Planning a value of travel time study

VoTT studies have specific design requirements that differ from other DCE applications. Getting the scope, design, and recruitment right from the start avoids expensive revisions later.

This article explains how to plan a value of travel time study, covering the key design decisions specific to VoTT research, WebTAG compliance.

Ben White, 07.07.2026

What makes VoTT studies different

A value of travel time study is not just any DCE applied to transport. VoTT studies have specific methodological requirements: the pivot design linking SP levels to each respondent's actual trip; the RP/SP combination for more reliable estimates; trip purpose segmentation; and the need for results to be comparable with or justifiable against national benchmark values.

These requirements make VoTT studies more complex to design and conduct than standard DCE studies - but also more valuable. Getting VoTT estimates right can determine whether a billion-pound infrastructure investment passes or fails its business case.

Key planning decisions for VoTT studies

Geographic and corridor scope: a national VoTT study and a corridor-specific study require very different sample sizes, recruitment strategies, and geographic coverage. Corridor-specific studies should oversample the relevant corridor while national studies require geographic stratification.

Trip purpose segmentation: WebTAG requires separate VoTT estimates for business, commuting, and leisure trips. This typically requires a large enough sample to estimate separate models for each purpose - usually 150–200 per purpose segment minimum.

Mode segmentation: VoTT may differ significantly by mode. Car users typically have higher VoTT than bus users for the same trip. If mode segmentation is required, the sample needs to include adequate respondents for each mode quota.

In-vehicle vs walk/wait time: VoTT studies may need to estimate separate values for in-vehicle time, walk time, wait time, and interchange time. Each of these requires specific design elements and adequate sample size.

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Planning your VoTT study with SurveyEngine

Step 1: Define the scope and output requirements. Specify: geographic coverage, trip purpose segments, mode segments, time components (in-vehicle, walk, wait, interchange), and whether reliability values are also required. These decisions determine sample size and design complexity.

Step 2: Design the RP collection instrument. The RP module must collect: mode, origin and destination type, trip purpose, door-to-door time, fare, interchange count, and any other relevant attributes for your design. Pilot the RP questions to ensure they produce consistent, plausible responses.

Step 3: Generate the pivot SP design. Use SurveyEngine's design engine to generate a pivot design with offset percentages appropriate for your sample's trip length distribution. Ensure the design produces adequate variation in time and cost levels across the full range of RP values.

Step 4: Plan the sample with adequate cell sizes. Calculate minimum cell sizes for each trip purpose × mode × geographic segment combination. Use SurveyEngine's sampling team to estimate the recruitment cost and timeline for each cell.

Step 5: Plan the validation against benchmarks. Before finalising the report, compare your VoTT estimates against WebTAG or equivalent national values. Prepare a justification for any significant differences that can be presented to the commissioning authority.

Worked example - regional VoTT study scope

A regional transport authority commissions a VoTT study for a metropolitan area to update values used in local CBAs. Scope: three trip purposes (business, commuting, leisure) × three modes (car, bus, rail) × two time periods (peak, off-peak). Minimum 100 respondents per cell = 1,800 minimum. With 20% contingency: 2,160 respondents.

SurveyEngine designs a combined RP/SP survey with 8 pivot SP tasks per respondent. Fieldwork is conducted using a combination of on-site recruitment at major transport hubs (for rail and bus respondents) and online panel with geographic and trip-purpose quotas (for car and off-peak respondents). Total fieldwork: 6 weeks. Results are presented with comparison against WebTAG 2023 values and a formal justification for a 7% departure on business VoTT attributable to the region's higher-than-average income profile.