Introduction

The growing interest in the cognitive foundations of behavior within the information

systems (IS) field has led to a focus on representing and analyzing the cognitions of

individuals and groups. Cognitive representations are created by eliciting the relevant

cognitions of the participants and casting their cognitions into appropriate structural

representations. Over the years there have been numerous methods of representing

cognition that have been used, such as: argument mapping (Fletcher & Huff, 1990),

context analysis (e.g., Birnhaum-More & Weiss, 1990), repertory grid (e.g., Tan & Hunter,

2002), and the Self-Q technique (e.g., Bougon, Weick & Binkhorst, 1977) to name a few.

Causal mapping is an additional technique that can be used to represent cognition.

Causal mapping captures the structure of the causal assertions of an individual or group.

Many believe that causal mapping holds great promise in addressing phenomena from

a cognitive perspective, which is an under-utilized lens in the IS field. As we move causal

mapping into the IS field, it is important that we understand the method, its strengths and

limitations and place it within the spectrum of research methods. Many researchers have

made assumptions (both explicit and implicit) regarding causal mapping, without explicating

the steps involved. Thus buried in many of the studies found in the literature are

the steps used to develop the cognitive representations of participants.

This chapter seeks to explicate the causal mapping (CM) process so that researchers and

practitioners can utilize this method to address IS issues within organizations using a

cognitive lens. The objectives of the chapter are two-fold:

• To demonstrate in detail how CM can be used to understand IS issues from a

cognitive perspective

• To provoke interest in expanding the boundaries of the CM method within the IS

field as we present advances and issues related to CM

In the remainder of the chapter, I provide the motivation behind causal mapping research

and detail the causal mapping approach for both capturing individual maps and deriving

collective causal maps. Next, I detail the representation and analysis of the maps, and

discuss some key issues to address when reporting the results. I conclude the chapter

with a summary of the key decision points researchers will face when conducting causal

mapping research.