This paper proposes a clustering technique that minimizes the need for subjective human intervention and is based on elements of rough set theory （RST）. The proposed algorithm is unified in its approach to clusterin...This paper proposes a clustering technique that minimizes the need for subjective human intervention and is based on elements of rough set theory （RST）. The proposed algorithm is unified in its approach to clustering and makes use of both local and global data properties to obtain clustering solutions. It handles single-type and mixed attribute data sets with ease. The results from three data sets of single and mixed attribute types are used to illustrate the technique and establish its efficiency.展开更多
Company experts and academicianshave paid significant attention to issues of new product/service development. However, few studies have been carried outtodiscuss innovative product/service development mindful of the c...Company experts and academicianshave paid significant attention to issues of new product/service development. However, few studies have been carried outtodiscuss innovative product/service development mindful of the competitive positions between competitors. This study introduces a hybrid method of positioning analysis, conjoint analysis and rough set theory to understand the competition positions and facilitate innovative product/service development from the customers’ perspective. The hybrid method is also supported by in-depth interviewing, factor analysis, preference regression, ideas simulation, ideas selection, and specific weight valuation methods. We choose the automobile maintenance industry in Taiwan, whose objective is to improve product/service qualities and enhance customers’ satisfaction and loyalty.This is also the subject of our empirical study. The results show that the proposed hybrid method is effective for innovative product/service development. Moreover, the empirical findings provide useful information for automobile maintenance providers so that they may be better able to pay attention to their competitive positions and their customers’ preferences, and better able to facilitate their innovative automobile maintenance service development, in order to achieve sustainable competitive advantages.展开更多
文摘This paper proposes a clustering technique that minimizes the need for subjective human intervention and is based on elements of rough set theory （RST）. The proposed algorithm is unified in its approach to clustering and makes use of both local and global data properties to obtain clustering solutions. It handles single-type and mixed attribute data sets with ease. The results from three data sets of single and mixed attribute types are used to illustrate the technique and establish its efficiency.
文摘Company experts and academicianshave paid significant attention to issues of new product/service development. However, few studies have been carried outtodiscuss innovative product/service development mindful of the competitive positions between competitors. This study introduces a hybrid method of positioning analysis, conjoint analysis and rough set theory to understand the competition positions and facilitate innovative product/service development from the customers’ perspective. The hybrid method is also supported by in-depth interviewing, factor analysis, preference regression, ideas simulation, ideas selection, and specific weight valuation methods. We choose the automobile maintenance industry in Taiwan, whose objective is to improve product/service qualities and enhance customers’ satisfaction and loyalty.This is also the subject of our empirical study. The results show that the proposed hybrid method is effective for innovative product/service development. Moreover, the empirical findings provide useful information for automobile maintenance providers so that they may be better able to pay attention to their competitive positions and their customers’ preferences, and better able to facilitate their innovative automobile maintenance service development, in order to achieve sustainable competitive advantages.
