Consumer Preference Analysis on Attributes of Milk Tea: A Conjoint Analysis Approach
Ardvin Kester S Ong1,2,3, Yogi Tri Prasetyo1, Ma Althea Deniella C Libiran3
1School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines.
Consumers prioritize milk tea pearl size and sugar level most. This study used conjoint analysis to reveal key preferences for milk tea attributes like ice amount and price, guiding beverage firms.
Area of Science:
- Consumer Behavior Analysis
- Food Science and Technology
Background:
- Milk tea has seen significant consumption growth since 2011.
- Understanding consumer preferences is crucial for beverage market success.
Purpose of the Study:
- To identify the most preferred milk tea attributes using Conjoint Analysis.
- To quantify the relative importance of various milk tea components to consumers.
Main Methods:
- Employed Conjoint Analysis with an orthogonal design.
- Evaluated consumer preferences across attributes: pearl size, sugar level, price, brand, milk tea type, cream cheese, and ice amount.
Main Results:
- Pearl size emerged as the most significant attribute (29.137%).
- Sugar level (17.373%) and ice amount (17.190%) were also highly influential.
- Brand (2.147%) and cream cheese inclusion (9.525%) had the least impact on preference.
Conclusions:
- Milk tea firms should focus on optimizing pearl size and sugar level to meet consumer demand.
- Findings offer insights into beverage attribute preferences applicable globally.
- This research aids in strategic product development within the competitive beverage industry.
More Related Videos
08:43PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis
Published on: May 11, 2017
09:12Optimization of Processing of Tiebangchui with Highland Barley Wine Based on the Box-Behnken Design Combined with the Entropy Method
Published on: May 19, 2023
Related Concept Videos
Factorial Design
Decision Making: P-value Method
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
Kendall's Tau Test
A τ value...
Multiple Comparison Tests
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
Convenience Sampling Method
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
Two-Way ANOVA
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
