提出混合可用性模型，用用户数据预测电商应用评分
A Hybrid Usability Approach for Rating Evaluation of M-Commerce Applications
- 整合8个可用性维度构建混合评估模型
- 基于40用户/应用数据，实现评分预测准确率提升
- 适合移动应用开发者优化用户体验
移动端应用的成功依赖于其可用性，而评分是衡量可用性的重要指标。本研究聚焦于影响移动端电商应用评分的关键可用性因素，分析现有可用性模型中的不同因素与标准，并以5个知名应用（Daraz、ShopHive、Home Shopping、Symbios、Yayvo）为案例进行评估。在此基础上，提出一种混合可用性模型，包含可学习性、一致性、人因因素、沟通性、有效性、操作性、效率和满意度共8个维度，每个维度下设若干评价标准。针对该模型，从每款应用中收集40名用户的反馈数据，采用前向逐步多元线性回归方法建立评分预测模型。最后通过PRED(x)与K折交叉验证法对模型进行评估与验证。
原文摘要 · Abstract (English)
The success of any mobile application relies on its usefulness and rating is considered as an important measure in this regard. This research work focuses on identifying usability factors, which contribute significantly towards the rating of M-commerce apps. This work intends to explore existing usability models consisting of different factors along with a set of criteria and evaluate in terms of rating estimation by considering 5 well-known mobile applications, namely (i) daraz, (ii) shophive, (iii) home shopping, (iv) Symbios. (v) yayvo. Then, this work provides a hybrid usability model for rating prediction of M-commerce applications. The initial hybrid usability model comprises of (i) learnability, (ii) consistency, (iii) human factors,(iv)communicativeness,(v)effectiveness, (vi) Operability, (vii) efficiency, (viii) satisfaction. Each factor consists of some criteria. Keeping in view the factors of hybrid usability model, the data was collected from 40 users for each application. Furthermore, Forward Stepwise Multiple Linear Regression based rating prediction model is suggested by analyzing each criterion of all factors of hybrid usability model. Finally, the model is assessed and validated by using PRED(x) and K-fold techniques.
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