Summary: | 碩士 === 國立體育學院 === 體育研究所 === 86 === The population of Internet leads online marketing to rise. Before marketing on Internet, it is necessary to understand the users. This study investigated the users on the Homepages of this two Professional Baseball leagues in Taiwan - Chinese Professional Baseball League (CPBL), and Taiwan Major League (TML). The purpose is to understand the Demography, the Participators'' and Spectators'' Behaviors of the Baseball games, and the Involvement of the Professional Baseball games. Then, it discussed if there were different kind categories with the Involvement of the Professional Baseball games. After analyzing, the study offered some reference to segment markets.
This study distributed the questionnaires to the users on the homepage of CPBL with E-Mail, and to the users on the homepage of TML with World Wide Web (W W W). 292 questionnaires of CPBL were obtained, and 392 questionnaires of TML were obtained.
The results were as follows:
1.According to the Involvement of professional baseball games, this study categorized the users into four clusters with Clusters Analysis.
2.The clusters of CPBL were significantly different on Sex, Educational Level, and Income; the clusters of TML were significantly different on Sex, Educational Level, and Age.
3.In the aspect of Participators'' and Spectators'' Behavior of baseball games, the clusters of CPBL were significantly different on Participation, Participated Frequency, Categories of Games, and, Supported Teams; the clusters of TML were significantly different on Participation, Participated Frequency, Categories of Games, Watching Ways, Supported Teams, and Matches of Teams.
4.There were significantly difference between the Participators and Spectators Behaviors of baseball games between Demography:
(1)In Sex aspect, the part of CPBL were significantly different on Participation, Participated Frequency, Categories of Games, and Spectators'' Partners; the part of TML were significantly different on Participation, Participated Frequency, Categories of Games, Watching Ways, and Spectators'' Partners.
(2)In Educational Level aspect, the part of CPBL were significantly different on Participation, Participated Frequency, Supported Teams, and Watching Time; the part of TML were significantly different on Participation, Categories of Games, and Watching Ways.
(3)In Age aspect, the part of CPBL were significantly different on Participation, Participated Frequency, Categories of Games, and Spectators'' Partners; the part of TML were significantly different on Participation, Spectators'' Partners, Supported Teams, and Watching Time.
(4)In Jobs aspect, the part of CPBL were significantly different on Participation, Participated Frequency, Spectators'' Partners, and Matches of Teams; the part of TML were significantly different on Participation, Participated Frequency, Categories of Games, and Spectators'' Partners, Watching Ways, Supported Teams, and Matches of Teams.
(5)In Income aspect, the part of CPBL were significantly different on Participation, Participated Frequency, and Spectators'' Partners; the part of TML were significantly different on Participation, Participated Frequency, Watching Ways, Spectators'' Patrtners, and Supported Teams.
(6)In Fanily and Marriage aspect, the part of CPBL were significantly different on Participated Frequency, Spectators'' Partners, and Watching Times; the part of TML were significantly different on Participation, Spectators'' Partners, and Information Source.
(7)In Residence aspect, the part of CPBL were significantly different on Watching Times; the part of TML were signifcantly different on Watching Ways, Supported Teams, and Matches of Teams.
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