Updates are delayed due to technical difficulties. How many people are staying at home? How far are people traveling when they don’t stay home? Which states and counties have more people taking trips? The Bureau of Transportation Statistics (BTS) now provides answers to those questions through our new mobility statistics. The Trips by Distance data and number of people staying home and not staying home are estimated for the Bureau of Transportation Statistics by the Maryland Transportation Institute and Center for Advanced Transportation Technology Laboratory at the University of Maryland. The travel statistics are produced from an anonymized national panel of mobile device data from multiple sources. All data sources used in the creation of the metrics contain no personal information. Data analysis is conducted at the aggregate national, state, and county levels. A weighting procedure expands the sample of millions of mobile devices, so the results are representative of the entire population in a nation, state, or county. To assure confidentiality and support data quality, no data are reported for a county if it has fewer than 50 devices in the sample on any given day. Trips are defined as movements that include a stay of longer than 10 minutes at an anonymized location away from home. Home locations are imputed on a weekly basis. A movement with multiple stays of longer than 10 minutes before returning home is counted as multiple trips. Trips capture travel by all modes of transportation. including driving, rail, transit, and air. The daily travel estimates are from a mobile device data panel from merged multiple data sources that address the geographic and temporal sample variation issues often observed in a single data source. The merged data panel only includes mobile devices whose anonymized location data meet a set of data quality standards, which further ensures the overall data quality and consistency. The data quality standards consider both temporal frequency and spatial accuracy of anonymized location point observations, temporal coverage and representativeness at the device level, spatial representativeness at the sample and county level, etc. A multi-level weighting method that employs both device and trip-level weights expands the sample to the underlying population at the county and state levels, before travel statistics are computed. These data are experimental and may not meet all of our quality standards. Experimental data products are created using new data sources or methodologies that benefit data users in the absence of other relevant products. We are seeking feedback from data users and stakeholders on the quality and usefulness of these new products. Experimental data products that meet our quality standards and demonstrate sufficient user demand may enter regular production if resources permit.

According to a November 2024 survey, four out of 10 consumers worldwide reported using an AI-based tool for travel planning. While 12 percent of respondents used artificial intelligence both when planning a trip and during a vacation, 17 percent of the sample relied on AI tools only for travel planning.

Vacation Rental Statistics: Renting a place on vacation is what refreshes our minds. Every year, global tourists focusing on millennials spend around 180 billion dollars on travel every year. Therefore, the market is expected to rise at a CAGR of 5.3% between 2022 to 2030. Today, planning and booking a short or long vacation has become easy, you can simply ask ChatGPT your itinerary for the trip and book on the websites that provide the cheapest price rates for the accommodation. These Vacation Rental Statistics are including the most recent data focusing on global as well as American holiday rental markets. Don’t you think it's already summertime and you should be booking a vacation to the beach? Editor’s Choice Due to the remote working system, the duration of vacations has been increased by 68% resulting in 21 to 30-day stays. As of today, there are 31.3% of privately owned vacation rentals in the United States of America with 600,000 Americans using online platforms to rent out their places. As of 2022, around 138 million nights got booked for rental listing in the United States of America. From a worldwide perspective, revenue in the vacation rentals market is expected to reach $96.85 billion in 2023. The global comparison of Vacation Rental Statistics confirms that in 2023, most of the revenue in the market will be generated from the United States of America. Around the world, 700 million travellers used vacation rentals and more than 60 million Americans preferred to stay in holiday rentals in 2022. As of 2022, the primary booking method for vacation rentals in the United States of America was online methods (76%), and offline methods (24%). The demand for vacation rentals that allow pets have increased by 40%. Furthermore, Vacation Rental Statistics of online booking state that the percentage of the same will rise to 80% by 2026. 43% of the rental hosts manage their property by themselves whereas 25% of the properties are managed by professionals.

An August 2022 survey asked travelers worldwide about the expected use of a series of planning tools for trips in 2033. While over half of the respondents expected to rely on travel apps offering all the services needed to plan a trip, just 36 percent of the sample mentioned voice-based search engines.

This table contains information regarding the mobility of the residents of the Netherlands aged 6 or older in private households, so excluding residents of institutions and homes. The table contains an overview of the average distance per trip and the average travel time per trip. These are regular trips on Dutch territory, including domestic holiday mobility. The distance travelled is based on stage information. Excluded in this table is mobility based on series of calls trips.

Data available from: 2018

Status of the figures: The figures in this table are final.

Changes as of 4 July 2024: The figures for year 2023 are added.

When will new figures be published? Figures for the 2024 research year will be published in mid-2025

In 2024 , tourism expenditures amounted to € 110.11 Bn. and tourism revenues to € 37.06 Bn. in Germany. Further data and statistics on travel duration, travel intensity, number of vacation trips and vacation travelers as well as their expenditures up to the year 2000. Travel market statistics (revenue, expenditure, travel duration, travel intensity, travelers & vacations etc.) with interactive charts incl. download. Dashboard, data, KPIs & more .. ITOMA.IO - The IT & Tourism Experts

Monthly U.S. citizen departures are collected and reported in Tourism Industries U.S. International Air Travel Statistics (I-92 data) Program.

In 2024 , tourism expenditures amounted to € 15.69 Bn. and tourism revenues to € 24.27 Bn. in Austria. Further data and statistics on travel duration, travel intensity, number of vacation trips and vacation travelers as well as their expenditures up to the year 2000. Travel market statistics (revenue, expenditure, travel duration, travel intensity, travelers & vacations etc.) with interactive charts incl. download. Dashboard, data, KPIs & more .. ITOMA.IO - The IT & Tourism Experts

The Travel Time to Work dataset was compiled using information from December 31, 2023 and updated December 12, 2024 from the Bureau of Transportation Statistics (BTS) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The Travel Time to Work table from the 2023 American Community Survey (ACS) 5-year estimates was joined to 2023 tract-level geographies for all 50 States, District of Columbia and Puerto Rico provided by the Census Bureau. A new file was created that combines the demographic variables from the former with the cartographic boundaries of the latter. The national level census tract layer contains data on the number and percentage of commuters (workers 16 years and over who did not work from home) with a range of travel times to work.

This statistic shows the frequency at which U.S. adults generally go on a vacation outside of the United States, by income. It was found that **** percent of U.S. adults from households earning ****** to ****** U.S. dollars per year go on holiday outside the United States multiple times a year. By way of comparison, the corresponding figure for those from households earning 100,000 to ******* U.S. dollars per year was ** percent.

Introduction

Business Travel Statistics: Even after the upsurge of the COVID-19 pandemic, business travel remains an essential aspect of growing your business. Business travel allows for the exploration of new opportunities and outlooks for those who travel. Despite various technological advancements, corporate travel trends show that there is no replacement for face-to-face interactions.

Traveling can also hold up corporate initiatives for developing skills, networking, and recruitment. Nevertheless, the introduction of COVID-19 has thrown a wrench at some of those travel plans and has led to the importance of risk assessment and essential changes in future travels. We shall shed more light on Business Travel Statistics through this article.

How many people are staying at home? How far are people traveling when they don’t stay home? Which states and counties have more people taking trips? The Bureau of Transportation Statistics (BTS) now provides answers to those questions through our new mobility statistics. The Trips by Distance data and number of people staying home and not staying home are estimated for the Bureau of Transportation Statistics by the Maryland Transportation Institute and Center for Advanced Transportation Technology Laboratory at the University of Maryland. The travel statistics are produced from an anonymized national panel of mobile device data from multiple sources. All data sources used in the creation of the metrics contain no personal information. Data analysis is conducted at the aggregate national, state, and county levels. A weighting procedure expands the sample of millions of mobile devices, so the results are representative of the entire population in a nation, state, or county. To assure confidentiality and support data quality, no data are reported for a county if it has fewer than 50 devices in the sample on any given day. Trips are defined as movements that include a stay of longer than 10 minutes at an anonymized location away from home. Home locations are imputed on a weekly basis. A movement with multiple stays of longer than 10 minutes before returning home is counted as multiple trips. Trips capture travel by all modes of transportation. including driving, rail, transit, and air. The daily travel estimates are from a mobile device data panel from merged multiple data sources that address the geographic and temporal sample variation issues often observed in a single data source. The merged data panel only includes mobile devices whose anonymized location data meet a set of data quality standards, which further ensures the overall data quality and consistency. The data quality standards consider both temporal frequency and spatial accuracy of anonymized location point observations, temporal coverage and representativeness at the device level, spatial representativeness at the sample and county level, etc. A multi-level weighting method that employs both device and trip-level weights expands the sample to the underlying population at the county and state levels, before travel statistics are computed. These data are experimental and may not meet all of our quality standards. Experimental data products are created using new data sources or methodologies that benefit data users in the absence of other relevant products. We are seeking feedback from data users and stakeholders on the quality and usefulness of these new products. Experimental data products that meet our quality standards and demonstrate sufficient user demand may enter regular production if resources permit.

‘This dataset provides information regarding the total approved actual expenses incurred by Montgomery County government employees traveling non-locally (over 75 miles from the County’s Executive Office Building at 101 Monroe St. Rockville, MD) for official business, beginning on or after August 12, 2015. The dataset includes the name of traveling employee; the employee’s home department; travel start and end dates; destination; purpose of travel; and actual total expenses funded by the County. Update Frequency: Monthly

Introduction

Vacation Rental Statistics: The way people choose to stay during vacations has changed over the years. Instead of opting for traditional hotel stays, many travelers now prefer to rent separate properties. This allows them to cook their meals and enjoy more privacy. While hotels offer more amenities, privacy is a top priority for most travelers.

Renting out properties can also be very lucrative for owners, especially with the right amenities. Vacation rental trends are expected to be more significant in 2024, as seen in recent vacation rental statistics.

A 2024 survey of adults in the United States found that ** percent of respondents aged 30 to 44 traveled annually internationally or to other U.S. regions. In contrast, ** percent of individuals in the same age group reported that they never traveled.

The Daily Mobility Statistics were derived from a data panel constructed from several mobile data providers, a step taken to address the reduce the risks of geographic and temporal sample bias that would result from using a single data source. In turn, the merged data panel only included data from those mobile devices whose anonymized location data met a set of data quality standards, e.g., temporal frequency and spatial accuracy of anonymized location point observations, device-level temporal coverage and representativeness, spatial distribution of data at the sample and county levels. After this filtering, final mobility estimate statistics were computed using a multi-level weighting method that employed both device- and trip-level weights, thus expanding the sample represented by the devices in the data panel to the at-large populations of each state and county in the US.

Data analysis was conducted at the aggregate national, state, and county levels. To assure confidentiality and support data quality, no data were reported for a county if it had fewer than 50 devices in the sample on any given day.

Trips were defined as movements that included a stay of longer than 10 minutes at an anonymized location away from home. A movement with multiple stays of longer than 10 minutes--before returning home--was counted as multiple trips.

The Daily Mobility Statistics data on this page, which cover the COVID and Post-COVID periods, are experimental. Experimental data products are created using novel or exploratory data sources or methodologies that benefit data users in the absence of other statistically rigorous products, and they not meet all BTS data quality standards.

Explore the statistics for Travel eCommerce in 2025, including store count by region and platform, estimated sales amount by platform and region, products sold by platform and region, and total app spend by platform and region. Gain insights into regional preferences, market penetration, consumer trends, and technological investments within the Travel sector. Discover the leading regions and platforms, as well as the dynamics of sales and product volumes. Stay informed about the evolving landscape of Travel online stores for a comprehensive understanding of the market.

This chart offers a detailed view of the estimated sales amounts for Travel stores across different regions. In United States, the sales figures are particularly impressive, with the region generating $26.53B, which accounts for 41.93% of the total sales in this category. United Kingdom follows with robust sales, totaling $7.21B and representing 11.39% of the overall sales. Unknown also contributes significantly to the market with sales amounting to $1.63B, making up 2.58% of the total. These numbers not only illustrate the economic vitality of each region in the Travel market but also highlight regional consumer preferences and spending power.

The summary statistics by North American Industry Classification System (NAICS) which include: operating revenue (dollars x 1,000,000), operating expenses (dollars x 1,000,000), salaries wages and benefits (dollars x 1,000,000), and operating profit margin (by percent), of travel agencies (NAICS 56151) & tour operators (NAICS 56152) & other travel arrangement and reservation services (NAICS 56159), annual, for five years of data.