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Means-End Chain Laddering/Bevis
Metodebevisregister

Means-End Chain Laddering

Means-end chain analysis explains consumer choice by linking the concrete attributes of a product to the consequences of using it and ultimately to the personal values those consequences serve. Jonathan Gutman's 1982 model proposed that consumers categorize products by the desirable consequences they deliver, and that these consequences are valued because they help attain higher-order life values, so a chain runs attribute to consequence to value. Laddering, formalized by Thomas Reynolds and Jonathan Gutman, is the interviewing technique that uncovers these chains by repeatedly asking why a feature matters until the respondent reaches the underlying values. The resulting ladders are content-coded into attributes, consequences, and values, then summarized in an implication matrix counting how often each element leads to another. Applying a cutoff to that matrix yields a hierarchical value map (HVM), a network showing the dominant attribute-consequence-value pathways for the category. The approach reveals not just what consumers want but why, providing a values-grounded foundation for positioning and advertising strategy.

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Means-End Chain Analysis and Laddering (Attributes-Consequences-Values)
Taksonomisk metoderegister · process-pipeline / marketing
  • Gutman, J. (1982). A Means-End Chain Model Based on Consumer Categorization Processes. Journal of Marketing, 46(2), 60-72. · DOI 10.1177/002224298204600207
  • Reynolds, T. J., & Gutman, J. (1988). Laddering Theory, Method, Analysis, and Interpretation. Journal of Advertising Research, 28(1), 11-31. · DOI 10.1080/00218499.1988.12467766
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Same method familyImplicit Reaction-Time Brand Measuresmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketProjective Techniques in Consumer Researchmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketZMET (Zaltman Metaphor Elicitation Technique)machine-suggested · Relational suggestion, not evidence.

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