The Study of Market Segmentation of Audience Attendance in Dance \performances:Life Style,Viewing Motivation,Information resources and Viewing Preference.

• Main Authors: YU-WEN TSAI, 蔡郁玟
• Other Authors: 莫季雍
• Format: Others
• Language: zh-TW
• Published: 2000
• Online Access: http://ndltd.ncl.edu.tw/handle/44109990066951979720

碩士 === 國立體育學院 === 體育研究所 === 88 === The purpose of this study was to investigate the market segmentation of audience attendance in dance performances: their life style, viewing motivation, and viewing preference. Subjects were audience attendance in ticketed dance performances and were asked to complete a questionnaire. The collected data were analyzed by factor analysis, cluster analysis, discriminating analysis, ANOVA, Chi-square test, and descriptive statistics. The main findings were as follows: 1. Audience attendance in dance performances could be classified as “art enthusiasm”, “fashion”, “art opinion”, “art instrumentality”, and “art participation” according to art-specific life style. 2. Audience attendance in dance performances could be classified as “acquire knowledge”, “beguile loneliness”, and “social and relax” according to viewing motivation. 3. Audience attendance in dance performances could be classified as 4 clusters including “art snob”, “passive participant”, “art lover”, and “sociality” according to 5 art-specific life styles. 4. (1)Demographic variables: There were significant differences in age, educational background, art interest, art learning experience among clusters. There was no significant gender difference. (2)Information resources: There were significant differences in “introduction from friends or the elders” and “posters in public places” among clusters. There was no significant difference in other information resources. (3)Viewing preferences: There were significant differences in “ballet”, “folk dance”, and “modern dance” among clusters. (4)Viewing motivation: There were significant differences in “acquire knowledge”, “beguile loneliness” and “social and relax” among clusters. 5. There were significant differences in viewing motivation among background variables as income, age, educational background, art interest, art learning experience among clusters. But there was no significant gender difference in viewing motivation. 6. There were significant correlation between life style of “art enthusiast”, “art instrumentality”, “art participation”, “fashion”, and “art opinion” and viewing motivation of “acquire knowledge”, “beguile loneliness” and “social and relax”.