According to a 2023 global survey, higher costs and personal safety ranked as the main obstacles for female travelers to go on a solo trip. Overall, ** percent and ** percent of respondents, respectively, stated so. Not having someone to share the trip with and the fear of getting lost were other common obstacles that year.

According to a 2023 global survey, female travelers considered flexibility and freedom to be the main motivations to go on a solo trip. That year, roughly **** out of 10 respondents said they mainly traveled alone for this reason. Getting away from routines and responsibilities was also another popular motive for taking a solo trip, mentioned by ** percent of the sample.

In 2023, Spanish female solo travelers had the highest share of international travel reviews among the selected countries, with *********** of their total reviews referring to trips abroad. In contrast, just ***** percent of reviews by Brazilian female solo travelers that year related to international trips.

According to a 2023 global survey, solo female travelers mainly chose their destination according to cultural and historical attractions. That year, ** percent of the sample said it was the main factor when selecting a destination for a solo trip. The beauty of the destination and the local cuisine and food were considered other important factors, as mentioned by ** percent and ** percent of respondents, respectively.

The Fearless Wanderess is a travel blog dedicated to empowering women to take the plunge and explore Europe and beyond on their own terms. Claire, the founder, has spent years honing her skills as a solo traveler, having lived, studied, and worked in multiple countries during her bachelor's degree. She shares her expertise and passion for travel through in-depth guides, helpful tips, and personal anecdotes. The website features a vast array of topics, including destinations, packing lists, and travel resources, all geared towards solo female travelers.

Whether you're a seasoned traveler or just starting to plan your next adventure, The Fearless Wanderess has got you covered. From guides on the best eSIM options for Europe to recommendations for the safest places to travel alone, Claire's expert advice will help you navigate the ups and downs of solo travel. With a focus on empowering women to take control of their travels, The Fearless Wanderess is more than just a blog – it's a community of like-minded individuals who share a passion for discovering new places and cultures.

According to a 2022 global survey, female solo travelers were mainly interested in cultural sightseeing. That year, ** percent of respondents said it was their main activity of interest when traveling alone. Experiencing the nature and wildlife was another popular activity, mentioned by ** percent of the sample.

Financial overview and grant giving statistics of Travel Women Hawaii

About this dataset

Context

The dataset tabulates the population of Travelers Rest by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Travelers Rest across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of female population, with 56.64% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Travelers Rest is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Travelers Rest total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Travelers Rest Population by Race & Ethnicity. You can refer the same here

Abstract

The World Bank WeTour Project aimed to contribute to improved knowledge of the characteristics of Women-owned/led Micro, Small and Medium Sized Enterprises (WSMEs) in tourism in Ghana and Sierra Leone. It is intended that this knowledge and data will be used by projects and programs in those countries to inform the design of gender-targeted tourism SME support services. This survey is representative of male and female enterprises.

Geographic coverage

In Sierra leone, two destination areas were identified as Freetown and the Western Area.

Analysis unit

Micro, Small and Medium Tourism and tourism-related enterprises

Universe

The universe of MSMEs in Tourism and Tourism-related sectors of Freetown and the Western Area in Sierra Leone comprises 1,067 entities identified individually in the sampling frame.

Kind of data

Sample survey data [ssd]

Sampling procedure

The universe of tourism and tourism related SMEs was constructed in each country using all available sources. For both countries the original sample frame of SMEs was compiled from previous sample frames developed for enterprise surveys by EEC International, the amalgamation of past listings of SMEs from the NSO and other public registries, as well as numerous other sources collated from business associations and other publicly available sources of tourism-related information portals, namely: travel agent reservation systems such as Amadeus and Sabre, tourism and tourism-related websites such as Expedia and TripAdvisor, as well as establishments referenced on Google Maps and appearing on Google Street View. The sample frame for micro enterprises was planned to result from systematic block enumeration in the targeted locations. During the block enumeration, entities were identified by a number on a list and a geographical reference (map or other description of the location), information on its apparent activity (tourism or tourism-related), as well as visible gender composition (no apparent female, no apparent male, mixed presence). Neither the activity composition nor the gender composition were known at inception. The validation of the sample frame consisted in ensuring that there were no foreign elements (activities not included in the universe under study).

The sampling strategy that EECI applied for the Tourism and Tourism related Sectors applying consisted in randomly drawing from the frame of MSMEs a screened sample until the minimum number of male and female respondents targeted was obtained, inclusive of the expected non-response.

For Sierra Leone, the frame contained a total of 1,067 entities, of which 705 micros and 362 SMEs. A random draw of 323 entities, consisting of 212 micros and 111 SMEs generated through a screening 125 female entities and 198 male entities. The entire group of 125 female entities was directed to interviewing, and the first 125 male entities that were screened, were directed to interviewing, with an expected 120 respondents by genre. For more details see Methodology Note provided under Related Documents.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Data entry and quality controls were implemented by the contractor then data was delivered to the World Bank. The World Bank validated data were validated for logical consistency, flagging problems that were then corrected by the implementing contractor.

Response rate

The response rate was 96.6% for Sierra Leone. There are slight variations of these indicators by sub-groups of businesses.

Sampling error estimates

According to sample design, it is possible to generalize survey results (at a precision of 7.5% and a confidence level of 90%) at the sector level, and the respective gender sub-groups of businesses.

India Foreign Tourist Arrivals: Female: Eastern Europe: Kazakhstan data was reported at 9,376.000 Person in 2017. This records an increase from the previous number of 8,034.000 Person for 2016. India Foreign Tourist Arrivals: Female: Eastern Europe: Kazakhstan data is updated yearly, averaging 7,851.000 Person from Dec 2008 (Median) to 2017, with 10 observations. The data reached an all-time high of 10,092.000 Person in 2014 and a record low of 3,684.000 Person in 2008. India Foreign Tourist Arrivals: Female: Eastern Europe: Kazakhstan data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under India Premium Database’s Tourism Sector – Table IN.QB017: Foreign Tourist Arrivals: by Gender: Female.

India Foreign Tourist Arrivals: Female: North America: Canada data was reported at 157,656.000 Person in 2017. This records an increase from the previous number of 147,833.000 Person for 2016. India Foreign Tourist Arrivals: Female: North America: Canada data is updated yearly, averaging 116,334.500 Person from Dec 2008 (Median) to 2017, with 10 observations. The data reached an all-time high of 157,656.000 Person in 2017 and a record low of 99,943.000 Person in 2008. India Foreign Tourist Arrivals: Female: North America: Canada data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under India Premium Database’s Tourism Sector – Table IN.QB017: Foreign Tourist Arrivals: by Gender: Female.

This workbook provides data and data dictionaries for the SFMTA 2017 Travel Decision Survey. On behalf of San Francisco Municipal Transportation Agency (SFMTA), Corey, Canapary & Galanis (CC&G) undertook a Mode Share Survey within the City and County of San Francisco as well as the eight surrounding Bay Area counties of Alameda, Contra Costa, San Mateo, Marin, Santa Clara, Napa, Sonoma and Solano. The primary goals of this study were to: • Assess percent mode share for travel in San Francisco for evaluation of the SFMTA Strategic Objective 2.3: Mode Share target of 50% non-private auto travel by FY2018 with a 95% confidence level and MOE +/- 5% or less. • Evaluate the above statement based on the following parameters: number of trips to, from, and within San Francisco by Bay Area residents. Trips by visitors to the Bay Area and for commercial purposes are not included. • Provide additional trip details, including trip purpose for each trip in the mode share question series. • Collect demographic data on the population of Bay Area residents who travel to, from, and within San Francisco. • Collect data on travel behavior and opinions that support other SFMTA strategy and project evaluation needs. The survey was conducted as a telephone study among 804 Bay Area residents aged 18 and older. Interviewing was conducted in English, Spanish, Mandarin, Cantonese, and Tagalog. Surveying was conducted via random digit dial (RDD) and cell phone sample. All survey datasets incorporate respondent weighting based on age and home location; utilize the “weight” field when appropriate in your analysis. The survey period for this survey is as follows: 2017: February - April 2017 The margin of error is related to sample size (n). For the total sample, the margin of error is 3.4% for a confidence level of 95%. When looking at subsets of the data, such as just the SF population, just the female population, or just the population of people who bicycle, the sample size decreases and the margin of error increases. Below is a guide of the margin of error for different samples sizes. Be cautious in making conclusions based off of small sample sizes. At the 95% confidence level is: • n = 804(Total Sample). Margin of error = +/- 3.4% • n = 400. Margin of error = +/- 4.85% • n = 100. Margin of error = +/- 9.80%

In 2020, ** percent of respondents both male and female have expressed that their travel habits are likely to change post-COVID-19. ** percent of male and ** percent of female respondents opted for traveling less frequently by any means post-pandemic.

Graph and download economic data for Employed full time: Wage and salary workers: Reservation and transportation ticket agents and travel clerks occupations: 16 years and over: Women (LEU0254715100A) from 2000 to 2024 about agents, clerical workers, travel, occupation, females, full-time, reserves, transportation, salaries, workers, 16 years +, wages, employment, and USA.

India Foreign Tourist Arrivals: Female: Eastern Europe: Russian data was reported at 158,975.000 Person in 2017. This records an increase from the previous number of 128,450.000 Person for 2016. India Foreign Tourist Arrivals: Female: Eastern Europe: Russian data is updated yearly, averaging 93,997.500 Person from Dec 2008 (Median) to 2017, with 10 observations. The data reached an all-time high of 158,975.000 Person in 2017 and a record low of 46,991.000 Person in 2008. India Foreign Tourist Arrivals: Female: Eastern Europe: Russian data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under India Premium Database’s Tourism Sector – Table IN.QB017: Foreign Tourist Arrivals: by Gender: Female.

India Foreign Tourist Arrivals: Female: Africa: Sudan data was reported at 6,897.000 Person in 2017. This records an increase from the previous number of 3,965.000 Person for 2016. India Foreign Tourist Arrivals: Female: Africa: Sudan data is updated yearly, averaging 1,774.000 Person from Dec 2010 (Median) to 2017, with 8 observations. The data reached an all-time high of 6,897.000 Person in 2017 and a record low of 307.000 Person in 2011. India Foreign Tourist Arrivals: Female: Africa: Sudan data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under India Premium Database’s Tourism Sector – Table IN.QB017: Foreign Tourist Arrivals: by Gender: Female.

A September 2023 study developed an index score to rank the safest countries for solo female travelers worldwide. Based on the analysis, Spain reported the highest figure, with a score of **** out of 10. Norway and the Netherlands followed on the list, with scores of **** and ****, respectively.

India Foreign Tourist Arrivals: Female: Western Europe: Finland data was reported at 9,458.000 Person in 2017. This records an increase from the previous number of 8,358.000 Person for 2016. India Foreign Tourist Arrivals: Female: Western Europe: Finland data is updated yearly, averaging 9,190.000 Person from Dec 2008 (Median) to 2017, with 10 observations. The data reached an all-time high of 13,653.000 Person in 2008 and a record low of 8,267.000 Person in 2015. India Foreign Tourist Arrivals: Female: Western Europe: Finland data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under India Premium Database’s Tourism Sector – Table IN.QB017: Foreign Tourist Arrivals: by Gender: Female.

Total overseas expenditure for the financial year for The Department of Child Safety, Youth and Women. This is additional information reported in lieu of inclusion in the annual report. Read the complete annual report