**4. Conceptual framework on adoption of big data analytics**

The study is guided by the conceptual framework shown on **Figure 6** below:

#### **4.1 Research methodology**

The study's research philosophy, as well as the research design, research approach, data collection instruments, target population, sampling method, and data processing techniques, are all explained in the Research Methodology. The research philosophy, approach, strategy, choice, time horizon, and techniques and processes constitute the layers, as shown on **Figure 7**.

The Mixed Method Research and the Pragmatism paradigm utilized in this study are closely related on a philosophical level (MMR). A worldview or paradigm known as pragmatism ought to guide the majority of mixed-methods studies. It is a problem-focused attitude that holds that the best research techniques are those that contribute most significantly to the solution of the research topic. When conducting social science research, this frequently entails combining quantitative and qualitative

**Figure 6.** *Conceptual framework.*

methodologies to assess various facets of a research subject. The pragmatic worldview served as the foundation for the Mixed Methods Research technique. A mixedmethods strategy was used in this study, combining qualitative (Focus Group discussions) and quantitative techniques (a questionnaire). System logs, document analysis, and a literature review were also utilized in this study.

The purpose for the Focus Group discussion was to research and determine on how to use and implement Big Data to improve production for both oilseeds and textile production and international trade for Sub-Saharan Africa (SSA). The Focus Groups were derived from 10 Groups of Masters students at the University of Zimbabwe in the 2021 cohort who then were tasked to conduct surveys and interview the management of various corporates in Zimbabwe and other nearby Southern African countries involved in the oilseeds and textile industries. Secondary data was collected form the World Bank, FAO [FAOSTAT, www.faostat.org] and US Department of Agriculture (https://apps.fas.usda.gov/psdonline/circulars/oilseeds.pdf) for analysis.

*A Big Data Analytics Architecture Framework for the Production and International Trade… DOI: http://dx.doi.org/10.5772/intechopen.107225*

**Figure 7.** *Research onion (Saunders et al., 2009:138).*
