The last topic I will discuss in the Research Design section is the tradeoffs. One of the most important activities when designing a research approach is understanding the tradeoffs that we have to make. For instance, issues like sampling (including procedures and size), the precision of measures, and the number of variables are common.
I will briefly discuss method variance, as I have mentioned it as a potential problem in previous posts. It is generally understood that research focusing on macro-level questions (such as strategy) rarely use laboratory experiments, and rarely have the problem of common method variance.
This discussion is an extension on the Lab, Field, and Survey post.
The place where we conduct research on organizations can have a significant impact not only on how we conduct research but also on the results of our studies and investigations. This means paying attention to methodological fit, and how we match the type of research question we wish to explore with the type of setting to use for it.
The first step to consider, is what the current state of theory is at. Next, we will select a specific setting, which will have implications for the amount of control we have over extraneous variables.
Qualitative techniques for data collection are suited for the exploratory studies when little is know about the phenomena. That is, these techniques are well suited for the early stage of the five-step logical path for the programmatic research (McGrath, 1964). However, these techniques are not suited for the testing theories or making causal inferences, as they do not allow for manipulation or control of variables. As Lee et al (1999) suggest, qualitative techniques are well suited for the purpose of description, interpretation, and explanation but are not suited for issues of prevalence, generalizability, and calibration.
In this post I will summarize lab, field, and surveys. The most important things to remember are the measures that are used and the inferences each approach allows us to make.
In the previous post, I detailed a few different types of research designs. In this post I will talk about an important element in research design: Time.
According to Mitchell and James, time is treated as a commodity that can be broken into meaningful segments or blocks. It flows evenly and consistently, it’s precise and quantifiable, and is ordinal.