Most of us commit a fundamental mistake in either not closely examining the theory or misunderstanding the theory itself. Let us digest the fact that theory is cornerstone to all meaningful research. At an early stage, realizing that we are not the first to do research, we begin to honour the work of previous researchers in the domain. This is called “Scholar’s integrity”. Now what exactly is the idea of theory? We are going to set aside our previous learning and refresh our idea on theory. Bacharach (1989) says that “theory is a statement of relationships between two or more concepts within a boundary of assumption and constraints. In simpler words theory is used to describe, explore, explain and predict the phenomena in the given context. (Gregor,2010).
The role of theory is to provide explanations at a macro level within and among concepts. Say for instance, we are interested in verifying the relationship between rise in the advertisement expenditure and its impact on sales revenue. Advertisement and Sales revenues are independent concepts or constructs. And the explanation of their relationship forms the theory. This theory can be represented in multitude ways, typically in the form of statements (Hypothesis), Diagrams (Theoretical models), equations (Statistical Model) and visual representation (Tables and Charts). Theory then plays a major role in giving the “thesis” its validity. Further, theory must manifest in every phase of research. This alone will yield a sound and robust Thesis.
Any formal research process must progress hand in hand with theory and data. Theory and measurement obviously depend on one another, but clearly, theory precedes measurement and dominates academic research work. An appropriate theory combined with measurement has an amazing explanatory power; on the contrary simply measuring without theoretical concurrence is at best a statistical orphan. During the early stage of physical science research, most of the scientists and philosophers like Francis Bacon an empiricist himself, believed that pure observation is sufficient. Subsequently Karl Popper’s school of thought confirmed that theory follows Observation and is equally important. Further, with the advent of statistics and quantitative confirmations, testing of hypothesis began to gain acceptance. At present, machine learning and data mining are shaping the way research is being conducted, where observation of large data is gradually leading to capture and formulation of unnoticed theory. In nut shell, research is not data alone. But when coupled with relevant theory, it has the potential to produce a terrific Thesis.