本文以解構式計畫行爲理論做爲概念架構,在資料具備受限特質之前提下,以受限分量迴歸法來進行正負向風險認知對不同飲酒程度消費者之酒精消費量決策分析。根據分析結果顯示,結合貝氏風險學習架構的解構式計劃行爲理論解釋因子對酒精消費量確實有顯著的決策解釋效果,其中,又以行爲態度面向中的正負向風險認知變數影響效果最爲顯著。又對於輕度酒精消費區間之消費者,其所擁有的正向與負向風險認知的酒精消費彈性,皆顯著大於中度與重度酒精消費區間之消費者。故相關決策單位欲以資訊教育的方式來勸導民眾避免過度酒精消費帶來的健康傷害時,對於輕度酒精消費量區間的消費者而言,會有最大的效果。反之,對於屬於中度偏向重度、以及重度飲酒區間的消費者來說,資訊管道對酒精消費量的影響力遠不及其在輕度飲酒區間裡的表現,其酒精消費決策更可能是受到酒癮影響之結果。
This paper uses the conceptual framework of decomposed theory of planned behavior to analyze a set of censored data. The censored quantile regression is conducted for the diverse risk perceptions of alcohol consumption decision, i.e. a positive risk perception and a negative risk perception. The results show that all explanatory variables do have impacts on the decision of alcohol consumption under the framework of Bayesian learning and decomposed theory of planned behavior. Among these, the risk perception variables with either positive risk or negative risk perception have the most significant impacts. The alcohol consumption elasticities of risk perception for either positive or negative risk perception under the light alcohol consumption are all higher than those under the median and heavy levels of alcohol consumption. As such, group with light alcohol consumption is more effective than other two groups if the related agents intend to educate general public about the impact of alcohol consumption on the health through information delivery. Groups with median and heavy alcohol consumption are mostly affected by the addiction to the consumption of alcohol.
為了持續優化網站功能與使用者體驗,本網站將Cookies分析技術用於網站營運、分析和個人化服務之目的。
若您繼續瀏覽本網站,即表示您同意本網站使用Cookies。