B. Use of information communications technology at the data collection stage
21.7. Electronic data collection includes the use of electronic questionnaires via computer assisted personal interviewing (CAPI), computer assisted telephone interviewing (CATI), computer assisted web interviewing (CAWI) and Internet data collection (possibly via an Internet portal), among others. Electronic forms may ease the collection of data but also present new challenges as well as opportunities, for example for improving editing. In particular, they offer the possibility of using built-in edits previously not possible in paper or other non-electronic modes of data collection. More generally, electronic data collection can result in other efficiency gains by allowing for the study and upgrading of current editing practices or editing practices associated with other non-electronic collection modes, analysis of different problems using multimode data collections, measuring the respondent burden and measuring the quality and reliability of responses in order to provide valuable information to other survey processes.
21.8. The use of electronic questionnaires improves accuracy and timeliness and, at the same time, reduces survey cost, reporting burden and processing burden. First, the elimination of the need for the statistical agency to manually enter data from surveys prevents a common source of error. Moreover, improved accuracy results from the possibility of adding built-in automatic edits in electronic questionnaires, allowing respondents to avoid errors or reduce the time spent filling in questionnaires. For example, devices such as automatic data fills and calculations, prompts for missing fields and automatic skipping of not applicable questions could help the respondent to fill in the questionnaire more easily, more accurately and faster. Although, as with any form of questionnaire, it is possible for survey respondents to misinterpret the questions, electronic questionnaires would help to reduce that risk by including within the electronic forms notes explaining the type of information that is expected from respondents and definitions of key concepts. Therefore, the use of electronic questionnaires is encouraged as it enhances data quality, and, in the case of statistics compiled within the framework for describing the international supply of services, can also help in the collection of multiple variables (e.g., receipts or payment for services and associated quantity indicators, such as number of mode 4 persons/trips) and accompanying dimensions (service type, partner, relationship between the parties, modes of supply, etc.).
21.9. It is very difficult to measure the real impact of the use of such questionnaires on accuracy, given the self-selective nature of the respondents who choose the electronic option. Compilers should also be aware that use of electronic questionnaires may introduce a certain bias in survey results (at least in the early stages of implementation), because some potential respondents may be unable to participate owing to the lack of access to, or the lack of familiarity with, the appropriate technology (e.g., those without a computer or Internet access, the elderly, low-income groups or those with little education).
21.10. There are several methods that compilers can employ to encourage respondents to provide data via electronic questionnaires. For example, compilers can explain the time-saving benefits of such questionnaires to respondents or can offer incentives (e.g., temporary access to or previews of information on survey results, or free deliveries of customized data queries). Compilers are also advised not to underestimate the value of providing a high level of customer service and thanking respondents for their responses, regardless of the method of questionnaire response. Finally, it is important to note that the success of the implementation of such a process also lies in the cooperation of survey managers and information technology specialists.
21.11. Computer Assisted Personal Interviewing (CAPI) CAPI is a computer assisted data collection method that replaces pen-and-paper methods of survey data collection and usually conducted at the home or business of the respondent using a portable electronic device, such as a laptop, notebook or tablet. As the technology advances to provide lighter devices with longer battery life and more user-friendly software, CAPI is expected to be used more often, especially for quick turnaround surveys.
21.12. Internet data collection (IDC) IDC is a means of quick survey data collection using the Internet in which respondents submit responses using web-based forms, sometimes available on statistics “portals”. A system administrator retrieves the completed forms and routes them for further processing. Existing systems of IDC often produce ready-made data files with all answers, which can subsequently be combined, if necessary, with data obtained by other modes of collection.
21.13. Electronic file transmission Compilers can also collect data via transmissions of data files (e.g., spreadsheets or in text format) through a secure website or e-mail address. That method has the advantage of eliminating the need for the compiler to manually enter data from a survey; however, automatic edits or checks for accuracy may not be built into the data file in the most straightforward way in an electronic questionnaire.
21.14. Extensible Business Reporting Language (XBRL) reporting XBRL is an XML-based computer language developed for the electronic transmission of business and financial reports. Some regulatory agencies have established processes for businesses to fulfil their mandatory reporting requirements using XBRL standards. XBRL tools have also been developed for the reporting of financial information to taxation and statistical agencies. Such tools reduce the cost of compliance for businesses by building reporting requirements into standard accounting software packages in a way that automates the process of reporting to government agencies.
21.15. The core methodology is an XBRL taxonomy that defines all the data items that the relevant agencies require from businesses. An essential step in developing the taxonomy is harmonizing the data items collected by different government agencies. If two agencies require the same definition of a data item, it is given the same name. If the different agencies establish that they need different definitions, then they are specified with different names. That harmonization process not only simplifies reporting by businesses by standardizing definitions, it also assists with the integration of statistics, ensuring that different collection agencies have coherent data definitions.