The Second Generation of the Laddering Methodology and Its Use in Studying Decision Making

The Second Generation of the Laddering Methodology and Its Use in Studying Decision Making

Gabriele Morandin (University of Bologna, Italy), Massimo Bergami (University of Bologna, Italy), and Richard P. Bagozzi (University of Michigan, USA)
DOI: 10.4018/978-1-4666-6371-8.ch013
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The laddering technique can be considered a meaning-based qualitative approach for understanding preferences, motivations, and other general determinants of consumer and organizational choices. This chapter begins by presenting the original version of the laddering technique and its limitations and then introduces the technique's second generation. Based on Means-End Chains Theory (MEC Theory), the laddering methodology is used to uncover mental schemas in the form of cognitive maps by using principles derived from social network analysis. The bases for motives, goals, or values can be studied with such procedures. It also allows us to understand the influence of cognitive schemas on attitudes and behaviors through appropriate quantitative tests. Using data from a sample of 102 members of the Ducati community participating in a motorcycle event, the authors present the rationale and procedures involved in laddering and illustrate its overall approach while discussing its strengths and weaknesses.
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Mec Theory And The Original Version Of Laddering

In the original version of laddering (Gutman, 1982, p. 60), “Means are objects (products) or activities in which people engage […]. Ends are valued states of being […]. A means-end chain model is a model that seeks to explain how a product or service selection facilitates the achievement of desired end-states”. The theory is based on three fundamental assumptions derived from cognitivism: (1) values play a dominant role in directing choice patterns; (2) people face a wide offer of products and activities coherent with their values, grouping them in categories so as to reduce choice complexity; and (3) actions produce consequences, and people learn to associate particular consequences with specific actions. Consequences refer to any physiological or psychological result that arises—directly or indirectly, earlier or later—from consumer behavior. The central aspect of the model is that people choose products that produce desired consequences and minimize undesired ones.

As shown in Figure 1, the general model assumes that people attribute importance and meaning to consequences. These attributions are modified by the situation that induces the person to consider the consequences in the light of situational demands. The relevant consequences emerging from this person-situation interaction constitute the basis for of a functional classification of products that can best produce the relevant consequences. These products are chosen on the basis of the attributes they possess that imply their ability to produce the desired consequences while avoiding undesired ones. Over time, people learn to distinguish between products they would use, those they would not, and what types of situations would lead them to use or choose not to use them.

Figure 1.

Means-end chains model (adapted from Gutman, 1982)


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