| 摘要(英) |
In recent years, environmental protection issues have gradually attracted the attention of the public. In addition to environmental initiatives, they have gradually begun to start at all levels around our lives. Enterprises have also begun to propose solutions to give consumers more friendly choices. Cosmetics products are important products in most people’s lives, but they will not be the first product that comes to mind. Cosmetics products directly touch the skin, they must be strictly controlled in terms of ingredient selection, manufacturing process, and packaging. The sustainable production and consumption of cosmetics products has begun to attract social attention.
This research aims to explore the impact of consumer attitudes and motivations towards sustainable cosmetics products on purchasing behavior through segmentation analysis, and cut into three aspects: demographic variables segmentation, sustainability attitudes and purchase motivation segmentation analysis and consumer segmentation analysis.
From the results, it is found that the demographic variables for the consumption amount of sustainable cosmetics products are not very different in gender, age, and region. Therefore, it is recommended to use personal annual income and family annual income to divide consumers into groups, or according to sustainable cosmetics. The attitude, motivation and willingness to buy sustainable cosmetics products are divided into groups. Through consumer segmentation analysis, it is found that ethnic groups with higher annual income do not have the highest buying attitude and willingness to buy, but relative to the annual income of the family, it will still affect the consumption and purchase intention of Cosmetics products.
This research can provide the industry with different thinking about consumer segmentation, and can have a clearer customer positioning for the product and formulate different marketing strategies.
Keyword：Sustainable cosmetics products, Sustainable awareness, Segmentation analysis, Cluster analysis |
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