Evaluating Driver Behaviour at Nobina Oy: Integrating Mystery Shopping and Telematics in Public Transport
Soini, Artturi (2025)
2025
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https://urn.fi/URN:NBN:fi:amk-2025091524694
https://urn.fi/URN:NBN:fi:amk-2025091524694
Tiivistelmä
This thesis investigates the recurring safety and performance challenges among public transport drivers at Nobina Oy, a major bus operator in Turku, Finland. Despite the presence of a digital driver monitoring system (Vihreä Matka) and coaching interventions, certain drivers continue to demonstrate risky behaviours, leading to vehicle damage, service disruption, and passenger complaints. The objective of this study was to examine how accurately these monitoring systems reflect real-world driving behaviour and to identify what factors differentiate high-risk drivers from safer peers.
A development-oriented research approach was used, combining quantitative data analysis with qualitative observation. Six drivers identified internally as higher-risk were covertly observed using a mystery shopping method during routine service. Their behaviour was assessed in four thematic categories: driving control, anticipation, passenger interaction, and professionalism. The observation results were then compared against Vihreä Matka telematics data and historical incident records.
The findings show a mismatch between monitored performance scores and actual on-road behaviour. While some drivers with high telematics scores engaged in unsafe practices (e.g. reactive braking, poor communica-tion), others with lower system ratings demonstrated competent and customer-friendly conduct. These re-sults suggest that current digital tools insufficiently capture human and situational factors critical to safety.
Development proposals include reinforcing feedback systems within coaching practices, integrating observa-tional methods selectively, and using existing data sources more holistically to detect emerging risk. The study concludes that combining automated monitoring with targeted, human-centred observation provides a more accurate and actionable understanding of driver behaviour. These insights have direct applicability for Nobina Oy and broader implications for driver management strategies in sustainable public transport.
A development-oriented research approach was used, combining quantitative data analysis with qualitative observation. Six drivers identified internally as higher-risk were covertly observed using a mystery shopping method during routine service. Their behaviour was assessed in four thematic categories: driving control, anticipation, passenger interaction, and professionalism. The observation results were then compared against Vihreä Matka telematics data and historical incident records.
The findings show a mismatch between monitored performance scores and actual on-road behaviour. While some drivers with high telematics scores engaged in unsafe practices (e.g. reactive braking, poor communica-tion), others with lower system ratings demonstrated competent and customer-friendly conduct. These re-sults suggest that current digital tools insufficiently capture human and situational factors critical to safety.
Development proposals include reinforcing feedback systems within coaching practices, integrating observa-tional methods selectively, and using existing data sources more holistically to detect emerging risk. The study concludes that combining automated monitoring with targeted, human-centred observation provides a more accurate and actionable understanding of driver behaviour. These insights have direct applicability for Nobina Oy and broader implications for driver management strategies in sustainable public transport.