A Data Analytics Approach to Persona Development for The Future Mobile Office
A Data Analytics Approach to Persona Development for The Future Mobile Office
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DOI：
10.1177/1071181320641240
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发表时间：
2020-12
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影响因子：
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通讯作者：
A. Kamaraj;Atefeh Katrahmani;Mengyao Li;John D. Lee
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文献类型：
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作者：
A. Kamaraj;Atefeh Katrahmani;Mengyao Li;John D. Lee
使用自动驾驶汽车作为移动的交通工具的概念现在正在出现。因此，必须重新设计自动化车辆的车载环境，以支持执行工作相关任务时的用户交互。在设计阶段，交互设计师经常使用人物角色来了解目标用户群。人物角色是原型用户的代表，并根据用户调查和访谈数据构建。虽然是数据驱动的，但用户数据的大样本通常是定性评估的，可能会导致角色不能代表目标用户群。为了创建具有代表性的人物角色，本文展示了一种数据分析方法，使用职业信息网络（O*NET）的数据，为未来的移动的广告人物角色开发。O*NET由968个职业的数据组成，每个职业由277个特征定义。使用降维对数据进行了缩减，并使用聚类分析确定了7个人物角色。最后，使用逻辑回归确定每个人物角色的重要特征。
The concept of using automated vehicles as mobile workspaces is now emerging. Consequently, the in- vehicle environment of automated vehicles must be redesigned to support user interactions in performing work-related tasks. During the design phase, interaction designers often use personas to understand target user groups. Personas are representations of prototypical users and are constructed from user surveys and interview data. Although data-driven, large samples of user data are typically assessed qualitatively and may result in personas that are not representative of target user groups. To create representative personas, this paper demonstrates a data analytics approach to persona development for future mobile workspaces using data from the occupational information network (O*NET). O*NET consists of data on 968 occupations, each defined by 277 features. The data were reduced using dimensionality reduction and 7 personas were identified using cluster analysis. Finally, the important features of each persona were identified using logistic regression.