Choice of Research Design

A research design is like a roadmap—you can see where you currently are, where you want to be at the completion of your journey, and can deter­mine the best (most efficient and effective) route to take to get to your desti­nation. We may have to take unforeseen detours along the way, but by keep­ing our ultimate objective constantly in mind and using our map we can arrive at our destination. Our research purpose and objectives suggest which route (design) might be best to get us where we want to go. but there is more than one way to “get there from here.” Choice of research design is not like solving a problem in algebra where there is only one correct answer and an infinite number of wrong ones. Choice of research design is more like se­lecting a cheesecake recipe—some are better than others but there is no one which is universally accepted as “best.” Successfully completing a research project consists of making those choices that will fulfill the research purpose and obtain answers to the research questions in an efficient and effec­tive manner.

Choice of design type is not determined by the nature of the strategic de­cision faced by the manager such that we would use research design A whenever we need to evaluate the extent of a new product opportunity, or design B when deciding on which of two advertising programs to run. Rather, choice of research design is influenced by a number of variables such as the decision maker’s attitude toward risk, the types of decisions be­ing faced, the size of the research budget, the decision-making time frame, the nature of the research objectives, and other subtle and not-so-subtle fac­tors. Much of the choice, however, will depend upon the fundamental ob­jective implied by the research question:

• To conduct a general exploration of the issue, gain some broad in­sights into the phenomenon, and achieve a better “feel” for the sub­ject under investigation (e.g.. What do customers mean by “good value”?).

• To describe a population, event, or phenomenon in a precise manner where we can attach numbers to represent the extent to which something occurs or determine the degree two or more variables covary (e.g., determine the relationship between age and consumption rate).

• To attribute cause and effect relationships among two or more vari­ables so that we can better understand and predict the outcome of one variable (e.g., sales) when varying another (e.g., advertising).