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The purpose of this paper is to use an evaluation of a micro-place-based hot-spot policing implementation to highlight the potential issues raised by data quality standards in the recording and measurement of crime data and police officer movements.

The study focusses on an area of London (UK) which used a predictive algorithm to designate micro-place patrol zones for each police shift over a two-month period. Police officer movements are measured using GPS data from officer-worn radios. Descriptive statistics regarding the crime data commonly used to evaluate this type of implementation are presented, and simple analyses are presented to examine the effects of officer patrol duration (dosage) on crime in micro-place hot-spots.

The results suggest that patrols of 10-20 minutes in a given police shift have a significant impact on reducing crime; however, patrols of less than about 10 minutes and more than about 20 minutes are ineffective at deterring crime.

Due to the sparseness of officer GPS data, their paths have to be interpolated which could introduce error to the estimated patrol dosages. Similarly, errors and uncertainty in recorded crime data could have substantial impact on the designation of micro-place interventions and evaluations of their effectiveness.

This study is one of the first to use officer GPS data to estimate patrol dosage and places particular emphasis on the issue of data quality when evaluating micro-place interventions.

Location-based games (LBGs) have afforded novel information technology (IT) developments in how people interact with the physical world. Namely, LBGs have spurred a wave of territoriality (i.e. controlling) and exploration (i.e. discovering) of augmented physical space that are driven by different social dynamics related to group formation, social connectivity and altruism. The aim of this study is to investigate this dynamic and how it is further related to the use intensity of location-based IT.

This work presents a structural equation model that connects social dimensions of play to territorial control and exploration, and playing intensity. The model was tested with psychometric data gathered from a global sample of Pokémon GO players (N = 515).

In the tested sample, players' social self-efficacy and altruism were positively associated with team identification. Team identification, in turn, was positively associated with both territorial control and exploration tendency. Territorial control had a significant relationship with playing intensity; however, exploration tendency did not. This implies territorial control is the stronger predictor of playing intensity.

The findings suggest that human primal urges to conquer and control geographical territory may surface in the digital reimagination of physical space. LBGs offer opportunities for making use of new forms of play (territorial control and exploration) in motivating locative behaviours.

This research quantifies the relationships between a social predisposition, team identification, territorial control, exploration tendency and playing intensity in the context of Pokémon GO. It contributes new knowledge to the understanding of territorial behaviour (control and exploration) in location-based IT.