University of Central Florida STARS Electronic Theses and Dissertations, 2004-2019 2006 Avl And Response Time Reduction: Image And Reality Charles Russo University of Central Florida Part of the Criminology and Criminal Justice Commons Find similar works at: https://stars.edu/etd University of Central Florida Libraries http://library.edu This Doctoral Dissertation (Open Access) is brought to you for free and open access by STARS. It has been accepted for inclusion in Electronic Theses and Dissertations, 2004-2019 by an authorized administrator of STARS. For more information, please contact STARS@ucf. STARS Citation Russo, Charles, "Avl And Response Time Reduction: Image And Reality" (2006).
Electronic Theses and Dissertations, 2004-2019.edu/etd/814 AVL AND RESPONSE TIME REDUCTION: IMAGE AND REALITY by CHARLES W. University of Central Florida, 1992 M. University of Central Florida, 1995 M. University of Central Florida, 1996 A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Public Affairs Program in the College of Health and Public Affairs at the University of Central Florida Orlando, Florida Fall Term 2006 Major Professor: Raymond Surette © 2006 Charles W.
Russo ii ABSTRACT Automatic vehicle locator (AVL) systems, utilizing military’s global positioning system, may impact response time to law enforcement calls for service. In order to evaluate the impacts of AVL on response time to calls for service at the Altamonte Springs Police Department (ASPD), computer aided dispatch (CAD) data from years 1999 to 2003 were analyzed. The analysis of each of the data sets consisted of an initial sequence chart, an analysis of variance (ANOVA), a means plot and a linear regression. Interviews of ASPD personnel were conducted to understand user perceptions of AVL.
Based on the ANOVA results, trends indicate that weekly response time was significantly lower during the AVL partial implementation period than during the pre or post AVL stages across all categories of data analyzed. Based on the regression results, trends indicate that the overall impact of AVL on response time for all categories analyzed is flat and show AVL as having no overall impact on response time across all calls for service analyzed. An exception to this is the findings related to Priority 3 calls for service; however this exception can be attributed to performance during the pre AVL implementation stage. These results do not suggest a capability for AVL to reduce response time to calls for service in a meaningful comprehensive way.
Thus, the study’s hypotheses are not supported. iii TABLE OF CONTENTS CHAPTER 1 – INTRODUCTION ……………………………………………. 1 Altamonte Springs Police Department – A Community Policing Agency ………………………………………………………. 4 Military Technology Applications in Domestic Law Enforcement ………………………………………………….
6 CHAPTER 2 – LITERATURE REVIEW ……………………………………… 14 Introduction …………………………………………………. 14 The Dismissal of Police Response Time ……………………. 16 Citizen Delay and the Reporting of Crime …………………. 19 Citizen Satisfaction and the Reemergence of Police Response Time - Why Police Response Time is Important to Administrators ……………………………………………….
21 Call Priority Levels …………………………………………. 26 Community Policing and Response Time ……………………. 27 AVL and Community Policing ………………………………. 31 Technology and Response Time …………………………….
31 National Emergency Number: 9-1-1 …………………………. 35 CHAPTER 3 – RESEARCH METHODOLOGY ……………………………… 39 Quantitative Methods ………………………………………… 39 Response Time Data …………………………………………. 46 Combined Data Set Analysis (All Priority Calls) ……………. 50 Priority 3 Data Set Analysis ………………………………….
56 Priority 2 Data Set Analysis …………………………………. 61 Priority 1 Data Set Analysis …………………………………. 67 Summary of Statistical Analysis ……………………………. 85 Summary of Findings ………………………………………… 85 Limitation of this Study ……………………………………… 87 Unresolved AVL Issues ……………………………………… 89 Law Enforcement, Community Policing and AVL ………….
89 Technology and Law Enforcement Administrators …………. 92 The Future of AVL in Law Enforcement Applications ……. 94 iv APPENDIX A: SPSS SYNTAX ……………………………………………… 98 APPENDIX B: ALL CALLS FOR SERVICE REGRESSION RESIDUAL ANALYSIS ……………………………………………………………………. 100 APPENDIX C: PRIORITY 3 CALLS FOR SERVICE REGRESSION RESIDUAL ANALYSIS ……………………………………………………….
104 APPENDIX D: PRIORITY 2 CALLS FOR SERVICE REGRESSION RESIDUAL ANALYSIS ………………………………………………………. 108 APPENDIX E: PRIORITY 1 CALLS FOR SERVICE REGRESSION RESIDUAL ANALYSIS ………………………………………………………. 112 APPENDIX F: QUANTITATIVE ANALYSIS SUMMARY TABLES ………. 116 APPENDIX G: ALARM CALLS FOR SERVICE DATA SET ANALYSIS.
119 APPENDIX H: ASSIST CALLS FOR SERVICE DATA SET ANALYSIS …. 128 APPENDIX I: CRASH CALLS FOR SERVICE DATA SET ANALYSIS …. 137 APPENDIX J: DISTURBANCE CALLS FOR SERVICE DATA SET ANALYSIS ……………………………………………………………………. 145 APPENDIX K: SUSPICIOUS PERSON CALLS FOR SERVICE DATA SET ANALYSIS …………………………………………………………………….
154 APPENDIX L: IMPLIED CONSENT ………………………………………. 162 APPENDIX M: INTERVIEW SUMMARIES ………………………………. 172 v LIST OF FIGURES Figure 1 – Call for Service Timeline ……………………………………………. 15 Figure 2 – Calls for Service Indicating Priority per Year ……………………… 47 Figure 3 – Sequence Chart of All Calls for Service Week 1 to Week 265 (Response Time Mean in Seconds, Time in Weeks) …………………………… 51 Figure 4 – Sequence Chart of Priority 3 Calls for Service Week 1 to Week 265 (Response Time Mean in Seconds, Time in Weeks) …………………………… 57 Figure 5 – Sequence Chart of Priority 2 Calls for Service Week 1 to Week 265 (Response Time Mean in Seconds, Time in Weeks) …………………………… 63 Figure 6 – Sequence Chart of Priority 1 Calls for Service Week 1 to Week 265 (Response Time Mean in Seconds, Time in Weeks) …………………………… 68 vi LIST OF TABLES Table 1 – ASPD AVL Implementation Timeline ……………………………….
39 Table 2 – Priority 2 Calls for Service (Frequency) by Classification …………. 48 Table 3 – Priority 1 Calls for Service (Frequency) by Classification …………. 49 Table 4 – Priority 3 Calls for Service (Frequency) by Classification …………. 49 Table 5 – Individual Call Type Analysis ……………………………………….
50 Table 6 – ANOVA of All Calls for Service Response Time Mean ……………. 52 Table 7 – All Calls for Service Outliers ………………………………………. 53 Table 8 – ANOVA of All Calls for Service Response Time Outliers Mean …. 53 Table 9 – Descriptive Statistics for Response time for All Calls for Service in Seconds ………………………………………………………………………….
54 Table 10 – All Calls for Service Regression …………………………………… 55 Table 11 – ANOVA of Priority 3 Calls for Service Response Time Mean ……. 58 Table 12 – Priority 3 Calls for Service Outliers ………. 58 Table 13 – ANOVA of Priority 3 Calls for Service Response Time Outliers Mean 58 Table 14 – Descriptive Statistics for Response time for Priority 3 Calls for Service in Seconds ……………………………………………………………… 59 Table 15 – Priority 3 Calls for Service Isolated Regression …………………… 60 Table 16 – ANOVA of Priority 2 Calls for Service Response Time Mean ……. 64 Table 17 – Priority 2 Calls for Service Outliers ……………………………….
64 Table 18 – ANOVA of Priority 2 Calls for Service Response Time Outliers Mean 64 Table19 – Descriptive Statistics for Response time for Priority 2 Calls for Service in Seconds ………………………………………………………………………. 65 Table 20 – Priority 2 Calls for Service Regression ……………………………. 65 Table 21 – ANOVA of Priority 1 Calls for Service Response Time Mean ……. 69 Table 22 – Priority 1 Calls for Service Outliers ……………………………….
69 Table 23 – ANOVA of Priority 1 Calls for Service Response Time Outliers Mean 69 Table 24 – Descriptive Statistics for Response time for Priority 1 Calls for Service in Seconds ……………………………………………………………… 70 Table 25 – Priority 1 Calls for Service Regression ……………………………. 70 Table 26 - Findings ANOVA Summary with Outliers Isolated/Removed ……. 72 Table 27 - Findings Regression Summary with Outliers Isolated/Removed …. 73 vii INTRODUCTION The adaptation of military technology for use in United States law enforcement applications has a long history.
Immediately after World War I, the law enforcement community demonstrated an interest in the use of chemical agents to control both criminals and unruly crowds. They had hoped chemical agents would have the same effects on its intended targets here domestically as they had on the opposing forces in the battlefields of Europe (Edwards, Granfield & Onnen, 1997). Other later technological adoptions include such items as protective barrier systems, personal protective equipment, night vision devices, first responder and communications equipment. This project will focus on communications equipment, particularly the military’s global positioning system and law enforcement applications.
It will focus on response time to law enforcement calls for service. A specific working example of these applications is studied within a Florida municipal police department. Altamonte Springs Police Department – A Community Policing Agency With a resident population of over 40,000 and a typical daytime population in excess of 80,000 people, the Altamonte Springs Police Department, FL (ASPD) represents one of the over 4500 of all law enforcement agencies in the United States serving a population of between 10,000 and 100,000 people (Reaves & Goldberg, 1999). ASPD is also one of the 93 percent of agencies serving a population between 10,000 and 100,000 people that is practicing community policing strategies (Bureau of Justice Statistics [BJS], 2006).
1 In the spring of 2003, the Altamonte Springs Police Department, FL (ASPD) integrated an automatic vehicle locator (AVL) system into their computer aided dispatch1 (CAD) procedures. AVL relies on the military’s global positioning system (GPS) and its system of thirty satellites and five ground stations for its data (GPS Satellite, 2004). The intent of this integration was to improve response time to calls for service for field units. With this system in place, the dispatchers can identify the location of all field units superimposed on a street map.
Supplied with real time vehicle locations, it was hypothesized that supervisors and dispatchers would be better able to direct the closest field unit to the call thus reducing the amount of time the caller has to wait for a field unit. Support for reducing response time today is articulated strongest in the community policing literature. Community policing literature suggests that response time should be positively impacted by the use of AVL. Response time reduction is important, community policing argues, because of response time’s assumed relationship to citizen satisfaction.
The specific question addressed by this study that has not been answered in community policing or other literature is whether AVL integration will truly reduce the response time to calls for service for field units. To answer this question, this project will analyze CAD data from the ASPD. Conclusions drawn 1 Computer Aided Dispatch (CAD) – Software, in conjunction with hardware, that suggests specific patrol units to dispatch for a call for service based on predetermined parameters, such as call location, call type, unit location in reference to the call and the department’s standard operating procedures (SOPs) (VisionAIR, 2000). 2 from this study have implications to a large number of law enforcement agencies practicing community policing because of their desire to improve response time to calls for service.
Modern community oriented policing has only been an accepted practice for police agencies since the early 1980s when Herman Goldstein forwarded his views of problem oriented policing (POP). Before that, policing was conducted in a more “traditional” setting, with officers walking and driving around neighborhoods and keeping the peace (Wrobleski & Hess, 2000). Popular with both police and residents, it was not uncommon for citizens to be on a first-name basis with the local law enforcement (Wrobleski & Hess, 2000). Known as the officer friendly era, this was the time period preceding the crime busters and g-men era popularized in media and entertainment.
While some of this is glamorized in old movies, there is some truth to the fact that police and community worked together more than they do now. There was a sense of common cause that does not exist today (Wrobleski & Hess, 2000). Many contemporary police departments, even if their efforts are misguided, are trying to return to those days of working together to prevent crime and reduce the fear of crime. A core element of these efforts is to reduce response time.
Departments feel that if they can improve response time to calls for service, they can improve citizen satisfaction with police service. If citizen satisfaction with police service is improved, departments and citizens can move closer towards those lost days of law enforcement community cooperation (International City/County Management Association, 1997; Spelman & Brown, 1984).