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Extension of the technology acceptance model in electronic commerce.

机译:扩展电子商务中的技术接受模型。

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摘要

Electronic-commerce has become an important channel for conducting business. Researchers as well as market executives are trying to better understand online consumer behavior. One model used by researchers to understand behavior in the information systems field in general is the technology acceptance model (TAM). The TAM variables are perceived usefulness, perceived ease of use, and intentions. In this study, the TAM was applied in the E-commerce field. The original TAM was extended, by adding four predictor variables. The four predictor variables were process satisfaction, outcome satisfaction, expectations, and E-commerce use. In addition, the TAM was extended by measuring actual behavior as opposed to measuring intentions as a substitute for actual behavior in previous TAM application studies. E-commerce actual use was measured in terms of four criterion variables. The four criterion variables were purchase, access number, access total time, and access average time. A free simulation was carried out for two months. Subjects were able to access the study music selling website and order CDs online. The study results show that the extended TAM explains E-commerce actual behavior better than the original TAM. In addition, out of the study predictor variables, outcome satisfaction had the highest relative predictive importance when explaining E-commerce use in terms of purchase. However, when explaining E-commerce use in terms of access number, access total time, and access average time, the predictor variable process satisfaction had the highest relative predictive importance.
机译:电子商务已成为开展业务的重要渠道。研究人员以及市场主管都在努力更好地了解在线消费者的行为。研究人员通常用来理解信息系统领域行为的一种模型是技术接受模型(TAM)。 TAM变量被视为有用性,易用性和意图。在这项研究中,TAM被应用于电子商务领域。通过添加四个预测变量来扩展原始TAM。四个预测变量是过程满意度,结果满意度,期望和电子商务使用。此外,通过测量实际行为来扩展TAM,而不是通过测量意图来替代以前的TAM应用研究中的实际行为。电子商务的实际使用是根据四个标准变量来衡量的。四个标准变量是购买,访问次数,访问总时间和访问平均时间。免费模拟进行了两个月。受试者能够访问研究音乐销售网站并在线订购CD。研究结果表明,扩展的TAM可以比原始TAM更好地解释电子商务的实际行为。另外,在研究预测变量中,当以购买方式解释电子商务使用时,结果满意度具有最高的相对预测重要性。但是,当根据访问次数,访问总时间和访问平均时间来解释电子商务的使用时,预测变量的过程满意度具有最高的相对预测重要性。

著录项

  • 作者

    Fayad, Rima.;

  • 作者单位

    Utah State University.;

  • 授予单位 Utah State University.;
  • 学科 Business Administration General.; Computer Science.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 156 p.
  • 总页数 156
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 贸易经济;自动化技术、计算机技术;
  • 关键词

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