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研究生: Xibri, Blerta
Xibri, Blerta
論文名稱: 臺灣Y世代與Z世代美妝產業市場區隔之研究
Market Segmentation of Generation Y and Z in Taiwan for the Cosmetic Industry
指導教授: 沈永正
Shen, Yung-Cheng
學位類別: 碩士
Master
系所名稱: 管理研究所
Graduate Institute of Management
論文出版年: 2020
畢業學年度: 108
語文別: 英文
論文頁數: 54
英文關鍵詞: generation Z, generation Y and Z in Taiwan
DOI URL: http://doi.org/10.6345/NTNU202001155
論文種類: 學術論文
相關次數: 點閱:179下載:49
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  • This study focuses on generational lifestyle in Taiwan. More precisely, this paper has the purpose to define market segments regarding generation Y and generation Z for the
    cosmetic industry. The market segmentation of both generations is used as a basis to further build a comparison. A quantitative method was used to get data for this research.
    A questionnaire was developed to conduct this research and define different purchase groups among these two generations in order for marketers to better tackle and tailor
    their targeting strategies accordingly. The generations’ behaviour and interests towards cosmetics is further analysed concluding in different market segments which are then used to compare the characteristics that generation Y and Z present. The first part of this thesis explores literature concerning the cosmetic industry, market segmentation approaches and already observed characteristics of each generation. The second part consists in data analysis using the questionnaire for gathering the data and further investigating it through SPSS as a statistical tool.

    CHAPTER I INTRODUCTION 1 CHAPTER II LITERATURE REVIEW 3 Cosmetics Industry 3 Industry Overview 3 Industry Trends 5 Market Segmentation 8 Geographic Segmentation 10 Socio-Demographic Segmentation 10 Psychographic Segmentation 11 Behavioural Segmentation 11 Personality Traits of Generation Y & Z 12 Characteristics of Generation Y 12 Characteristics of Generation Z 13 Characteristics of Generation Y and Z in Taiwan 13 CHAPTER III RESEARCH METHODS 15 Research Approach 15 Data Collection 15 Sample and Participant Selection 17 Assessment and Measures 17 Data Analysis 18 Descriptive Statistics 18 Factor Analysis 19 Cluster Analysis 25 CHAPTER IV FINDINGS AND DISCUSSION 34 Findings 34 Discussion 39 CHAPTER V CONCLUSIONS AND RECOMMENDATIONS 43 Conclusions 43 Recommendations 44 REFERENCES 46 APENDIX I 52

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