The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/19786900

Kirstin Foolen-Torgerson; Fleur Kilwinger (2023): MECAnalysisTool: A method to analyze consumer data. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/19786900.v2

Dataset

x choose version: version 1 - 2022-07-06

• Measurement Standards and Calibration Services
• Commercial Services
• Commerce, Management, Tourism and Services
• Economic Framework

consumer behaviour, data aggregation, decision making, Hierarchical value map, Laddering, Means-end chain analysis, MEC, product evaluation, product valuation

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Kirstin Foolen-Torgerson , Fleur Kilwinger

This Excel based tool was developed to analyze means-end chain data. The tool consists of a user manual, a calculator file for analyzing your data, and instructional videos.

The purpose of this tool is to aggregate laddering data into hierarchical value maps showing means-end chains. The summarized results consist of (1) a summary overview,

(2) a matrix, and (3) output for copy/pasting into NodeXL to generate hierarchal value maps (HVMs). To use this tool, you must have collected data via laddering interviews. Ladders are codes linked together consisting of attributes, consequences and values (ACVs).

• 2022-07-06 first online

• 2023-05-01 published, posted

4TU.ResearchData

docx, xlsx, pptx

Methodological considerations on the means-end chain analysis revisited

• https://www.youtube.com/watch?v=uz96RLX99NI
• https://www.youtube.com/watch?v=ugFFXSob8X8&t=279s

Business Economics, Wageningen University & Research
Knowledge Technology and Innovation, Wageningen University & Research