Methodology and Quality Update

Latest Update on Methodology and Quality

30/12/2025

Statistical Presentation

Data description

The Digital Economy Survey 2024 presents accurate and comprehensive data on the digital economy in the Kingdom of Saudi Arabia, in line with the requirements of relevant international, regional, and national statistical organizations concerned with this field.
The Digital Economy Survey is a survey conducted to collect data on the main characteristics as follows:
Objectives of the Digital Economy Statistics Survey:
•    Providing a data source that helps calculate the contribution of the digital economy to the GDP of the Kingdom of Saudi Arabia
•    Identifying key indicators related to the digital economy.
Key Targeted Indicators of the Digital Economy Statistics Survey:
•    Share of the digital economy's contribution to Saudi Arabia's gross product.

Classifications

The National Classification of Economic Activities (ISIC4) is applied in the Digital Economy Survey:
The statistical classification based on the International Standard of Industrial Classification of All Economic Activities (ISIC4) is used to describe the productive activities of an establishment.
The classifications are available on the GASTAT website:  www.stats.gov.sa

Statistical concepts and definitions

Terms and Concepts of the Digital Economy Survey:
•    Digital economy:
The digital economy consists of economic activities that are conducted or facilitated through digital technologies. This definition stipulates that the digital economy includes all economic activities that rely on the use of digital inputs or are significantly enhanced through the use of digital inputs, including digital technologies, digital infrastructure, digital services, and data. 
•    Establishment:
An economic unit with a legal entity (holding a commercial registration) that engages in a specific economic activity and is owned by an individual, a group of individuals, a company, a quasi-government sector, or an institution.
•    Economic activity:
The economic activity of an establishment is defined as all activities or services carried out or provided by the establishment that generate revenue. In some cases, an establishment may not derive financial returns from its activities, as is the case with charitable associations that rely on donations. Where an establishment has two or more economic activities, the economic activity that generates the highest revenue is selected. The classification of economic activity for establishments is based on the International Standard Industrial Classification (ISIC4).

Data sources

The data of the Digital Economy Statistics are based on two sources:
First source: The first source of the Digital Economy Statistics data is the Digital Economy Survey:
The Digital Economy Survey 2024 is the primary source of data for the Digital Economy Statistics. It should be noted that the share of the digital economy was calculated based on the Gross Domestic Product.
Second source: Secondary data
Structural Business Statistics
Third source: From administrative records issued by the Ministry of Commerce:
 With regard to data on the number of commercial registrations related to e-commerce, software publishing, and the provision of cloud computing services, reliance was placed on administrative records issued by the Ministry of Commerce.
The key main variables published for the Digital Economy Survey data are: 
•    The share of the digital economy in the Gross Domestic Product of the Kingdom of Saudi Arabia.

Designing the data collection tool

An electronic form was designed in the Computer-Assisted Personal Interviewing (CAPI) format to ensure ease of use by field researchers and in the Computer-Assisted Telephone Interviewing (CATI) format to enable communication with targeted respondents by telephone. Data were collected using a questionnaire prepared and designed by specialists in digital economy statistics at the General Authority for Statistics. International recommendations, standards, and definitions were taken into account during the design of the questionnaire, which was also presented to relevant entities to obtain their views and feedback. The questions were formulated in a specific scientific manner to standardize the administration of questions by researchers. 
The questionnaire includes several sections, including:
•    Section one: Identification data of the establishment.
•    Section two: Economic activity of the establishment.
•    Section three: E-commerce
•    Section four: Digital Delivery
•    Section five: Digital intermediation platform (privately owned or owned by another party)
•    Section six: Data sharing, analysis, and dissemination
•    Section seven: Questions related to specific activities

Method of calculating the indicators:
The indicator of the contribution of the digital economy to the Gross Domestic Product is calculated by estimating the value added of the digital economy relative to the Gross Domestic Product of the Kingdom of Saudi Arabia.
Review and Correction Rules:
Audit and control rules have been established in the form to ensure that the data collected is consistent, accurate, and logical. These rules were designed by establishing logical relationships between responses, questions, and different variables to help the field researcher detect any errors directly during data entry.
To ensure the quality of the Digital Economy Survey data, four types of validation and editing rules were established, as follows:
•    Automated adjustment rules:
These rules were established for the automatic calculation of certain fields or the automatic adjustment of responses in specific fields, in line with some questionnaires, totaling (3) rules.
•    Navigation rules between sections and fields:
Special rules were programmed to regulate automatic navigation between sections and fields based on the respondent’s answers, totaling 33 rules.
•    Error rules:

These are rules that cannot be bypassed during the data entry process. Field researchers are required to correct the data by referring back to the respondent to verify its accuracy. The total number of these rules exceeds 51.
•    Alert rules (warnings):
These rules are designed to verify the correctness of the data entered by the researcher. The field researcher may override them if the data accuracy is confirmed, with a total of approximately 15 rules.

Questionnaire test (cognitive test)

The outputs of the cognitive testing conducted in 2022 were utilized for the Digital Economy Survey. Interviews were conducted on a random sample of establishments, and cognitive testing was applied to a number of questionnaire items based on the pillars of cognitive testing. A number of observations were identified related to the following aspects: the overall concept of the question, clarity of question wording, clarity of the terms used in the question, and the appropriateness of the response options, culminating in the preparation of a report providing a comprehensive summary of the cognitive testing results.

Statistical population

The statistical population of the Digital Economy Survey consists of all establishments responding to the Structural Business Statistics Survey that were selected based on the Economic Business Frame. This frame includes all establishments engaged in economic activities in the Kingdom of Saudi Arabia and serves as the list containing all units of the target population for this survey and for other economic surveys conducted by the General Authority for Statistics. It includes the classification of all establishments by economic activity at multiple levels, as well as establishment size, administrative regions, and other basic data used in constructing various economic samples. The sampling frame is considered the list of all establishments that meet the survey conditions specified by the responsible department.

Sample Design

The sample was designed with a two-stage stratified cluster systematic random sampling method, in which in the first stage a random sample was selected from the primary sampling units (counting areas) for each stratum of the adopted sampling design.

Stratification:
To increase the efficiency of the sample and improve its representation of the target population, establishments in the sampling frame were classified into homogeneous strata. In order to obtain more accurate results compared to a simple random sample of the same size, and to provide a sufficient number of establishments at publishable levels, the stratification was applied across three levels as follows: 
•    Stratification at the fourth-level classification of economic activity (ISIC4).
•    Stratification at the level of administrative regions.
•    Stratification by establishment size categories, which are:
-   Micro enterprises: Establishments with 1 to 5 employees.
-    Small enterprises: Establishments with 6 to 49 employees.
-    Medium enterprises: Establishments with 50 to 249 employees.
-    Large enterprises: Establishments with more than 249 employees. 
Sample size:

The sample size was calculated at the level of each stratum of the study domain (economic activity at the fourth level of the International Standard Industrial Classification (ISIC4)). h 
The resulting sample size calculated for each study domain (economic activity at the second level of the International Standard Industrial Classification (ISIC4)) was then allocated across establishment size classes and subsequently across administrative regions using the Probability Proportional to Size (PPS) allocation method. This allocation method reduces the variance of weighting factors, thereby reducing the variance of estimates, and increasing design efficiency. In addition, the sample size at the study domain level was adjusted to a minimum acceptable number of establishments to obtain a sufficient response size for publishing accurate estimates of the targeted indicators. Moreover, all medium and large establishments were included in the sample with a 100% selection probability due to their importance.
Accordingly, the above-mentioned calculations resulted in a total sample size of (35,195) establishments.

Statistical unit (sampling unit)

The statistical unit of the Digital Economy Survey is the economic establishment.

Data collection

Data collection from the survey:
Data for the Disability Survey is collected through Computer-Assisted Telephone Interviews (CATI), Computer-Assisted Web Interviews (CAWI), and Computer-Assisted Personal Interviews (CAPI).
Data collection from administrative records:
In coordination with the relevant departments of the General Authority for Statistics involved in conducting the survey and managing data collection, the administrative data for the Digital Economy Survey publication are obtained from the Ministry of Commerce, including commercial registration data. 
The data is stored in the authority's databases after undergoing auditing and review processes following approved statistical methods and recognized quality standards. If errors or discrepancies are discovered, the data is cross-referenced with the data source for correction or clarification.

Data collection frequency 

The process of collecting Food Security Statistics data is carried out on an annual basis.

Reference area

The Digital Economy Survey covers the 13 administrative regions in the Kingdom of Saudi Arabia.

Reference period (time reference)

The reference period for the Digital Economy Survey data is the year 2024:
Data from administrative records are based on the last day of each quarter of each calendar year.

Base period

Not applicable. 

Measurement unit

Some results are measured as percentages (e.g., the share of the digital economy in the Gross Domestic Product), while other indicators are measured in numerical or quantitative units.

Time coverage

The data is available from the year 2022 to 2024.

Publication frequency

The results of the Digital Economy Survey are published on an annual basis in accordance with the approved statistical plan.

Statistical processing

Error detection

Accurate procedures are implemented to detect errors in the data collected during the field survey and stored in the data lake. This is achieved through automating the data collection tool and applying the necessary constraints and procedures to control and manage the entered data, ensuring quality, accuracy, and consistency, in addition to using supporting methods to measure quality indicators. These procedures include:
Data are reviewed and cross-checked to ensure their accuracy in a manner appropriate to their nature, to enhance the quality and accuracy of the statistics produced. 

The data for the current publication year are also compared with those of the previous year to ensure their validity and consistency during data preparation, processing, extraction of results, and review.
In addition to processing and tabulating the data to verify their accuracy, all outputs are stored and uploaded to the database after being calculated by the General Authority for Statistics, to be reviewed and processed by specialists in the Digital Economy Statistics Department using modern technologies and software designed for this purpose.
As for administrative records data, validation and review processes are conducted through the following procedures: 
•    Reviewing internal consistency among the provided data to ensure logical coherence.
•    Comparing the provided data with previous records to ensure validity and prepare for data processing, results extraction, and review.
In the Digital Economy Survey, statistical researchers collect from respondents a detailed description of the fields. This information is then coded in-house through an automated process, which is reviewed by a dedicated team of coding experts using a series of consistency checks.
Data editing:

Specialists of digital economy statistics department have processed and analyzed data in this stage, and this step was based on the following measures:
•    Sorting and arranging data in groups or different categories in a serial order.
•    Summarizing detailed data into key points or data.
•    Combining many data segments and ensuring their interconnection.
•    Handling incomplete or missing data.
•    Processing illogical data.
•    Converting data into statistically significant data.
•    Arranging, presenting, and interpreting data.

Data integration and matching from multiple sources 

 Not applicable.

Imputation and calibration

Weighting:
The basic sample weights are calculated based on the strata used in the sample design and allocation. The selection probability of establishment i from stratum h is denoted by   ; accordingly, the weight of the establishment selected in the sample is calculated as follows:

Non-response weight adjustment:
Weight adjustment to compensate for non-response or missing data is applied to ensure adequate sample representation. This adjustment is carried out after data collection and processing, once response statuses have been identified, according to the following equation:

  represents the non-response–adjusted weight in stratum (or adjustment class) h. The adjustment (or correction) factor for each stratum (or adjustment class), denoted by   , is calculated as follows: 

Where R represents the responses and NR represents the non-responses.

Seasonal adjustments

 Not applicable, only final results will be published.

Adjustment of preliminary results 

The initially calculated statistical outputs were reviewed and updated after the completion of processing, with the aim of correcting identified errors or improving accuracy based on internal reviews.

Used Resources

Quality dimensions

Suitability

A criterion that indicates the extent to which the product meets users’ needs.

User needs 

Internal users at the General Authority for Statistics of Digital Economy Statistics data:
•    National Accounts Department
Some external users significantly benefit from the Digital Economy Statistics data, most notably:
•    Government entities.
•    Regional and international organizations.
•    Research institutions.
•    Media.
•    Individuals.
Key variables most utilized by external users:

Completeness 

Digital economy data are based on data collected from a sample of economic establishments representative of various economic sectors across the Kingdom of Saudi Arabia, to provide comprehensive information on Digital Economy Statistics indicators. The data are complete.

Accuracy and reliability 

A measure that indicates how close the estimates or calculations are to the true or exact values that reflect reality.

Overall accuracy 

•    The data collected is improved through the researchers, that have been selected according to a set of practical and objective criteria and training program related to the field of work.
•    Alert, prevention, and correction rules are applied during the data collection process on the electronic questionnaire for the Digital Economy Survey to improve data quality.
•    Data is checked with previous years to identify any significant changes in the data.
•    The internal consistency of the data is checked before it is finalized.
•    The links between variables are checked and coherence between different data series is confirmed.

Timeliness and punctuality 

A standard that measures the time gap between the availability of information and the occurrence of the event.
However, timeliness reflects the time difference between the date of data publication and the target date when it is actually published.

Timeliness 

GASTAT uses the Special Data Dissemination Standard (SDDS) issued by the International Monetary Fund. According to this standard, all statistics agencies are required to publish data on an annual basis, with a delay of not more than half a year (180 days) after the end of the reference period. If the data are from different source, they may be published in a different frequency.

Punctuality 

Publication takes place in accordance with the release dates published in the statistical calendar for Digital Economy Statistics on the website of the General Authority for Statistics.
The data are made available at the expected time, as scheduled in the statistical release calendar. In the event of any delay in publication, the General Authority for Statistics will provide the reasons.

Coherence and comparability

A standard that refers to the necessity of internal and temporal consistency of statistics, their logical coherence, and their comparability and integration across different regions and sources.

Comparability - geographical

The statistical data related to the Digital Economy Survey are follow standardized international definitions and standards, ensuring their comparability both nationally and internationally.

Comparability - over time 

The survey was first implemented in 2022 and is conducted on an annual basis. Comparability - over time

Coherence- Cross domain

The data are consistent, as their coherence is verified against all other statistics containing similar indicators. These procedures contribute to ensuring integration and coherence among statistics, thereby enhancing data reliability and the quality of the analyses based on them, and ensuring that the results are free from any unjustified inconsistencies.

Coherence- Sub-annual and annual statistics 

Not applicable, as the Digital Economy Survey is conducted on an annual basis.

Coherence- National Accounts 

The Digital Economy Statistics data are consistent with the national accounts, as the contribution of the digital economy is calculated using Gross Domestic Product.

Coherence- Internal 

The digital economy indicators have full internal coherence, as they are all based on the same set of microdata.

Accessibility and clarity

The accessibility of data for users, the availability of detailed or aggregated data, as well as the availability of the methodology and quality report.

Press releases

The announcements for each publication are available on the statistical calendar as mentioned in 10.1. The press releases can be viewed on the website of GASTAT on the link: 
Press release

Publications

The General Authority for Statistics issues Digital Economy Survey publications and reports regularly in accordance with a pre-prepared dissemination plan, and they are published on the Authority’s website. GASTAT is keen to publish its publications in a way that serves all users of different types, including publications in different formats that contain (publication tables, data graphs, indicators, methodology and quality report, and used questionnaires) in both English and Arabic.
The results of the Digital Economy Survey are available at:
The Digital Economy Survey

Online database

The data is published on the statistical database:
GASTAT (stats.gov.sa)

Microdata accessibility

Accurate data is unit-level disaggregated data obtained from multiple sources such as sample statistical surveys, general population and housing censuses, and administrative systems, providing detailed information about the characteristics of individuals, families, business entities, and geographical areas, supporting the construction and development of statistical indicators and scientific research.
Different types of microdata files are available to meet diverse information needs.
•    Public use: 
It consists of sets of records containing information on individuals, households, or business entities anonymized in such a way that the respondent cannot be identified either directly, such as by name, address, contact number, identity number, etc., or indirectly (by combining different – especially rare – characteristics of respondents), such as age, occupation, education, etc.
•    Scientific use:
Microdata files are produced in accordance with defined methodologies and in response to data users’ requests for datasets with specific characteristics, supporting strategic studies, decision-making, and scientific research on individuals, households, and establishments, while ensuring the exclusion of any direct identifiers and compliance with confidentiality protection controls.
Qualified users who meet the standards and procedures of confidentiality protection can access the files of scientific use of accurate data through the platform "ITAHA" of the General Authority for Statistics, while the most sensitive data for use is shared by visiting the accurate data laboratory within a secure environment managed by the Authority.

References and standards

The concepts, definitions, issues, and classifications are based on the following international recommendations and standards: 
•    A Roadmap toward a Common Framework for Measuring the Digital Economy: Report for the G20 Digital Economy Task Force, Saudi Arabia 2020, issued by the Organisation for Economic Co-operation and Development (OECD).
•    Manual for the Production of Statistics on the Digital Economy (2020), issued by the United Nations Conference on Trade and Development.
https://unctad.org/system/files/official-document/dtlstict2021d2_en.pdf

Quality assurance

GASTAT declares that it considers the following principles: Impartiality; ensuring that the statistical product is user-oriented; maintaining the quality of processes and outputs; enhancing the effectiveness of statistical operations; and reducing the burden on respondents. 
Data is validated through procedures and quality controls that are applied during the process at various stages, such as data entry, data collection, and other final controls.

Quality assessment

The General Authority for Statistics performs all statistical activities in accordance with the national model, the Generic Statistical Business Process Model (GSBPM). Under the GSBPM, the final phase of statistical activities is the overall evaluation stage, during which the information collected in each phase or sub-process is used to prepare an evaluation report that summarizes all challenges related to the quality of each statistical process and serves as input for improvement and development actions.

Confidentiality

Confidentiality - Policy

According to Royal Decree No. 23 dated 07/12/1379, data must always be kept confidential and must be used by GASTAT for statistical purposes only.
Therefore, the data is protected in the data servers of GASTAT.

Confidentiality - Data Treatment

Data of SMEs survey are presented in right tables in order to summarize, understand, as well as extract their results. Moreover, to compare them with other data, and to obtain statistical significance about the selected study population. However, referring to such data indicated in tables is much easier than going back to check the original questionnaire that may include some data like names and addresses of individuals, and names of data providers, which violates data confidentiality of statistical data.
“Anonymity of data” is one of the most important procedures. To keep data confidential,
GASTAT removed information on individual persons, households, or business entities such a way that the respondent cannot be identified either directly such as: (name, address, contact number, identity number etc.) or indirectly (by combining different - especially rare - characteristics of respondents) such as: (age, occupation, education etc.).

Dissemination policy

Statistical calendar

 The Digital Economy Survey has been included in the statistical calendar.
Statistical Calendar

User access

One of the objectives of the General Authority for Statistics is to better meet its clients’ needs; therefore, it promptly provides them with the results of the Digital Economy Survey publication once the survey results are released.
Customer questions and inquiries about the publication and its results are also received through various communication channels, such as:
•    GASTAT official website:   www.stats.gov.sa
•    GASTAT official email address:   info@stats.gov.sa
•    Official visits to GASTAT’s official head office in Riyadh or one of its branches in Saudi Arabia.
•    Official letters.
•    Statistical telephone: (199009).