5 Discussion 170
6.5.1 Policy Analysis 170
6.5.2 Implications for Modeling and Practice 171
6.6 Conclusion 172
7.1 Introduction 175
7.2 Property Value Changes as a Social Impact of Foreclosed Housing 176
7.3 A Model of PVI for Foreclosed Housing 178
7.4 The PVI Model 180
7.4.1 The Foreclosure Process 181
7.4.2 Modeling Foreclosure Phase Transitions with a Markov Chain 182
7.4.3 Estimation of Proximate Property Value Impacts 184
7.5 Case Study: The Neighborhood Developers 186
7.5.1 Data and Model Specifications 186
7.5.2 Computational Results 190
7.5.3 Clustering Effects 191
7.6 Discussion 196
7.7 Model Validity and Limitations 199
7.7.1 Nonlinearities in Aggregate Impacts 199
7.7.2 Representativeness of Data Sources 200
7.7.3 Sensitivity to Transition Probabilities 200
7.7.4 Impacts of Multiple Foreclosures 200
7.7.5 Wider Range of Social Impacts 201
7.7.6 Model Validity 201
7.8 Conclusion 202
Section 3 Prescriptive Analysis and Findings 205
8 Social Benefits of Decision Modeling for Property Acquisition 207
8.1 Introduction 207
8.2 CDC Practice in Foreclosed Housing Acquisition 209
8.3 A Multiobjective Model of Foreclosed Housing Acquisition 212
8.3.1 Decision Model 212
8.3.2 Input Data 215
8.4 Model Solutions 220
8.4.1 Constraint on Number of Units Acquired 221
8.4.2 Budget Constraint 233
8.5 Discussion 243
8.6 Conclusion and Next Steps 244
9 Acquiring And Managing A Portfolio Of Properties 247
9.1 Introduction 247
9.2 Dynamic Modeling of the Foreclosed Housing Acquisition Process 248
9.3 Model Formulation 251
9.4 Policy Analysis Under Different Fund Accessibility Cases 253
9.4.1 Acquisition Policies Under No Fund Expiration 253
9.4.2 Acquisition Policies Under Fund Expiration 257
9.5 Case Study: Codman Square Neighborhood Development Corporation 259
9.5.1 Data Description 260
9.5.2 Implementation Under No Fund Expiration 261
9.5.3 Implementation Under Fund Expiration 265
9.6 Conclusion 269
10 Strategic Acquisition Investments Across Neighborhoods 273
10.1 Introduction 273
10.2 General Framework of FRAP 275
10.3 Model Formulation 276
10.3.1 Methodology Overview 276
10.3.2 FHAP with Simple Resource Allocation 277
10.3.3 FHAP with Gradual Uncertainty Resolution 282
10.3.4 Model Variations and Extensions 286
10.4 Case Study: Codman Square Neighborhood Development Corporation 289
10.4.1 Data Description and Parameter Justification 289
10.4.2 Resource Allocations and Impacts of Model Parameters 292
10.4.3 Policy Implications for CDCs 303
10.5 Conclusion 304
11 Conclusion: Findings and Opportunities in Decision Analytics for Foreclosure Response and Community Development 307
11.1 Introduction 307
11.2 Key Findings 308
11.2.1 Foreclosure Crisis and Responses 308
11.2.2 Engagement with Community-Based Organizations 308
11.2.3 Decision-Modeling Fundamentals: Values and Attributes 309
11.2.4 Foreclosed Property Strategy Design Using Decision Models 310
11.3 Research Insights 312
11.4 Lessons Learned 314
11.5 Community-Based Operations Research: A Reassessment 316
11.6 Research Extensions 319
11.7 Conclusion 320.
Notes:
Includes bibliographical references and index.
Other Format:
Online version: Johnson, Michael P., 1964- author. Decision science for housing and community development
ISBN:
9781118974995
1118974999
OCLC:
915774373

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Library Catalog Using Articles+ Library Account