- 學位論文
以系統品質、服務品質與資訊品質探討網路衝動性購買行為之研究
The influence of system quality,service quality,and information quality on online impulse buying.
摘要
隨著網路時代的來臨，傳統消費的方式受此影響，可在網際網路進行交易，無論是實體商店或是網路商店，最受矚目的議題皆在於環境因素，消費者會在購買決策的過程中受到環境因素的影響改變其行為模式，本研究著重於網路的衝動性購買行為。過去網路衝動性購買行為的探討，多是使用網頁少數因素來作探討，但個別因素的探討，只是網頁因素中的必要條件，卻非充分條件。本研究以S-O-R理論為基礎，將網頁品質的三項衡量：系統品質、服務品質和資訊品質，藉由情緒和購物享樂特質探討對衝動性購買行為的影響。 本研究採用問卷調查，以消費者近一年在最常使用的網路商店之消費經驗為主進行調查，並經由網路發放問卷，共計問卷527份；由於系統品質、服務品質和資訊品質對衝動性購買行為之文獻有限，本研究採用探索性研究，並以適合探索性研究的分析方法：PLS-SEM來進行分析，以期望能將預測最大化，增加內生變數的解釋力。 本研究結果如下： 1.服務品質與資訊品質對情緒和購物享樂特質的影響，比系統品質佳。 2.系統品質、服務品質和資訊品質對購物享樂特質解釋力不佳。 3.正面情緒和購物享樂特質越高，越能增加消費者的瀏覽行為。 4.正面情緒、購物享樂特質和瀏覽行為，皆對衝動購買欲望有正向影響。 5.衝動購買欲望對純粹式衝動性購買行為和計劃式購買行為皆有正向影響，解釋力皆高。
並列摘要
As the era of internet has come, the way of shopping has also influenced, allowing people to carry out transaction through internet. No matter whether they are brick and mortar shops or online shops, the most popular issue is about environment. Consumers usually change their ways during the process of making a decision because of the environment surrounding them. In this research, the content focuses on online impulse buying. In the past, the discussion about this involved individual factors of Web site. However, since those discussions of individual factors are only necessary but not sufficient conditions of Web site. The purpose of this research, based on S-O-R theory, is to take three aspects to measure website quality, including system quality, service quality and information quality. As these are all relating to consumers’ emotions and the shopping enjoyment, they can help us understand why they affect online impulse buying. This study use questionnaires which focus on consumption experience of consumer on the most commonly used online shop in nearly a year. A total of 527 questionnaires were collected. Since the limitation of reference about system quality, information quality, and service quality to impulse buying, this study use PLS-SEM which is suited for theory development to analyze. This study expect to max R square of the explained variance by PLS-SEM.