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.

The survey was conducted in Cameroon between July November 2016 as part of Enterprise Surveys project, 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 361 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.

Abstract

This survey was conducted in Egypt between October 2016 and April 2017 to gain an understanding of what firms experience in the private sector.

The Enterprise Surveys, through interviews with firms in the manufacturing and services sectors, capture business perceptions on the biggest obstacles to enterprise growth, the relative importance of various constraints to increasing employment and productivity, and the effects of a country's business environment on its international competitiveness. They are used to create statistically significant business environment indicators that are comparable across countries. The Enterprise Surveys are also used to build a panel of enterprise data that will make it possible to track changes in the business environment over time and allow, for example, impact assessments of reforms.

Data from 1,827 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses.

The survey topics include firm characteristics, information about sales and suppliers, competition, infrastructure services, judiciary and law enforcement collaboration, security, government policies, laws and regulations, financing, overall business environment, bribery, capacity utilization, performance and investment activities, and workforce composition.

Geographic coverage

National

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 was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.

Industry stratification was designed in the way that follows: the universe was stratified into nine (9) manufacturing and five (5) services industries. The manufacturing industries are Extractives (ISIC Rev. 3.1 code 11), Food, Beverages and Tobacco (ISIC Rev. 3.1 code 15 & 16), Textiles and Garments (ISIC code 17 & 18), Chemicals and Chemical products (ISIC code 24), Petro-chemicals, Rubber and Plastics (ISIC code 23 & 25), Non-metallic mineral products (ISIC code 26), Leather products (ISIC code 19), Furniture, Paper and Printing and Wood products (ISIC code 20-22, 36), Basic Metals and Metal products (ISIC codes 27 & 28) Machinery, Equipment, Electronics, Vehicles and Recycling (ISIC codes 29-35, 37).While the services industries are Wholesale, Retail and Automotive trade (ISIC codes 50-52), Hospitality and Tourism (ISIC codes 55& 63), Transportation (ISIC codes 60-62), ICT (ISIC codes 64 & 72) and Real Estate and Construction (ISIC codes 45 & 70). Note that the global ES methodology excludes Extractives as well as Real Estate activities from the universe of inference. Consequently, for Egypt, there are two datasets available, one including all observations, and another excluding firms that work in Extractives and Real Estate.

For the Egypt 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 for the Egypt ES was done across seven regions: Greater Cairo, Wes Delta, Suez Region, Middle and East Delta, Northern Upper Egypt, Southern Upper Egypt and Frontier.

The sample frame consisted of listings of firms from several sources. For panel firms, the list of 3,846 firms from the Egypt 2004 and 2013 ES was used. For fresh firms (firms not covered in Egypt 2004 and 2013), firm data from Central Agency for Public Mobilization and Statistics (CAPMAS) and General Authority For Investment and Free Zones (GAFI) was used.

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 15.6% (702 out of 4,488 establishments).

Mode of data collection

Face-to-face [f2f]

Research instrument

The structure of the database reflects the fact that two different versions of the survey instrument were used for all registered establishments. 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.

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, while 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 the refusal to respond as a different option from don’t know. 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.

The number of realized interviews per contacted establishment was 0.41. 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 0.06.

The Business Structure Database (BSD) contains a small number of variables for almost all business organisations in the UK. The BSD is derived primarily from the Inter-Departmental Business Register (IDBR), which is a live register of data collected by HM Revenue and Customs via VAT and Pay As You Earn (PAYE) records. The IDBR data are complimented with data from ONS business surveys. If a business is liable for VAT (turnover exceeds the VAT threshold) and/or has at least one member of staff registered for the PAYE tax collection system, then the business will appear on the IDBR (and hence in the BSD). In 2004 it was estimated that the businesses listed on the IDBR accounted for almost 99 per cent of economic activity in the UK. Only very small businesses, such as the self-employed were not found on the IDBR.

The IDBR is frequently updated, and contains confidential information that cannot be accessed by non-civil servants without special permission. However, the ONS Virtual Micro-data Laboratory (VML) created and developed the BSD, which is a 'snapshot' in time of the IDBR, in order to provide a version of the IDBR for research use, taking full account of changes in ownership and restructuring of businesses. The 'snapshot' is taken around April, and the captured point-in-time data are supplied to the VML by the following September. The reporting period is generally the financial year. For example, the 2000 BSD file is produced in September 2000, using data captured from the IDBR in April 2000. The data will reflect the financial year of April 1999 to March 2000. However, the ONS may, during this time, update the IDBR with data on companies from its own business surveys, such as the Annual Business Survey (SN 7451).

The data are divided into 'enterprises' and 'local units'. An enterprise is the overall business organisation. A local unit is a 'plant', such as a factory, shop, branch, etc. In some cases, an enterprise will only have one local unit, and in other cases (such as a bank or supermarket), an enterprise will own many local units.

For each company, data are available on employment, turnover, foreign ownership, and industrial activity based on Standard Industrial Classification (SIC)92, SIC 2003 or SIC 2007. Year of 'birth' (company start-up date) and 'death' (termination date) are also included, as well as postcodes for both enterprises and their local units. Previously only pseudo-anonymised postcodes were available but now all postcodes are real.

The ONS is continually developing the BSD, and so researchers are strongly recommended to read all documentation pertaining to this dataset before using the data.

Linking to Other Business Studies
These data contain IDBR reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.

Latest Edition Information
For the sixteenth edition (March 2024), data files and a variable catalogue document for 2023 have been added.

Mayor's Order 2017-115 establishes a comprehensive data policy for the District government. The data created and managed by the District government are valuable assets and are independent of the information systems in which the data reside. As such, the District government shall: maintain an inventory of its enterprise datasets; classify enterprise datasets by level of sensitivity; regularly publish the inventory, including the classifications, as an open dataset; and strategically plan and manage its investment in data.The greatest value from the District’s investment in data can only be realized when enterprise datasets are freely shared among District agencies, with federal and regional governments, and with the public to the fullest extent consistent with safety, privacy, and security. For more information, please visit https://opendata.dc.gov/pages/edi-overview. Previous years of EDI can be found on Open Data.

Provides a list of all the datasets available in the Enterprise Data Inventory for the Small Business Administration.

From 2020 to 2022, the total enterprise data volume will go from approximately one petabyte (PB) to 2.02 petabytes. This is a 42.2 percent average annual growth over these two years. It is worth noting that internally managed data centers will continue to be the locations in which most of the data will be stored.

This is a listing of all datasets within the Department of Defense (DoD). Please note that this is a work in progress.

Base de cet annuaire : https://www.data.gouv.fr/fr/datasets/observatoire-edtech/ Critère de sélection : entreprises de la Edtech ayant leur siège social en France Sources des données ajoutées : Afinef Edtech France Les pepites tech Village by CA Méthode : Vérification et suppression des entreprises ayant cessé leur activité sur le fichier original et augmentation par les données présentes sur des sites publics. Suppression des données personnelles des dirigeants, de la taille d’entreprise et de la date de création présentes sur le fichier original Catégorisation adaptée et augmentée du fichier original Présentation détaillée dans le premier onglet du fichier. AU 20/05/21, 566 entrées.

This is the historic impact factors of Vie Et Sciences De L'entreprise computed for each year in CSV format. The first column shows the exaly JournalID for mixing this table with those of other journals

Breakdowns of research and development spending and employment by UK business across different market sectors. Source agency: Office for National Statistics Designation: National Statistics Language: English Alternative title: BERD

Question 1.1.8b: From 2015 onwards, have the beneficial owners of extractive companies been disclosed?, 1.3.4a: From 2015 onwards, have environmental mitigation management plans been publicly disclosed?, 1.1.10a: From 2015 onwards, has the government publicly disclosed signed licences/contracts?, 1.4c: What is the name of the largest company in which the government has a controlling share (i.e. an SOE)?

• Pour vous abonner à notre lettre d'information Sirene open data actualités, cliquez ici • Pour consulter nos lettres d'information Sirene open data actualités, cliquez ici Fichiers stock Les fichiers stock définitifs au format 3.11 sont publiés le 26 mars 2024 en lieu et place des précédents fichiers 3.9. Cinq fichiers stock mensuels compactés (format ZIP) sont mis à disposition : le fichier stock des unités légales (unités légales actives et cessées dans leur état courant au répertoire) le fichier stock des valeurs historisées des unités légales le fichier stock des établissements (établissements actifs et fermés dans leur état courant au répertoire) le fichier stock des valeurs historisées des établissements le fichier stock des liens de succession des établissements Chaque fichier compacté (Format ZIP) contient un fichier de données en format CSV. Les fichiers mis en ligne à partir du 1er du mois sont une image du répertoire Sirene à la date du dernier jour du mois précédent. Un fichier stock d’un mois donné remplace celui du mois précédent. Les unités légales cessées et les établissements fermés y figurent, offrant ainsi l’accès aux données Sirene depuis 1973. Mises à jour Les mises à jour infra mensuelles de ces fichiers, y compris quotidiennes, sont possibles : en utilisant l’API Sirene disponible sur le catalogue des API de l’Insee. Avec l’API, vous accédez en effet à des variables indiquant, tant pour les établissements que pour les unités légales, la date du dernier traitement effectué. Il s’agit des variables dateDernierTraitementUniteLegale et dateDernierTraitementEtablissement. Dès lors que cette date est différente de celle du même enregistrement dans votre fichier stock, vous savez qu’une mise à jour a été effectuée. La documentation sur les variables et les services de l'API Sirene est disponible sur l’API Sirene, onglet Documentation ; en utilisant « Constituer une liste » sur sirene.fr (sélectionner l'onglet Date de mise à jour) pour pouvoir télécharger des fichiers constitués des mises à jour quotidiennes. Vous pouvez consulter à ce sujet la lettre Sirene open data actualités n°2. La base Sirene contenant des données à caractère personnel, l'Insee attire votre attention sur les obligations légales qui en découlent : Le traitement de ces données relève notamment des obligations du règlement général sur la protection des données (RGPD), de la Loi 78-17 du 6 janvier 1978 modifiée, dite Loi CNIL Selon votre usage du jeu de données, il est ainsi de votre responsabilité de tenir compte du statut de diffusion le plus récent de chaque personne physique, qui tient compte des oppositions formulées par certaines d'entre elles, à la consultation ou l'utilisation de leurs données Sirene par des tiers autres que les administrations ou organismes habilités. Les unités légales ou les établissements qui ont un statut de diffusion codé « P » (resp. statutDiffusionUniteLegale ou statutDiffusionEtablissement) font l’objet d’une diffusion partielle des données consécutive à une demande d’opposition. Pour une opposition de personne physique, l’identité de l’entrepreneur (nom, prénoms…), l’adresse dans la commune et la géolocalisation seront masquées (c’est-à-dire non diffusées par l’API Sirene). Pour une opposition de représentants légaux d’une personne morale, l’adresse de l’établissement dans la commune et sa géolocalisation seront masquées. Il est entendu que les données relatives aux représentants légaux ne sont pas diffusées par l’Insee en Open Data, même en l’absence d’opposition, et ce conformément à l’article R 123-232 du Code de commerce. Si vous êtes une entreprise : ATTENTION , pour toute demande de création, de modification ou de changement concernant votre situation administrative, nous vous invitons à contacter le Guichet Unique ATTENTION, aucune demande de ce type parvenant sur ce site ne pourra être satisfaite.

Analysis of ‘Nombre de mises en service sur installations existantes Entreprise et PME-PMI’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/58a280d5a3a72974c1f1156d on 11 January 2022.

--- Dataset description provided by original source is as follows ---

Ce jeu de données restitue le nombre de mises en service par segment de clients Entreprise et PME-PMI aux mailles département, région et Enedis. Le réseau exploité par Enedis exclut les ELD et SEI.

Visualisez aussi les données de mises en service sur installations existantes Entreprise et PME-PMI sur notre site internet.

--- Original source retains full ownership of the source dataset ---

In 2023, IT spending on enterprise software amounted to around 913 billion U.S. dollars worldwide, a growth of 12.4 percent from the previous year. Like nearly all sub-segments of the IT services industry, the enterprise software market has experienced high levels of growth in recent years, with market revenues more than doubling in the decade between 2010 and 2020. The COVID-19 global pandemic also did not slow down growth in the software sector as initially feared. For further information about the COVID-19 pandemic, please visit our dedicated Facts and Figures page.

Enterprise software

With year-on-year growth frequently exceeding 10 percent, the enterprise software market is the fastest growing segment in the overarching IT industry. Enterprise software aims at responding to the needs of organizations, often specifically addressing the efficiency of their core business processes. Many enterprise software sub-segments, such as business process management (BPM) software, enterprise resource planning (ERP) software, and customer relationship management (CRM) software, have grown into massive markets in their own right. CRM software focuses on analyzing and improving business interactions with both current and future customers and is expected to bring in over 55 billion dollars in sales in 2024. ERP software focuses more closely on corporate data collection and interpretation, and is forecast to account for another 107 billion dollars in overall revenue.

• Report Overview
• Key Takeaways
• Component Analysis
• Deployment Mode Analysis
• Enterprise Size
• End-Use Industry
• Key Маrkеt Segments
• Driving Factors
• Restraining Factors
• Growth Opportunities
• Challenges
• Regional Analysis
• Key Players Analysis
• Recent Developments
• Report Scope

Abstract

The documented dataset covers Enterprise Survey (ES) panel data collected in Liberia in 2009 and 2017, as part of the Enterprise Survey initiative of the World Bank. An Indicator Survey is similar to an Enterprise Survey; it is implemented for smaller economies where the sampling strategies inherent in an Enterprise Survey are often not applicable due to the limited universe of firms.

The objective of the 2009-2017 Enterprise Survey is to obtain feedback from enterprises in client countries on the state of the private sector as well as to build a panel of enterprise data that will make it possible to track changes in the business environment over time and allow, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the Indicator Survey data provides information on the constraints to private sector growth and is used to create statistically significant business environment indicators that are comparable across countries.

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

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 the universe, covered in the Enterprise Surveys is the non-agricultural 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.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the 2009-2017 Liberia Enterprise Survey (ES) was selected using stratified random sampling, following the methodology explained in the Sampling Note. Stratified random was preferred over simple random sampling for several reasons: - To obtain unbiased estimates for different subdivisions of the population with some known level of precision. - To obtain unbiased estimates for the whole population. 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 subsector 72, IT, which was added to the population under study), and all public or utilities sectors.

• To make sure that the final total sample includes establishments from all different sectors and that it is not concentrated in one or two of industries/sizes/regions.
• To exploit the benefits of stratified sampling where population estimates, in most cases, will be more precise than using a simple random sampling method (i.e., lower standard errors, other things being equal.)
• Stratification may produce a smaller bound on the error of estimation than would be produced by a simple random sample of the same size. This result is particularly true if measurements within strata are homogeneous.

• The cost per observation in the survey may be reduced by stratification of the population elements into convenient groupings.

  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 Liberia 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 for the Liberia ES was done across three regions: Montserrado, Margibi, and Nimba.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instruments are available: - Services and Manufacturing Questionnaire - Screener Questionnaire.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/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% 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.

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

There was a high response rate especially as a result of positive attitude towards the international community in collaboration with the government in their reconstruction efforts after a period of civil strife.There was also very positive attitude towards World Bank initiatives.

The global enterprise data management market size was valued at USD 89.34 billion in 2022 and is expected to grow at a compound annual growth rate (CAGR) of 12.1% from 2023 to 2030

In 2010, IFC conducted a study to estimate the number of micro, small, and medium enterprises (MSMEs) in the world, and to determine the degree of access to credit and use of deposit accounts for formal and informal MSMEs. The study used primarily data from the World Bank Enterprise Surveys (ES). In 2011 the data was revisited as new enterprise surveys became available. The resulting database, IFC Enterprise Finance Gap Database, covers 177 countries. This dataset provides summary values for dfferent categories.

Source: http://finances.worldbank.org/d/b4d6-42j9