Show simple item record

dc.contributor.authorLochu, Peter
dc.date.accessioned2021-01-27T06:11:57Z
dc.date.available2021-01-27T06:11:57Z
dc.date.issued2020
dc.identifier.urihttp://erepository.uonbi.ac.ke/handle/11295/154235
dc.description.abstractThe study examines the influence of location intelligence to law enforcement and in particular National Police Service focusing on Nairobi County for the period between 2010 and 2019. The research was necessitated by a perceived increase in crime statistics even after introduction of structural and operational reforms which were aimed to bring efficiency and effectiveness within NPS. The specific objectives of the study was to examine the extent location data supported NPS operations; to evaluate policy frameworks guiding collection, processing and storage of location data by law enforcers; and to find out NPS experiences after integrating location aware technology to its operations. To conceptualize the study in a broader context, the study made use of Crime Pattern and Rational Choice theories. The study also adopted a qualitative study approach in order to obtain subjective attitudes of respondents. Structured questionnaires and key informants formed primary data collection tools while secondary data was collected through review of relevant literature. The target population for the study was 800 employees of NPS deployed to criminal intelligence departments within Nairobi County while the sample size engaged was 260 respondents. The qualitative data collected was edited, coded and tabulated using Microsoft Excel statistical package before carrying out analysis. The study established that NPS understood the value of LD processing in ensuring success of its mission. The Service also had adequate location datasets at its disposal which was predominantly applied for predictive policing, fleet management and operational awareness. However, drawback to this asset was inadequate skilled personnel to collect and process the location data. The study further found that although there were adequate policy frameworks to support data collection and processing by NPS, the country lacked a national Spatial Data Infrastructure (SDI) to facilitate access and sharing of geographic information among government departments. Privacy concerns were also observed by respondents as they interacted with location intelligence platforms. To ensure NPS maximally utilized LD to meet its law enforcement needs, the study recommended that there is need to capacity build its human resource in LI concepts and invest in appropriated LD processing platforms. The Service further need to create awareness among its staff on the importance of embracing technology for law enforcement. Finally, to realize full potential of LI technology, the government need to regard location data as an asset or infrastructure that needs to be managed in the national interest by fast tracking development of National SDI as stipulated in Vision 2030 development blue print. In view of the above findings, the study suggests further research on the influence of LI on operations of other national security organs. The study ought to bring out various operational practices of the technology that can be shared among them to enhance their effectiveness in the fight against crime and national defense. Other studies may also be carried out on influence of national policy frameworks on law enforcement.en_US
dc.language.isoenen_US
dc.publisherUniversity of Nairobien_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectLocation Intelligence in Law Enforcementen_US
dc.titleInfluence of Location Intelligence in Law Enforcement: a Case of National Police Service,Nairobi County; 2010-2019en_US
dc.typeThesisen_US


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivs 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States