Acceptance of electric passenger cars in commercial fleets

Globisch, Joachim; Dütschke, Elisabeth; Schleich, Joachim

doi:10.1016/j.tra.2018.06.004

Cited by 43 publications

(27 citation statements)

References 17 publications

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“…Theory of Planned Behavior foresees that the more fortunate an individual assesses the certain behavior, more probably he will be anticipated to perform that behavior [32]. In transportation sector it has significant relationship with behavioral intention [41] and specifically for ETC acceptance [42]. As motorists get more positive felling from using IoT service on roads, the more inclined they are, and therefore, the more likely they are eager to adopt the services.…”

Section: A Theory Of Technology Acceptance Modelmentioning

confidence: 99%

Predicting IoT Service Adoption towards Smart Mobility in Malaysia: SEM-Neural Hybrid Pilot Study

Ahmed¹,

Hizam²,

Sentosa³

et al. 2020

IJACSA

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Smart city is synchronized with digital environment and its transportation system is vitalized with RFID sensors, Internet of Things (IoT) and Artificial Intelligence. However, without user's behavioral assessment of technology, the ultimate usefulness of smart mobility cannot be achieved. This paper aims to formulate the research framework for prediction of antecedents of smart mobility by using SEM-Neural hybrid approach towards preliminary data analysis. This research undertook smart mobility service adoption in Malaysia as study perspective and applied the Technology Acceptance Model (TAM) as theoretical basis. An extended TAM model was hypothesized with five external factors (digital dexterity, IoT service quality, intrusiveness concerns, social electronic word of mouth and subjective norm). The data was collected through a pilot survey in Klang Valley, Malaysia. Then responses were analyzed for reliability, validity and accuracy of model. Finally, the causal relationship was explained by Structural Equation Modeling (SEM) and Artificial Neural Networking (ANN). The paper will share better understanding of road technology acceptance to all stakeholders to refine, revise and update their policies. The proposed framework will suggest a broader approach to investigate individual-level technology acceptance.

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Section: A Theory Of Technology Acceptance Modelmentioning

confidence: 99%

Predicting IoT Service Adoption towards Smart Mobility in Malaysia: SEM-Neural Hybrid Pilot Study

Ahmed¹,

Hizam²,

Sentosa³

et al. 2020

IJACSA

View full text Add to dashboard Cite

show abstract

“…Acceptance can also be increased by advertising and marketing, which might include word-of-mouth recommendation [77]. Additionally, Globisch et al [78] stressed the importance of providing EV users with the necessary information, support and assistance to overcome technical failures, as a way to foster the EV deployment. They also found that focusing on the vehicle design (perceived enjoyment) of EVs can significantly influence the choice of the car purchased.…”

Section: Influence On Which Kind Of Vehicle To Purchasementioning

confidence: 99%

Banning Diesel Vehicles in London: Is 2040 Too Late?

et al. 2019

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Air pollution contributes to 9400 deaths annually in London and diesel vehicles are considered a major source of lethal air pollutants. Consequently, the UK government announced its intention to ban diesel vehicles by 2040 to achieve a sustainable zero-carbon road transport system. Since no empirical studies have used a bottom-up approach to seek Londoners' views, it is therefore worth investigating the public opinion regarding this forthcoming ban. This paper aims to fill this research gap by taking London as a case study. A survey was designed, and fieldwork was conducted to distribute questionnaires to Londoners. Completed questionnaires were analysed using both quantitative and qualitative methods. The findings revealed that the majority of Londoners would be in favour of the ban if they were sufficiently exposed to the appropriate sources of information and were favourably disposed towards environmental protection measures. The results also showed that Londoners were more likely to switch to electric vehicles (EVs) if they were offered generous incentives and encouraged to use scrappage schemes. The present study makes a strong case for enforcing the ban well before 2040. The significance of this research is to provide clearer signals regarding the future of diesel vehicles, which in turn will strengthen the EV policy and uptake.

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“…The technology acceptance model (TAM) (Davis et al, 1989) was initially conceived to understand the acceptance of information and communication technologies. It has since been applied to several other technologies or services, including eco-friendly transportation systems by private households (Chen & Lu, 2016) or the acceptance of electric vehicles (Globisch et al, 2018).…”

Section: Technology Acceptance Modelmentioning

confidence: 99%

What could make islanders use a new public transport system? Identifying the determinants of the intention to use a new Reserved Public Transport Lane in the urban area of Fort-de-France, Martinique What could make islanders use a new public transport system? Identifying the determinants of the intention to use a new Reserved Public Transport Lane in the urban area of Fort-de-France, Martinique

Fointiat¹,

Feliot-Rippeault²

2019

ISJ

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In 2015, Fort-de-France, the main city of Martinique, a small French West Indies island, made the ambitious decision to introduce a new mode of public transportation, a reserved public transport lane, or 'RPTL'. Based on the Technology Acceptance Model, we conducted a survey to identify the determinants of intention to use the new mode of transport by current public transport users on the island. These determinants seem to vary depending on the frequency of use of the current transport system. Hence, when people already used public transport every day (high frequency), their intention to use the RPTL is solely predicted by the perceived usefulness of the RPTL. For those who use it less often (moderate frequency), only the norm-i.e., what others do-and age were predictors of intention to use the RPTL. Finally, for rare public transport users (low frequency), their intention is predicted by perceived usefulness and social norms. These results show that all users have different reasons for using this new mode of transport. Identifying these determinants could be useful to local politicians, enabling them to make efficient information and promotion campaigns for the RPTL, and especially designed for those potential users who are not familiar with public transport.

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Acceptance of electric passenger cars in commercial fleets

Cited by 43 publications

References 17 publications

Predicting IoT Service Adoption towards Smart Mobility in Malaysia: SEM-Neural Hybrid Pilot Study

Predicting IoT Service Adoption towards Smart Mobility in Malaysia: SEM-Neural Hybrid Pilot Study

Banning Diesel Vehicles in London: Is 2040 Too Late?

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