User acceptance of smart e-bikes: What are the influential factors? A cross-country comparison of five European countries

被引:2
|
作者
Kapousizis, Georgios [1 ]
Sarker, Rumana [2 ]
Ulak, M. Baran [1 ]
Geurs, Karst [1 ]
机构
[1] Univ Twente, Dept Civil Engn, Drienerlolaan 5, NL-7522 NB Enschede, Netherlands
[2] Monash Univ, Dept Civil Engn, Melbourne, Australia
关键词
Cycling safety; E-bikes; UTAUT2; User acceptance; SEM; Multigroup analysis; OF-FIT INDEXES; DISCRIMINANT VALIDITY; UNIFIED THEORY; TECHNOLOGY; SAFETY; QUESTIONNAIRE; INFORMATION; BICYCLES; VEHICLES; DRIVERS;
D O I
10.1016/j.tra.2024.104106
中图分类号
F [经济];
学科分类号
02 ;
摘要
Electric bicycles (e-bikes) have been promoted in many countries to replace motorised transport modes and mitigate transport externalities such as traffic congestion and emissions. However, there are also concerns about crash risks and crash severity for e-bike users. Leveraging new technologies could help improve e-bike safety, amongst other safety enhancing measures, but there is little knowledge of the users' acceptance of such technologies. This study aims to explore the user acceptance of e-bikes (pedelec with power assistance up to 25 km/h or speed-pedelec with assistance up to 45 km/h) with active road safety assistance (in short: Smart e-bikes) to improve cycling safety by adopting the extended unified theory of acceptance and use of technology 2 (UTAUT2). A cross-country survey was administered in five European countries-Austria, Belgium, Germany, Greece, and the Netherlands, each differing in population, cycling culture and e-bike market sizes. A sample of 1,589 respondents, including e-bike owners and people interested in buying an e-bike, was analysed using a structural equation model (SEM). Conclusions indicate that performance expectancy, hedonic motivation and perceived safety were the strongest constructs of behavioural intention to use Smart e-bikes in the aggregated sample. All constructs vary significantly across the five countries, which can partly be explained by sociodemographic factors. Geographical factors such as city size, low availability of cycle paths and population density do not explain differences in user acceptance.
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页数:17
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