Questionnaires’ Design 82

Questionnaires are one of the instruments used in the collection of primary data from respondents and are designed for the statistical analysis of the responses (Mellenbergh, 2008). Questionnaires are a quick, simple and inexpensive way of collecting data from a number of respondents. Because questionnaires do not involve an interviewer or an observer, they tend to be free from interviewer bias. More importantly, the anonymity offered by questionnaires can help respondents to discuss issues which they might be reluctant to discuss in a one-to-one interview. Questionnaires need to be designed carefully if they are to provide reliable information. As a downside questionnaires can be considered inflexible because the information exchange is limited to the specified questions. Consequently, questionnaires can fail to identify the underlying causes of a problem and its potential solutions. Some of the problems a researcher may face with

using a questionnaire are low response rate, time delays, no control over who completes it, problems with incomplete questionnaires and not being possible to give assistance if required (Parajuli, 2004).

There are two types of questionnaire surveys, depending on how they are administered. The first type is the self-administrated questionnaire, whereby the researcher himself/herself distributes the questionnaire, explains the questionnaire then asks the respondents to answer all the questions and then collects the response later. The second type is the interview-administrated questionnaire, whereby the researcher asks the questions, records the answers of each respondent and then transcribes them afterwards. The researcher employed the two types of questionnaires. The self-administrated questionnaire was to elicit information about technological resistances factors. Based upon the results of self-administrated questionnaire, interviews were conducted to gain information about the effectiveness of the frame work.

The researcher used a self-administrated-questionnaire (see Appendix A), personally delivered it by hand to each respondent and full explanation of the questionnaires was provided and then collected the responses later.

The researcher opted for a self-administrated questionnaire in order to maximize the response and thus consequently increase data reliability. It also allows the researcher to interact with the respondents and gives more control to the researcher. Further, when collecting the questionnaires the researcher could check if some of the questionnaires are not completed or if the respondents needed some further clarifications with regard to some questions, as has been the case in this research. However, one of the main disadvantages of this type of method is that the respondents control the time of answering the questionnaires. The stance taken in this research is to allow between thirty –to-fifty minutes extra time for completing the questionnaires in order to ensure high quality feedback. A total of thirteen were given extra time to complete the questionnaires properly.

3.6.1.1 Piloting the Questionnaire Survey

After designing the questionnaire, prior to using them a pilot study was made by the researcher. The questionnaire was piloted in two stages. Firstly, through personal contact with the respondents by undertaking two in-depth discussions with five managers in different public companies in the UAE. These managers provided extensive feedback on the questionnaire. Secondly, the questionnaire was piloted with six PhD students in Salford and Manchester Universities in UK. The purpose of the pilot study was to ensure that there was a sufficient variation in response, that the questions provided were understood; that no questions were unnecessary; that the length of the questionnaire was not off-putting; that there was clarity and simplicity of language, and that the scale items and evidence of acquiescence as well as all the instructions were clear. The questionnaire included general demographic questions relating to age, gender, experience, income and department. Feedback given by the participants helped the researcher to refine the questionnaire, thus showing the importance of this pilot study.

3.6.1.2 Measuring and Scaling

The survey questionnaire was designed to measure the factors that affect employee resistance to technology change in UAE public sector companies. The survey responses were measured based on a five point scale (Likert scale) where the responses given had options ranging from strongly disagree to strongly agree (Strongly disagree = 1, Don’t agree = 2, Neutral = 3, Agree = 4, and Strongly agree = 5). This type of scale helps in understanding the opinions and views of the respondents. Using such a type of scale helps the researcher to measure the level of employee resistance towards technology change.

3.6.1.3 Survey Questionnaire Sample

The researcher initially conducted a pilot study, as discussed above and questionnaire was handed over only to those who were interested. The survey sample included a total of 8 questions relating to demographics (age, gender), personal information (education, job, income, experience). The questionnaire also contained a further 10 questions relating to

the drivers for technology change, reasons for employee resistance to technology change, reasons for management resistance to technology change, and the necessary strategies to mitigate the resistance to technology change. Before distributing the survey questionnaire to the employees, the researcher explained the purpose of the survey to the participants and reiterated important instructions for completing the questionnaire. A total of 200 employees from four different companies were selected. Fifty employees from each company participated in the survey. These companies included Al Ain Municipality, Tawam Hospital, the Social Affairs Department and Al Ain Distribution Company. The questionnaire was distributed to an identified sample of 200 people, of which 173 responded to the survey. Of the received 173 responses only 160 were duly filled and completed. These responses were only considered for further research analysis that gave a 92.5 % response, which constitutes a high response rate. The thirty respondents were omitted because of lack of completeness to most of the questions. Having high response rate helps the researcher to avoid bias in results and brings transparency in the results.