Promoting data-driven and real-world applicability driven approaches to theorization: Yet another essential requirement of contemporary science

This paper attempts to extend our previous papers and publications on the philosophy of science and 
the scientific method most notably those pertaining to context-based theorization, and the knowledge 
production lifecycle or the knowledge production process. We begin this paper by discussing what 
theorization is all about, and discuss the process of theorization and hypothesis-building in brief 
including a summation and summarization of the various steps involved. We would like to impress upon 
our audiences, the need and importance of data-driven and real-world applicability driven theorization 
in the context of the twenty-first century, with an aim to demonstrate that the most ideal principles are 
still not followed in twenty-first century research. In sum, the core concepts of grounded theory are also 
still mostly not followed. We need not only metrics-driven approaches, but more meta data and meta 
theorization. To prove our point and prove our case, we extract and present a large number of basis 
examples from economics, particularly micro economics. These observations will of course also apply to 
other fields of the social sciences, and non social sciences as well. Much is to be gained by streamlining 
scientific method, and bringing it uptodate in all aspects and respects, more so through revolutionary 
change.