Introduction

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In empirical works employing causal maps, researchers usually address the content,

structure or behavior of causal maps (a point that was elaborated in Chapter I). Contentbased

studies typically focus on the specific concepts in a causal map or the differences

among concepts across maps. Structure refers to the pattern of relationships, or the

differences among patterns in comparative studies. Indeed most of the studies reported

in this book have chosen to focus on content or structure.

By the term, “the behavior of causal maps” we mean the prediction or analysis of

decisions or actions that one can make, based on a given causal map. Some examples

will illustrate the meaning of this definition. For example, if a firm constructed a

competitor’s causal map with industry conditions as a set of causes and strategic actions

as consequences, the firm may be interested in using the causal map to predict the

behavior of its competitor, i.e., predicting its competitor’s strategic actions. This is of

great interest in competitive intelligence systems. In another sense, behavior could refer

to the analysis of the consequences of specific policy actions initiated by a firm. As an

example, in Information System (IS) design work, if a causal map of the implementation

process is constructed (that embraces relevant stakeholders), then designers can assess

the consequences of various managerial alternatives in order to identify satisfactory

actions that can be initiated by the management during implementation.

The analysis of the behavior of causal maps remains the Holy Grail in research using

causal mapping. Although the analysis of behavior is much more prevalent in intervention

contexts, empirical research on the behavior of causal maps is almost non-existent.

This has been partly due to the absence of easily accessible methodological tools and

theoretical lenses. Thus, the primary goal of this chapter is to invite future research in

causal map theory focusing on behavior, not merely the content and structure of the

maps. Specifically, the chapter aims to: 1) review and summarize promising avenues to

connect causal maps and behavior; and 2) enumerate some specific tools to deploy in

each avenue.

The scheme of this chapter is as follows: In the next section, we will provide an overview

of the fruitful approaches to examining the behavior of causal maps. Following that, we

will deal with three simulation approaches. Next we will sketch the empirical approach that

we are beginning to witness in some disciplines. We will conclude with a comparative

analysis of these approaches.

At the outset, we want to make one observation to place our discussion in perspective:

Our approach is to identify fruitful, but not yet tested techniques for the analysis of the

behavior of causal maps. Only as these techniques are put to use, will we know their

relative merits or applicability. Thus, this chapter represents a preliminary guide to the

uncharted territories that remain in the methodology of causal mapping.