隨著大數據分析技術的進步,個人化推薦系統已廣被導入電商平台,做為個人化行銷利器,期以精準掌握及推薦消費者偏好的產品,縮短瀏覽時間及提高下單的意願。然而,消費者對於推薦系統所提供的資訊認知,可能導致對於產品的期待與實際收到貨品後的感受有顯著差距,進而產生失望及退貨意念。此,本研究主要針對服飾產品,為探討電商網站的個人化推薦系統呈現的平臺品質是否能影響消費者的購買意願和日後收到實際物品後的退貨意願。 經由過往的文獻基礎規畫,本研究建構一個消費者行為模式,包含以個人化推薦系統、沉浸、購買意願、購後滿意度與退貨意願的相關性研究架構。再以兩階段問卷蒐集台灣MOMO和蝦皮購物購物平臺購買服飾的使用者對個人化推薦系統品質及各構面的觀感。經由實證資料的分析結果發現: (1)個人化推薦系統對顧客增加了購買意願;(2)顧客購後是否滿意或是萌生退貨意願與個人化推薦系統無相關,電商仍須注重實際商品的良劣,如果只是注重個人推薦系統所帶來的銷售量,忽略購後顧客的真實滿意與否,將顧此彼;(3)女性與居住偏鄉區域的顧客退貨意願較高,須注意其相關的需求與提供其相對應的措施因應。
With the advancement of big data analysis technology, personalized recommendation systems have been widely introduced into e-commerce platform, hoping to be a marketing tool for personal and consumer-preferred products. However, the maybe be a worse way for consumers browsing the internet,causing information cognitive imblanace easily when they find practical product is defferent with screen. Therefore, this study mainly focuses on products of apparel items whether recommdation systems would influence customer’s purchase intention and then subsequent after purchase satisfaction and return intention. Based on past literature, this study constructs a consumer behavior model, including personalized recommendation systems, immersion, purchase intention, after purchase satisfaction and return intention.related to research architecture. Then, a two-stage questionnaire was used to collect Taiwan MOMO and Shopee shopping platform.According to the results, it is found that: (1) The personalized recommendation systems increases the purchase intention.(2) Whether customers are satisfied after purchasing or has no relationship with the personalized recommendation systems. E-commerce companies must still pay attention to the quality of the actual products.(3) Women and customers living in remote geographical areas are more willing to return goods, and they must pay attention to their related needs.