CONJOINT ANALYSIS VS PREFERENCE ANALYSIS: A COMPARISON

1987 ◽  
Vol 60 (3c) ◽  
pp. 1063-1068
Author(s):  
THOMAS R. SCHORP ◽  
H. LEE MEADOW
Keyword(s):  
Conjoint Analysis ◽  
Preference Analysis

scholarly journals Preference analysis of determining jobs using conjoint analysis

2020 ◽  
Vol 1442 ◽  
pp. 012040
Author(s):  
R D Karima ◽  
R Setiadi ◽  
T Siswantining
Keyword(s):  
Conjoint Analysis ◽  
Preference Analysis

scholarly journals Consumer Preference Analysis on Attributes of Milk Tea: A Conjoint Analysis Approach

Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1382
Author(s):  
Ardvin Kester S. Ong ◽  
Yogi Tri Prasetyo ◽  
Ma. Althea Deniella C. Libiran ◽  
Yuanne Mae A. Lontoc ◽  
Joyce Anne V. Lunaria ◽  
...  
Keyword(s):  
Conjoint Analysis ◽  
Consumer Preferences ◽  
Orthogonal Design ◽  
Consumer Preference ◽  
Analysis Approach ◽  
Cream Cheese ◽  
Preference Analysis ◽  
Price Range ◽  
Consumer Preference Analysis

Milk tea is a famous drink that has been heavily consumed since 2011. This study aimed to determine the combination of milk tea attributes that were most preferred using a Conjoint Analysis Approach. Specifically, this study utilized different attributes such as the size of tapioca pearls, sugar level, price range, brands, type of milk tea, cream cheese inclusion, and the amount of ice. Conjoint analysis with the orthogonal design was utilized to evaluate the preference of milk tea among consumers. The results showed that pearl size was the attribute most considered by consumers (29.137%), followed by sugar level (17.373%), the amount of ice (17.190%), the type of drink (13.421%), price (11.207%), and the least considered were cream cheese inclusion (9.525%) and the brands (2.147%). The findings of this study will be beneficial to milk tea firms about consumer preferences regarding the various attributes of milk tea. Finally, the result of this study could be applicable to different beverage-focused studies worldwide.

Conjoint Analysis vs Preference Analysis: A Comparison

1987 ◽  
Vol 60 (3_part_2) ◽  
pp. 1063-1068
Author(s):  
Thomas R. Schori ◽  
H. Lee Meadow
Keyword(s):  
Conjoint Analysis ◽  
The Other ◽  
Optimal Configuration ◽  
Preference Analysis

Conjoint and Preference Analyses were used in an attempt to identify a potential new product's optimal configuration. From each analysis, the same conclusions were drawn, that is, there was no analytic advantage of one analysis over the other. Since the Preference Analysis was more simple and less costly to use, this procedure seems more desirable to use in optimizing a new product's design.

Customer Preference Analysis on Fashion Online Shops using the Kano Model and Conjoint Analysis

2015 ◽  
Vol 6 (5) ◽  
pp. 881 ◽  
Author(s):  
Amalia Suzianti ◽  
Nurza Dwi Prisca Faradilla ◽  
Shabila Anjani
Keyword(s):  
Conjoint Analysis ◽  
Kano Model ◽  
Preference Analysis ◽  
Customer Preference ◽  
Online Shops

Applications of Conjoint Analysis in Industrial-Organizational Psychology

2006 ◽  
Author(s):  
Robert D. Pritchard ◽  
Melissa J. Sargent ◽  
Deborah DiazGranados ◽  
Neal W. Schmitt
Keyword(s):  
Conjoint Analysis ◽  
Organizational Psychology ◽  
Industrial Organizational Psychology

Investigating user preferences in night bus lines operation using Conjoint Analysis in the city of Thessaloniki, Greece

2020 ◽  
Author(s):  
Dimitrios Nalmpantis ◽  
Dimitra Giannaka ◽  
Stavros Malliaris ◽  
Evangelos Genitsaris ◽  
Ioannis Karagiotas ◽  
...  
Keyword(s):  
Conjoint Analysis ◽  
User Preferences ◽  
The City
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