RESEARCH METHODOLOGY
5.4 Research choices
114 5.3.4 Research approach adopted
Research objective helps to determine research approach, in that, if the research objective is to find the relationship between variables- like in this case of this research determining the influence of psychological factors, political environment and information awareness on entrepreneurial behaviour, highly structured and consistent data collection process will be used with a closed-ended questions forming the bulk of the questionnaire’s structure. This will facilitate statistical analysis and interpretation of numerical data collected through survey necessitating the adoption of quantitative research methods for this study (Creswell, 2013;
Szafranski, 2009; Vogt, 2006, 2012). The choice is made based on the strengths inherent in quantitative research approach in explaining relationship between constructs to find correlations and significant differences in the constructs; which will also assist in finding cause and effect relationships to make suggestions. Also, quantitative research method helps to explain structured numerical and non-numerical data collection and examination processes resulting in dependable research conclusions (Franz, 2013; Evans et al., 2011).
115
will enable data collection and analysis through numerical (quantitative) form which are subjected quantitative data analysis techniques to report the findings in numerical form (Saunders et al., 2009, p. 151). The main limitation of employing mono-method is that it lacks data triangulation. More so, it breeds questionable validity and reliability of the research instrument (Saunders et al., 2009). However, this study adopted, a conventionally tested and acceptable research instruments measuring tools (general efficacy scale, perceived stress scale and readiness for entrepreneurship) which possess acceptable level of validity and reliability to develop the research instrument used by the study. Hence, the researcher find mono-method suitable to measure the relationship between the influence of psychological factors, political environment and information awareness on entrepreneurial behaviour among youths in Mpumalanga province.
5.4.2 Mixed methods
Mixed research methods can be explained as the process of gathering, examining and explaining quantitative and qualitative data in a single study. It involves the integration of both quantitative and qualitative data, findings and processes which are analysed either sequentially or concurrently in a single study (Saunders et al., 2009; Creswell et al., 2009).
Hanson et al. (2008) suggest the essence of mixed methods as (a) Enriched findings (b) In- depth analysis (c) Ability to test a model or theory (d) Magnified participants’ inputs (e) Acceptable validity and reliability which improves general trustworthiness of the study.
Hanson et al., (2008) & Creswell et al., (2009) listed the types of mixed methods design as (a) Sequential Designs (sequential explanatory, sequential exploratory and sequential transformative designs) and (b) Concurrent Designs (concurrent triangulation, concurrent nested and concurrent transformative designs).
5.4.2.1 Concurrent mixed designs
Concurrent mixed designs enables research data to be applied simultaneously. It is the combination of numerical and non-numerical techniques applied to data collection system and equivalent analysis of the data (Cameron, 2009). Combining methods concurrently gives the necessary impetus and basis to adequately answer research questions comprehensively.
Wilson (2010) explained that the paradigm behind cross-sectional survey of combining a structured questionnaire and unstructured questionnaire in a single study is to establish the effectiveness of concurrent mixed design to answer research questions (Creswell, 2009, 2017). Concurrent mixed designs allows the researcher the luxury of structuring the
116
questionnaire in a way to align responses towards pre-determined scope of his investigation while the unstructured part gives in-depth insights to critical areas that further explains the emphatic feelings of respondents. Three concurrent methods designs will be highlighted here to further explain its relevance to research choices.
5.4.2.1.1 Concurrent Triangulation method design- This applies to a research choice where both quantitative data and qualitative data are collected simultaneously. The theoretical lens views is by implication, while both quantitative and qualitative data are collected concurrently, it is analysed separately howbeit concurrently interpreted, result is afterwards compared to arrive at a conclusion. Figure 4.5 gives a pictorial description of concurrent triangulation.
Figure 5.2 Concurrent Triangulation Design
Adapted from Designing a Mixed Methods Research (Phillip Adu, 2013)
5.4.2.1.2 Concurrent Nested method Design- Nested method is similar to triangulation method as data are collected concurrently; however, there is a distinct difference on the applicability of data analysis and interpretation. Nested method is similar to a ‘bird nest’ that is usually woven together to arrive at a desired outcome. The key word here is integration.
Theories can be developed implicitly or explicitly depending on which approach the researcher decided to start with, quantitative data and qualitative data are collected concurrently and integrated before it is analysed. Data collected are merged and analysed
117
together to give a complimentary interpretation of outcome. Figure 4.6 below is a graphic depiction of Nested design.
Figure 5.3 Concurrent Nested Designs
Adapted from Designing a Mixed Methods Research (Phillip Adu, 2013)
5.4.2.1.3 Concurrent Transformative Design- This method facilitates numerical and non- numerical data collection and analysis concurrently based on the statement of problem and the research objectives (Hanson et al., 2005). Theories are developed through explicit advocacy lens to develop framework of the study. Though data are collected concurrently different priority may be accorded to one method of data collection and analysis above the other sometimes they may be accorded equal priority (Creswell, 2017). Data analysis are done separately but are integrated at the interpretation stage. The importance of transformative mixed methods was explained by Hanson et al. (2008) where they posited that transformative mixed methods enable access to information from various worldviews inspiring respondents’ insights of the construct to enable better conceptualisation of a phenomenon from the respondents’ emphatic position in relation to the theoretical suggestions. Figure 4.7 explains concurrent transformative design.
118 Figure 5.4 Concurrent Transformative Designs
Adapted from Designing a Mixed Methods Research (Phillip Adu, 2013)
Mixed methods in summary combines numerical and non-numerical data, analysed and interpreted to establish a phenomenon. The option of transforming numerical data into narrative format (non-numerical data), analysed and interpreted, as well as conversion of non- numerical data into numerical codes for statistical analysis is opened to a researcher, which facilitates validity and reliability of researched problems.
5.4.3 Research design adopted for the study
Having reviewed different philosophies, strengths and weaknesses of several research approaches and designs deliberated above; this study adopted the most suitable strategy being guided by the objectives of the study. Therefore non-experimental research strategy was adopted supported by crosssectional data collection approach utilising descriptive designs accompanied by some exploratory, survey, and archival features. This was necessary due to the need to collect data at different locations and at different points in time (Edmonds &
Kennedy, 2012) from selected youths at designated locations from each district using several variables in order to validate the relationship between variables (Walker & Greene, 2009).
The adoption of the approach facilitated access to data collection from different categories of unemployed youths in Ehlanzeni, Gert Sibande and Nkangala districts of Mpumalanga province. Although, the study adopted a quantitative research method in data collection, there
119
was an open-ended section of the questionnaire which was designed to further gather quantitative data among participants from the three districts in order to get a general consensus on what the youths feel influences psychological factors, political environment and information awareness on entrepreneurial behaviour in the province; while the closed ended led respondents to a predetermined direction to infer causation and general perception. The design also, allowed insights into the impact of government intervention strategies (political environment) and how this has not adequately arrived at a lasting solution. Review of related literature that adopted this approach serve as a basis for adopting this approach.