Distribution Traditional means 38 17.5
Both 74 34.1
Total 217 100.0
Websites used to distribute music
iTunes 41 18.9
Social Media Websites 113 52.1
SAmp3.com 36 16.6
Napster 11 5.1
Soundcloud 47 21.7
Other 14 6.5
Total 262 120.9
Music is aligned with
Customer demands 58 26.7
Label demands 42 19.4
My own artistic taste 117 53.9
Total 217 100.0
Source: Developed by the researcher from data analysis.
Question 9 on the research instrument allowed the respondent to select more than one option hence the frequency and percentage differs from other questions.
Questions from questionnaires can be easily coded;
Questionnaires are often a catharsis for respondents; and
Questionnaires benefit the scientific community if the measures are well-validated and reliable.
3.3.1 Questionnaire Design
According to Bernard (2000:25-67), a covering letter should form part of the questionnaire. The covering letter provides respondents with a clear indication of the purpose of the study, entailing that participation is voluntary and that the respondent is free to withdraw from participating at any time. The letter also guarantees confidentiality. Furthermore, it provides the contact details of the researcher and the supervisor, including an approximate time frame for completing the questionnaire.
The questionnaire is designed using closed-ended questions. Saunders, Lewis and Thornhill (2012:667) describe closed-ended questions as questions where participants choose responses from a limited number of given alternatives. The three main sections of the questionnaire were:
Section A
Section A addressed questions pertaining to the biographical variables of the respondents which are measured on a nominal scale. The variables included age, gender, marital status, race, educational qualifications, tenure, music creation and distribution. These questions, numbered 1-10, requires the respondent to choose their answer from a list of alternatives. Respondents are required to mark an X or circle the most appropriate response category as provided by the researcher.
Section B
Section B contained six dichotomous questions with options of ‘Yes’ or ‘No’ answers. These questions, numbered, 11-16 related to the variables regarding the push-push strategies used by musicians.
Section C
Interval scale or rating questions using a 5-point Likert scaling method comprised Section C.
Section C consisted of 22 closed-ended questions relating to the sub-dimensions of digital music distribution. These statements are presented on a 5-point Likert scale ranging from strongly disagree (1), to disagree (2), neutral (3), agree (4) and strongly agree (5). Closed-ended questions allows the researcher to code the information easily for data analysis (Sekaran and
Bougie, 2010). The Likert scale type questions in Section C pertain to the three key independent variables of the study, namely, music distribution, technological value adding innovations related to supply and demand, and the supply chain’s competence and capability.
The questionnaire is strategically structured in order to enable data collection across each independent variable. According to Korb (2012:1) a variable is “the key characteristic or attribute of an individual, group, educational system, or the environment that is of interest in a research study.” Variables can be straightforward or easy to measure (Section A of the questionnaire), whilst others are more complex (those related to Sections B and C of the questionnaire). Kumar (2014:66) describes independent and dependent variables as follows:
Independent variable: the cause assumed to be responsible for bringing about change in a phenomenon or situation. The independent variables in this study are music distribution, technology value adding innovations related to supply and demand, and the supply chain’s competence and capability
Dependent variable: the outcome or change brought about by the introduction of an independent variable. The dependent variable identified for the purpose of this research study is digital music distribution. Digital music distribution is a construct of a decentralised distribution.
3.3.2 Measurement Scales
There are three measurement scales namely; ordinal, nominal and interval scales. A scale is a tool that is used to distinguish individuals on the variables of interest to the study (Sekaran, 2003). There are four types of measurement scales/types of data: nominal, ordinal, interval and ration. This study adopts nominal and interval scales. According to McNabb (2004:80-81)
“nominal data is simply a naming or classification scale” whereas “a typical use of ordinal data is to measure people’s preferences or ranking for services or things”. Alternatively, ordinal data can be gathered using Likert scale type questions and interval level data can be ranked and categorised (Waxman, 2013:60-80). An example of nominal data is intervals between kilometres per litre when viewing the economy. Interval data is normally numeric. Black (2011:9) noted that ratio-level data have similar characteristics to interval data. However, ratio data takes into consideration numbers to the absolute zero and the number zero cannot be manipulated. Examples of ratio data are productivity measures, weight and volume.
3.3.3 Administration of questionnaire
Data is collected by administering questionnaires personally and by electronic mail to Durban musicians. Respondents click on the link provided in the e-mail to complete the questionnaire created on the online survey tool known as Google Drive, as recommended. Respondents were requested to return hard or electronic versions of the completed questionnaire. Questionnaires can be described as including all methods of data collection in which each person is asked to respond to the same set of questions in a pre-determined order (de Vaus, 2002; Saunders et al., 2012). Punch (2003) explains that quantitative research is essentially about investigating and understanding how and why variables are related to each other. The researcher has the option of selecting either a concept or a variable or both (Kumar, 2014:63). Please refer to Appendix C to view the research instrument.
3.3.4 In-house Pretesting and Pilot Testing
In-house pretesting and pilot testing was undertaken to enhance the validity of the research instrument and process. The pretesting of a questionnaire should occur prior to final administration in order to uncover any potential shortcomings in the questionnaire design and administration (Remenyi, Williams, Money, and Swart, 2010). The limitations are related to the effectiveness of the questionnaire by determining the strengths and weaknesses with regard to question format, wording and order. The researcher informs the respondents that the pretest is a practice run. Pretesting tests for question variation, meaning, task difficulty, time consumed, and the respondent’s interest and attention (Bell, 2010; Saunders et al., 2012). A formal approach to pretesting occurs in the form of a pilot study which is a replication of the full study but on a smaller scale (Saunders et al., 2012:451). By addressing specific aspects of the research, pilot testing helps to determine whether the selected procedures will operate as intended. Hence, it enables the survey questions to be refined and reduces the risk of the main study being flawed. In this study, a pilot test was undertaken with ten musicians.
The pilot study identified two errors. The first was in question 1 where the third option was a repetition of the second option of “26 to 35 years”. This error was rectified and option 3 was changed to “36 to 45 years”. The second error identified related to question 27, where
“complimentary” technologies had been misspelt. This was corrected to “complementary”
technologies. No potential problems surfaced once the corrections were made after the pilot phase and the full data collection process followed.