| 苏畅,周垚,袁晓芳.基于GOMS模型的网上购物流程设计优化研究[J].包装工程,2021,42(6):113-119. |
| 基于GOMS模型的网上购物流程设计优化研究 |
| Design and Optimization of Online Shopping Process Based on GOMS Model |
| 投稿时间：2020-12-22 |
| DOI：10.19554/j.cnki.1001-3563.2021.06.016 |
| 中文关键词: 网络购物平台 GOMS任务分析 操作流程 |
| 英文关键词: online shopping platform GOMS task analysis operation process |
| 基金项目:陕西省科学技术厅青年项目(2020JQ760);中国人类工效学学会—津发科技优秀青年学者联合研究基金(CES-Kingfar-2019-002) |
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| 中文摘要: |
| 目的 随着电子商务的不断发展，各种网络购物平台应运而生。探究不同网络购物平台的操作流程对用户的影响从而提高购物平台的有用性。方法 通过GOMS任务分析方法对几类常见的购物网站操作流程进行建模，并对所得模型进行操作时间的预测与分析，采用编程软件对得到的几类购物网站的操作流程模型进行设计从而开展绩效实验与问卷访谈。结果 GOMS模型所预测的购物操作流程时间与实际的操作时间结果一致;购物操作流程中的点击行为用时少于指向行为;减少购物操作流程中的不必要选中可以有效地减少操作时间与错误率;当被试对购物操作流程熟悉时，每一个操作步骤的心理准备(M)时间可以去掉。结论 对不同网络购物平台操作流程的研究可以很好地提高购物平台系统的可用性，从而提升用户的满意度并增强用户的购物体验。 |
| 英文摘要: |
| With the continuous development of e-commerce, various online shopping platforms emerge as the times require. The work aims to explore the influence of different online shopping platform operation processes on users, so as to improve the usefulness of shopping platform. The operation processes of several common shopping websites were modeled by GOMS task analysis method, and the operation time of the models was forecasted and analyzed. Then, the operation process models of several shopping websites were designed by VB programming software, so as to carry out the performance experiment and questionnaire interview. The shopping operation process time predicted by GOMS model was consistent with the actual operation time. The click behavior in the shopping operation process tookless time than the pointing behavior. Reducing unnecessary selection in the shopping operation process couldeffectively reduce the operation time and error rate. When the subjects were familiar with the shopping operation process, the psychological preparation time Mof each operation step couldbe removed. The research on the operation processes of different online shopping platforms can improve the usability of shopping platform system, so as to improve user’s satisfaction and enhance user’s shopping experience. |
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