Investigation on predictive policing adoption, innovative officer performance and crime mitigation among Abu Dhabi police
In the face of rapid technological advancements and globalization, Abu Dhabi Police encounters challenges in the adoption of predictive policing. This approach, characterized by technological integration, data privacy concerns, and potential resistance among law enforcement personnel, requires overc...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2024
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| Online Access: | http://eprints.utem.edu.my/id/eprint/28333/1/Investigation%20on%20predictive%20policing%20adoption%2C%20innovative%20officer%20performance%20and%20crime%20mitigation%20among%20Abu%20Dhabi%20police.pdf http://eprints.utem.edu.my/id/eprint/28333/2/Investigation%20on%20predictive%20policing%20adoption%2C%20innovative%20officer%20performance%20and%20crime%20mitigation%20among%20Abu%20Dhabi%20police.pdf http://eprints.utem.edu.my/id/eprint/28333/ https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=124285 |
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| Summary: | In the face of rapid technological advancements and globalization, Abu Dhabi Police encounters challenges in the adoption of predictive policing. This approach, characterized by technological integration, data privacy concerns, and potential resistance among law enforcement personnel, requires overcoming obstacles such as training requirements and adapting to new methodologies. The global trend of widespread adoption of predictive policing, leveraging artificial intelligence and big data, underscores the urgency to combat crime, enhance surveillance, and keep law enforcement agencies abreast of criminal activities. In Abu Dhabi Police, predictive policing emerges as a potential linchpin in the criminal justice system, aiding investigations and bolstering public safety initiatives. Nonetheless, uncertainties surround the adoption behavior of this technological paradigm, prompting the study to delve into how predictive policing, incorporating key components of artificial intelligence and big data, can effectively mitigate crime through officer training and collaborative learning within the General Command of Abu Dhabi Police. The research draws on theoretical foundations such as activity theory, complexity theory, crime theory, and technology adoption to establish a conceptual framework for analysis. Embracing a quantitative and systematic approach rooted in positivism, the study employs a deductive approach for theoretical inference, employing theory and hypotheses to validate evidence in the field. A survey targeting 2,500 police officers engaged in crime scene management at Abu Dhabi Police, with a sample size of 357 (n = 357) using a fairly stratified sampling approach within the criminal security sector, serves as the primary data collection method. The study utilizes a validated survey questionnaire, emphasizing validity and reliability to enhance overall research credibility. Prior to the main data collection, a pilot study was conducted to validate the data collection tool. The findings underscore that the adoption of predictive policing enhances officer performance in innovation, collaborative learning, and overall crime mitigation. Notably, the study reveals a positive correlation between predictive policing and innovative officer performance, with officer innovation performance subsequently positively impacting crime reduction performance. Collaborative learning serves as a significant mediator, enhancing the effect of officer innovation on crime reduction performance within Abu Dhabi Police. The implications of this study extend to government, corporate entities, academia, and society, offering insights into the transformative potential of predictive policing in enhancing law enforcement effectiveness and public safety. |
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