Kirstin Foolen-Torgerson; Fleur Kilwinger (2022): MECAnalysisTool: A method to analyze consumer data. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/19786900.v1

Dataset

x choose version: version 2 - 2023-05-01 (latest)

• Measurement Standards and Calibration Services
• Commercial Services

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 data input file to correctly organise your MEC data, a calculator file to analyse 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, 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