Hostels price bunglur in india hostal name ---- name of hostel gender --- whitch type of hostal male or female hostal

Address ----- place of hostal month price --- you stey in monthly price par day price ---- daily price

this data extract indian website : https://www.gopgo.in/bengaluru/pgo-properties?city_id=689&latitude=12.971599&longitude=77.594563&search_by=city_id&page=2&total_properties=3763

Hostel Market Outlook

According to our latest research, the global hostel market size reached USD 7.2 billion in 2024, reflecting a robust industry that continues to evolve with changing traveler preferences and demographic shifts. The market is projected to grow at a CAGR of 10.4% from 2025 to 2033, with the market size expected to reach USD 19.2 billion by 2033. This impressive growth trajectory is primarily driven by the increasing popularity of budget accommodation among students, backpackers, and young professionals, as well as the integration of digital platforms that make booking hostels more accessible and efficient worldwide.

One of the key growth factors propelling the hostel market is the rising demand for affordable and flexible accommodation solutions, particularly among millennials and Generation Z. These demographics are increasingly prioritizing experiential travel over luxury, seeking communal living spaces that foster social interaction and cultural exchange. Hostels, with their shared dormitories, common areas, and organized social events, perfectly align with these preferences. The proliferation of international student exchange programs and working holiday visas has further fueled demand, making hostels a preferred choice for long-term stays and transient travelers alike. Additionally, the trend toward digital nomadism has encouraged hostels to innovate their offerings, incorporating co-working spaces and high-speed internet, thus broadening their appeal to remote workers and freelancers.

Technological advancements have also played a pivotal role in the expansion of the hostel market. The widespread adoption of online travel agencies (OTAs) and direct booking platforms has made it easier for travelers to compare prices, read reviews, and secure reservations in real time. This digital transformation has not only enhanced the visibility of hostels on a global scale but also enabled operators to optimize pricing strategies and occupancy rates through data analytics. The integration of contactless check-in, mobile key access, and personalized guest experiences has further elevated the standard of hostel accommodation, bridging the gap between budget and boutique offerings. As a result, hostels are increasingly attracting a more diverse clientele, including working professionals and families seeking value-driven travel options.

Sustainability and community engagement are emerging as significant growth drivers in the hostel market. Many hostel operators are adopting eco-friendly practices, such as energy-efficient designs, waste reduction initiatives, and partnerships with local businesses. These efforts resonate strongly with environmentally conscious travelers, who are willing to pay a premium for sustainable accommodation. Moreover, hostels are leveraging their unique position within local communities to offer authentic cultural experiences, such as guided tours, language classes, and volunteering opportunities. This focus on responsible tourism not only enhances the guest experience but also contributes to the long-term viability of the hostel sector.

From a regional perspective, Europe remains the largest and most mature market for hostels, accounting for over 35% of global revenue in 2024. The region’s rich cultural heritage, extensive backpacker routes, and supportive infrastructure make it a hotspot for hostel accommodation. Asia Pacific is witnessing the fastest growth, driven by rising middle-class incomes, expanding tourism sectors in countries like Thailand, Vietnam, and India, and a burgeoning youth population. North America and Latin America are also experiencing steady growth, fueled by increasing domestic travel and the popularity of urban hostels in major cities. The Middle East & Africa, though still nascent, present significant untapped potential as tourism development accelerates in key destinations. The interplay of these regional dynamics ensures a vibrant and competitive global hostel market.

Type Analysis

The hostel market

The size of the Youth Hostel market was valued at USD 3719 million in 2023 and is projected to reach USD 6090.10 million by 2032, with an expected CAGR of 7.3% during the forecast period.

The global Backpacker Hostel market is projected to reach a value of $XX million by 2033, expanding at a CAGR of XX% during the forecast period (2025-2033). The increasing popularity of budget travel, particularly among millennials and Gen Z, is driving the market growth. Moreover, the rise of digital booking platforms and the growing availability of affordable accommodation options are further contributing to the market expansion. The market is segmented based on application (personal travel, group travel) and type (double room, multiple room). The personal travel segment holds a larger market share due to the increasing number of solo travelers seeking budget-friendly accommodation options. The double room segment dominates the market in terms of type, as it offers a balance between privacy and cost-effectiveness. Key players in the market include Notting Hill, Selina, URBANY HOSTEL LONDON, YHA London St Pancras, CityHub, The Bee Hostel, Hostel One, Beau M, The People, BackpackerBerlin, EastSeven Berlin Hostel, Itaca Hostel, Wombat's, Alter Hostel, and Urban Garden Hostel.

This dataset contains a fully synthetic but realistic collection of hostel-life expenses recorded between January and March 2025. It reflects typical spending patterns of a college hosteller, including food, snacks, travel, stationery, laundry, and medical expenses.

✅ Suitable For: • Exploratory Data Analysis (EDA) • Time-series analysis • Visualization practice (bar charts, pie charts, line charts) • Building budget tracking dashboards • Data cleaning exercises • Machine learning practice

✅ Why this dataset? Beginners often struggle to find simple, clean datasets that are easy to analyze. This dataset is created with students in mind and is perfect for learning Python, Pandas, Matplotlib, Seaborn, Plotly, and feature engineering.

✅ Legal Note: All data is artificially generated by the author. No personal or sensitive information is used. Safe for public use.

Columns: • Date
• Expense_Type
• Amount
• Payment_Mode
• Notes

The hostel market has emerged as an integral component of the global travel and accommodation industry, catering particularly to budget-conscious travelers seeking affordable and community-oriented lodging options. Traditionally characterized by shared dormitory-style accommodations and communal spaces, hostels have

The Bed and Breakfast and Hostel industry has seen considerable growth and change in recent years. Rather than remaining purely budget accommodation options, these smaller establishments have flourished, carving out a unique niche in the hospitality sector. With a focus on affordability, authenticity and personalized services as their key differentiators, they bring a new flavor to the otherwise impersonal hotel-dominated landscape. Besides a low COVID base year, this adaptability has resulted in a robust increase in revenue at an annualized rate of 9.9%, hitting an expected $3.1 billion in 2025 and witnessing a moderate growth of 2.0% in the same year. Further, industry profit is anticipated to reach 8.1%. However, the industry has also undergone its own set of challenges. This niche has seen its budget-focused clientele siphoned off by short-term sublease services like Airbnb, which caters to customers seeking a more localized travel experience. Yet, hope isn't lost. Recent regulatory crackdowns on house-sharing services, especially in major metropolitan cities, could be a boon for B&Bs and hostels, presenting their unique offerings as refreshed alternatives to the market. The inflationary pressure has nonetheless complicated the scene. The small-scale nature of these operations has been both an advantage and a hurdle, making them susceptible to numerous challenges and a rollercoaster of uncertainties. Despite these headwinds, industry predictions suggest a silver lining. With a projected annualized growth of 2.0%, the industry is expected to reach $3.5 billion by 2030. Considering these market shifts, regulatory changes and variability in accommodation preferences, the Bed and Breakfast and Hostel industry has proven its mettle. These smaller-scale ventures have navigated the rocky waters with agility, creating a notable presence within the ever-evolving business landscape. Despite the challenges mentioned, the projected revenue growth and rising demand for their distinct offerings suggest a positive outlook for their continued success.

Explore the booming youth hostel market! Discover key growth drivers, emerging trends, and market size projections for budget travel, backpacker accommodations, and hostels worldwide from 2019-2033.

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The global Hospitality ERP market size was valued at USD 729 million in 2025 and is expected to expand at a CAGR of 5.7% from 2025 to 2033. The market growth is attributed to the increasing adoption of cloud-based ERP solutions, the rising demand for integrated systems to streamline operations, and the growing need for real-time data and analytics in the hospitality industry. Key drivers include the increasing need for operational efficiency, the growing adoption of mobile and cloud-based solutions, and the increasing demand for data-driven insights. The market is segmented based on application into hotel, hostel, resort, and others. The hotel segment accounted for the largest market share in 2025 due to the increasing number of hotel chains and the growing demand for integrated systems to manage multiple properties. Based on deployment type, the cloud-based segment is expected to grow at the highest CAGR during the forecast period due to its cost-effectiveness, scalability, and ease of deployment. The key players in the market include Deskera, Epicor Software, IBM, Infor, Microsoft, Oracle, SAP, Sage, Tech Cloud ERP, BAASS, The Answer Company, Abacre, and Qloapps. The market is highly competitive with a number of established players and emerging vendors offering a wide range of solutions. Mergers and acquisitions are expected to continue in the market, as companies seek to expand their product portfolios and geographic reach.

The global capsule hotel market, valued at $228.9 million in 2025, is projected to experience robust growth, driven by a compound annual growth rate (CAGR) of 6.5% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, the increasing popularity of budget-friendly travel options among millennials and Gen Z, who prioritize experiences over luxury accommodations, significantly boosts demand. Secondly, the rise of eco-conscious tourism and the appeal of unique, space-saving designs contribute to the sector's attractiveness. Furthermore, strategic locations in major tourist hubs and business districts enhance accessibility and convenience for travelers. The market also benefits from technological advancements, such as online booking platforms and improved facility management systems, streamlining operations and enhancing the customer experience. However, the market faces certain challenges. Competition from traditional hotels and the emergence of alternative budget accommodations, such as hostels and shared apartments, pose threats. Fluctuations in tourism patterns due to global events and economic conditions can impact occupancy rates. Regulations regarding space and safety standards in capsule hotels also vary across regions, posing operational complexities. To mitigate these challenges, operators are focusing on enhancing amenities, providing personalized services, and leveraging technology to optimize pricing strategies and target specific demographics effectively. The continued focus on innovation, strategic partnerships, and efficient management will be crucial for sustained growth within this dynamic market.

The Backpacker Hostel market has emerged as a vital segment of the global hospitality industry, catering to budget-conscious travelers seeking affordable accommodation and cultural experiences. Characterized by a sociable atmosphere, backpacker hostels provide more than just a bed; they foster community, enabling gu

[212+ Pages Report] The global travel accommodation market size is expected to grow from USD 646 billion in 2021 to USD 1161 billion by 2030, at a CAGR of 12.59% from 2022-2030

Abstract

The Project for Statistics on Living standards and Development was a countrywide World Bank Living Standards Measurement Survey. It covered approximately 9000 households, drawn from a representative sample of South African households. The fieldwork was undertaken during the nine months leading up to the country's first democratic elections at the end of April 1994. The purpose of the survey was to collect statistical information about the conditions under which South Africans live in order to provide policymakers with the data necessary for planning strategies. This data would aid the implementation of goals such as those outlined in the Government of National Unity's Reconstruction and Development Programme.

Geographic coverage

National

Analysis unit

Households

Universe

All Household members. Individuals in hospitals, old age homes, hotels and hostels of educational institutions were not included in the sample. Migrant labour hostels were included. In addition to those that turned up in the selected ESDs, a sample of three hostels was chosen from a national list provided by the Human Sciences Research Council and within each of these hostels a representative sample was drawn on a similar basis as described above for the households in ESDs.

Kind of data

Sample survey data [ssd]

Sampling procedure

(a) SAMPLING DESIGN

Sample size is 9,000 households. The sample design adopted for the study was a two-stage self-weighting design in which the first stage units were Census Enumerator Subdistricts (ESDs, or their equivalent) and the second stage were households. The advantage of using such a design is that it provides a representative sample that need not be based on accurate census population distribution in the case of South Africa, the sample will automatically include many poor people, without the need to go beyond this and oversample the poor. Proportionate sampling as in such a self-weighting sample design offers the simplest possible data files for further analysis, as weights do not have to be added. However, in the end this advantage could not be retained, and weights had to be added.

(b) SAMPLE FRAME

The sampling frame was drawn up on the basis of small, clearly demarcated area units, each with a population estimate. The nature of the self-weighting procedure adopted ensured that this population estimate was not important for determining the final sample, however. For most of the country, census ESDs were used. Where some ESDs comprised relatively large populations as for instance in some black townships such as Soweto, aerial photographs were used to divide the areas into blocks of approximately equal population size. In other instances, particularly in some of the former homelands, the area units were not ESDs but villages or village groups. In the sample design chosen, the area stage units (generally ESDs) were selected with probability proportional to size, based on the census population. Systematic sampling was used throughout that is, sampling at fixed interval in a list of ESDs, starting at a randomly selected starting point. Given that sampling was self-weighting, the impact of stratification was expected to be modest. The main objective was to ensure that the racial and geographic breakdown approximated the national population distribution. This was done by listing the area stage units (ESDs) by statistical region and then within the statistical region by urban or rural. Within these sub-statistical regions, the ESDs were then listed in order of percentage African. The sampling interval for the selection of the ESDs was obtained by dividing the 1991 census population of 38,120,853 by the 300 clusters to be selected. This yielded 105,800. Starting at a randomly selected point, every 105,800th person down the cluster list was selected. This ensured both geographic and racial diversity (ESDs were ordered by statistical sub-region and proportion of the population African). In three or four instances, the ESD chosen was judged inaccessible and replaced with a similar one. In the second sampling stage the unit of analysis was the household. In each selected ESD a listing or enumeration of households was carried out by means of a field operation. From the households listed in an ESD a sample of households was selected by systematic sampling. Even though the ultimate enumeration unit was the household, in most cases "stands" were used as enumeration units. However, when a stand was chosen as the enumeration unit all households on that stand had to be interviewed.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

All the questionnaires were checked when received. Where information was incomplete or appeared contradictory, the questionnaire was sent back to the relevant survey organization. As soon as the data was available, it was captured using local development platform ADE. This was completed in February 1994. Following this, a series of exploratory programs were written to highlight inconsistencies and outlier. For example, all person level files were linked together to ensure that the same person code reported in different sections of the questionnaire corresponded to the same person. The error reports from these programs were compared to the questionnaires and the necessary alterations made. This was a lengthy process, as several files were checked more than once, and completed at the beginning of August 1994. In some cases, questionnaires would contain missing values, or comments that the respondent did not know, or refused to answer a question.

These responses are coded in the data files with the following values: VALUE MEANING -1 : The data was not available on the questionnaire or form -2 : The field is not applicable -3 : Respondent refused to answer -4 : Respondent did not know answer to question

Data appraisal

The data collected in clusters 217 and 218 should be viewed as highly unreliable and therefore removed from the data set. The data currently available on the web site has been revised to remove the data from these clusters. Researchers who have downloaded the data in the past should revise their data sets. For information on the data in those clusters, contact SALDRU http://www.saldru.uct.ac.za/.

Abstract

Every person, household and institution present in South Africa on Census Night, 9-10 October 1996, should have been enumerated in Census '96. The intent was to provide a count of all persons present within the territory of the Republic of South Africa at that time. More specifically, the purpose of this census was to collect, process and disseminate detailed statistics on population size, composition and distribution at a small area level. The 1996 South African population Census contains data collected on HOUSEHOLDS and INSTITUTIONS: dwellling type, home ownership, household assets, access to services and energy sources; INDIVIDUALS: age, population group, language, religion, citizenship, migration, fertility, mortality and disability; and economic characteristics of individuals, including employment activities and unemployment.

Geographic coverage

The South African Census 1996 has national coverage.

Analysis unit

The units of analysis for the South Africa Census 1996 were households, individuals and institutions

Universe

The South African Census 1996 covered every person present in South Africa on Census Night, 9-10 October 1996 (except foreign diplomats and their families).

Kind of data

Census/enumeration data [cen]

Sampling procedure

The data in the South African Census 1996 data file is a 10% unit level sample drawn from Census 1996 as follows:

1) Households: • A 10% sample of all households (excluding special institutions and hostels)

2) Persons: • A 10% sample of all persons as enumerated in the 1996 Population Census in South Africa

The census household records were explicitly stratified according to province and district council. Within each district council the records were further implicitly stratified by local authority. Within each implicit stratum the household records were ordered according to the unique seven-digit census enumerator area number, of which the first three digits are the (old) magisterial district number.

Mode of data collection

Face-to-face [f2f]

Research instrument

Different methods of enumeration were used to accommodate different situations and a variety of questionnaires were used. The information collected with each questionnaire differed slightly. The questionnaires used were as follows:

Questionnaire 1: (Household and personal questionnaire) This questionnaire was used in private households and within hostels which provided family accommodation. It contained 50 questions for each person and 15 for each household. Every household living in a private dwelling should have been enumerated on a household questionnaire. This questionnaire obtained information about the household and about each person who was present in the household on census night.

Questionnaire 2: (Summary book for hostels) This questionnaire was used to list all persons/households in the hostel and included 9 questions about the hostel. A summary book for hostels should have been completed for each hostel (that is, a compound for workers provided by mines, other employers, municipalities or local authorities). This questionnaire obtained information about the hostel and also listed all household and/or persons enumerated in the hostel. Some hostels contain people living in family groups. Where people were living as a household in a hostel, they were enumerated as such on a household questionnaire (which obtained information about the household and about each person who was present in the household on Census Night). On the final census file, they will be listed as for any other household and not as part of a hostel. Generally, hostels accommodate mostly individual workers. In these situations, persons were enumerated on separate personal questionnaires. These questionnaires obtained the same information on each person as would have been obtained on the household questionnaire. The persons will appear on the census file as part of a hostel. Some hostels were enumerated as special institutions and not on the questionnaires designed specifically for hostels.

Questionnaire 3: (Enumerator's book for special enumeration) This questionnaire was used to obtain very basic information for individuals within institutions such as hotels, prisons, hospitals etc. as well as for homeless persons. Only 6 questions were asked of these people. The questionnaire also included 9 questions about the institution. An enumerator's book for special enumeration should have been completed for each institution such as prisons and hospitals. This questionnaire obtained information on the institution and listed all persons present. Each person was asked a brief sub-set of questions - just 7 compared to around 50 on the household and personal questionnaires. People in institutions could not be enumerated as households. Homeless persons were enumerated during a sweep on census night using a special questionnaire. The results were later transcribed to standard enumerator's books for special enumeration to facilitate coding and data entry.

Response rate

The final calculation of the undercount of persons, based on analysis of a post-enumeration survey (PES) conducted shortly after the original census, was performed by Statistics South Africa. The estimated reponse rates are detailed below, both according to stratum and for the country as a whole. An estimated 10,7% of the people in South Africa, through the course of the census process, were not enumerated. For more information on the undercount and PES, see the publication, "Calculating the Undercount in Census '96", Statistics South Africa Report No. 03-01-18 (1996) which is included in the external documents section.

Undercount of persons by province (stratum, in %):

Western Cape 8,69
Eastern Cape 10,57
Northern Cape 15,59
Free State 8,75
KwaZulu-Natal 12,81
North West 9,37
Gauteng 9,99
Mpumalanga 10,09
Northern Province 11,28

South Africa 10,69

The Youth Hostel market, a vital segment of the hospitality industry, provides affordable and communal lodging options, primarily targeting young travelers, students, and budget-conscious adventurers. Over recent years, this market has experienced notable growth, driven by an increased interest in budget travel, cul

Dormplace Platforms Market Outlook

According to our latest research, the global Dormplace Platforms market size is estimated at USD 2.14 billion in 2024, with a robust growth trajectory expected over the next decade. The market is projected to reach USD 6.78 billion by 2033, expanding at a noteworthy CAGR of 13.6% during the forecast period. The primary growth driver for the Dormplace Platforms market is the increasing demand for digital solutions that streamline student housing, enhance roommate matching, and facilitate secure rental transactions, as universities and property managers seek to modernize their operations and improve user experiences.

A significant growth factor for the Dormplace Platforms market is the rapid digital transformation within the education and property management sectors. As universities and student housing providers strive to offer seamless, tech-enabled experiences, the adoption of web-based and mobile-based platforms has surged. These platforms address key pain points, such as efficient roommate matching, real-time rental listings, and secure payment gateways. The proliferation of smartphones and increased internet penetration among students further bolster this trend, enabling users to access critical housing services on the go. Additionally, the shift toward hybrid learning models and the globalization of higher education have amplified the need for flexible, scalable housing solutions, driving the expansion of Dormplace Platforms worldwide.

Another crucial factor propelling market growth is the evolving expectations of Generation Z and Millennial students, who prioritize convenience, transparency, and community engagement in their housing experiences. Dormplace Platforms cater to these preferences through integrated community features, digital lease management, and social networking functionalities. The integration of advanced technologies such as artificial intelligence, machine learning, and data analytics enhances roommate compatibility algorithms and personalizes housing recommendations, setting new standards for user satisfaction. Moreover, the COVID-19 pandemic accelerated the digitization of student services, making online housing platforms indispensable for universities and property managers aiming to maintain safe and efficient housing operations.

Strategic collaborations and partnerships between Dormplace Platforms, universities, and property management companies are also fueling market expansion. These alliances enable platforms to offer exclusive listings, tailored services, and value-added features that address the unique needs of students and institutional clients. The growing trend of international student mobility, particularly in regions like North America, Europe, and Asia Pacific, has further intensified the demand for reliable, cross-border housing solutions. As institutions compete to attract and retain students, investment in Dormplace Platforms has become a strategic imperative, contributing to the marketÂ’s sustained growth momentum.

From a regional perspective, North America currently leads the Dormplace Platforms market, accounting for the largest revenue share in 2024. The regionÂ’s advanced digital infrastructure, high concentration of universities, and strong culture of off-campus living support widespread platform adoption. Europe follows closely, driven by increasing student mobility and regulatory support for digital housing solutions. The Asia Pacific region is poised for the fastest growth, with surging student populations and rapid urbanization fueling demand for scalable, tech-enabled housing platforms. Latin America and the Middle East & Africa are emerging markets, presenting untapped opportunities for platform providers as higher education expands and digital adoption accelerates.

In the context of student accommodations, the concept of a Hostel has been evolving significantly. Traditionally seen as a budget-friendly housing option for students, hostels are now integrating more digital solutions to enhance the living experience. Modern hostels are increasingly adopting features from Dormplace Platforms, such as digital roommate matching and online payment systems, to provide a seamless and efficient experience for their residents. This transformation is driven by the need to cater to tech-savvy students who expect convenience and connectivity