A strong research methodology ensures insights reflect real operations rather than anecdote. The methodology document details sampling rules, survey design, interview protocols, data cleaning, and analytical frameworks. For commercial fleets, adopting a similar rigour improves your internal EV strategy and avoids costly missteps.

1) The mixed-methods approach: surveys + interviews + triangulation

The study’s methodology combines quantitative surveys with qualitative semi-structured interviews:

• Structured survey responses provide pattern detection and statistical trends
• Semi-structured interviews allow deeper understanding of context, behaviours, and operational constraints
• Triangulation ensures that interview insights are grounded in survey data rather than isolated narratives

2) Sampling strategy and representation

The research did not aim to produce statistically representative national estimates. Instead, it used purposive sampling, meaning participants were selected based on operational characteristics likely to reveal meaningful contrasts (e.g., fleets with EV experience vs those without). This strategy maximises insight per respondent.

How participants were grouped

• By vehicle type (ICE, PHEV, BEV)
• By route category (local, regional, national)
• By duty cycle characteristics (predictable vs variable mileage)

3) Survey instrument design: consistent definitions and time windows

To ensure that charging behaviour was comparable across operators, the survey used consistent definitions and clearly framed questions:

• Charging episodes were categorised by time windows: daytime (07:00–20:00) and overnight (20:00–07:00)
• Route distances were categorised in intuitive bands (for example, <15 miles, 15–50 miles, >50 miles)
• Charging was not only logged by location, but also by context (depot, residential, public)

4) Interview protocols: balancing structure with flexibility

Interviews were semi-structured, meaning there was a consistent set of core questions (for comparability) but also room to explore unique operational issues. Interview guides covered:

• Charging practices and infrastructure access
• Barriers encountered and workarounds developed
• Perceptions of smart charging and anticipated future needs

5) Data validation and quality assurance measures

The methodology document describes checks to ensure data completeness and logical consistency, including:

• Cross-validating survey responses with interview narratives
• Flagging anomalous responses for follow-up or exclusion
• Using clearly defined schemas for route groups, charging times, and vehicle types

6) Translating method into action: your EV rollout diagnostics toolkit

The methodology itself forms a checklist that commercial fleets can use to audit their EV readiness:

• Define your duty cycles with route categories that match charging feasibility
• Collect charging logs using standard time bins to identify patterns and gaps
• Combine quantitative logs with qualitative interviews to capture driver behaviour and workarounds
• Use logical QA checks to ensure your data is complete and comparable across areas

FAQ: applying methodology to your fleet