Online Survey

The second phase of the study involved a quantitative approach, and for that purpose an online survey was selected to collect empirical data in order to test the proposed framework. Prior research has shown that online survey technique has more superiority and provides more advantages over other data collection techniques such as interview and postal surveys (Sheehan, 2001). Particularly, conducting an online survey is much quicker than other approaches (Sheehan and McMillan, 1999). The technique provides an easier and more immediate means of response (Flaherty, et al., 1998). Besides, an online survey is more cost effective than a paper survey (Sheehan and Hoy, 1999). In addition, an online survey is easy to administer and it is effortless.

There are many online software tools which allow researchers to create and distribute their questionnaires online at low effort. Appendix C provides some examples of the currently used online packaging tools for distributing online survey. After considering several factors (e.g. functionality, availability, productivity, and cost), it was decided to use Qualtrics (www.qualtrics.com) to design and distribute the online survey.

Through this type of tool researchers can distribute their questionnaires to a geographically dispersed population of thousands of people in a very short period of time (Sheehan 2001). While other approaches such as postal survey, interview, and focus group take a longer time to target large populations and would be very costly (Wright, 2005). Furthermore, online survey tools also enable researchers to track and monitor the questionnaires constantly, to find out the number of people accessing the questionnaire, to find out about the number of people completing the questionnaire, to discover the number of undelivered questionnaires, which ultimately helps improve

129

the sampling procedures (Sheehan 2001). Accordingly, online surveys enable researchers to save time by allowing researchers to collect data while they carry out other work (Sheehan 2001). Moreover, researchers can also save money through utilising an online survey as postal surveys can often be costly (Wright, 2005). It is believed that online surveys enable researchers to collect less biased data as compared to other approaches such as interview and focus groups (Wright, 2005). For example, prior studies have reported that individuals are often seen to hesitate to express themselves and their views openly in face-to-face communications (Wright, 2005). Therefore, for all the great benefits online surveys provide, it has been increasingly used to study online populations and it has being seen as a successful data collection technique for studying online behaviours and internet use (Andrews, et al., 2003, Wright, 2005).

However, online surveys suffer from several drawbacks which require some careful considerations (Sheena, 2001, Wright, 2005). Particularly, collecting data through an online survey is a challenging task to achieve because low response rate and incomplete returned questionnaires are the two of major problems associated with the technique (Deutskens et al., 2004, De Vaus, 2002, p.97). In addition, issues related to the sampling procedures are other disadvantages of online surveys (Andrews et al., 2003, Wright 2005). However, the current literature shows that several considerations (e.g. paying careful attention to formatting, survey lengths, question structure, and user interface design) can help mitigate these issues. Accordingly, in the following subsections these considerations were carefully considered during the survey.

4.5.3.1 Quality Design

Previous researchers have suggested that the quality of design of an online questionnaire is a significant factor that can improve the online survey response rate (Dillman, 2000, Deutskens et al., 2004). Based on an extensive literature review, Andrews et al. (2003) have provided several guidelines for designing quality online

130

surveys as shown in Table 4-10. Accordingly, these guidelines were implemented during the survey design.

Table 4-10: Quality Guidelines to Improve Survey Design (Andrew et al., 2003) Guidelines

1. Supports multiple platforms and browsers/e-mail clients

2. Provides automatic transfer of responses to a database

3. Controls for browser settings 4. Prevents survey alteration 5. Detects multiple submissions

automatically

6. Provides response control and displays 7. Presents questions in a logical or

adaptive manner 8. Provides for links to definitions, menus, button and check box options and so forth 9. Allows saving responses before

completion

10. Does not require familiarity with survey presentation software

11. Collects open-ended or quantified-option responses

12. Displays appear quickly to participant 13. Provides automatic feedback with

completion

14. Tracks response source of response failure 15. Uses paper questionnaire design

principles

16. Provides automatic transfer of responses to a database

4.5.3.2 Survey Length

It is believed that a long online questionnaire has a negative impact on the response rate (Dillman, 2000, Deutskens et al 2004). Although there is no agreement on the terms ‘long’ and ‘short’ for online questionnaires, it has been suggested that the shorter the questionnaire the better response rate (Deutskens et al, 2004, Deutskens et al 2004). For that reason, attempts were made to make the survey as short as possible. A pilot study was carried out and this helped in reducing the number of the questions asked (See Section 4.5.5).

131 4.5.3.3 Survey Language

Survey language also affects the response rate in online surveys. It is believed that when designing a questionnaire it is important to formulate the questions in a way that is easy to understand by the participants (De Vaus, 2002). Accordingly, throughout the questionnaire words were used that ware clear and easy to understand.

Explanation was given for words that were ambiguous. For example the word

‘regularly’ could mean different things to different people. Hence, in the survey it was explained by two words ‘on daily or weekly bases. To ensure the language was easy to understand and there was no ambiguity, the survey was tested with experts, colleagues, and the target audiences (See Section 4.5.5).

4.5.3.4 Follow-up

Following-up contacts have been seen as a powerful technique for increasing response rates in online surveys (Dillman, 2000, Deutskens et al., 2004). Researchers have reported that, this technique has to be done carefully as sending several follow-ups could irritate potential respondents (Deutskens et al., 2004). It has been suggested to send a follow up email after a specific period of time. For example, the average response time typical in an online survey is 5 to 6 days (Deutskens et al., 2004), and therefore it has been suggested that one can maximise responses by following up one week after the initial invitation (Dillman, 2000). Consequently, follow-up emails were sent to all the participants and this helped improve the response rate.

4.5.3.5 Incentives

Financial incentive (e.g. money, vouchers, and books) has been recognised as another effective technique for increasing online survey response rate (Wright 2005, Deutskens et al., 2004). However, providing an incentive require some careful attention, since providing rewards to every participant could often result in obtaining incorrect information because some people may participate just to receive the gift.

For that reason, a different approach was used in this study. Participants were entered

132

into a raffle draw to win a memory stick. They were also offered an executive summary of the research outcome.

4.5.3.6 Ethical and Privacy Issue

Ethical and privacy concerns remain important in online surveys and this has a significant impact on response rate (Evans and Mathur, 2005). Accordingly, the informed consent form was designed and then embedded in the survey and the invitation letter to address any ethical and privacy issues that the participant may have. In the invitation letter the aim of the research was explained to the participants and promises made to them that the survey will not do any harm to their businesses and their information was going to be kept 100% confidential (See Appendix D) 4.5.4 The Questionnaire and Structure

The questionnaire was developed according to the hypotheses developed.

Throughout the questionnaire a ‘Likert Scale’ was utilised to make it easier for the participants to answer the questions (De Vaus, 2003). Each question asked aimed to test the identified variables and measures and relationships in developed framework.

In total the questionnaire consisted of 18 main questions which were divided into five main parts. The first part contained questions with regards to the participant’s business characteristics. The second part contained questions with regards to the participants’ active participation behaviour, followed by the third part which contained questions associated with variables identified under U&G. The next two sets of questions related to the variables identified under SET and ISSM. In the final section some demographic questions were asked.