Data collection method: computer-administered, Internet-based survey 131

For primary data collection of the small-scale complementary study, various data collection instruments exist (refer to section 5.4.3). The best suitable method to address the research problem and answer the research objective of this study was a computer-administered, Internet-based survey – respondents could complete it at their own convenience, remain anonymous, and therefore encourage more honest results, and data could be gathered quickly and captured instantly.

Berndt and Petzer (2011:143) and Hair et al. (2006:245) describe it as placing a structured questionnaire on a Website for prospective respondents to read and complete by themselves i.e., the questionnaire is hosted on a common Internet platform. Various computer-administered, Internet-based survey platforms exist, such as CreateSurvey, KwikSurveys, Survey Garden and Make Survey (Bradley, 2007:288). The researcher selected SurveyMonkey for this study due to familiarity with the tool and proven workability and credibility.

The advantages of using computer-administered, Internet-based surveys include (Berndt & Petzer, 2011:144; Bradley, 2010:288,452; Hair et al., 2006:247):

• Cost effectiveness: Most Internet-based services are free of charge or affordable – which makes it more cost effective compared to interviewer and self-administered data collection instruments.

• Short lead times: Internet-based surveys’ data collection and encoding is speedier compared to manual methods.

• Real-time data capturing: Internet-based surveys eliminates the need to manually encode data from paper survey forms.

• Convenience: Respondents can complete the survey at their own convenience and suitable time. In addition, it is easy and convenient for the researcher to administer the survey as everything is hosted on the researcher’s computer.

• Response type: Both open and closed-end questions can be hosted.

• Easy access: Easier access to respondents who may not be easily available through traditional collection methods is possible, and respondents remain anonymous.

The disadvantages of computer-administered, Internet-based surveys include (Berndt & Petzer, 2011:14; Malhotra, 2009:224):

• Low response rates: Typically low response rates are evident.

• Dubious honesty: It is easier for respondents to give fake / untrue answers.

Nonetheless, each identified sampling element received an email with an invitation and link to participate in the study. The questionnaire for this survey reflected a number of different response types and included three open-ended questions and a number of structured questions. The structured questions included one determinant-choice question, one frequency-determination question, and two different five-point scale-response questions that are described next:

• Determinant-choice question: This question format has fixed answers and requires of respondents to choose one response from a specified list of responses (Zikmund & Babin, 2010:273). Specifically, respondents were asked to classify the South African firm they work for into certain industries.

• Frequency-determination question: This question format also has fixed responses but the answers are about general frequency of occurrences (Zikmund & Babin, 2010:273). In this instance, responses were ordered in terms of how frequently the respondent received quantitative research reports.

• Scale-response question: This question format is where a continuum is used to measure attributes of a construct; respondents are asked to select a point on the scale that best expresses their feelings about a specific attribute (Burns

& Bush, 2010:301; Hair et al., 2006:394,395). Both scales for the questionnaire were anchored five-point scales; this means that the scale is anchored by primary descriptors at its two extreme points with cardinal numbers that make up the range of raw scale descriptors in-between (Hair et al., 2006:367; Aaker et al., 2004:292). The first scale’s points (rating attributes of quantitative research reports) were anchored as 1 “extremely poor” and 5

“excellent”. The second scale (measuring the need for improvement of

quantitative research reports) was anchored as 1 “to a great extent” and 5 “not at all”.

Each respondent completed this 5-minute Internet-based survey on SurveyMonkey. The questionnaire exhibits the following structure:

• Section A: Introduction – respondents were informed about the objective of the study and the length of the survey. They were also assured of their anonymity and confidentiality when the results were interpreted.

• Section B: Screening questions (qualifying criteria) – respondents were asked how frequently they received quantitative research reports from marketing research firms so that respondents who did not fit the criteria (less often than once a month), could be disqualified.

• Section C: Type of business the client firm conducts – in section C respondents were asked to classify the firm they work for in one of nine key industry categories which, amongst others, included automotive, cosmetics and personal care, financial, fast moving consumer goods industries and others.

• Section D: Evaluation of quantitative research reports received – in section D respondents were asked to identify any challenges they experienced in using quantitative research reports and were asked to rate a battery of predefined criteria (attributes) relating to quantitative research reports (namely: strategic usability, actionability, business relevance, satisfying information needs, ease of understanding, layout and flow of research results and visual appeal).

• Section E: Thank and close – the respondent was thanked for his / her time and was given the opportunity to add any additional comments relating to the topic.

5.6.3 Data analysis

The most common methods of quantitative data analysis include: frequencies, percentages, means, ranges, confidence intervals, mean differences, cross-tabulations, correlation and regression (Burns & Bush, 2006:425; Aaker et al., 2004:438-442; Cant et al., 2003:55). To achieve the objectives, limited analysis was applied to this data by using Microsoft Excel – only frequencies and

percentages were used to explain the data, since the main purpose of this phase of the research was to quantify the need for strategic reports and to measure the client’s overall evaluation of quantitative reporting (refer to section 6.3).