Background: Last-mile delivery constitutes the most inefficient and costly part of logistics processes, thus increasing the importance of research in this area. Numerous alternative solutions and current technological advancements are being investigated to reduce the negative effects and make it more efficient and cost-effective. One of these alternatives is the use of electric vehicles for last-mile delivery. There is limited research on factors influencing user acceptance in the literature, and also a lack of studies on factors influencing driver acceptance. In this study, the authors aim to investigate the factors influencing drivers' acceptance of using electric vehicles for LMD of small and medium-sized parcels. Methods: This study examines the factors influencing drivers' acceptance of e-vehicles for last-mile delivery within the framework of the Technology Acceptance Model (TAM). In addition to the basic TAM variables, the current research adds the independent variables of environmental concern and enjoyment to the conceptual model. Results: Based on data from 180 participants in Turkiye, it was observed that environmental concern and perceived ease of use did not have an impact on perceived usefulness. Furthermore, the lack of influence of enjoyment on intentions is another important finding of the research. However, the other hypotheses were supported. Conclusions: Based on the present research It is understood that drivers need time to fully adopt electric vehicles. The increasing integration and automation efforts among relevant parties, as well as the adaptation of vehicles for large-scale shipments, will contribute to the increased use of electric vehicles. Besides, technical issues related to electric vehicle delivery, as well as traffic regulations, should be promptly planned, and real-life tests and pilot programs should be accelerated and expanded.
Purpose: This study evaluates the acceptance of GPS/GPRS-based telematics technology in freight road transport companies registered in Poland. Design/methodology/approach: The evaluation is based on a survey of 500 representative road transport companies carried out in 2020. The Technology Acceptance Model was estimated, and its results were checked for robustness. The scope of the information collected in telematics systems is defined in terms of its perceived utility and perceived ease of use at the operational management level. The latent factors affecting technology use are defined and implemented. Findings: Most respondents (80%) claimed that telematics systems had a considerable influence on the effectiveness and efficiency of the whole company's operation. It contributed to a higher number of orders executed per time unit, more effective use of the driver's working time, and increased the entrepreneurs' trust in the company. The companies employing more workers recognize the higher usefulness of telematics systems and are motivated to use the technology more widely than smaller enterprises. TAMs estimated separately for small and medium-sized enterprises did not significantly differ among the parameter estimates. Research limitations/implications: The Technology Acceptance Model is a useful analytical tool for evaluating telematics technology acceptance by the road transport sector. The study is based on a random sample of enterprises observed once in 2020. It is recommended to monitor them in two or three waves to compare the dynamics of the telematics usage process. It is planned to continue the study in that direction. Practical implications: The outcomes are valuable in practice twofold. Firstly, the extension of telematics systems use is interesting for final users, i.e., road transport companies that will find scope for their application. Secondly, the results are helpful for system providers who get knowledge on telematics perception from enterprise management. Originality/value: Although widely applied to other IT systems, the TAM model has not been used to evaluate the use of telematics in road transport companies. The paper justifies TAM's categories at the operational management level in road transport enterprises, contributing to understanding managers' behavioral aspects of decision-making.
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