DOI: 10.5061/dryad.vhhmgqp3p
title: Dataset of air travelers’ ground transportation choice at four airports in Northern California

description: Prior studies of travel mode choice in airport ground transportation
 identified several important relationships between traveler/trip
 attributes and their selected access mode. However, those studies did not
 comprehensively account for qualitative aspects of ground access mode
 choice, such as general and transportation-specific attitudes and
 perception of mode-specific airport infrastructure. To add insights into
 air travelers’ ground transportation choices, this study collected a
 dataset with a survey administered among travelers using one of four major
 airports in Northern California in the post-pandemic era. Among other
 analyses presented in the report, we analyzed airport ground access mode
 choice, and its relationships with travelers’ socio-demographics,
 attitudes toward transportation and related topics (e.g., environmental
 friendliness), and opinions about transportation infrastructures and
 services (e.g., airport parking fees). We identified relationships between
 air traveler attitudes or opinions and their mode choice not examined in
 prior studies. Specifically, travelers with pro-environment attitudes
 preferred public transit and ridehailing services over private vehicles,
 even when ridehailing services may not be more environmentally friendly
 than private vehicles. Regarding public transit, travelers are more likely
 to choose this often if they highly rate its service frequency and
 accessibility from their home to a nearby station. The results suggest
 policymakers, airport authorities, and transit agencies consider
 electrification of ridehailing fleets, expansion of bus and rail service
 availability to air travelers’ neighborhoods, and higher parking fees to
 reduce driving in private vehicles to the airport.
description: The travel survey dataset was collected through Qualtrics online
 opinion panel platform. Qualtrics users are invited to participate in the
 survey. The following screening questions were shown to the potential
 participants to determine if they were eligible for the study: 1) The zip
 code of the respondent’s residential address was within the 21 counties in
 Northern California of our study region (Alameda, Contra Costa, Marin,
 Napa, Solano, Sonoma, San Mateo, San Francisco, Santa Clara, El Dorado,
 Placer, Sacramento, Sutter, Yolo, Yuba, Merced, San Joaquin, Stanislaus,
 Monterey, San Benito, and Santa Cruz), 2) The age of the respondent must
 be 18 or older, and 3) The respondent had flown to or from at least one of
 the following airports: Metropolitan <strong>Oakland</strong>
 International Airport (OAK), Norman Y. Mineta <strong>San
 Jose</strong> International Airport (SJC),
 <strong>Sacramento</strong> International Airport (SMF),
 <strong>San Francisco</strong> International Airport (SFO) in
 the last three years. After the data collection, we
 eliminated some bad responses that completed the survey in an
 unrealistically short time, with flatlining responses in a section, with
 too many long-distance trips reported, and/or with an invalid flight
 itinerary (e.g., SFO to OAK). 
description: # Dataset of air travelers’ ground transportation choice at four airports
 in Northern California
 [https://doi.org/10.5061/dryad.vhhmgqp3p](https://doi.org/10.5061/dryad.vhhmgqp3p) ## Description of the data and file structure This dataset is collected during the project "Air travelers’ Ground Transportation Choice at Four Airports in Northern California" (USDOT Grant 69A3551747114). It contains the survey responses regarding the use of the four airports in Northern California (Metropolitan **Oakland** International Airport (OAK), Norman Y. Mineta **San Jose** International Airport (SJC), **Sacramento** International Airport (SMF), **San Francisco** International Airport (SFO)). During the survey, participants were asked to provide their social demographics, the frequency of long-distance trips in the last 12 months and 2019, and the specific details of their last air travel. Questions about one's last air travel included the details of airport ground access that the survey taker used, the flight origin/destination, flight date/time, number of accompanying people traveling, and so on.  ### Data Cleaning After the data collection, we eliminated some bad responses that completed the survey in an unrealistically short time, with flatlining responses in a section, with too many long-distance trips reported, and/or with an invalid flight itinerary (e.g., SFO to OAK).  # Dataset Description ## Data format The dataset is in the SPSS dataset format (.sav). The original dataset was downloaded from Qualtrics platform. The cleaned dataset was exported by Haven R package and it was modified with SPSS v29. ## Variables ### Metadata * **m_datetime** Datetime when the response is made [character, "DD-MMM-YYYY HH:mm:ss"] * **m_id** Individual ID [character] ### Social Demographic Factors * **a_yearborn** Birth year [numeric] * **a_race_asian** Race, Asian or Pacific Islander [dummy] * **a_race_black** Race, Black or African American [dummy] * **a_race_native** Race, Native American [dummy] * **a_race_white** Race, White or Caucasian [dummy] * **a_race_other** Race, other [dummy] * **a_race_other_text** Race, text input for other [character] --- * **a_hispanic** Hispanic [labelled] * 1: Yes * 0: No * **a_gender** Gender [labelled] * 1: Woman * 2: Man * 3: Prefer to self-describe * **a_education** Educational attainment [labelled] * 1: Some grade/high school * 2: Completed high school or GED * 3: Some college/technical school * 4: Bachelor's degree(s) * 5: Graduate degree(s) (e.g., MS, PhD, MBA) * 6: Professional degree(s) (e.g., JD, MD, DDS) * **a_income** Household income level [labelled] * 1: Less than $25,000 * 2: $25,000 to $49,999 * 3: $50,000 to $74,999 * 4: $75,000 to $99,999 * 5: $100,000 to $149,999 * 6: $150,000 to $199,999 * 7: $200,000 or more * **a_employment** Employment status [labelled] * 1: I currently do not work * 2: I work full-time * 3: I work part-time * 4: I have two or more * 5: I only do unpaid work (e.g., volunteering, unpaid internship) * 6: I am retired * 7: Other (please specify): * **a_vehicles** Number of vehicles in household [labelled] * 1: 0 * 2: 1 * 3: 2 * 4: 3 * 5: 4 * 8: 5 or more ### Airport Ground Access Experience * **b_time_outbound** Time of the outbound flight [labelled] * **b_time_return** Time of the return flight [labelled] * 1: Midnight - 0:59 AM * 2: 1:00 AM - 1:59 AM * 3: 2:00 AM - 2:59 AM * 4: 3:00 AM - 3:59 AM * 5: 4:00 AM - 4:59 AM * 6: 5:00 AM - 5:59 AM * 7: 6:00 AM - 6:59 AM * 8: 7:00 AM - 7:59 AM * 9: 8:00 AM - 8:59 AM * 10: 9:00 AM - 9:59 AM * 11: 10:00 AM - 10:59 AM * 12: 11:00 AM - 11:59 AM * 13: Noon - 12:59 PM * 14: 1:00 PM - 1:59 PM * 15: 2:00 PM - 2:59 PM * 16: 3:00 PM - 3:59 PM * 17: 4:00 PM - 4:59 PM * 18: 5:00 PM - 5:59 PM * 19: 6:00 PM - 6:59 PM * 20: 7:00 PM - 7:59 PM * 21: 8:00 PM - 8:59 PM * 22: 9:00 PM - 9:59 PM * 23: 10:00 PM - 10:59 PM * 24: 11:00 PM - 11:59 PM --- * **b_airport_outbound** The airport used for the outbound flight [labelled] * 1: Metropolitan Oakland International Airport (OAK) * 2: Norman Y. Mineta San Jose International Airport (SJC) * 3: Sacramento International Airport (SMF) * 4: San Francisco International Airport (SFO) * 5: I took the first flight from another airport (Please specify): * 6: I didn’t take a flight during the outbound trip (e.g., I drove, or used Amtrak or Greyhound); however, I did take a fl * **b_airport_return** The airport used for the return flight [labelled] * 1: Metropolitan Oakland International Airport (OAK) * 2: Norman Y. Mineta San Jose International Airport (SJC) * 3: Sacramento International Airport (SMF) * 4: San Francisco International Airport (SFO) * 5: I took the last flight to another airport (Please specify): * 6: I didn’t take a flight during the return trip (e.g., I drove for the entire trip, or used Amtrak or Greyhound); howeve * 7: I have not made the return trip yet (e.g., I am currently staying in another city for a long-term work visit) * **b_datetime_outbound** Date and time of the outbound flight [character, "ddd MMM DD YYYY HH:mm:ss {timezone}"] * **b_datetime_return** Date and time of the return flight [character, "ddd MMM DD YYYY HH:mm:ss {timezone}"] --- * **b_accompany_family_children_outbound** Number of accompanying family/relative children (under 18) for the outbound flight [labelled] * **b_accompany_family_adult_outbound** Number of accompanying family/relative adults (18 to 64) for the outbound flight [labelled] * **b_accompany_family_old_outbounds** Number of accompanying family/relative older adults (65 or older) for the outbound flight [labelled] * **b_accompany_friend_outbound** Number of accompanying friends for the outbound flight [labelled] * **b_accompany_colleague_outbound** Number of accompanying colleagues for the outbound flight [labelled] * **b_accompany_family_children_return** Number of accompanying family/relative children (under 18) for the return flight [labelled] * **b_accompany_family_adult_return** Number of accompanying family/relative adults (18 to 64) for the return flight [labelled] * **b_accompany_family_old_return** Number of accompanying family/relative older adults (65 or older) for the return flight [labelled] * **b_accompany_friend_return** Number of accompanying friends for the return flight [labelled] * **b_accompany_colleague_return** Number of accompanying colleagues for the return flight [labelled] * 1: 0 * 2: 1 person * 3: 2 people * 4: 3 people * 5: 4 people * 6: 5 people or more --- * **b_luggage_checked_outbound** Number of checked luggage for the outbound flight [numeric] * **b_luggage_checked_return** Number of checked luggage for the return flight [numeric] * **b_luggage_carryon_outbound** Number of carry-on luggage for the outbound flight [numeric] * **b_luggage_carryon_return** Number of carry-on luggage for the return flight [numeric] --- * **b_means_private_alone_outbound** Mode of transportation to the airport for the outbound flight, private vehicle driven alone [dummy] * **b_means_private_pool_outbound** Mode of transportation to the airport for the outbound flight, private vehicle driven with others [dummy] * **b_means_private_passenger_outbound** Mode of transportation to the airport for the outbound flight, private vehicle as a passenger (driver did not fly) [dummy] * **b_means_private_shuttle_outbound** Mode of transportation to the airport for the outbound flight, private shuttle [dummy] * **b_means_other_shuttle_outbound** Mode of transportation to the airport for the outbound flight, other (e.g., hotel) shuttle [dummy] * **b_means_bus_outbound** Mode of transportation to the airport for the outbound flight, public bus [dummy] * **b_means_rail_outbound** Mode of transportation to the airport for the outbound flight, rail [dummy] * **b_means_ridehailing_outbound** Mode of transportation to the airport for the outbound flight, ridehailing (e.g., Uber, Lyft) [dummy] * **b_means_taxi_outbound** Mode of transportation to the airport for the outbound flight, taxi [dummy] * **b_means_other_outbound** Mode of transportation to the airport for the outbound flight, other [dummy] * **b_means_other_outbound_text** Mode of transportation to the airport for the outbound flight, text input for other [character] * **b_means_private_alone_return** Mode of transportation from the airport for the return flight, private vehicle driven alone [dummy] * **b_means_private_pool_return** Mode of transportation from the airport for the return flight, private vehicle driven with others [dummy] * **b_means_private_passenger_return** Mode of transportation from the airport for the return flight, private vehicle as a passenger (driver did not fly) [dummy] * **b_means_private_shuttle_return** Mode of transportation from the airport for the return flight, private shuttle [dummy] * **b_means_other_shuttle_return** Mode of transportation from the airport for the return flight, other (e.g., hotel) shuttle [dummy] * **b_means_bus_return** Mode of transportation from the airport for the return flight, public bus [dummy] * **b_means_rail_return** Mode of transportation from the airport for the return flight, rail [dummy] * **b_means_ridehailing_return** Mode of transportation from the airport for the return flight, ridehailing (e.g., Uber, Lyft) [dummy] * **b_means_taxi_return** Mode of transportation from the airport for the return flight, taxi [dummy] * **b_means_other_return** Mode of transportation from the airport for the return flight, other [dummy] ### Opinion about Infrasturcture and Services Bound to Airport Ground Transportation * **b_means_other_return_text** Mode of transportation from the airport for the return flight, text input for other [character] * **c_parking_availability** Agreement level to the statement "It is always easy to find an available parking lot to use." [labelled] * **c_parking_easeofuse** Agreement level to the statement "It is easy to use the parking lot facility." [labelled] * **c_parking_accessibility_airport** Agreement level to the statement "It is easy to physically access the parking lot facility from the airport terminal." [labelled] * **c_parking_affordability** Agreement level to the statement "The parking lot facility is affordable to use." [labelled] * **c_parking_cleanliness_airport** Agreement level to the statement "The parking lot facility is well sanitized and kept clean." [labelled] * **c_bus_availability** Agreement level to the statement "The bus service has a good frequency so I can get a ride without waiting long." [labelled] * **c_bus_easeofuse** Agreement level to the statement "It is easy to use the bus service at the airport." [labelled] * **c_bus_accessibility_airport** Agreement level to the statement "It is easy to physically access the bus stop facility from the airport terminal." [labelled] * **c_bus_accessibility_home** Agreement level to the statement "It is easy to physically access a bus stop from my home." [labelled] * **c_bus_affordability** Agreement level to the statement "The bus service is affordable to use." [labelled] * **c_bus_cleanliness_airport** Agreement level to the statement "The bus and the bus stop are kept clean and well maintained." [labelled] * **c_rail_availability** Agreement level to the statement "The rail service has a good frequency so I can get a ride without waiting long." [labelled] * **c_rail_easeofuse** Agreement level to the statement "It is easy to use the rail service at the airport (<i>e.g.,</i> purchase a ticket or navigate to the station from the terminal)." [labelled] * **c_rail_accessibility_airport** Agreement level to the statement "It is easy to physically access the rail station from the airport terminal." [labelled] * **c_rail_accessibility_home** Agreement level to the statement "It is easy to physically access a rail station from my home." [labelled] * **c_rail_afforadbility** Agreement level to the statement "The rail service is affordable to use." [labelled] * **c_rail_cleanliness_airport** Agreement level to the statement "The rail vehicle and the rail station are kept clean and well maintained." [labelled] * **c_ridehailing_availability** Agreement level to the statement "Ridehailing services have drivers around so I can get a ride without waiting long." [labelled] * **c_ridehailing_easeofuse** Agreement level to the statement "It is easy to use ridehailing services at the airport via the pick-up/drop-off locations." [labelled] * **c_ridehailing_accessibility_airport_pickup** Agreement level to the statement "It is easy to physically access the pick-up location from the airport terminal." [labelled] * **c_ridehailing_accessibility_airport_dropoff** Agreement level to the statement "It is easy to physically access the airport terminal from the drop-off location." [labelled] * **c_ridehailing_cleanliness_interior** Agreement level to the statement "The interior of the ridehailing vehicle is well sanitized and kept clean." [labelled] * **c_ridehailing_cleanliness_airport** Agreement level to the statement "The pick-up/drop-off locations at the airport are kept clean and well maintained." [labelled] * 1: Strongly disagree * 2: Somewhat Disagree * 3: Neither agree nor disagree * 4: Somewhat agree * 5: Strongly agree * 6: I don't know --- ## Code/software The dataset requires IBM SPSS Statistics to edit, or Haven R package to view/use/modify.  ## Access information Other publicly accessible locations of the data: * None Data was derived from the following sources: * N/A