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E-grāmata: Multiple Objective Analytics for Criminal Justice Systems [Taylor & Francis e-book]

(University of Louisville, Kentucky, USA)
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"Criminal justice systems are complex and difficult to design and operate. This is due to their many interacting parts, and their dynamic and probabilistic nature, as well as their interfaces with other systems. This book reviews the use of analytics to address issues in criminal justice system and discusses the various sources of data associated with the systems. This book is meant to be used by those who would like 1) an introduction to criminal justice systems and 2) an illustration of how some of thevarious methodologies of analytics can be used to address specific issues in criminal justice systems. This book will be of interest to faculty, students, and researchers in schools/departments of criminal justice, law, public affairs, political science,industrial engineering, and management. In addition, the book should be of use to government analysts who study the effects of criminal programs and laws"--

Criminal justice systems are complex and difficult to design and operate. This is due to their many interacting parts, and their dynamic and probabilistic nature, as well as their interfaces with other systems. This book reviews the use of analytics to address issues in criminal justice system and discusses the various sources of data associated with the systems.

This book is meant to be used by those who would like 1) an introduction to criminal justice systems and 2) an illustration of how some of the various methodologies of analytics can be used to address specific issues in criminal justice systems.

This book will be of interest to faculty, students, and researchers in schools/departments of criminal justice, law, public affairs, political science, industrial engineering, and management. In addition, the book should be of use to government analysts who study the effects of criminal programs and laws.

Preface xi
Acknowledgments xv
Author Biography xvii
1 Criminal Justice Systems in the United States
1(24)
1.1 Introduction
1(1)
1.2 Crime: Definition, Classification, and Costs
1(2)
1.3 Reasons for Crime
3(1)
1.4 Criminal Justice Systems: Definition, Laws, Resources, and Processes
3(2)
1.5 Data Relating to Criminal Justice in the United States
5(13)
1.5.1 Data and Models for Decision Making
5(3)
1.5.2 The United Crime Reporting Program, the Summary Reporting System, and Crime Rates
8(5)
1.5.3 Data on the Solving of Crimes
13(1)
1.5.4 The National Incidence-Based Reporting System, the Law Enforcement Officers Killed and Assaulted Program, and the Hate Crime Statistics Program
14(4)
1.6 Data Comparing Criminal Justice in the United States to Other Countries
18(4)
1.7 Issues Associated with Criminal Justice Systems in the United States
22(1)
1.8 Summary and a Look Forward
23(2)
2 Analytics and Criminal Justice Systems
25(34)
2.1 Introduction
25(1)
2.2 Decisions Associated with Criminal Justice Systems and Why They Are Difficult to Make
25(9)
2.2.1 Decisions in General
25(1)
2.2.2 Decision Makers and Stakeholders for Criminal Justice Systems
26(2)
2.2.3 Decisions for Criminal Justice Systems
28(1)
2.2.4 Analytics and Operations Research
29(2)
2.2.5 Complexities Which Make Decisions Difficult for Criminal Justice Systems
31(3)
2.3 Analytic Methodologies for Dealing with Criminal Justice Systems
34(21)
2.3.1 Problem Structuring Methods
34(2)
2.3.1.1 An Illustrative Example of Problem Structuring for Juvenile Crime
36(3)
2.3.2 Generating Multiple Objectives and Multiple Performance Measures for a Decision Situation
39(1)
2.3.2.1 An Illustrative Example: Determining Objectives and Performance Measures for Setting Up a Syringe Exchange Program
40(7)
2.3.3 Cost-Benefit Analysis
47(1)
2.3.4 Multiattribute Value Functions and Multiattribute Utility Functions
48(2)
2.3.4.1 An Illustrative Example: Using a Multiattribute Utility Function for the Decision of Whether to Use a Court-Appointed Attorney
50(4)
2.3.5 Simulation Modeling and Analysis
54(1)
2.4 A Review of Selected Applications of Analytics to Criminal Justice Systems
55(4)
3 Using Multiple Objective Analytics to Address Issues Associated with Criminal Justice Systems
59(40)
3.1 Introduction
59(1)
3.2 Privatization of Prisons
60(15)
3.2.1 Data on Prisons and the Motivation for Privatization
60(1)
3.2.2 Advantages and Disadvantages of Privatization
61(1)
3.2.3 Democrats vs. Republicans with Respect to Privatization
62(1)
3.2.4 The Literature on Private vs. Public Prisons
62(4)
3.2.5 An Illustrative Example: Development of a Multiattribute Value Function to Compare Prisons
66(1)
3.2.5.1 Determination of Objectives and Attributes
66(5)
3.2.5.2 Assessment of the MAV Function
71(3)
3.2.5.3 Ranking Proposals from Private Companies
74(1)
3.3 Bail Reform
75(24)
3.3.1 The Bail Process
75(1)
3.3.2 Difficulties Associated with the Current Bail Process
76(1)
3.3.3 Trends in Bail Reform
77(2)
3.3.4 Advantages and Disadvantages of Keeping a Defendant Incarcerated Prior to Trial
79(1)
3.3.5 Current Approaches and Suggestions for the Bail Process
80(3)
3.3.6 A Multiple Objective, Decision Theoretic Model for Selection of Pretrial Conditions
83(1)
3.3.6.1 Stakeholders
83(1)
3.3.6.2 Alternatives and Process Description
84(2)
3.3.6.3 Input Parameters, Probabilities, and Control Variables for the Model
86(3)
3.3.6.4 Attributes for the Multiattribute Utility Function
89(1)
3.3.6.5 Criterion, Alternatives, Parameters, and Multiattribute Utility Function for the Example
90(4)
3.3.6.6 The Simulation Model and Results
94(3)
3.3.6.7 Final Discussion of the Model
97(2)
4 Using Multiple Objective Analytics to Improve Federal Laws
99(18)
4.1 Introduction
99(1)
4.2 The Violent Crime Control and Law Enforcement Act of 1994
100(6)
4.2.1 Impetus for the Law
100(1)
4.2.2 Elements of the Law
100(1)
4.2.3 Implementation Results
101(1)
4.2.4 Detractors and Supporters
102(1)
4.2.5 Motivation of Criminals
103(1)
4.2.6 The Law's Effect on Crime
103(1)
4.2.7 A Cost-Benefit Analysis of the COPS Program
104(1)
4.2.8 The Law and Incarceration Rates
105(1)
4.3 Criminal Justice Reform Act of 2018 (The First Step Act)
106(11)
4.3.1 Impetus for the Law
106(1)
4.3.2 Provisions of the Law
107(1)
4.3.3 Criticisms of the Law
107(1)
4.3.4 The Prisoner Assessment Tool Targeting Estimated Risks and Needs (PATTERN)
108(2)
4.3.5 An Illustrative Example: Optimizing Over Controls for the First Step Act
110(7)
References 117(16)
Index 133
Gerald W. Evans is Professor Emeritus in the Department of Industrial Engineering at the University of Louisville (UL). His research and teaching interests lie in the areas of multiciteria decision analysis, simulation modeling and analysis, optimization, logistics and project management.

Previous positions include Industrial Engineer for the Department of the Army, and Senior Research Engineer for General Motors Research Laboratories. He has also served as an ASEE Faculty Fellow at NASA's Langley Research Center and Kennedy Space Center.

Dr. Evans received his BS in Mathematics in 1972, his MS in Industrial Engineering in 1974, and his PhD in Industrial Engineering in 1979, all from Purdue University.

Dr. Evans has served as Principal Investigator or Co-Principal Investigator on over $5 million of funded research from organizations such as the National Science Foundation, the Defense Logistics Agency, NASA, the National Institute for Hometown Security, Louisville Metro Government, General Electric, and United Parcel Services among other organizations. In addition, he has done consulting work in the areas of simulation modeling and analysis, project management, and economic analysis for a variety of organizations.

He has published approximately 100 papers in various journals and conference proceedings. His paper: "An Overview of Techniques for Solving Multiobjective Mathematical Programs," published in 1984 was listed as one of the most cited publications in Management Science over the last 50 years (from the 2004 commemorative CD: Celebrating 50 years of Management Science, INFORMS Publication). In addition, his co-authored paper: S.J. Ellspermann, G.W. Evans, and M. Basadur, "The Impact of Training on the Formulation of Ill Structured Problems," Omega 35:2, pp. 221-236, April 2007 received the 12th Annual Citation of Excellence Award as one of the top 50 management articles out of 15,000 articles published in 2007 (Emerald Management Reviews), 2008.

Dr. Evans is the author of Multiple Criteria Decision Analysis for Industrial Engineering: Methodology and Applications, CRC Press, Taylor and Francis Group, Boca Raton, FL, 2017, and co-editor of the book: Analytics, Operations, and Strategic Decision Making in the Public Sector, Hershey, PA.: IGI Global, 2019. He has also served as co-editor of the Proceedings of the Winter Simulation Conference in 1993 and 1999, and of a special issue of Computers and Industrial Engineering entitled "Multi-Criteria Decision Making in Industrial Engineering" (November, 1999). He has been a reviewer for approximately 25 different journals, an Associate Editor for the Institute of Industrial Engineers (IIE) Transactions, a Director of the Operations Research Division of IIE, and a Vice President of IIE.

In addition, he has directed or co-directed the research of approximately 90 masters students and 20 doctoral students while at the University of Louisville.

Dr. Evans has received the Fellow Award and the Operations Research Division Award from Institute of Industrial and Systems Engineering, the Moving Spirit Award from INFORMS for his work with the UL INFORMS Student Chapter, the Dean's Award for Outstanding Graduate Teaching; and he was a University of Louisville nominee for Outstanding Faculty of Adult Learners for Kentukiana Metroversity Inc. He is listed in American Men and Women of Science, Who's Who in Engineering, and Who's Who in America.
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