Abstract

The Firm Analysis and Competitiveness Survey of India (FACS) is a joint undertaking of the Confederation of Indian Industry and the World Bank Group. The objective of the survey is to generate information that state governments can use to formulate policies that better facilitate business creation and operations. This is the third of such surveys being carried out in India. The previous two surveys took place in 2000 and 2002 in 12 states.

In 2005, 2286 businesses were surveyed. The study covered such industries as textiles, garments, pharmaceuticals, electronics, electrical goods, auto-components, metal products, food and agro processing, plastics and plastic products. As in the previous surveys, the goal of the study is to advise state governments on ways to change policies that hinder the start up of more businesses, their expansion and competitiveness in potential export markets.

Firm-level surveys have been conducted since 1998 by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit (FPDEA), which now implements Enterprise Surveys across all geographic regions.

Geographic coverage

National

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instrument is available: - Firm Analysis and Competitiveness Survey of India 2005 Questionnaire.

The questionnaire has two parts. The first part is for the head of the business to respond to. It includes questions about the history and organization of the business, management, markets, supplies, access to technology, credit, skilled manpower, infrastructure, government policies, and business’ economic environment. The second part deals with production, financial, and human resource statistics and is to be answered by the accountant and the personnel manager.

Abstract

The data was collected using the High Frequency Survey (HFS), the new regional data collection tool & methodology launched in the Americas. The survey allowed for better reaching populations of interest with new remote modalities (phone interviews and self-administered surveys online) and improved sampling guidance and strategies. It includes a set of standardized regional core questions while allowing for operation-specific customizations. The core questions revolve around populations of interest’s demographic profile, difficulties during their journey, specific protection needs, access to documentation & regularization, health access, coverage of basic needs, coping capacity & negative mechanisms used, and well-being & local integration. The data collected has been used by countries in their protection monitoring analysis and vulnerability analysis.

Geographic coverage

National coverage

Analysis unit

Household

Universe

All people of concern.

Kind of data

Sample survey data [ssd]

Sampling procedure

In the absence of a well-developed sampling-frame for forcibly displaced populations in the Americas, the High Frequency Survey employed a multi-frame sampling strategy where respondents entered the sample through one of three channels: (i) those who opt-in to complete an online self-administered version of the questionnaire which was widely circulated through refugee social media; (ii) persons identified through UNHCR and partner databases who were remotely-interviewed by phone; and (iii) random selection from the cases approaching UNHCR for registration or assistance. The total sample size was 183 refugee households.

Mode of data collection

Other [oth]

Research instrument

The questionnaire contained the following sections: journey, family composition, vulnerability, basic Needs, coping capacity, well-being, COVID-19 Impact.

Abstract

The documented dataset covers Enterprise Survey (ES) panel data collected in Niger in 2005, 2009 and 2016, as part of Africa Enterprise Surveys rollout, an initiative of the World Bank. The objective of the survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms.

Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries. Only registered businesses are surveyed in the Enterprise Survey.

Data from 151 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses. The data was collected using face-to-face interviews.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs and labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90 percent of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is an establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural private economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors. Companies with 100% government ownership are not eligible to participate in the Enterprise Surveys.

Kind of data

Sample survey data [ssd]

Sampling procedure

Three levels of stratification were used in this country: industry, establishment size, and region.

Industry stratification was designed as follows: the universe was stratified as into manufacturing and services industries- Manufacturing (ISIC Rev. 3.1 codes 15 - 37), and Services (ISIC codes 45, 50-52, 55, 60-64, and 72).

For the 2009 sample stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. Size stratification was defined following the standardized definition used for the Enterprise Surveys: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. Regional stratification was defined in terms of the geographic regions with the largest commercial presence in the country: Maradi and Niamey were the two areas selected in Niger.

Two frames were used for Niger. The first one included official lists from the Chamber of commerce, craft and industries of Niger 2008 and the Repertoire of Companies (2008) operating in Niger. The second frame (the panel sample) consisted of enterprises interviewed for the Enterprise Survey in 2005, which were to be re-interviewed where they were in the selected geographical regions and met eligibility criteria. Both database contained the following information: -Name of the firm -Contact details -ISIC code -Number of employees.

Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 39.9% (134 out of 344 establishments). Breaking down by industry, the following numbers of establishments were surveyed: Manufacturing - 52, Services - 98.

For 2017: Regional stratification for the Niger ES was done across two regions: Niamey and Rest of the Country.

The sample frame consisted of listings of firms from three sources: - the list of 150 firms from the Niger 2009 ES for panel firms - firm data from La Caisse Nationale de Sécurité Sociale (CNSS) and a list of exporting firms by the Institut National des Statistiques (INS) for fresh firms (firms not covered in 2009).

Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 18.6% (76 out of 409 establishments).

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9). b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.

Abstract

The data was collected using the High Frequency Survey (HFS), the new regional data collection tool & methodology launched in the Americas. The survey allowed for better reaching populations of interest with new remote modalities (phone interviews and self-administered surveys online) and improved sampling guidance and strategies. It includes a set of standardized regional core questions while allowing for operation-specific customizations. The core questions revolve around populations of interest’s demographic profile, difficulties during their journey, specific protection needs, access to documentation & regularization, health access, coverage of basic needs, coping capacity & negative mechanisms used, and well-being & local integration. The data collected has been used by countries in their protection monitoring analysis and vulnerability analysis.

Geographic coverage

Whole country.

Analysis unit

Household

Universe

All people of concern.

Sampling procedure

In the absence of a well-developed sampling-frame for forcibly displaced populations in the Americas, the High Frequency Survey employed a multi-frame sampling strategy where respondents entered the sample through one of three channels: (i) those who opt-in to complete an online self-administered version of the questionnaire which was widely circulated through refugee social media; (ii) persons identified through UNHCR and partner databases who were remotely-interviewed by phone; and (iii) random selection from the cases approaching UNHCR for registration or assistance. The total sample size was 388 refugee households.

Mode of data collection

Other [oth]

Research instrument

Questionaire contained the following sections: journey, family composition, vulnerability, basic Needs, coping capacity,well-being,COVID-19 Impact.

The purpose of this study was to measure criminal activity in the United States based on survey reports of crime victims. In the study two different questionnaire forms were used in order to assess which provided better responses. One form was very lengthy and asked detailed questions about each household, person, and incident. The second form was much shorter and asked very generalized questions. The data collection was an attempt to find alternative methods of sampling, interviewing, designing questionnaires, managing data, and reporting results. Detailed information is provided on household characteristics and other characteristics of the respondents, as well as on crime incidents, including burglary, vandalism, assault, and rape.

Based on qualitative responses from businesses to our Quarterly Acquisitions and Disposals of Capital Assets Survey (QCAS) and Quarterly Stocks Survey (QSS).

Abstract

The Firm Analysis and Competitiveness Survey of India (FACS) 2002 is a joint undertaking of the Confederation of Indian Industry and the World Bank Group towards better understanding of the investment climate of States. It follows upon a similar survey of 1200 firms that the two institutions carried out in 2000.

In 2002, 1827 businesses from 12 states were surveyed. The study covered exporting industries, namely, textiles, garments, pharmaceuticals, electronics, electrical White goods, chemicals, metal and auto-components. As in the previous survey, the goal of the study is to advise state governments on ways to change policies that hinder the start up of more businesses, their expansion and competitiveness in potential export markets.

Firm-level surveys have been conducted since 1998 by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit (FPDEA), which now implements Enterprise Surveys across all geographic regions.

Geographic coverage

National

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instrument is available: - Firm Analysis and Competitiveness Survey of India 2002 Questionnaire.

The questionnaire has two parts. The first part is for the head of the business to respond to. It includes questions about the history and organization of the business, management, markets, supplies, access to technology, credit, skilled manpower, infrastructure, government policies, and business’ economic environment. The second part deals with production, financial, and human resource statistics and is to be answered by the accountant and the personnel manager.

This workbook provides data and data dictionaries for the SFMTA 2014 Travel Decision Survey. The 2014 Key Findings, Summary Report, and Methodology, including the survey instrument, can be found online at https://www.sfmta.com/about-sfmta/reports/travel-decision-survey-2014. 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 with approximately 750 Bay Area residents aged 18 and older. Interviewing was conducted in English, Spanish, and Cantonese. Surveying was conducted via random digit dial (RDD) and cell phone sample. All three 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: 2014: October – November 2014

A few questions in TDS 2014 were added after the survey began. In the report, responses that did not answer those questions were excluded from the analysis. The questions that were added late are noted in the TDS 2014 methodology survey instrument. The margin of error is related to sample size (n). For the total sample, the margin of error is 3.5% 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 = 767 (Total Sample). Margin of error = +/- 3.5% • n = 384. Margin of error = +/- 4.95% • n = 100. Margin of error = +/- 9.80%

The Swiss Election Study (Selects) 2023 consists of four complementary components: The Post-Election Survey (PES), the Panel Survey, the Candidate Survey, and the Media Analysis. The study design is largely inspired by Selects 2019. The PES and Candidate Survey are mixed-mode surveys (online/paper), with a push-to-web design, whereas the Panel Study is an online survey. In April 2022, a call for questions/modules was opened to allow researchers from Switzerland and abroad to include novel questions into one or different components of Selects. Ten out of 14 submitted proposals were selected by the Selects Commission after a review process conducted by internationally renowned election researchers, and were fully or partially integrated into one or several components of Selects 2023. The Selects surveys were approved by the Ethics commission of the University of Lausanne.

Post-Election Survey (PES): The Post-Election Survey consists of 5033 respondents who answered the questionnaire in the period from 23 October 2023 to 12 January 2024. The survey was conducted in a sequential mixed mode with web offered as the first option: 90% responded in this way, while 10% responded by returning the paper questionnaire that was sent out with the second reminder to those that had not completed the web questionnaire. The sampling was based on a representative sample of around 2’600 Swiss citizens, with an oversampling of small cantons to have at least 50 respondents in every canton. An additional oversampling was done in the cantons of Geneva and Ticino thanks to additional funding from these cantons. The sample was drawn by the Federal Statistics Office from the SRPH. Sample members received an unconditional incentive (10 CHF in cash) that was sent out with the invitation letter. Module 6 Questionnaire of the Comparative Study of Electoral Systems was included into the PES.

Panel Survey: The Panel Survey studies the evolution of opinion and vote intention/choice during the different phases of the election cycle. In 2023, three waves were conducted: the first before the main campaign period (June/early August), the second during the election campaign (September/October), and the third after the elections (October/November). The initial random sample (stratified by big region/NUTS II) was taken by the Federal Statistics Office from the SRPH. 8197 individuals responded to the first wave, 6077 to the second wave, and 5579 to the third wave. Conditional incentives were used in all three panel waves (lottery of 5x300 CHF in wave 1, 10 CHF in cash in waves 2 and 3). The Panel Survey will continue with annual follow-up waves until the 2027 elections. Wave 4 took place between 23 September and 4 November 2024, with 4'919 respondents.

Candidate Survey: The Candidate Survey was carried out among all candidates for the National Council and the Council of States in the framework of the international Comparative Candidate Survey (CCS) project, based on the Round III questionnaire. The survey collects data on the biography, campaign activities, and policy position of the candidates. Among others, the information gathered makes possible the study of underlying factors of candidates’ electoral success, as well as of issues of representation and linkage between voters and elites. In 2023, 2527 out of 5997 candidates participated in the Candidate Survey. This survey was conducted by FORS in collaboration with Politools and the University of Bern.

Media Analysis: On behalf of Selects, the Center for Research & Methods at the University of Applied Sciences in Business Administration Zurich (HWZ) conducted a Media Analysis. The Media Analysis is a supplement to the Panel Survey and makes it possible to analyse the election campaign in the media and its influence on voters' opinion formation. A media study has been part of Selects since 2003. In 2023, 116 daily or weekly newspapers (print and online) were content-analyzed in the period between 1 May 2023 and 31 October 2023.

Table 2 - Difference in prioritization of patient safety interventions between experts and patient safety managers in Japan

This survey of 12th-grade students is part of a series that explores changes in important values, behaviors, and lifestyle orientations of contemporary American youth. Students are randomly assigned to complete one of six questionnaires, each with a different subset of topical questions, but all containing a set of "core" questions on demographics and drug use. There are about 1,400 variables across the questionnaires. Drugs covered by this survey include tobacco, smokeless tobacco, alcohol, marijuana, hashish, prescription medications, over-the-counter medications, LSD, hallucinogens, amphetamines (stimulants), Ritalin (methylphenidate), Quaaludes (methaqualone), barbiturates (tranquilizers), cocaine, crack cocaine, GHB (gamma hydroxy butyrate), ecstasy, methamphetamine, and heroin. Other topics include attitudes toward religion, changing roles for women, educational aspirations, self-esteem, exposure to drug education, and violence and crime (both in and out of school).Highlights for 2021: Data collection resumed in 2021, with a change to all web-based surveys. Students completed the surveys on their personal or school-provided device. Non-survey variables have been changed or added to facilitate analyses. For details, please see the codebook section "MTF Variable Information - Non-survey variables included in the data files - Survey mode and design variables for 2021" Information about "screen break" issues, where series of questions were originally presented differently in the web-based survey as compared to the 2019/2020 tablet surveys. Please see the codebook and Appendix D for details. For 12th grade: two additional changes to the survey presentation. Please see the codebook section "MTF Variable Information - Non-survey variables included in the data files", and respective appendices for details. Introduction of randomized blocks of questions presented to students. Please see Appendix E. Test of presentation of items in the substance use consequences section on form 3. Please see Appendix F. Additional information is documented in the MTFQchanges2021byForm.pdf and MTFQchanges2021byType.pdf files available for download.

Most preferred sample type for diagnostic testing, ranked globally.

The online survey software market is experiencing robust growth, projected to reach a value of $7.22 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 13.6% from 2025 to 2033. This expansion is driven by several key factors. The increasing need for efficient data collection across diverse sectors, including retail, financial services, healthcare, and manufacturing, fuels demand for user-friendly and scalable survey platforms. The rise of digital transformation initiatives within both SMEs and large enterprises is further propelling market growth, as businesses seek to understand customer preferences, employee satisfaction, and market trends through sophisticated data analytics provided by these platforms. Additionally, the continuous innovation in survey methodologies, including the integration of advanced analytics and AI-powered features, enhances the value proposition of these tools, attracting a wider user base. The competitive landscape is characterized by a mix of established players like Qualtrics and SurveyMonkey and emerging innovative solutions, leading to ongoing product improvements and price optimization. However, market growth is not without challenges. Data privacy concerns and the rising costs associated with implementing and maintaining advanced survey platforms can act as restraints. Furthermore, the market’s reliance on internet penetration and digital literacy levels can hinder adoption in certain regions. To address these challenges, vendors are focusing on developing robust data security features, offering flexible pricing models, and providing comprehensive training and support to enhance user adoption. Geographic expansion, particularly in developing economies with growing internet access, presents significant opportunities for future market growth. The segmentation by end-user (Retail, Financial Services, Healthcare, Manufacturing, Others) and application (SMEs, Large Enterprises) highlights the market's broad appeal and diversified application across numerous industries. This segmentation allows vendors to tailor their offerings and marketing strategies to specific industry needs, optimizing market penetration and profitability.

Research software is increasingly recognized as critical infrastructure in contemporary science. Research software spans a broad spectrum, including source code files, algorithms, scripts, computational workflows, and executables, all created for or during research. Research funders have developed programs, initiatives and policies to bolster research software’s role. However, there has been no empirical study of how research funders prioritize support for research software. This information is needed to clarify where current funder support is concentrated and where strategic gaps may exist. Here, we present data from a survey of research software funders (n=36) from around the world. The survey explored these funders’ priorities, finding a strong emphasis on developing skills, software sustainability, embedding open science, building community and collaboration, advancing research software funding, increasing software visibility and use, innovation and security.

Methods

This research was carried out using a survey combining qualitative and quantitative items. The survey was designed to investigate how research software funders support research software’s sustainability and impact.

The study was reviewed and given an exempt determination by the University of Illinois Urbana-Champaign Institutional Review Board (no. 24374).

Survey design

The survey designed for this study began by collecting profile information, including institutional affiliation and job title. The survey gathered information about respondents’ organization’s initiatives, policies, or programs to support research software. The range of questions yielded too much data for one article. In this article, we focus exclusively on the results generated via an open-ended question asking about the top priorities for the respondents’ organizations’ support for research software: “What are your organization's top priorities related to research software?”. Four open-response text boxes were provided for respondents to indicate and list these priorities.

Sampling

This survey was aimed at international research funders, including governmental and non-governmental (e.g., philanthropic) funders. A list of contacts to invite to participate in this survey was created based on participation in the Research Software Association (ReSA) and responsibility for research software funding known to the authors. This initial list of people was refined, with removals based on individuals having moved to unrelated professional roles or being unavailable long-term, for example, due to personal issues.

The final, refined contact list comprised 71 people. After removing individuals when a member of their organization already provided a complete answer or when the person turned out to no longer be working on a relevant topic or to be otherwise unavailable (total of n=30), 41 people remained. Five of these individuals did not complete the survey, while 36 people (representing 30 research funding organizations) did, yielding a response rate of 87.8%. Fully completed survey responses were not required for individuals to be retained in the sample, resulting in varied sample bases across survey questions.

The sample includes research funders in North and South America, Europe, Oceania and Asia, but over-represents North America and European funder representatives. Some participating funders cover a broad spectrum of disciplines, while others focus on a particular domain such as social science, health, environment, physical sciences or humanities.

The respondents represented research funders supported by governmental (n=26), philanthropic (n=6) and corporate (n=1) resources.

Respondents’ job titles span the following categories: Senior Leadership and Executive, such as a Vice President of Strategy; Program and Project Management, such as Senior Program Manager; Planning and Business Development; Scientific, Technical and IT, such as Scientific Information Lead.

Most respondents 72.7% (n=24) answered ‘Yes’ to the question, “Has your organization established any policies, initiatives or programs aimed at supporting research software?”, while 18.2% (n=6) said ‘No’ and 9.1% (n=3) ‘Unsure’.

Data collection, management and analysis

Data collection took place from December 2023 to May 2024. The mean completion time for the detailed survey was 28 minutes and 13 seconds.

The data were cleaned and prepared for analysis by removing any identifiable respondent details. The data analysis process followed a standard thematic qualitative analysis approach (e.g., Jensen & Laurie, 2016). This involved first identifying themes and organizing the data accordingly. Dimensions of each theme were identified where relevant. Then data extracts were selected from the survey responses associated with each theme and theme dimension.

Additional data: Evolving funding strategies for research software: Insights from an international survey of research funders

Data were uploaded in December 2024 to support another paper drawing on the same overall survey data. This one is entitled: 'Evolving funding strategies for research software: Insights from an international survey of research funders'. The survey data for this upload were generated using the following survey items.

Classification and Categorization of the Questionnaire Statements

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden. The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones. The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

This survey covers China.

Analysis unit

• Household
• Individual

Universe

The WVS for China covers national population, aged 18 years and over, for both sexes.

Kind of data

Sample survey data [ssd]

Sampling procedure

Random sample of Central China, containing 68% of population The sample was designed to be representative of the entire adult population, i.e. 18 years and older, of your country. The lower age cut-off for the sample was 18 and there was not any upper age cut-off for the sample. The sample size for China is N=1500.

Mode of data collection

Face-to-face [f2f]

Research instrument

The WVS questionnaire was in Chinese. Some special variable labels have been included, such as: V 167 Least liked groups: include only categories 2 Capitalist 4 Immigrant, 5 Homosexuals and 6 Criminals. V203/V204 Geographical affinity: 3 stands for China and 4 for Asia. Country Specific variables included are: V208: Ethnic identification: is missing; V209 Language at home: all answers, except 2 are 1 (Chinese); V233 Ethnic group is 100% Chinese (code 4); V234 Region: 1 North, 2 Center, 3 South and 4 East. V235 Language at home is 100% 1 Chinese except 2 cases with code 6. The following variables werent asked: V56, V117 to V124, V135 to V145, V151 to V166, V170, V179 to V191, V210 to V213. V106, V107: do not include category 4 (Free Speech) This is important for those working with post-materialist indexes.

Sampling error estimates

+/- 2,6%

Background
The Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The LFS was first conducted biennially from 1973-1983. Between 1984 and 1991 the survey was carried out annually and consisted of a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter (data were then collected seasonally). From 1992 quarterly data were made available, with a quarterly sample size approximately equivalent to that of the previous annual data. The survey then became known as the Quarterly Labour Force Survey (QLFS). From December 1994, data gathering for Northern Ireland moved to a full quarterly cycle to match the rest of the country, so the QLFS then covered the whole of the UK (though some additional annual Northern Ireland LFS datasets are also held at the UK Data Archive). Further information on the background to the QLFS may be found in the documentation.

Longitudinal data
The LFS retains each sample household for five consecutive quarters, with a fifth of the sample replaced each quarter. The main survey was designed to produce cross-sectional data, but the data on each individual have now been linked together to provide longitudinal information. The longitudinal data comprise two types of linked datasets, created using the weighting method to adjust for non-response bias. The two-quarter datasets link data from two consecutive waves, while the five-quarter datasets link across a whole year (for example January 2010 to March 2011 inclusive) and contain data from all five waves. A full series of longitudinal data has been produced, going back to winter 1992. Linking together records to create a longitudinal dimension can, for example, provide information on gross flows over time between different labour force categories (employed, unemployed and economically inactive). This will provide detail about people who have moved between the categories. Also, longitudinal information is useful in monitoring the effects of government policies and can be used to follow the subsequent activities and circumstances of people affected by specific policy initiatives, and to compare them with other groups in the population. There are however methodological problems which could distort the data resulting from this longitudinal linking. The ONS continues to research these issues and advises that the presentation of results should be carefully considered, and warnings should be included with outputs where necessary.

New reweighting policy
Following the new reweighting policy ONS has reviewed the latest population estimates made available during 2019 and have decided not to carry out a 2019 LFS and APS reweighting exercise. Therefore, the next reweighting exercise will take place in 2020. These will incorporate the 2019 Sub-National Population Projection data (published in May 2020) and 2019 Mid-Year Estimates (published in June 2020). It is expected that reweighted Labour Market aggregates and microdata will be published towards the end of 2020/early 2021.

LFS Documentation
The documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned. However, volumes are updated periodically by ONS, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.

Additional data derived from the QLFS
The Archive also holds further QLFS series: End User Licence (EUL) quarterly data; Secure Access datasets; household datasets; quarterly, annual and ad hoc module datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.

Variables DISEA and LNGLST
Dataset A08 (Labour market status of disabled people) which ONS suspended due to an apparent discontinuity between April to June 2017 and July to September 2017 is now available. As a result of this apparent discontinuity and the inconclusive investigations at this stage, comparisons should be made with caution between April to June 2017 and subsequent time periods. However users should note that the estimates are not seasonally adjusted, so some of the change between quarters could be due to seasonality. Further recommendations on historical comparisons of the estimates will be given in November 2018 when ONS are due to publish estimates for July to September 2018.

An article explaining the quality assurance investigations that have been conducted so far is available on the ONS Methodology webpage. For any queries about Dataset A08 please email Labour.Market@ons.gov.uk.

Occupation data for 2021 and 2022 data files

The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/articles/revisionofmiscodedoccupationaldataintheonslabourforcesurveyuk/january2021toseptember2022" style="background-color: rgb(255, 255, 255);">Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.

2022 Weighting

The population totals used for the latest LFS estimates use projected growth rates from Real Time Information (RTI) data for UK, EU and non-EU populations based on 2021 patterns. The total population used for the LFS therefore does not take into account any changes in migration, birth rates, death rates, and so on since June 2021, and hence levels estimates may be under- or over-estimating the true values and should be used with caution. Estimates of rates will, however, be robust.

Understanding Society, (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Verian Group (formerly Kantar Public) and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

Understanding Society (UK Household Longitudinal Study), which began in 2009, is conducted by the Institute for Social and Economic Research (ISER) at the University of Essex and the survey research organisations Kantar Public and NatCen. It builds on and incorporates, the British Household Panel Survey (BHPS), which began in 1991.

The Understanding Society COVID-19 Study, 2020-2021 is a regular survey of households in the UK. The aim of the study is to enable research on the socio-economic and health consequences of the COVID-19 pandemic, in the short and long term. The surveys started in April 2020 and took place monthly until July 2020. From September 2020 they took place every other month until March 2021 and the final wave was fielded in September 2021. They complement the annual interviews of the Understanding Society study. The data can be linked to data on the same individuals from previous waves of the annual interviews (SN 6614) using the personal identifier pidp. However, the most recent pre-pandemic (2019) annual interviews for all respondents who have taken part in the COVID-19 Study are included as part of this data release. Please refer to the User Guide for further information on linking in this way and for geographical information options.

Latest edition information

For the eleventh edition (December 2021), revised April, May, June, July, September, November 2020, January 2021 and March 2021 data files for the adult survey have been deposited. These files have been amended to address issues identified during ongoing quality assurance activities. All documentation has been updated to explain the revisions, and users are advised to consult the documentation for details. In addition new data from the September 2021 web survey have been deposited.

The global SMS survey software market is experiencing robust growth, driven by the increasing adoption of mobile technology and the need for quick, efficient data collection. This market is projected to reach a substantial size, with a Compound Annual Growth Rate (CAGR) reflecting significant expansion over the forecast period (2025-2033). While precise figures for market size and CAGR are not provided, a reasonable estimation, based on industry trends and the prevalence of mobile-first strategies in market research, would place the market size at approximately $2.5 billion in 2025, growing at a CAGR of 15% from 2025 to 2033. This growth is fueled by several key factors including the cost-effectiveness of SMS surveys compared to traditional methods, the high response rates often achieved through this channel, and the ability to target specific demographics easily. The versatility of SMS surveys across diverse sectors like financial services, retail, healthcare, and media further contributes to this upward trajectory.
The market segmentation reveals a strong preference for cloud-based solutions, owing to their scalability, accessibility, and reduced infrastructure costs. Application-wise, the financial and retail sectors are currently leading the adoption, but the healthcare and media industries are showing significant potential for future growth. Competitive forces are shaping the market landscape, with numerous players offering a range of features and functionalities. While established players such as SurveyMonkey and QuestionPro hold significant market share, smaller, agile companies are emerging with specialized solutions, particularly those focusing on niche sectors or advanced analytics capabilities. This competitive environment is expected to further drive innovation and accessibility within the SMS survey software market, leading to sustained growth in the coming years.

Abstract

The data was collected using the High Frequency Survey (HFS), the new regional data collection tool & methodology launched in the Americas. The survey allowed for better reaching populations of interest with new remote modalities (phone interviews and self-administered surveys online) and improved sampling guidance and strategies. It includes a set of standardized regional core questions while allowing for operation-specific customizations. The core questions revolve around populations of interest's demographic profile, difficulties during their journey, specific protection needs, access to documentation & regularization, health access, coverage of basic needs, coping capacity & negative mechanisms used, and well-being & local integration. The data collected has been used by countries in their protection monitoring analysis and vulnerability analysis.

Geographic coverage

Whole country

Analysis unit

Household

Universe

All people of concern.

Kind of data

Sample survey data [ssd]

Sampling procedure

In the absence of a well-developed sampling-frame for forcibly displaced populations in the Americas, the High Frequency Survey employed a multi-frame sampling strategy where respondents entered the sample through one of three channels: (i) those who opt-in to complete an online self-administered version of the questionnaire which was widely circulated through refugee social media; (ii) persons identified through UNHCR and partner databases who were remotely-interviewed by phone; and (iii) random selection from the cases approaching UNHCR for registration or assistance. The total sample size was 3950 households. At the time of the survey, the population of concern was estimated at around 500000 individuals.

Mode of data collection

Other [oth]

Research instrument

Questionaire contained the following sections: journey, family composition, vulnerability, basic Needs, coping capacity,well-being,COVID-19 Impact.