Description
In crisis situations, such as hostage situations, kidnapping or personal crisis, a trained police crisis negotiator may be deployed to guide the subject(s) toward a peaceful resolution. To reduce harm, the crisis negotiator communicates with the person in crisis (PiC) to influence their behaviour. Recognizing the significance of understanding influencing factors in such high-stake situations, a crisis negotiation database is currently being developed in the Netherlands. For each deployment, different aspects of the crisis negotiation are tracked ranging from incident type, location, applied influencing strategies, and more psychological aspects, such as the relationship between negotiator and PiC, subjects, or victims. The database enables in-depth analysis to provide valuable information for future crises and possible policy amendments grounded on evidence-based insights. However, the success of this database hinges on two significant elements: the effective utilization of the system and the quality of the entered data. While research on new technology use often adopts the Technology Acceptance Model (TAM, see Marangunić & Granić, 2015), the model assesses the behavioural intention to use the system overlooking the actual use. The latter is particularly important for police systems, as they are often associated with poor data quality, resulting in the “garbage in, garbage out” phenomenon (O’Conners et al., 2022; Sanders et al., 2015). The consequences of unreliable knowledge emphasizes the critical need to study the actual use and the input quality of a crisis negotiation database.
In this bachelor thesis project, we will have a closer look at factors influencing the actual utilization and data quality of a crisis negotiation system. To study this an extended Technology Acceptance Model, with actual use measures, will be assessed. The assignment aligns with the PhD project of Jedidjah Schaaij focusing on the development, implementation, and data analysis of a Dutch Crisis Negotiation Database.
Research questions
For example:
- How do the different TAM factors correlate with the actual use of the crisis negotiation database?
- To what extent do participants accurately and comprehensively input data into a police database system after a simulated crisis negotiation scenario?
- What factors promote high quality input in a crisis negotiation database system?
Type of research
Most likely an online survey with a crisis scenario but the set-up depends on the specific research questions. Research methods can be quantitative, qualitative, experimental, or involve a mixed approach.
Key words
Crisis negotiations, Data-driven policing, Technology acceptance model, Data Quality
Information
Please contact Lynn Weiher (l.weiher@utwente.nl) when you are interested in this assignment. The assignment is open to two students.
Literature
Darroch, S., & Mazerolle, L. (2012). Intelligence-Led Policing. Police Quarterly, 16(1), 3– 37. https://doi.org/10.1177/1098611112467411
Giebels, E., & Noelanders, S. (2004). Crisis negotiation: A multiparty perspective. Universal Press.
Marangunić, N., & Granić, A. (2015). Technology acceptance model: A literature review from 1986 to 2013. Universal Access in the Information Society, 14(1), 81–95. https://doi.org/10.1007/s10209-014-0348-1
O’Connor, C. D., Ng, J., Hill, D., & Frederick, T. (2022). Thinking about police data: Analysts’ perceptions of data quality in Canadian policing. The Police Journal: Theory, Practice and Principles, 95(4), 637–656. https://doi.org/10.1177/0032258X211021461
Sanders, C. B., Weston, C., & Schott, N. (2015). Police Innovations, ‘Secret Squirrels’ and Accountability: Empirically Studying Intelligence-led Policing in Canada. The British Journal of Criminology, 55(4), 711–729. https://doi.org/10.1093/BJC/AZV008
Sandhu, A., & Fussey, P. (2021). The ‘uberization of policing’? How police negotiate and operationalise predictive policing technology. Policing and Society, 31(1), 66–81. https://doi.org/10.1080/10439463.2020.1803315