ASS: Exp: FI: SCOR: Commodity Contracts Brokerage data was reported at 3.399 USD bn in 2016. This records a decrease from the previous number of 3.602 USD bn for 2015. ASS: Exp: FI: SCOR: Commodity Contracts Brokerage data is updated yearly, averaging 3.602 USD bn from Dec 2003 (Median) to 2016, with 11 observations. The data reached an all-time high of 5.100 USD bn in 2008 and a record low of 2.960 USD bn in 2003. ASS: Exp: FI: SCOR: Commodity Contracts Brokerage data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.H021: Annual Services Survey: Employer Firms Expense.

UK product proportions by industry for the Annual Survey of Goods and Services (ASGS)

Provides estimates of revenue and other measures for most traditional service industries. The Bureau of Economic Analysis uses these data in its preparation of the Gross Domestic Product (GDP), national income and product accounts, and its benchmark and annual input-output tables. The Bureau of Labor Statistics uses the data as input to its producer price indexes and in developing productivity measurements. The Centers for Medicare and Medicaid Services (CMS) uses the data to estimate expenditures for the National Health Accounts. The Coalition of Service Industries uses data for general research and planning. Trade and professional organizations use the estimates to analyze industry trends and benchmark their own statistical programs, develop forecasts, and evaluate regulatory requirements. The media use estimates for news reports and background information. Private businesses use the estimates to measure market share; analyze business potential; and plan investment decisions.

Abstract

The central statistical offices in most countries place heavy emphasis on constructing sound databases for all activities within the services sector. PCBS’ Services Statistics Program is part of the Economic Statistics Program, which is part of the larger program for establishing the System of Official Statistics for Palestine. PCBS initiated, in the reference year 1994, the economic surveys series. The series includes, in addition to the services survey, surveys on industry, internal trade construction-contractors, and transport and storage sectors for the purpose of establishing a time series database of economic activities in line with international recommendations specified in System of National Account (SNA) 93 and in the UN manual for Services Statistics.

1. Objectives: The objective of the survey was to obtain data on:

2.1 Number of enterprises and persons engaged in services by activity and location. 2.2 Value of output, intermediate consumption and stocks. 2.3 Value added components. 2.4 Payments and transfers. 2.5 Capital formation. 2.6 Contribution of the surveyed activities to the GDP and other National Accounts variables.

Target Population

PCBS depends on the International and Industrial Classification of all economic activities, version 3, (ISIC - 3) by the United Nation to classify the economic activities. The services survey covers the following activities: 1. Hotels and restaurants 2. Real estate, renting and business activities 3. Education 4. Health and social work 5. Other community, social and personal service activities

Geographic coverage

West Bank and Gaza Strip

Analysis unit

Enterprise constitutes the primary sampling unit (PSU)

Universe

Enterprise: It is an economic entity that is capable, in its own right, of owning assets, incurring liabilities and engaging in economic activities and in transactions with other entities. Includes enterprise related to household and branches, and enterprise related to non-financial companies sector.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of the Services Survey is a single-stage stratified random - systematic sample in which the enterprise constitutes the primary sampling unit (PSU). Three levels of strata were used to arrive at an efficient representative sample (i.e. economic activity, size of employment and geographical levels). The sample size amounted to 1,278 enterprises out of the 12,402 enterprises that comprise the survey frame.

Mode of data collection

Face-to-face [f2f]

Research instrument

Survey Questionnaire

There is one form of the services survey questionnaire 2002, related to household and branches, and the non-finance companies sector. The questionnaire contains the following main variables: 1. Number of employees in a company and their compensations. 2. The output of the main and second activities. 3. Goods production inputs. 4. Various payments and transfers. 5. Indirect taxes. 6. Enterprises assets.

Cleaning operations

Data processing: For ensuring quality and consistency of data, a set of measures were taken to account for strengthening accuracy of data as follows: - Preparing data entry program before data collection for checking readiness of the program for data entry. - A set of validation rules were applied on the program for checking consistency of data. - Efficiency of the program was checked through pre-testing in entering few questionnaires, including incorrect information for checking its efficiency, in capturing these information. - Well trained data keyers were selected and trained for the main data entry. - Weekly or biweekly data files were received by project management for checking accuracy and consistency, notes of correction are provided for data entry management for correction.

Response rate

82.4%

Sampling error estimates

Statistical Errors: The findings of the survey are affected by statistical errors due to using sampling in conducting the survey for the units of the target population, which increases the chances of having variances from the actual values we expect to obtain from the data had we conducted the survey using comprehensive enumeration. The variance of the key goods in the survey was computed and dissemination was carried out on the level of the Palestinian Territory for reasons related to sample design and computation of the variance of the different indicators.

Non-Statistical Errors These types of errors could appear on one or all the survey stages that include data collection and data entry: Response errors: these types of errors are related to responders, fieldworkers, and data entry personnel. And to avoid mistakes and reduce the impact has been a series of actions that would enhance the accuracy of the data through a process of data collection from the field and the data processing.

This dataset includes the average of the response rates of "Agree" or "Strongly Agree" for each question on the Civil Division Annual Survey regarding satisfaction with customer service in the areas of: timeliness, courtesy, communication, caring, ease of use and resolution of the issue.

This page provides data for the Civil Division Annual Survey performance measure.

This data set includes the responses, categorized by question, for the Civil Division Annual Survey. Responses include, Strongly Agree, Agree, Neither agree nor disagree, disagree and strongly disagree.

The performance measure dashboard is available at 5.08 Civil Division Annual Survey.Additional InformationSource: Department annual survey

Contact: Jenny Armstrong

Contact E-Mail: Jenny_Armstrong@tempe.gov

Data Source Type: Excel

Preparation Method: Surveys are tallied and the responses for each category averaged to determine the aggregate effectiveness rate.

Publish Frequency: Annually

Publish Method: Manual

Data Dictionary

Services Ind Survey: Info Ind: Sales: SD: Software Orders data was reported at 415.341 JPY bn in May 2018. This records an increase from the previous number of 362.224 JPY bn for Apr 2018. Services Ind Survey: Info Ind: Sales: SD: Software Orders data is updated monthly, averaging 377.541 JPY bn from Jan 1994 (Median) to May 2018, with 293 observations. The data reached an all-time high of 1,493.137 JPY bn in Mar 2006 and a record low of 84.664 JPY bn in Apr 1994. Services Ind Survey: Info Ind: Sales: SD: Software Orders data remains active status in CEIC and is reported by Ministry of Economy, Trade and Industry. The data is categorized under Global Database’s Japan – Table JP.S063: Survey of Selected Services Industries.

This dataset contains the employee survey results for Business Services.

Data Description: This data set contains a record of all Citizen Service Requests (CSRs) feedback survey responses. When CSRs are closed out by the City, customers who provide an email address are automatically sent a notification that their work has been completed, as well as a link to a customer service satisfaction survey. Customers are able to provide feedback on work completion, satisfaction level, and any additional information. No identifying personal customer/citizen information (name, contact information, or additional comments) is included in this data.

Data Creation: Data generated when CSR feedback surveys are submitted

Data Created By: DPS

Refresh Frequency:

CincyInsights: The City of Cincinnati maintains an interactive dashboard portal, CincyInsights in addition to our Open Data in an effort to increase access and usage of city data. This data set has an associated dashboard available here: https://insights.cincinnati-oh.gov/stories/s/Customer-Service-CSR-Satisfaction/ks8a-xggj/

Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this dataset.

Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).

Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad

This survey consisted of 4 surveys covering a total of eighteen different services of Wake County. The study attempted to measure resident satisfaction with public services provided by the county. A set of common core questions plus demographics were contain in each survey.

This survey is the sixth in a series of comprehensive nationwide surveys designed to help the Department of Veterans Affairs (VA) plan its future programs and services for Veterans. This is the first time VA has included groups other than Veterans.

Graph and download economic data for Women Employees, Private Education and Health Services (CES6500000010) from Jan 1964 to May 2025 about females, health, establishment survey, education, services, employment, and USA.

Albania Business Survey: sa: Services: Confidence Indicator data was reported at 24.800 % Point in Apr 2025. This records an increase from the previous number of 24.281 % Point for Mar 2025. Albania Business Survey: sa: Services: Confidence Indicator data is updated monthly, averaging 14.920 % Point from May 2016 (Median) to Apr 2025, with 108 observations. The data reached an all-time high of 32.630 % Point in May 2024 and a record low of -45.681 % Point in Apr 2020. Albania Business Survey: sa: Services: Confidence Indicator data remains active status in CEIC and is reported by Bank of Albania. The data is categorized under Global Database’s Albania – Table AL.S006: Business Survey: Services.

Graph and download economic data for All Employees, Personal and Laundry Services (CEU8081200001) from Jan 1990 to May 2025 about laundry, establishment survey, services, employment, and USA.

Abstract

An Enterprise Survey is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of business environment topics including access to finance, corruption, infrastructure, crime, competition, and performance measures. The objective of the Enterprise Survey is to gain an understanding of what firms experience in the private sector.

As part of its strategic goal of building a climate for investment, job creation, and sustainable growth, the World Bank has promoted improving the business environment as a key strategy for development, which has led to a systematic effort in collecting enterprise data across countries. The Enterprise Surveys (ES) are an ongoing World Bank project in collecting both objective data based on firms’ experiences and enterprises’ perception of the environment in which they operate.

Geographic coverage

National coverage

Analysis unit

The primary sampling unit of the study is the 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 universe of the study, is the non-agricultural economy. It comprises: all manufacturing sectors according to the group classification of ISIC Revision 3.1: (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this 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.

Kind of data

Sample survey data[ssd]

Sampling procedure

The sample for 2017 Colombia ES was selected using stratified random sampling, following the methodology explained in the Sampling Note.

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

Industry stratification was designed as follows: the universe was stratified into three manufacturing industries and two services industries- Food and Beverages (ISIC Rev. 3.1 code 15), Textiles and Garments (ISIC codes 17,18), Other Manufacturing (ISIC codes 16, 19-37), Retail (ISIC code 52) and Other Services (ISIC codes 45, 50, 51, 55, 60-64, and 72).

For the Colombia ES, size stratification was defined as follows: small (5 to 19 employees), medium (20 to 99 employees), and large (100 or more employees).

Regional stratification was done across five regions: Bogota, Cali, Medellin, Barranquilla and Cartagena

Note: See Sections II and III of "The Colombia 2017 Enterprise Surveys Data Set" report for additional details on the sampling procedure.

Mode of data collection

Face-to-Face[f2f]

Research instrument

Two questionnaires - Manufacturing and Services were used to collect the survey data.The questionnaires have common questions (core module) and respectfully additional manufacturing and services specific questions. The eligible manufacturing industries have been surveyed using the Manufacturing questionnaire (includes the core module, plus manufacturing specific questions). Retail firms have been interviewed using the Services questionnaire (includes the core module plus retail specific questions) and the residual eligible services have been covered using the Services questionnaire (includes the core module). Each variation of the questionnaire is identified by the index variable, a0.

Response rate

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; whenever this was done, strict rules were followed to ensure replacements were randomly selected within the same stratum. Further research is needed on survey non-response in the Enterprise Surveys regarding potential introduction of bias.

The share of interviews per contacted establishments was 0.18. This number is the result of two factors: explicit refusals to participate in the survey, as reflected by the rate of rejection (which includes rejections of the screener and the main survey) and the quality of the sample frame, as represented by the presence of ineligible units. The share of rejections per contact was 0.44.

Abstract

The Ghana Statistical Service (GSS) and the World Bank Development Economics Research Group (DECRG) partnered to implement the survey. The purpose was to find out household's access to and use of available financial services.This was a follow-up to an earlier test of survey designs regarding household access to financial services. The underlying premise is that the identity of a respondent can affect the quality and completeness of the information provided, especially when that respondent is providing information about other household members.

The survey will examine whether questions about specific products (e.g. credit cards, life insurance policies, savings clubs) elicit more complete information than questions asking whether a respondent uses services from a type of provider (e.g. commercial bank, credit union).

To derive the data necessary for these tests, the Financial Service Survey incorporated an experimental design in which one of three versions of the survey instrument (questionnaire) was randomly administered to each household. Individual household members were also randomly selected to respond to some sections of the questionnaire.

Geographic coverage

National Regional District, Municipal, Metropolitan

Analysis unit

Individuals

Universe

The survey covered all adult household members (usual residents) aged 15 years and older.

Kind of data

Sample survey data [ssd]

Sampling procedure

The most recently visited enumeration areas (EAs) for the Ghana Living Standards Survey Round 5 (GLSS5) were targeted for the survey. This is because the characteristics of these households may not have changed much, and they were more likely to recollect information they had already provided. All the 120 EAs visited in the 10th and 11th cycles of the GLSS5 were included in the survey, with an additional 34 EAs selected from the 60 EAs visited in the 9th cycle. Households within the 154 EAs were listed and 15 selected randomly from each EA yielding a total of 2,310 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three types of questionnaires were used in the survey:

1. Group 1 Questionnaire - All questions in the three (3) sections were administered to all household members aged 15 years and older. It collected information on background characteristics, the use of financial services and products and actions and attitudes towards accessing and using financial services and products.

2. Group 2 Questionnaire - Sections 1 and 2 of this questionnaire were administered to all household members aged 15 years and older. Sections 3 and 4 were administered to household members randomly selected using the Kish Grid based on given criteria.

3. Group 3 Questionnaire - All questions in section (1) were administered to heads of household and one randomly selected household member and covered background characteristics. Section two (2) was administered to heads of household and covered the use of financial services. Sections 3 and 4 were administered to a randomly selected household member and covered the use of financial services and products and actions and attitudes towards access and use of financial services and products.

All the questionnaires were in English and whenever necessary, the interview was conducted in a language of the respondent's choice. An interpreter was also used where the interviewer was not proficient in the respondent's choice of language.

Cleaning operations

The GSS data editing occurs at three levels:

1. Field editing by interviewers and supervisors
2. Office editing
3. Data cleaning and imputation

Response rate

Out of the 2,310 households selected for the survey, 2,292 were identified and successfully enumerated. This yielded a response rate of 99.2 percent.

Biennial Business Survey data summary for Quality of Business Services survey results. The Business Survey question that relates to this dataset is: “Quality of services provided by City of Tempe” Respondents are asked to rate their satisfaction level using a scale of 1 to 5, where 1 means "Very Dissatisfied" and 5 means "Very Satisfied".This page provides data for the Quality of Business Services performance measure.The performance measure dashboard is available at 5.01 Quality of Business Services.Additional InformationSource:Contact: Wydale HolmesContact E-Mail: wydale_holmes@tempe.govData Source Type: .pdf, ExcelPreparation Method: The City contracts with a vendor to conduct the survey, analyze the data and prepare for publication.Publish Frequency: Every other yearPublish Method: Manual, .pdfData Dictionary

Dataset is an archived set and will no longer be updated. This is a summary dataset for Planning and Business Licensing satisfaction rating from the Developer Survey Raw Data.

Percentage of survey responders rating their satisfaction level at 4 and above.

Slovenia Business Survey: Services: Demand data was reported at 4.608 % in Apr 2025. This records an increase from the previous number of 1.154 % for Mar 2025. Slovenia Business Survey: Services: Demand data is updated monthly, averaging 10.553 % from Apr 2002 (Median) to Apr 2025, with 277 observations. The data reached an all-time high of 44.768 % in Jul 2007 and a record low of -60.236 % in Jun 2020. Slovenia Business Survey: Services: Demand data remains active status in CEIC and is reported by Statistical Office of the Republic of Slovenia. The data is categorized under Global Database’s Slovenia – Table SI.S005: Business Survey: Services.