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The Influence of Affective Brand Experience Dimension on Brand Equity of the Smartphone Millennial Users in Malaysia
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作者 Iman Khalid A-Qader Azizah Binti Omar Mohammad Rabiul Basher Rubel 《Management Studies》 2017年第1期25-37,共13页
This study intends to highlight the power of affective brand experience dimension and link how it can influence brand equity of smartphone users in Malaysia. Measurement items for affective brand experience dimension ... This study intends to highlight the power of affective brand experience dimension and link how it can influence brand equity of smartphone users in Malaysia. Measurement items for affective brand experience dimension and brand equity were developed by integrating existing literature and qualitative in-depth interviews with students who own and use a smartphone. Therefore, 359 usable questionnaires were returned. Data were analyzed using PLS-SEM to test the influences of affective brand experience dimension on brand equity. The study found that affective brand experience dimension is an important factor influencing brand equity of smartphone users in Malaysia. The study provides evidence that the affective brand experience dimension positively influences brand equity. The distinctive contribution of this research is that it examines the influence of affective brand experience dimension on customer-based brand equity in the context of smartphone brands in the Malaysian emerging markets. Such work is essential in understanding the importance of experiential marketing in an emerging economy such as Malaysia for building a strong smartphone brand. 展开更多
关键词 affective brand experience dimension brand equity millennial generation
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A Comparative Study on Two Techniques of Reducing the Dimension of Text Feature Space
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作者 Yin Zhonghang, Wang Yongcheng, Cai Wei & Diao Qian School of Electronic & Information Technology, Shanghai Jiaotong University, Shanghai 200030, P.R.China 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2002年第1期87-92,共6页
With the development of large scale text processing, the dimension of text feature space has become larger and larger, which has added a lot of difficulties to natural language processing. How to reduce the dimension... With the development of large scale text processing, the dimension of text feature space has become larger and larger, which has added a lot of difficulties to natural language processing. How to reduce the dimension has become a practical problem in the field. Here we present two clustering methods, i.e. concept association and concept abstract, to achieve the goal. The first refers to the keyword clustering based on the co occurrence of 展开更多
关键词 in the same text and the second refers to that in the same category. Then we compare the difference between them. Our experiment results show that they are efficient to reduce the dimension of text feature space. Keywords: Text data mining
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