RESEARCH METHODOLOGY AND RESEARCH DESIGN
4.5 Research Design Implementation
4.5.1 Geographic Location of Phase One Implementation
4.5.2.1 Sample Type
This study used proportionate stratified random sampling based on the information from the database of the informal SMEs provided by the Ministry of Small-to-medium enterprises and
fraction in each of the strata that are proportional to that of the total population (Kothari, 2011).
This study developed these strata based on geographical location, that is, the provincial capital cities of Zimbabwe which are Harare, Bulawayo, Mutare, Gweru and Masvingo. The use of proportionate stratified random sampling ensured that at least one observation was picked from each of the strata and allows for the maximum understanding of the underlying phenomenon of interest (Kothari, 2011, Kardejejezska, Tadros and Baxter, 2012). Furthermore, it ensured a high degree of reliability and validity through the usage of both probability and non-probability sampling techniques.
The phenomenologist uses proportionate stratified random sampling to identify informants who can illuminate the phenomenon of interest and also who can effectively communicate their experiences (Klenke, 2008; and Bryman and Bell, 2011). Therefore, this sampling strategy ensured that all the population of the informal manufacturing SMEs was fairly represented in an attempt to achieve the aim and objectives of this research.
Proportionate stratified random sampling was used to solicit the responses of one thousand (1000) informal manufacturing small-to-medium enterprises in Harare, Bulawayo, Gweru, Masvingo and Mutare. The sample size used for the five (5) cities were 383 and the number of questionnaires anticipated to be collected was as follows: Harare 268, Bulawayo 92, Gweru 162, Masvingo 227, and Mutare 251 respectively, as shown in Table 4-4.
Table 4-4: Summary of the Structured Questionnaires administered and the number of Questionnaires Returned Thereof (response rate).
Provincial Capital Cities
Population (N)
Minimum Sample required size (n)
Computation for each stratum
Proportion for each stratum
No of
questionnaires to be administered
No. of Questionnaires Returned as a percentage
Harare 37032 103 37032/ 137619
x 383
27% 103/383 x 1000=
268
(239/268) 29%
Bulawayo 12517 35 12517/137619x
383
9% 35/383 x 1000 = 92 (83/92) 10%
Gweru 22126 62 22126/137619
x 383
16% 62/383 x1000 = 162
(153/162) 19%
Masvingo 31409 87 31409/137619
x 383
23% 87/383 x 1000 = 227
(178/227) 22%
Mutare 34535 96 34535/137619
x 383
25% 96/383 x1000 = 251
(170/251) 21%
Total 137619 383 100% 1000 823 (100%)
Source: FinScope MSME Survey Zimbabwe (2012) & ZIMSTATS (2013) Key Assumptions:
i. Proportionate stratified random sampling to be used for the five (5) provincial capital cities in Zimbabwe.
ii. Sample size 383: determined through calculation with a confidence level of 95% and Margin of Error of 5% [Cochran (1977) and Sekaran and Bougie (2013)].
iii. 1000 questionnaires were administered in the five (5) provincial capital cities.
In Zimbabwe, informal manufacturing SMEs data is not yet well documented with the researcher having to rely on the ZIMSTATS (2014), data indicating a total of 137 619 informal manufacturing SMEs that qualified for inclusion in the study. Most developing countries do not have accurate data concerning the informal SMEs owing to the high failure rate in some sectors.
4.5.3 Research Instrument: Questionnaire Development and Pre- Testing
De Vaus (2002) defines a questionnaire as a general term that is used to include all the methods of data collection in which each participant is asked to respond to a given set of questions in a predetermined order. Questionnaires are used extensively in SME financing and development research (for example, Norton, 1991; Michaelas, Chittenden and Poutzious, 1999), and the use of questionnaire surveys has recently come back into vogue in corporate finance as witnessed by seminal studies (for example, Graham and Harvey, 2001).
According to Zohrabi (2013), questionnaires are doubtless one way of obtaining primary data in any research. Richards and Schmidt (2002), observe that the critical point when designing a questionnaire is for the researcher to ensure that it is ‘reliable, valid and unambiguous’. This research study used closed-ended questionnaires since they provide the inquirer with quantitative or numerical data that is more efficient and easy to analyse (Seliger and Shohamy, 1989). The questionnaires were assigned the Likert-like scale scores from 1 to 5 (Likert, 1931; and Schuessler, 1971). Loudon and Bitta (1993) observe that the Likert-scale involves the process of putting together a list of statements relevant to issues under consideration with disagreement to agreement response scales. Sommer and Sommer (1997), further points out that the Likert-scale makes the scoring methodology user-friendly by using whole numbers from 1,2,3,4 and 5 from each variable in the questionnaire rather than numerical averages (for example 1.5, or 2.4). In this case, the population being investigated is measured by the mean sum of the weightings provided by the participants through coming up with the summation of the numerically coded agree and disagree results of each item to derive the score that indicates the extent to which the respondents agree or disagree with the variables being studied.
To ensure a better response rate and reliability and validity of the collected data the researcher
Research, Development and Marketing Skills Theme; Section B4: Business Structures, Environment and Location Theme, Section B5: Entrepreneurial and Management Skill Theme; Section B6: Legal and Regulatory Framework Theme, Section (6) sub-themes in the structured questionnaire.
Initial extraction was performed on the questionnaire to determine and identify any irregularities in the data. Certain items were dropped. However, an examination of the integrity of the construct was conducted to ensure that items removed and dropped did restrict the range of the concepts to be captured in the study.
In this study, the questionnaire that was used as a survey research instrument sought to collect information on the following six (6) sections and sub-themes that were developed based on the aim and study objectives.
i. Part1: Section A: General SME and Biographical Information,
ii. Part II: Section B: Challenges Faced Informal Manufacturing SMEs with six (6) themes.
Section B1: Access to Finance Theme;
Section B2: Infrastructure and Collateral Security Theme;
Section B3: Research, Development and Marketing Skills Theme;
Section B4: Business Structures, Environment and Location Theme;
Section B5: Entrepreneurial and Management Skill Theme; and
Section B6: Legal and Regulatory Framework Theme.
iii. Section C: Role of Informal Manufacturing SMEs on Economic Growth and Development;
iv. Section D: Role of Informal SMEs on Employment Generation;
v. Section E: Effectiveness of Economic Programmes Aimed at Informal Manufacturing SMEs; and
vi. Section F: Mentorship Programmes.
Initial extraction was performed on the questionnaire to determine and identify any irregularities’
in the data with the advice of an expert. Certain items were dropped. However, an examination of the integrity of the construct was conducted to ensure that items removed and dropped did restrict the range of the concepts to be captured in the study (Appendix 9: Survey - Structured Questionnaire).