Introduction

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.