Presented to: Presented by: Transportation leadership you can trust. Second Day Response Rates: Implications for CMAP’s Travel Tracker Survey 13th TRB Planning Applications Conference, Reno Cemal Ayvalik and Eric Petersen May 12, 2011

Introduction Many MPOs implement 2-day travel surveys Benefits: Statistical insights at a lower cost than surveying twice as many households. Risks: Significant day-to-day variation in individual travel: – major activities at the tour level, – number of stops and duration, – scheduling of activities, – mode shifts – and route choice. Respondent fatigue likely to bias the results. 2

Measuring Fatigue Stop activities may be omitted on second day. Work tours may be less affected than other travel purposes. Issues possible in full chain of activities or omissions in maintenance or leisure activities on the second day. Markers that might raise flags or minimize concern. – The respondent actually indicates whether the data is being read off hard copies of a travel diary or reported from memory. – One respondent providing information on all household members. 3 Clues for response fatigue.

Correcting for Response Fatigue Depending on the severity of the problem, there are a variety of options: – Discarding the entire record; – Discarding the second day and treating the first day as if it were one-day data; – Reweighting either the second day or both days; – Adjusting the existing data with respect to VMT or activity duration; – Synthesizing missing information. However, modelers must know extent of the problem before making any adjustments or corrections. 4

Case study: Chicago Metropolitan Area In the 2008Travel Tracker household survey conducted for the Chicago Metropolitan Agency for Planning (CMAP): – More than 14,300 households, 10,000+ in 6-County Area. – About 30 percent of households in 6-County area were asked about their travel activities over 2 days (over 3,100 households). – The rest responded via one-day travel diaries. Is respondent fatigue an issue that leads to degradation in the data outweighing the advantage of 2-day surveys? 5

Household Level Observations 6 Household Trip Reporting from the 2-Day Survey Fewer Trips in the Second Day1, % More Trips in the Second Day1, % Same Number of Trips % 3, %

Household Level Observations 7 Household Trip Rates by Survey Duration and Day of the Survey Survey DurationDayN MeanStd Dev 1-Day17, Day13, Day23,

Person Level Observations 8 Person Trip Reporting from the 2-Day Survey Fewer Trips in the Second Day2, % More Trips in the Second Day1, % Same Number of Trips2, % 6, %

9 Person Trip Rates by Survey Duration and Day of the Survey Survey DurationDayN MeanStd Dev 1-Day116, Day16, Day26, Person Level Observations

10 Tour Level Observations Diaries from Typical Travel Day Weekdays Home-Based complete tours Adults, Age 16 or Over Work vs. Non-Work Tours

11 Tour Level Observations Number of Tours by Survey Type and Day of the Survey Survey Duration DayTour Type Number of Tours PercentMean Std Dev 1-Day1 Work 7, % Non-Work 13, % Day 1 Work 2, % Non-Work 3, % Work 2, % Non-Work 3, %

12 Tour Level Observations Tour Lengths by Survey Type and Day of the Survey Survey Duration DayTour Type Number of Tours PercentMean Std Dev 1-Day1 Work 7, % Non-Work 13, % Day 1 Work 2, % Non-Work 3, % Work 2, % Non-Work 3, %

Testable Hypotheses Hypothesis #1: Will respondent fatigue decrease the tour count and number of stops by tour type reported in 2-day surveys ? Hypothesis #2: Will respondent fatigue decrease the tour count and number of stops by tour type reported on the second day? Hypothesis #3: Will respondents reading from travel diaries suffer less fatigue? Hypothesis #4: Will respondent fatigue increase as the number of household members increases? 13

14 Tour Level Comparisons Reduction in number of tours and stops in tours is considered as an indicator of response fatigue. Tours in the first day of 2-Day survey and the 1-Day survey are compared first. Differences between the days in 2-Day survey were analyzed. Completion of a log, household size and survey type are used as explanatory variables. Number of tours and number of stops in a tour for work and non-work tours were dependent variables.

15 Tour Level Comparisons Work ToursNon-Work Tours ToursStopsToursStops Survey Duration More tours in 2-Day More stops in 2-Day Fewer tours in 2-Day Shorter tours in 2-Day Complete Logs Shorter tours from memory Fewer tours by memory Shorter tours by memory Interaction Dampened in 2-Day 1-Day vs. 2-Day Surveys Survey Duration More tours in 2-Day More stops in 2-Day Fewer tours in 2-Day Shorter tours in 2-Day Household Size More tours for Size 3+ More stops as size increases More Tours except for Size 3+ Shorter tours for Size 3+ Interaction Inconclusive Interaction Higher reduction for Size 3+

16 Tour Level Observations First vs. Second Day in 2-Day Survey Work ToursNon-Work Tours ToursStopsToursStops Survey Days Fewer work tours in Day 2 Complete Logs Fewer Tours from memory Shorter Tours from memory Interaction Survey Days Fewer work tours in Day 2 Household Size More tours for Size 3+ More stops for Size 3+ More tours with size (Size 3+) Shorter tours for Size 3+ Interaction

17 Summary of Results Two different types of fatigue can be evaluated: – Fatigue across survey types (mix of single and multi day diaries). – Fatigue across survey days within multi-day surveys. Based on trip comparisons: Less travel is reported by 2-day survey. Less travel is reported on second day of 2-day survey. Mandatory travel similar on first and second day. Fewer non-mandatory stops on the second day.

Summary of Results 18 Based on tours: H1: Equivalent number of tours reported by survey type. Fewer non-mandatory tours in the 2-day survey. Complexity of mandatory tours seems to be increasing in 2- day survey. – Are shorter non-mandatory tours condensed into longer mandatory tours in reporting or is it due to day-to-day variation? H2: No major differences between first and second day. More mandatory tours reported in first day.

Summary of Results H3: Shorter tours were observed from respondents who did not fill out a travel log. – The reason why they did not fill a diary is unknown. May be fatigue or the travel activity was actually short enough to recite from the memory. H4: Larger households - higher tour count and more stops Three-person households had unique patterns – More work tours – Primarily due to differences in member relationships and composition. 19

Next Steps Day-to-day variation. Unclear whether this is non-random. Use GPS data to establish a degree of day-to-day variation. Looking at the variation by different segments including: – household life cycles, – time of day, – activity patterns (linked activities, tours by complexity), – geography, and – data retrieval methods. Matched-Pair Design to control for socioeconomics. Model tour types and lengths using 1-Day survey data. Cross-validate using 1-Day and 2-Day survey data. 20