週末籃球聯賽參賽者持續參與預測模型之研究
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2021
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本研究旨在探討週末籃球聯盟球賽參賽者持續參與球隊之預測,以問卷調查法詢問週末籃球聯盟球賽參賽者之參與動機、團隊氣氛與社會支持與持續參與該球隊之情形,共回收272份網路問卷。根據回收問卷分析參與動機、團隊氣氛、社會支持與持續參與之現況與差異,並以多元迴歸分析變量間之關係,最後以邏輯斯迴歸建構出預測是否持續參與該球隊之模型。研究結果發現在多元迴歸分析中,參與動機 (β = .178,p = .003)、團隊氣氛 (β = .317,p< .001)、社會支持 (β = .232,p <.001) 對持續參與之預測模型R2為.352,且和持續參與有正向關係且達顯著水準。在邏輯斯迴歸分析中,以性別等15項人口統計變量以及參與動機、團隊氣氛、社會支持等三個變量之層面,對是否持續參與球隊之預測模型R2為.467,其中是否缺乏時間 (Wald = 4.400,p = .036,Exp(B) = 1.09)、球隊是否有原本就認識的人 (Wald = 8.422,p = .004,Exp(B) = 34.847)、休閒需求 (Wald = 4.071,p = .044,Exp(B) = 1.69) 等三個變量達到顯著水準,可有效預測是否持續參與球隊。最後根據研究結論,提供實務上的建議,供週末籃球聯賽參賽者與主辦單位作為改善持續參與的參考。
The purpose of this study was to construct the predictive model for continuous participation of weekend basketball league players. By questionnaire survey method, we studied the current status and discrepancy of participation motivation, team climate, social support, and continuous participation through 272 players. Then we analyze the relation between the four variables through multiple regression analysis and construct the predictive model through logistic regression analysis. In multiple regression analysis, we found that the R2 of the model for prediction of continuous participation is .352. Furthermore, participation motivation (β = .178,p = .003), team climate (β = .317,p< .001), and social support (β = .232,p <.001) have positive relation with continuous participation at significant level. In logistic regression analysis, we adopted 15 demographic variables and the dimensions of participation motivation, team climate, and social support to predict whether players would continuously participate in the team or not. The R2 of the model is .467. Among the variables, lack of time (Wald = 4.400,p = .036,Exp(B) = 1.09), whether there is someone you know originally (Wald = 8.422,p = .004,Exp(B) = 34.847), and leisure demand (Wald = 4.071,p = .044,Exp(B) = 1.69) predict continuous participation at significant level. Finally, according to the conclusion, we provide practical advices for players and organizers to improve continuous participation in weekend basketball league teams.
The purpose of this study was to construct the predictive model for continuous participation of weekend basketball league players. By questionnaire survey method, we studied the current status and discrepancy of participation motivation, team climate, social support, and continuous participation through 272 players. Then we analyze the relation between the four variables through multiple regression analysis and construct the predictive model through logistic regression analysis. In multiple regression analysis, we found that the R2 of the model for prediction of continuous participation is .352. Furthermore, participation motivation (β = .178,p = .003), team climate (β = .317,p< .001), and social support (β = .232,p <.001) have positive relation with continuous participation at significant level. In logistic regression analysis, we adopted 15 demographic variables and the dimensions of participation motivation, team climate, and social support to predict whether players would continuously participate in the team or not. The R2 of the model is .467. Among the variables, lack of time (Wald = 4.400,p = .036,Exp(B) = 1.09), whether there is someone you know originally (Wald = 8.422,p = .004,Exp(B) = 34.847), and leisure demand (Wald = 4.071,p = .044,Exp(B) = 1.69) predict continuous participation at significant level. Finally, according to the conclusion, we provide practical advices for players and organizers to improve continuous participation in weekend basketball league teams.
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持續參與, 參與動機, 團隊氣氛, 社會支持, 邏輯斯迴歸, continuous participation, participation motivation, team climate, social support, logistic regression