職業運動賽會消費者購票行為預測模式之建構－－以美國NBA丹佛金塊隊為例

A study on the construction of a prediction model of consumer ticket purchase behavior in professional sport events: An example of the NBA Denver Nuggets

目的：本研究主要目的是以消費者之實際購票行為建構一個購票選擇行為之預測模式。方法：資料來源由美國國家籃球聯盟丹佛金塊籃球隊行銷部經理提供部份資料庫資料進行學術研究之用，共計570筆。本研究以隨機效用模式為理論基礎，以順序普羅比模式為統計分析模式，建構一個消費者選擇門票種類之預測模式。本研究以STATA10統計軟體進行統計資料分析。結果：模式之預測正確率約為70％。模式中達顯著水準之變數包括對戰球隊是否具吸引力（z＝6.74，p＜.05）、球賽是否在下半球季（z＝3.03，p＜.05）、球賽是否有促銷（z＝-9.20，p＜.05）與顧客價值（z＝4.93，p＜.05）。結論：本研究結果顯示職業球隊門票收入之提升與行銷策略之擬定可藉由分析顧客過去之購買行為而達成，即運動產業營運績效之提升可藉由資料庫行銷技術達成。本研究結果可供國內職業運動聯盟經營團隊參考，但更重要的是本研究之思維期盼能提供國內職業運動聯盟經營團隊與政府相關單位一個尚未受到重視及廣泛應用的行銷技術。Purpose: This study was to establish a prediction model to predict consumers' purchasing behavior of professional sports event ticket purchases through analysis of a customer database. Methods: The dataset in the current study was pulled from the enormous database of the Denver Nuggets in the NBA and was provided by the Nuggets marketing manager for research only. The dataset under study consisted of 570 subjects. More specifically, based on the random utility model along with the ordered probit model, this study was to construct a prediction model on consumer's purchase of tickets for the Denver Nuggets. STATA 10 was utilized to analyze data. Results: The ratio of correct prediction was approximately 70%. The significant variables in the prediction model included 'attractive opponent' (z= 6.74, p< .05), 'second-half season' (z= 3.03, p< .05), 'promotion' (z= -9.20, p< .05), and 'customer value' (z= 4.93, p< .05). Conclusions: Although the results in the current study could be used for their marketing operation, what counts more was the thinking of the present study that would provide the domestic professional sport leagues and related governmental institutions with different perspectives.