| 摘要: | 現今的網路科技發達，也帶動了智慧型手機的蓬勃發展，已將近達到人手一機的普及，也因此改變了現代人的生活方式，科技的發展提昇了民眾生活方便性，也在政府全力推動的政策下，開啟了行動支付的新趨勢。本研究針對探討消費者使用行動支付時，會因[品牌形象]、[創新]、[滿意度]及人口統計變相等因素，進而改變使用意願。以近年行動支付的相關文獻探討及產業現況，試著以台灣目前行動支付市占率最高的 「LINE Pay」為例。本研究採用網路問卷方式且不記名、不以特定區域發放。問卷回收後並以統計軟體 SPSS22.0 作為統計分析工具，將回收樣本進行敘述性統計分析、信度分析、獨立樣本t檢定、單因子變異數分析及迴歸分析等方式，進行分析及統計。根據信度分析品牌形象、創新、滿意度及使用意願具有高度信度。獨立樣本T檢定，顯示無論男性或女性皆會因品牌形象、創新、滿意度影響其使用意願。單因子變異數分析中，年齡會因品牌形象、創新、滿意度影響其使用意願，教育程度及職業並無顯著差異。迴歸分析，品牌形象、創新、滿意度皆具正向支持會影響使用意願。綜合上述，除教育程度及職業，皆會因品牌形象、創新、滿意度影響其使用意願。
Today's network technology is developed, but also led to the vigorous development of smart phones, has reached the popularity of a machine per person, but also changed the way of life of modern people, the development of science and technology to improve the convenience of people's life, but also under the government's full promotion of the policy, opened a new trend of mobile payment. This study aims to explore how consumers will change their willingness to use mobile payment due to factors such as [brand image], [innovation], [satisfaction], and demographic disguise. Based on the literature discussion and industry status of mobile payment in recent years, try to take LINE Pay, which currently has the highest mobile payment market share in Taiwan, as an example. This study adopted an online questionnaire that was anonymous and not distributed in a specific area. After the questionnaires were collected, the statistical software SPSS22.0 was used as a statistical analysis tool to conduct analysis and statistics on the collected samples through narrative statistical analysis, reliability analysis, independent sample t-test, single-factor variance analysis and regression analysis. According to the reliability analysis, brand image, innovation, satisfaction, and usage intention are highly reliable. The independent sample T test shows that both men and women will have their intention to use the product due to brand image, innovation, and satisfaction. In single-factor variance analysis, age will affect usage intention due to brand image, innovation, and satisfaction, while education level and occupation have no significant differences. Regression analysis shows that brand image, innovation, and satisfaction all have positive support and will affect usage intention. Based on the above, in addition to education level and occupation, brand image, innovation, and satisfaction will affect their willingness to use. |
