LITHUANIAN DEPARTMENT OF STATISTICS

Knowledge Economy and Special Survey Statistics Division

29 Gedimino Ave, LT-01500 Vilnius, Lithuania

The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to collect the information on different types of innovation,  various aspects of the development of an innovation, objectives of innovation activities, sources of information, public funding or expenditure on innovation.  It is aim is to measure the innovativeness of sectors and enable the analysis of the factors of innovation.

 The CIS provides statistics by type of innovators, economic activities and size class of enterprises. The survey is currently carried out every two years across the EU Member States, EFTA countries and EU candidate countries.

In order to ensure comparability across countries, Eurostat together with the countries developed a Harmonised Data Collection (HDC) questionnaire accompanied by a set of definitions and methodological recommendations.

CIS 2018 concepts and its underlying methodology are based on the Oslo Manual (2018) 4th Edition. 

New review of the CIS2018  aims to meet several objectives :

1: Reduce subjectivity and biases in the main CIS indicators

2: Improve reporting about innovation activities and capabilities in the firm

3: Ensure international comparability (including compliance with the OM4)

4: Broaden the basis CIS information on enterprise management

5: Take better account the diversity of enterprises in the EU

6: Improve reporting about external drivers and enablers of innovation

7: Improve timeliness

8: Ensure the feasibility of data collection

9: Ensure continuity with the CIS 2016

10: Improve reporting about the output and impact of innovation

CIS2018 is conducted under Commission Regulation No 995/2012. This Regulation defines the mandatory target population of the survey referring to enterprises in the Core NACE economic sectors (see section 3.3.) with at least 10 employees. Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period (t, t-1, t-2), but some use only one calendar year (t or t-2).

Please consider CIS t to be the survey that refers to the same year of the quality report and CIS t-2 to be the previous survey e.g.: CIS  2018= CIS t then, CIS t-2=CIS 2016

Indicators related to the enterprises are classified by country, economic activity (NACE Rev. 2), size class of enterprises and type of innovation.

The main typology of classification of enterprises in reference to innovation is the distinction between innovation-active enterprises (INN) and not innovation-active enterprises (NINN).

The enterprise is considered as innovative (INN) if during the reference period it successfully introduced a product or business process innovation, had ongoing innovation activities, abandoned innovation activities or was engaged in in-house R&D or R&D contracted out. Non-innovative (NINN) enterprises had no innovation activity mentioned above whatsoever during the reference period.

CIS covers main economic sectors according to NACE Rev.2 broken down by size class of enterprises and type of innovation activity.

In accordance with Commission Regulation 995/2012 on innovation statistics, the following industries and services are included in the core target population. Results are made available with these following breakdowns :

All NACE – Core NACE (NACE Rev. 2  sections & divisions B-C-D-E-46-H-J-K-71-72-73 )

CORE INDUSTRY (excluding construction) (NACE Rev. 2 SECTIONS B_C_D_E)

10-12: Manufacture of food products, beverages and tobacco

13-15: Manufacture of textiles, wearing apparel, leather and related products

16-18: Manufacture of wood, paper, printing and reproduction

20: Manufacture of chemicals and chemical products

21: Manufacture of basic pharmaceutical products and pharmaceutical preparations

19-22: Manufacture of petroleum, chemical, pharmaceutical, rubber and plastic products

23: Manufacture of other non-metallic mineral products

24: Manufacture of basic metals

25: Manufacture of fabricated metal products, except machinery and equipment

26: Manufacture of computer, electronic and optical products

25-30: Manufacture of fabricated metal products (except machinery and equipment), computer, electronic and optical products, electrical equipment, motor vehicles and other transport equipment

31-33: Manufacture of furniture; jewellery, musical instruments, toys; repair and installation of machinery and equipment

D: ELECTRICITY, GAS, STEAM AND AIR CONDITIONING SUPPLY

E: WATER SUPPLY; SEWERAGE, WASTE MANAGEMENT AND REMEDIATION ACTIVITIES

36: Water collection, treatment and supply

37-39: Sewerage, waste management, remediation activities

CORE SERVICES (NACE Rev. 2 sections & divisions 46-H-J-K-71-72-73)(NACE code in the tables = G46-M73_INN)

46: Wholesale trade, except of motor vehicles and motorcycles

H: TRANSPORTATION AND STORAGE

49-51: Land transport and transport via pipelines, water transport and air transport

52-53: Warehousing and support activities for transportation and postal and courier activities

J: INFORMATION AND COMMUNICATION

58: Publishing activities

61: Telecommunications

62: Computer programming, consultancy and related activities

63: Information service activities

K: FINANCIAL AND INSURANCE ACTIVITIES

64: Financial service activities, except insurance and pension funding

65: Insurance, reinsurance and pension funding, except compulsory social security

66: Activities auxiliary to financial services and insurance activities

M: PROFESSIONAL, SCIENTIFIC AND TECHNICAL ACTIVITIES

71: Architectural and engineering activities; technical testing and analysis

72: Scientific research and development

73: Advertising and market research

71-73: Architectural and engineering activities; technical testing and analysis; Scientific research and development; Advertising and market research

  Additional coverage:

- construction (NACE Rev. 2 41–43)

In accordance with Commission Regulation 995/2012 on innovation statistics, the following size classes of enterprises according to number of employees are included in the core target population of the CIS:

• 10 - 49 employees
• 50 - 249 employees
• 250 or more employees

No deviations.

The description of concepts, definitions and main statistical variables is available in CIS 2018 European metadata file (ESMS) Results of the community innovation survey 2018 (CIS2018) (inn_cis11) in Eurostat database.

The statistical unit – the legal unit.

Legal unit –a conditional unit comprising legal persons whose existence is recognized by law, independently of the individuals or institutions that may manage or be members of them, and natural persons legally engaged in economic activities activities.

Core target population are all enterprises in CORE NACE activities (see 3.3.1) with 10 or more employees.

Reference area – country.

Five main indicators – by region, county.

Several rounds of Community Innovation Survey have been conducted so far at two-year interval since end of 90’s.

*two reference periods can be distinguished for CIS light: 2000-2002 and 2001-2003

Not relevant.

CIS indicators are available according to 3 units of measure:

NR: Number for number of enterprises and number of persons employed.

THS_EUR: Thousands of euros. All financial variables are provided in thousands of euros, i.e. Turnover or Innovation expenditure.

PC: Percentage. The percentage is the ratio between the selected combinations of indicators.

For CIS 2018, the time covered by the survey is the 3-year period from the beginning of 2016 to the end of 2018.

Some questions and indicators refer to one year — 2018.

The list of indicators covering the 3-year period and referring to one year according to the HDC is available in the Annex section of the European metadata (ESMS). 

CIS surveys are based on the Commission Regulation No 995/2012, implementing Decision No 1608/2003/EC of the European Parliament and of the Council on the production and development of Community statistics on science and technology.

This Regulation establishes innovation statistics on a statutory basis and makes the delivery of certain variables compulsory e.g. innovation activities, cooperation, development, expenditures and turnover (see the Regulation). Each survey wave may additionally include further variables. 

In addition, the Regulation defines the obligatory cross-coverage of economic sectors and size class of enterprises.

EU legislation and national Official statistics programme.

Not requested.

CIS data are transmitted to Eurostat via EDAMIS using the secured transmission system.

In the process of statistical data collection, processing and analysis and dissemination of statistical information, Statistics Lithuania fully guarantees the confidentiality of the data submitted by respondents (households, enterprises, institutions, organisations and other statistical units), as defined in the Confidentiality Policy Guidelines of Statistics Lithuania.

Description of Statistical Disclosure Control Methods, approved by Order No DĮ-124 of 27 May 2008 of the Director General of Statistics Lithuania.

Integrated Statistical Information System Data Security Regulations and Rules for the Secure Management of Electronic Information in the Integrated Statistical Information System, approved by Order No DĮ-240 of 16 September 2020 of the Director General of Statistics Lithuania.

By national policy on aggregated data confidentiality the minimum number of enterprises in breakdowns must to be 3 enterprises.

Statistical information is published following the Official Statistics Dissemination Policy Guidelines.

Statistical information is published on the Official Statistics Portal according to the Official Statistics Calendar.

Official Statistics Calendar

Statistical information is published following the Official Statistics Dissemination Policy Guidelines.

CIS is conducted and  statistical information disseminated at two-year interval.

Accessibility and clarity refer to the simplicity and ease for users to access statistics using simple and user-friendly procedure, obtaining them in an expected form and within an acceptable time period, with the appropriate user information and assistance: a global context which finally enables them to make optimum use of the statistics.

See below.

-              Online database (containing all/most results) : All main results On-line database – Database of Indicators (free of charge).

-              Analytical publication (referring to all/most results) : -

-              Analytical publication (referring to specific results, e.g. only for one sector or one specific aspect) : Main indicators in publication Business in Lithuania – published on 3 December of 2020.  

On-line database – Database of Indicators (Science and technology -> Innovation activities of enterprises)

Not requested.

CIS microdata can be accessed in the Safe Centre (SC) at Eurostat's premises in Luxembourg.

No other means of dissemination.

Not requested.

Methodological documentation – Innovation activites.

The survey meta-information post together with database. Meta-information Development of innovation activity is available from 31-03-20.

The process of the preparation of statistical information is described in the Innovative activity statistical survey methodology (only in Lithuanian).

Not requested.

Innovation data are popular among the users. Very often asked different information, which was not included into the publication or database.

The survey quality report – metadata – is produced and post together with database. Metadata Development of innovation activity is available from 31-03-20.

The quality of statistical information and its production process is ensured by the provisions of the European Statistics Code of Practice and ESS Quality Assurance Framework. 

In 2007, a quality management system, conforming to the requirements of the international quality management system standard ISO 9001, was introduced at Statistics Lithuania. The main trends in activity of Statistics Lithuania aimed at quality management and continuous development in the institution are established in the Quality Policy. Monitoring of the quality indicators of statistical processes and their results and self-evaluation of statistical survey managers is regularly carried out in order to identify the areas which need improvement and to promptly eliminate the shortcomings.

The survey response rate was 99 per cent. The survey are mandatory and only fully completed e-questionnaires are accepted. Respondents must answer to all questions, which are necessary to answer for them. Electronic survey is with strict validation rules.

Data for the survey were collected at regional statistical offices. The specialists of these offices were responsible for statistical data collection, sending reminders to the respondents, consulting them, checking and correction by the protocols of logical errors. The entry errors were detected both by manual comparisons and during running logical controls. But their number was relatively small. Logical errors were eliminated by the contacting with respondents.

After data collection, the quality of the information obtained was analysed. Additional macro and micro statistical data quality control were performed.

Verification of data according to additional control conditions, determination of exceptions of quantitative indicators, comparison of the data set with the data of the previous period, inaccuracies, trends of changes were performed. In case of deviations, the reasons for them were explained and, if necessary, the respondents contacted. Data were corrected if inaccuracies were identified.

The weaknesses were in the data collection. Often enterprises accounting departments completed questionnaires with a less knowledge about innovation, R&D and management. By them, the innovation is invention of absolutely a new product but not it‘s improvement.

The coefficient of variation for the percentage of innovative enterprises are good. Data calculated with the possibly accuracy.

The main users of statistical information are State authorities and agencies, international organisations, the media, research and business communities, students, whose needs are satisfied without a breach of the confidentiality principle.

The national questionnaire was harmonised with the national public institutions (Ministry of the Economy and Innovation, Ministry Education, Science and Sport, Research and Higher Education Monitoring and Analysis Centre, Lithuanian Innovation Centre).

User satisfaction in Statistics Lithuania:

From 2005, general user opinion surveys have been conducted on a regular basis. Official Statistics Portal traffic is monitored, website visitor opinion polls, general opinion poll on the products and services of Statistics Lithuania, target user group opinion polls and other surveys are conducted. In 2007, the compilation of a user satisfaction index was launched. The said surveys are aimed at the assessment of the overall demand for and necessity of statistical information in general and specific statistical indicators in particular.

More information on user surveys and their results is available in section User surveys on the Statistics Lithuania website.

User satisfaction survey related to CIS data was not carry out.

No derogations. Respondents must to answer to all necessary questions.

Not requested.

Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).

That part of the difference between a population value and an estimate thereof, derived from a random sample, which is due to the fact that only a subset of the population is enumerated.

The main indicator used to measure sampling errors for CIS data is the coefficient of variation (CV).

Coefficient of Variation= (Square root of the estimate of the sampling variance) / (Estimated value)

Formula:

where

Coefficient of variation (%) for key variables by NACE categories and for enterprises with 10 and more employees

[1] = Coefficient of variation for the percentage of innovative enterprises (INN) in the total population of enterprises (ENT18)
[2] = Coefficient of variation for the turnover of product innovative enterprises with new or improved products (TUR_PRD_NEW_MKT), as a percentage of total turnover of product innovative enterprises [TUR18,INNO_PRD].
[3] = Coefficient of variation for percentage of product and/or process innovative enterprises (incl. enterprises with abandoned and or on-going activities) involved in any innovation co-operation arrangement [COOP_ALL,INN], as a percentage of innovative enterprises (INN).

The variance estimator of the direct population total estimator (or the Horvitz-Thomson) was used.

Non-sampling errors occur in all phases of a survey. They add to the sampling errors (if present) and contribute to decreasing overall accuracy. It is important to assess their relative weight in the total error and devote appropriate resources for their control and assessment.

Coverage errors (or frame errors) are due to divergences between the target population and the frame population. The frame population is the set of target population members that has a chance to be selected into the survey sample. It is a listing of all items in the population from which the sample is drawn that contains contact details as well as sufficient information to perform stratification and sampling.

Not requested.

Not requested.

There were some divergences between the target population and the frame population due of economically not active enterprises. These errors were estimated according to the sample design.

The information is not available.

Measurement errors occur during data collection and generate bias by recording values different than the true ones. The survey questionnaire used for data collection may have led to the recording of wrong values, or there may be respondent or interviewer bias.

There are no measures.

Non response occurs when a survey fails to collect data on all survey variables from all the population units designated for data collection in a sample or complete enumeration.                                                                                                                                                                                              

There are two types of non-response:                                                                                                                                                                                      

1) Unit non-response, which occurs when no data (or so little as to be unusable) are collected about a population unit designated for data collection.                                                                                                                                                                      

a) Un-weighted unit non-response rate (%) = 100*(Number of units with no response or not usable response) / (Total number of in-scope (eligible) units in the sample)                                                                                                         

b) Weighted unit non-response rate (%) = 100*(Number of weighted units with no response or not usable response) / (Total number of in-scope (eligible) units in the sample)                                                                                                            

2) Item non-response, which occurs when only data on some, but not all survey data items are collected about a population unit designated for data collection.                                       

a) Un-weighted item non-response rate (%) = 100*(Number of units with no response at all for the item) / (Total number of eligible, for the item, units in the sample i.e. filters have to be taken into account) 

The survey was carried out mandatory. The unit non-response rate stood at 1 percent.

Respondents must answer to all necessary questions. Electronic survey was with strict validation rules.

There was no item non-response. No imputation done

See below.

Un-weighted and weighted unit non-response rate by NACE categories and for enterprises with 10 or more employees

The number of eligible units is the number of sample units, which indeed belong to the target population.

2 automatic reminders (3 days to deadline and 1 day after) were sent via the e-system. Then specialists of the Regional Statistical Offices sent / maked a call on average 3 times  to enterprises before enterprises were coded as non-responding.

See below.

Item non-response rate for Turnover (in Core NACE: B-C-D-E-46-H-J-K-71-72-73 enterprises with 10 or more employees).

There was no item non-response. No imputation done

Item non-response rate for new questions in CIS t (in Core NACE: B-C-D-E-46-H-J-K-71-72-73 enterprises with 10 or more employees)
 

There was no item non-response. No imputation done

The number of processing errors was relatively small. Logical errors were eliminated by the contacting with respondents. For logical inconsistencies about 7% of respondents were contacted.

Not requested.

Timeliness and punctuality refer to time and dates, but in a different manner.

The timeliness of statistics reflects the length of time between data availability and the event or phenomenon they describe.

Timeliness of national data – date of first release of national level : 20-12-2019

Not requested.

Punctuality refers to the time lag between the release date of data and the target date on which they were scheduled for release as announced officially.

Date of transmission of complete and validated data to Eurostat (Number of days between that data and 30 June 2020) : 26 June 2020 (4 days).

Comparability aims at measuring the impact of differences in applied statistical concepts and definitions on the comparison of statistics between geographical areas, non-geographical domains, or over time.

The coherence of statistical outputs refers to the degree to which the statistical processes by which they were generated used the same concepts (classifications, definitions, and target populations) and harmonised methods. Coherent statistical outputs have the potential to be validly combined and used jointly.

 Statistical data are comparable among the regions, counties of Lithuania and among EU countries.

Not requested.

Methodological deviations from the CIS Harmonised Data Collection (HDC)

Methodological deviations from the CIS Harmonised Data Collection (HDC)

Due to important methodological changes in CIS 2018 driven by Oslo Manual 2018, the data 2018 cannot be directly compared with previous CIS waves.

Not requested.

See the comparison between SBS and CIS data in the section 15.3.3 below.

Not requested.

Not requested.

This part compares key variables for aggregated CIS data with SBS data
Definition of relative difference between CIS and SBS data: DIFF = (SBS/CIS)*100

Comparison between SBS and CIS data (relative difference) by NACE categories and for enterprises with 10 or more employees

* Numbers are to be provided for the last year of the reference period (t)

Not requested.

Confidential information on the production cost of the CIS.

Not requested.

Not requested.

Not requested.

See below:

The source of the frame - the Statistical Business Register.

In accordance with section 2 of the annex of the Commission Regulation on Community statistics on innovation, enterprises in the NACE Rev. 2 sections B, C, D, E, H, J, K and in the NACE Rev. 2 divisions 46 and divisions 71, 72 and 73, and additionally section (section F) are covered.

The official up-to-date statistical Business Register of the country was used as a sampling frame. The target population were stratified into similar groups; the characteristics for the breakdown were: economic activities (in accordance with NACE Rev. 2) at least at a 2-digit level and enterprise size according to the number persons of employed (10–49, 50–249, 250+, excluding enterprises with 0-9 persons of employed).

The enterprises with 10-49 and 50-249 persons of employed are covered by sampling.

The enterprises size class (250+) persons of employed are covered by complete enumeration.

Within every NACE Rev 2 group the strata of enterprises were formed by number of persons employed groups. If in the strata are 7 or less enterprises, they are all involved in the statistical survey. The Neyman optimal allocation (with variable number of persons employed) was used for determination of the sample size for each stratum specified.

In each stratum simple random sampling was used. The final number of strata was 148.

The sample was designed with no reference to other surveys. Sample rate is 25.1 per cent of the population.

Gross sample – 2500. Net sample – 2458. Number of units with a response in the realised sample – 2433.

Variables and indicators filled or prefilled from other sources.

According to the Commission Regulation (UE) 995/2012, the innovation statistics shall be provided to Eurostat every two years in each even year. The data collection takes place every second year in year t-2 preceding the data provision.

For data collection, electronic questionnaires with a possibility to fill online or print and fill in a paper version were used. Data for the survey were collected at regional statistical offices. The specialists of these offices were responsible for statistical data collection, sending reminders to the respondents, consulting them, micro data editing, checking and correction by the protocols of logical errors.

Data entry together with data quality control was done using software specially designed for that purpose (on the basis of Oracle). It was prepared by ICT specialist of Statistics Lithuania. Data from electronic questionnaires are loaded automatically, papers questionnaires are entered by specialists of regional offices. After the data entry, checking and correction, the results were validated, the non-response rate was calculated and the grossing-up of the data was done.

The survey was carried out mandatory, it was included in the Official statistical programme.

The survey type – combination census/sample survey.

The enterprises with 10-49 and 50-249 employed are covered by sampling.

The enterprises size class (250+) employed are covered by complete enumeration.

The enterprises size class (250+) employed are covered by complete enumeration.

Data collection method

Not requested.

Operations performed on data to derive new information according to a given set of rules.

Imputation is the method of creating plausible (but artificial) substitute values for all those missing.

Definition of imputation rate:

Imputation rate (for the variable x) (%) = 100*(Number of replaced values) / (Total number of values for a given variable)

Definition of weighted imputation rate:

Weighted imputation rate= 100*(Number of total weighted replaced values) / (Total number of weighted values for a given variable)

Imputation rate for metric variables by NACE categories and for enterprises with 10 or more employees:

(1) = Total turnover in the last year of the reference period (t) (TUR)

(2) = Share of the turnover in the last year of the reference period (t) due to new or improved product new to the market in the total turnover for product innovative enterprises TUR_PRD_NEW_MKT/TUR(INNO_PRD)

(3) = R&D expenditure performed in-house (EXP_INNO_RND_IH)

Weights calculation method for sample surveys

The calibration method was not used.

Not requested.