Constructing a Framework From Quantitative Data Analysis: Advantages, Types and Innovative Approaches

Constructing a framework in research is the process of organising and structuring an intricate collection of facts, variables, or concepts in a manner that enhances the interpretation, analysis, and comprehension of their interconnections. Nevertheless, the absence of explicit procedures for constructing a framework may give rise to a problem statement for the present investigation. This study aims to refine advantages, types and innovative approaches in constructing a framework from a quantitative data analysis. This study suggests four innovative approaches for constructing a framework from quantitative data analysis, namely: (a) framework development from descriptive data analysis; (b) framework development from inferential data analysis; (c) framework integration from descriptive and inferential data analysis; and (d) framework simplification of the integrated framework. The design of these processes ensures accuracy and adherence to a reasonable order. In conclusion, the development of a framework based on quantitative data analysis offers a multitude of benefits for researchers and their endeavours. To enhance the accuracy and reliability of frameworks developed from quantitative data analysis, it is advisable to investigate the capabilities of machine learning and artificial intelligence (AI) in future studies.