User guide to means-end chain analysis. RTB User Guide
Means-end-chain analysis (MEC) comes from the field of marketing and consumer studies. Its attractiveness is the freedom it gives to respondents to select and verbalize their own constructs for evaluating a product or service. The means-end chain interviews consist of two parts: 1) attribute elicitation and 2) laddering. There are several methods for both parts. An elicitation technique useful for exploratory research is “triadic sorting,” based on Kelly’s repertory grid. In this technique, typically the farmer or trader is asked to sort three fairly similar products or services according to their perceived similarities and differences (Kelly, 1955). These personally relevant constructs are then linked to the respondent´s personal goals via laddering interviews. In the laddering interviews the interviewer is only allowed to ask “which one do you prefer” and “why is this important to you?” When all laddering interviews are conducted the responses are aggregated in a hierarchical value map, which gives an overview of how and why farmers collectively value a certain product or service. Because the interview follows a free response format which allows farmers to formulate personally relevant constructs in their own words, the farmers may come up with characteristics or motivations that researchers could not have imagined as important. The means-end chain analysis is suitable for exploratory research because it is more sensitive to the farmer’s point of view than a questionnaire survey. A means-end chain study requires about 40 interviews when using soft-laddering. Hard-laddering can be used with larger sample sizes, but it captures fewer of the farmers’ own categories. Application of the means-end chain analysis requires skill and practice.