Perceived risk of using online transportation during the COVID-19 pandemic: A MIMIC-model approach

Arlianto Arlianto, Lavenda Geshica
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Abstract

This study aims to assess the construct validity of the perceived risk scale on online transpor-tation users during the COVID-19 outbreak at once to test whether this scale can produce information that is not influenced by individual characteristics using Multiple Indicators and Multiple Cause (MIMIC) models. The 251 participants from different regions in Indonesia, such as East Java, Central Java, West Java, and outside Java participated in this study. The confirmatory factor analysis (CFA) approach was used as the main method in data analysis. The result showed that this six-aspect contextualized version of the scale was fit. The MIMIC model showed that this scale was not influenced by covariate variables, such as age, domicile, sex, marital status, length of time using online transportation, types of online transportation services, and occupation (except private employees). For further research, the exploratory study of risk perception and analysis of the roles of socioeconomic factors are suggested to do.
COVID-19大流行期间使用在线交通的感知风险:一种mimic模型方法
本研究旨在利用多指标多原因(Multiple Indicators and Multiple Cause, MIMIC)模型,评估新冠肺炎疫情期间在线交通用户感知风险量表的构建效度,检验该量表是否能产生不受个体特征影响的信息。来自印度尼西亚不同地区的251名参与者,如东爪哇、中爪哇、西爪哇和爪哇以外的人参加了这项研究。数据分析主要采用验证性因子分析(CFA)方法。结果表明,该量表的六方面情境化版本是合适的。MIMIC模型显示,该量表不受协变量的影响,如年龄、住所、性别、婚姻状况、使用在线交通工具的时间长短、在线交通服务类型和职业(私营雇员除外)。建议进一步开展风险感知的探索性研究和社会经济因素的作用分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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