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Understanding User Interaction Patterns within Online Systems for Public-Participation Transportation Planning

机译:了解在线系统中用于公众参与运输计划的用户交互模式

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摘要

Many research projects in public-participation geographic information systems focused on the development of software prototypes that were conceptualized to complement traditional forms of public participation. Given the challenges introduced by the heterogeneity of their user base, system design, and decision making process, empirical evaluations of such systems based on actual use have been scarce. This article reports on a rigorous empirical assessment of human-computer interaction of users of a web-based system for participatory transportation planning. We devised three groups of participants with belowaverage, average, and above-average interaction duration through hierarchical cluster analysis. Subsequently, the characteristics of the clusters were subjected to logistic regression analysis to determine the significance and strength of statistical associations between duration of interaction and a host of individual-level variables. Our results indicate a statistically significant reduction of the odds-ratio for participants with above-average duration of interaction in the case of no prior experience with online transportation discussions. No significant associations were found between overall duration of interaction and sociodemographic background, cognitive decision-making style, and travel behavior. We advocate for the development of adaptable participatory systems which accommodate flexibility in terms of both the user interface and pathways of the decision making process.
机译:公众参与的地理信息系统中的许多研究项目都专注于软件原型的开发,这些原型的概念化是对传统形式的公众参与的补充。鉴于用户群,系统设计和决策流程的异质性带来的挑战,基于实际使用情况的此类系统的实证评估已经很少。本文报告了对基于Web的参与性交通规划系统的用户的人机交互的严格经验评估。通过分层聚类分析,我们设计了三组参与者,其互动持续时间低于平均,平均和高于平均。随后,对聚类的特征进行逻辑回归分析,以确定相互作用持续时间与大量个体水平变量之间统计关联的重要性和强度。我们的结果表明,在没有任何在线交通讨论经验的情况下,互动持续时间高于平均水平的参与者的比值比在统计学上显着降低。在互动的总体持续时间与社会人口统计学背景,认知决策风格和旅行行为之间未发现显着关联。我们提倡开发适应性参与性系统,该系统在用户界面和决策过程的路径方面都具有灵活性。

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