Framework for integrating qualitative and quantitative data: study of electric motorcycle riders

Introduction. In order to reach the ambitious goal of reducing transport emissions in cities, the European Commission is striving to put in place measures to reduce greenhouse gas emissions. Many sectors are concerned, including the automotive industry. As thermal cars, thermal motorcycles are therefore destined to be replaced by their electric counterparts. Although the development of these vehicles could create new behaviours, vehicle dynamics and interactions, there is a lack of scientific understanding of these aspects.

Goals and methods. This paper aims to present conceptual and methodological tools for the investigation of the whole behaviour of electric motorcyclists in real world. A total of 18 electric and 9 thermal riders were observed for one month in France. The objective is to identify the specificities of electric motorbikes’ activity compared to thermal motorbikes.

Results. The main result of this paper is the presentation of a new methodological framework for data collection and analysis including quantitative and qualitative data. It combines a) vehicle dynamics data to “measure” the behaviour (speed, acceleration…), b) video recordings of trips by a camera embedded on the torsos in order to describe the driving context, and c) interviews to analyse the decision making process. Interviews are video-based ones and various “workshops” to encourage the participants to share their riding experiences (feelings, emotions…) and the transition from thermal to electric motorization. All these materials are combined in data processing to gain a comprehensive and global understanding of riding behaviour. The paper will present a couple of interesting results on this topic, allowed by this new kind of integrated analysis.

Conclusion. Lastly, we identify the pros and the cons of this framework and propose some guidelines for using these tools in a broader range of domains and we discuss advancements in data analysis methodologies.