基於交易記錄探討顧客信任及忠誠度對於健康產品銷售的影響;Investigating the impact of trust and loyalty in health industry with transaction log

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题名:	基於交易記錄探討顧客信任及忠誠度對於健康產品銷售的影響;Investigating the impact of trust and loyalty in health industry with transaction log
作者:	廖棋弘;Liao, Chi-Hung
贡献者:	企業管理學系
关键词:	信任;忠誠度;再購行為;trust;loyalty;repurchase behavior
日期:	2017-06-26
上传时间:	2017-10-27 13:11:57 (UTC+8)
出版者:	國立中央大學
摘要:	在注重健康的時代，保健食品市場需求有持續上向成長的趨勢，造就多元化的產品通路，讓消費者能在實體店面、電子商務、電視購物、電話行銷上皆能採購到日常所需的保健食品。近期全球市場調查報告也指出電子商務、電話行銷通路成長快速，在相關研究上信任被視為電子商務和電話行銷重要的影響因子之一。以往研究信任、忠誠度和再購意願主要採取問卷方式收集資料，而實際上各產業皆發現客戶填寫問卷的願意度不高，導致資料收集困難。而再購行為的衡量與相關模型的建立更是困難。近期有研究開始使用實際系統上的資料進行轉換，利用系統資料來衡量信任，但目前尚未用來驗證假設與衡量實際消費行為。本研究以保健食品產業在電話行銷通路上的交易活動為基礎，收集ERP 系統和客服系統上的資料，並建立操作型定義與資料轉換公式，以系統資料描述客戶信任、忠誠度和再購行為，利用多元迴歸和多元邏輯迴歸分析驗證已知的管理模型。經由模型的驗證推導操作型定義與資料轉換公式的正確性，並由此驗證信任與忠誠度可影響再購行為。;In the era of LOHAS, the demand for healthy food and supplement is growing rapidly.These products can be purchased through various channels such as brick and mortar stores,e-commerce, TV shopping, telemarketing. Among them, the e-commerce and telemarketing channels are the source of main growth. To promote usage of these channels, trust and loyalty are critical determinants. To verify research models, in the past, questionnaires have to be distributed to potential customers. However, in many cases, customers have low intention to participate in the surveys. Recently, due to the development of data driven analysis, researchers began using the data logged in systems to measure trust and apply the finding to recommend products. However, to the best of our knowledge, none have used system data to verify hypothesis and measure the actual consumer behavior. To verify if the data collected from systems can be used to confirm the relationships between trust, loyalty and purchasing behavior, the research collected data from an ERP system and customer service system and defined operational definitions for trust and loyalty and creates a formula for data transformation. The research uses multiple regression and multiple logistic regression to verify the model. The result showed that most of the relationships between trust, loyalty and purchasing behavior are supported. That is, data logged in systems can be used for not only data driven analysis but also for model validation.
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