Introduction
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Revealed causal mapping (RCM) is an increasingly powerful tool for several research
contexts including discovery, exploratory, hypothesis testing and intervention (see
Chapter I for a detailed discussion of the research contexts). This chapter provides
insights for conducting research in a discovery or exploratory context. In a discovery (or
exploratory) setting the initial data collection process is conducted without any preconceived
constructs in mind other than the general issue at hand. When using RCM as a
theory building or discovery methodology, rather than a theory confirming or hypothesis
testing methodology, the process must be open to allow constructs to be revealed
that had not been initially anticipated by the interviewer. It is important that one decide
at the beginning of a RCM study what data collection method is appropriate for the
phenomenon under study (see Chapter II). Since I have used the discovery and
exploratory research contexts in my work with revealed causal mapping, I will address my
comments only to those research contexts and specifically interactively elicited causal
maps. To make the process a bit clearer, I will use as a context portions of a much larger
study of IT personnel transition1.
In this chapter I will share what I have learned through the process of conducting revealed
causal mapping research. I will begin by discussing the interview process and identifying
causal statements from the interview texts. Then I will provide some insights on the
development of a coding scheme and will conclude with some thoughts on lessons
learned.