2025
Consumer Preferences and Utility in Milk Chocolate Selection: Conjoint Analysis and TOPSIS Method
NENIČKOVÁ, Zuzana; Lucie WALECZEK ZOTYKOVÁ and Radmila KRKOŠKOVÁBasic information
Original name
Consumer Preferences and Utility in Milk Chocolate Selection: Conjoint Analysis and TOPSIS Method
Authors
Edition
Prague, The 43rd International Conference on Mathematical Methods in Economics (MME 2025), p. 78-83, 6 pp. 2025
Publisher
The Czech Society for Operations Research
Other information
Language
English
Type of outcome
Proceedings paper
Field of Study
10102 Applied mathematics
Country of publisher
Czech Republic
Confidentiality degree
is not subject to a state or trade secret
Publication form
electronic version available online
References:
Organization unit
School of Business Administration in Karvina
ISBN
978-80-11-07486-9
ISSN
Keywords in English
conjoint analysis; preferences; TOPSIS
Tags
International impact, Reviewed
Changed: 15/1/2026 10:01, Ing. Zuzana Neničková, Ph.D.
Abstract
In the original language
This study examines consumer preferences in the context of milk chocolate selection using a conjoint analysis based on primary data collected through a questionnaire. The analysis focusses on four key attributes of the product: brand, price, weight, and content of certified cocoa. The results of the conjoint analysis provide the relative importance (weights) of individual criteria and estimate the utility associated with brand and certified cocoa content. The resulting preference structure serves as the basis for applying the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method to rank the actual chocolate products currently available on the market. This multicriteria decision-making framework allows for a systematic comparison of alternatives with respect to an ideal product profile. In addition, a sensitivity analysis is conducted to explore the robustness of the ranking outcomes. Specifically, we investigated the extent of the change in attribute weights required to alter the final product ranking. This provides insight into which attributes have the most influence on consumer choice under varying preference scenarios.