3.1 Framework
Respondents are examined how they perceived 8 department store skin care brands over 15 attributes based on 4 dimensions of brand equity. Later, a perceptual map is created by the result of brand equity measurement using MDS. From the perceptual map, we can find which brands are close to the ideal brand and which brands are not.
Figure 3.1 Research Framework
3.2 Data collection
To collect the data from the skin care customers, a questionnaire is conducted in Taipei city. In order to save cost and time, my survey was in the form of online survey and paper questionnaires. The survey focused on 19~50 year old women who are the most potential customers who will buy skin care products from department stores.
Lastly, the questionnaire designed for this study was originally drafted in traditional Chinese.
3.3 Questionnaire Design
My questionnaire can be divided into four parts. The first part focuses on 8 Skincare Brands’
Brand Equity Brand Loyalty
Price Premium
Satisfaction and Loyalty
Brand Association
are as such “How often do you buy skin care products at department stores?”, and the average amount of money spending on skin care products per time. In the second part, questions are designed to know what factor influences consumers’ most while
purchasing skin care at the department store, and what consumers value most in terms of skin care. For the third part, respondents are asked to evaluate 8 brands according to their preference and using experiences with 5-point Likert scale. 15 attributes used in the evaluations are based on Aaker’s brand equity. Finally, the fourth part is the simple survey of each respondent’s basic demographic information including age, marriage, occupation, education level, and monthly income. The table below summarizes all the variables used in the questionnaire.
Table 3.1 Variables List
Type of variable Scale Statement Demographic
variable
Nominal Scale Age Marriage Occupation Education level Monthly Income
Behavioral variable Nominal Scale Frequency of buying department store skincare products Average spending on department store skincare products per time.
Key factors when buying skincare products at department stores
Skin care concern Brand awareness Brands bought recently
Market Stimuli Nominal Scale Product Product Efficacy
(Whitening/Moisturing/Anti-aging) Elements
Brand Awareness Package Price Price Place Staff Service
Promotion Promotion activity Spokesperson
Advertisement(TV, magazines, etc) Source of information Nominal Scale Family/Friends
Internet Past Experience
8 brands Nominal Scale SHISEIDO, ESTEE LAUDER, LANCOME, SKII, CLINIQUE, SISLEY, BIOTHERM, KIEHL’S
Brand Loyalty Ordinal Scale (Five-point Likert Scale)
Price Premium Satisfaction
Perceived Quality Perceived Quality
Leadership
Brand Awareness Brand Awareness
Brand Association Perceived Value
Brand Personality Corporate Association Differentiation
3.4 Data Analysis Method
In my study, I use descriptive statistics, MANOVA, and MDS to analyze the data collected through questionnaires with an alpha level=0.1.
Descriptive Statistics
Descriptive statistics are used to describe the main features of a collection of data in quantitative terms. In my study, I use simple descriptive statistics such as frequency
to describe demographic characteristics and consumers’ buying behavior of my study sample.
One-Way MANOVA(Multivariate analysis of variance)
One-way ANOVA is used to test for differences among two or more independent groups. With this model, the dependent variable is continuous in nature, whereas the independent variables are categorical. It evaluates the effect of a single factor on a single dependent variable. Multi-way analysis of variance (MANOVA) is an extension of the one-way model that examines the effect of the grouping independent variable on multiple dependent variables. In this study, a one-way MANOVA, ANOVAs for each dependent variable and pairwise comparisons were conducted. Pairwise comparison generally refers to any process of comparing entities in pairs to judge which of each pair is preferred, or has a greater amount of some quantitative property. The method of pairwise comparison is used in the scientific study of preferences, attitudes, voting systems, social choice, public choice, and multiagent AI systems. In my study, pariwaise comparison was used to determine which brand received a greater evaluation on each attribute.
Multidimensional Scaling (MDS)
Generally, there are two scaling techniques commonly used in statistics which are comparative scales and noncomparative scales. Comparative scales involve the direct comparison of stimulus objects. Comparative scale data must be interpreted in relative terms and have only ordinal or rank order properties. In noncomparative scales, each object is scaled independently of the others in the stimulus set. The resulting data are generally assumed to be interval or ratio scaled. Both techniques have pros and cons.
Relative advantages of comparative scales
- Small differences between stimulus objects can be detected.
- Same known reference points for all respondents.
- Easily understood and can be applied.
- Involve fewer theoretical assumptions
- Tend to reduce halo or carryover effects from one judgment to another.
Relative disadvantages of comparative scales - Ordinal nature of the data
- Inability to generalize beyond the stimulus objects scaled
Multidimensional scaling (MDS) is a class of procedures for representing perceptions and preferences of respondents spatially by means of a visual display.
Perceived or psychological relationships among stimuli are represented as geometric relationships among points in a multidimensional space. These geometric
representations are often called spatial maps. The axes of the spatial map are assumed to denote the psychological bases or underlying dimensions respondents use to form perceptions and preferences for stimuli. In marketing, MDS is usually for taking the preferences and perceptions of respondents and representing them on a visual grid, called perceptual maps. In my study, MDS is used to plot the 9 brands including the ideal brand on a map such that those brands that are perceived to be very similar to each other in terms of brand equity are placed near each other on the map, and those brands that are perceived to be very different from each other are placed far away from each other on the map. Perceptual mapping can offer additional insight into the current position of one product and its potential in the face of competition. In this way, we can find out which brands are closer to the ideal brand and which are not in consumers’
mind.