may be allowed to save a partially completed form. At a later point in time, they can continue and complete the questionnaire. This is particularly important for business surveys where sometimes different departments of the business each have to complete a specific part of the questionnaire.
The questionnaire may be filled with already available information. The respondents only have to check them for changes. This can be useful in web panels. Example of such preloaded data are address of the respondent and employment status.
There can be a facility that automatically generates an e‐mail message to the survey agency if the respondent indicates he has complaints about the questionnaire. Such information can help to improve surveys and avoid future problems.
Response rates can be monitored over time. If the response is lower than expected, action can be undertaken. For example, customized e‐mail reminders are sent. However, although there are no costs attached to sending reminders, a good rule is to send them at well‐defined moments in time, should they be necessary. Do not overload slow respondents by reminders. The literature shows that this may lead to irritation and break‐off or lower data quality. Three or four reminders are enough.
The proper survey software can check that no respondent can complete the questionnaire more than once. Of course, this requires handing out unique identification codes to the individuals selected in the sample. Note that this does not work in case of self‐selection surveys.
Like in computer‐assisted interviewing, web questionnaires may contain route instructions. These instructions monitor that respondents only answer relevant questions and skip irrelevant questions.
By applying usability tests, the web questionnaires may be improved. Usability refers to the ease of use of a software application for a web questionnaire. Measures of usability refer to the speed in performing a task, the frequency of errors in performing a task, and user satisfaction with regard to an application interface, in terms of being easy to understand and use. Two techniques are especially valuable in usability testing:
Qualitative interviews. Usability tests apply to small groups of individuals. Using current or proposed standards for the interface, a fully functional web questionnaire creates. A group of people is invited considered typical of respondents. After completing the questionnaire, they get an in‐person in‐depth interview. The case study reported in Section 2.3 is an example of using qualitative interviews for questionnaire testing.
Analysis of paradata. Paradata are data concerning the actual web questionnaire completion process. As users complete the questionnaire, the actions are collected. The value of paradata in web and mobile web questionnaire testing, and in an analysis of response behavior, is becoming more and more significant. Information on the characteristics of the respondent's technical environment, respondent response time, errors made, and navigation behavior help to detect and correct problems in the questionnaire. Device used in completion is registered. This is especially important in mobile web surveys.
Survey data collection is expensive. Businesses even if interested in understanding consumers' behavior have to face with budget constraint. Many statistical agencies of governments face budget cuts; also, other survey organizations attempt to reduce data collection costs. Thus, it is worthwhile to consider cheaper modes of data collection. Web surveys or mobile web surveys are substantially cheaper than other modes of data collections. Thus, they are an appealing tool for data collection.
Of course, a web survey requires initial investment in computers, servers, and software. Additionally, there are initial costs for the sampling design (if the researcher uses a probability sampling approach) and for web questionnaire design and implementation. Skilled and specialized personnel, with an understanding of usability and visual design, are necessary to design and implement a web survey. There is a need to use programs for mobile optimization of questionnaires.
After these survey steps are over, there are no further data collection costs other than the costs of help desk personnel. Such a help desk is important in order to answer respondents' questions or to solve their problems (Lozar Manfreda, and Vehovar, 2008).
Field data collection is relatively cost‐free and not dependent on the number of questionnaires administered and completed. Automatically, the database with survey data generates, making data input costs irrelevant as well. No time and effort related to data entry and verification is required. For a comparison of the timing of return rates in mail and web surveys, see Dillman, Smith, and Christian (2014).
To sum up, large numbers of completed questionnaires can be collected in a very short time and at low costs.
Web surveys also have some other attractive properties worthwhile mentioning:
The possibility of obtaining server‐side and client‐side information allows for easily monitoring response burden in web surveys. This makes it possible to record how much time respondents need to complete the questionnaire. Analysis may show how the response burden is related to the response rate.
The use of short questionnaires reduces the response burden. It may help to split a large questionnaire into a number of small questionnaires. The administration of small questionnaires is possible at different moments in time. This does not increase the costs of the survey.
Web surveys are less intrusive, and they suffer less from social desirability effects.
Geographical boundaries are not a problem. Geography is not limiting web surveys in the same way as face‐to‐face interviews and mail and telephone surveys. Therefore, international target populations may be easily reached without special additional costs or time delays.
2.2.2.2 Disadvantages and Problems
A major problem of web‐based surveys is sample selection. For research applications, a random sample is desirable and often essential, and researchers may simply not have a comprehensive sampling frame of e‐mail addresses for people who drink fruit juices or go to church. Despite the huge growth of the Internet, there are still many people who do not have access to, or choose not to use, the Internet. There are also wide disparities in Internet access among ethnic, socioeconomic, and demographic groups. A sampling frame, including e‐mail addresses, of all members of the target population should be available to draw a random sample. In practice, this list is very rarely available. Therefore, large coverage problems arise, and this is the most relevant issue.
Sampling problems may particularly be an issue for general population surveys. For many specific populations, there are no problems. Examples are companies collecting customer satisfaction data, employers measuring job satisfaction, educators collecting course evaluations and conducting examinations, bloggers wanting to consult with their readers, and event organizers checking proposed attendance and meal and other preferences. While there is still a need for some caution, in terms of learning how to use the new technology with confidence, the use of web surveys has been growing rapidly and will clearly continue to grow. Inside the innovative contest web surveys present new methodological challenges, like the integration with other data sources.
A disappointing aspect of web surveys is that they do not contribute to solving the problem of decreasing response rates. It is widely recognized that they usually result in a rather low response rates. It should be noted that, despite low response rates, the use of server‐side and client‐side paradata can help to focus efforts on specific population that most need it.
2.2.3 AREAS OF APPLICATION
