- -

Analysis of factors influencing attitude and intention to use electric vehicles for a sustainable future

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Analysis of factors influencing attitude and intention to use electric vehicles for a sustainable future

Mostrar el registro sencillo del ítem

Ficheros en el ítem

Thumbnail
Nombre: GarciaSarmiento-G ...
Tamaño: 748.8Kb
Formato: PDF
Descripción: Versión del Autor.
Abrir
[Cerrado]
Nombre: JTT_Research_electric ...
Tamaño: 546.6Kb
Formato: PDF
Descripción: Versión editorial
Solicitar una copia al autor
dc.contributor.author García de Blanes Sebastián, María es_ES
dc.contributor.author Sarmiento-Guede, José Ramón es_ES
dc.contributor.author Azuara-Grande, Alberto es_ES
dc.contributor.author Juárez Varón, David es_ES
dc.date.accessioned 2023-12-18T19:05:46Z
dc.date.available 2023-12-18T19:05:46Z
dc.date.issued 2023-11-06 es_ES
dc.identifier.issn 0892-9912 es_ES
dc.identifier.uri http://hdl.handle.net/10251/200866
dc.description.abstract [EN] Spain is one of the countries that lead the contribution to the growing levels of consumption and environmental impacts. Specifically, it is the fifth most polluting country in the European Union. Given this situation, urban mobility represents one of the main challenges for sustainable development and the electric vehicle one of the most beneficial means of transport. The objective of this research article is to identify the core factors that influence the users of electric vehicles. For instance, a theoretical model based on the Meta-UTAUT Theory has been proposed, which uses the following variables: performance expectancy, effort expectancy, social influence, facilitating conditions, perceived risk, environmental concerns and how these variables influence the use behaviour and attitude towards electric vehicles. Data collection was carried out through a self-administered survey in which 326 responses were obtained. Data have been analysed using Structural Equation Modelling (SEM). The results show that the factors performance expectancy, social influence, and environmental concerns have a significant impact on the adoption of electric vehicles. However, it has been detected that the factors effort expectancy, facilitating conditions, and perceived risk are not significant. These results expand the available theoretical knowledge of the Meta-UTAUT and, from a practical perspective, provide public institutions and automotive companies with relevant information to improve their performance. Finally, this paper facilitates possible new technological developments in the field of transport planning and the use of electric vehicles. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof The Journal of Technology Transfer es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject.classification INGENIERIA DE LOS PROCESOS DE FABRICACION es_ES
dc.title Analysis of factors influencing attitude and intention to use electric vehicles for a sustainable future es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10961-023-10046-6 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Politécnica Superior de Alcoy - Escola Politècnica Superior d'Alcoi es_ES
dc.description.bibliographicCitation García De Blanes Sebastián, M.; Sarmiento-Guede, JR.; Azuara-Grande, A.; Juárez Varón, D. (2023). Analysis of factors influencing attitude and intention to use electric vehicles for a sustainable future. The Journal of Technology Transfer. 1-22. https://doi.org/10.1007/s10961-023-10046-6 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s10961-023-10046-6 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 22 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela S\502623 es_ES
dc.description.references Abbasi, H., Johl, S., Shaari, Z., Moughal, W., Mazhar, M., Musarat, M., Rafiq, W., Farooqi, A., & Borovkov, A. (2021). Consumer motivation by using Unified Theory of Acceptance and Use of Technology towards Electric vehicles. Sustainability, 13(21), 12177. https://doi.org/10.3390/su132112177. es_ES
dc.description.references Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T. es_ES
dc.description.references Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314–324. https://doi.org/10.1002/hbe2.195. es_ES
dc.description.references Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and Predicting Social Behavior. Prentice Hall. es_ES
dc.description.references Al-Majali, M. M. (2020). Influence of perceived risk dimensions on consumers’ attitudes towards buying electric vehicles (EVs) in Jordan. Jordan Journal of Business Administration, 16, 445–472. https://journals.ju.edu.jo/JJBA/article/download/101445/11346. es_ES
dc.description.references Amofah, D. O., & Chai, J. (2022). Sustaining consumer E-Commerce adoption in Sub-saharan Africa: Do Trust and Payment Method Matter? Sustainability (Switzerland), 14(14), 1–20. https://doi.org/10.3390/su14148466. es_ES
dc.description.references Anderson, J. E., Lehne, M., & Hardinghaus, M. (2018). What electric vehicle users want: Real-world preferences for public charging infrastructure. International Journal of Sustainable Transportation, 12(5), 341–352. https://doi.org/10.1080/15568318.2017.1372538. es_ES
dc.description.references Aranyossy, M. (2022). Technology Adoption in the Digital Entertainment Industry during the COVID-19 pandemic: An extended UTAUT2 model for Online Theater Streaming. Informatics, 9(3), https://doi.org/10.3390/informatics9030071. es_ES
dc.description.references Assaker, G., Hallak, R., & El-Haddad, R. (2020). Consumer usage of online travel reviews: Expanding the unified theory of acceptance and use of technology 2 model. Journal of Vacation Marketing, 26(2), 149–165. https://doi.org/10.1177/1356766719867386. es_ES
dc.description.references Bagade, P., Banerjee, A., & Gupta, S. K. S. (2017). Validation, Verification, and Formal Methods for Cyber-Physical Systems. In Cyber-Physical Systems (pp. 175–191). Elsevier. https://doi.org/10.1016/B978-0-12-803801-7.00012-2. es_ES
dc.description.references Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94. https://doi.org/10.1007/BF02723327. es_ES
dc.description.references Balakrishnan, J., Abed, S. S., & Jones, P. (2022). The role of meta-UTAUT factors, perceived anthropomorphism, perceived intelligence, and social self-efficacy in chatbot-based services? Technological Forecasting and Social Change, 180, 121692. https://doi.org/10.1016/j.techfore.2022.121692. es_ES
dc.description.references Bandura, A. (1986). Social foundations of Thought and Action: A cognitive Social Theory. Prentice Hall. es_ES
dc.description.references Bhat, F. A., Verma, M., & Verma, A. (2022). Measuring and Modelling Electric Vehicle Adoption of Indian Consumers. Transportation in Developing Economies, 8(1), 6. https://doi.org/10.1007/s40890-021-00143-2. es_ES
dc.description.references Biresselioglu, M. E., Kaplan, D., M., & Yilmaz, B. K. (2018). Electric mobility in Europe: A comprehensive review of motivators and barriers in decision making processes. Transportation Research Part A: Policy and Practice, 109, 1–13. https://doi.org/10.1016/j.tra.2018.01.017. es_ES
dc.description.references Bollen, K. A., & Liang, J. (1988). Some properties of Hoelter’s CN. Sociological Methods & Research, 16(4), 492–503. https://doi.org/10.1177/0049124188016004003. es_ES
dc.description.references Buranelli de Oliveira, M., Ribeiro da Silva, M., Jugend, H., De Camargo Fiorini, D., P., & Paro, C. E. (2022). Factors influencing the intention to use electric cars in Brazil. Transportation Research Part A: Policy and Practice, 155, 418–433. https://doi.org/10.1016/j.tra.2021.11.018. es_ES
dc.description.references Chen, C., Xu, X., & Frey, S. (2016). Who wants solar water heaters and alternative fuel vehicles? Assessing social–psychological predictors of adoption intention and policy support in China. Energy Research & Social Science, 15, 1–11. https://doi.org/10.1016/j.erss.2016.02.006. es_ES
dc.description.references Cooper, D. R., & Schindler, P. S. (2014). Business Research methods (12th ed.). McGraw Hill International Edition. es_ES
dc.description.references Cunningham, J. A., Damij, N., Modic, D., & Olan, F. (2023). MSME technology adoption, entrepreneurial mindset and value creation: A configurational approach. The Journal of Technology Transfer, 48(5), 1574–1598. https://doi.org/10.1007/s10961-023-10022-0. es_ES
dc.description.references Curtale, R., Liao, F., & van der Waerden, P. (2021). User acceptance of electric car-sharing services: The case of the Netherlands. Transportation Research Part A: Policy and Practice, 149, 266–282. https://doi.org/10.1016/j.tra.2021.05.006. es_ES
dc.description.references Davis, F. D. (1989). Perceived usefulness, perceived ease of Use, and user Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008. es_ES
dc.description.references Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to Use computers in the Workplace1. Journal of Applied Social Psychology, 22(14), 1111–1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x. es_ES
dc.description.references Degirmenci, K., & Breitner, M. H. (2017). Consumer purchase intentions for electric vehicles: Is green more important than price and range? Transportation Research Part D: Transport and Environment, 51, 250–260. https://doi.org/10.1016/j.trd.2017.01.001. es_ES
dc.description.references Di Foggia, G. (2021). Drivers and challenges of electric vehicles integration in corporate fleet: An empirical survey. Research in Transportation Business & Management, 2021, 100627. es_ES
dc.description.references Dowling, G. R. (1986). Perceived risk: The concept and its measurement. Psychology and Marketing, 3(3), 193–210. https://doi.org/10.1002/mar.4220030307. es_ES
dc.description.references Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 21(3), 719–734. https://doi.org/10.1007/s10796-017-9774-y. es_ES
dc.description.references Egbue, O., & Long, S. (2012). Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions. Energy Policy, 48, 717–729. https://doi.org/10.1016/j.enpol.2012.06.009. es_ES
dc.description.references European Enviroment Agency (2023). Europe’s air quality status 2023. Europe’s Air Quality Status 2023. https://www.eea.europa.eu/publications/europes-air-quality-status-2023. es_ES
dc.description.references Faiz, A., Weaver, C. S., & Walsh, M. P. (1996). Air pollution from motor vehicles: standards and technologies for controlling emissions. es_ES
dc.description.references Falchetta, G., & Noussan, M. (2021). Electric vehicle charging network in Europe: An accessibility and deployment trends analysis. Transportation Research Part D: Transport and Environment, 94, 102813. https://doi.org/10.1016/j.trd.2021.102813. es_ES
dc.description.references García de Blanes Sebastián, M., Guede, S., J. R., & Antonovica, A. (2022). Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.993935. es_ES
dc.description.references García de Blanes Sebastián, M., Antonovica, A., & Sarmiento Guede, J. R. (2023). What are the leading factors for using Spanish peer-to-peer mobile payment platform Bizum? The applied analysis of the UTAUT2 model. Technological Forecasting and Social Change, 187(November 2022), 122235. https://doi.org/10.1016/j.techfore.2022.122235. es_ES
dc.description.references Grant Thornton (2023). Mano a mano en la movilidad del futuro. es_ES
dc.description.references Gunawan, I., Redi, A. A. N. P., Santosa, A. A., Maghfiroh, M. F. N., Pandyaswargo, A. H., & Kurniawan, A. C. (2022). Determinants of Customer Intentions to Use Electric Vehicle in Indonesia: An Integrated Model Analysis. Sustainability, 14(4), 1972. https://doi.org/10.3390/su14041972. es_ES
dc.description.references Hair, J. F., Tathom, R. L., Anderson, R. E., & Black, W. C. (1998). Multivariate Data Analysis with readings. Prentice Hall. es_ES
dc.description.references Hair, J., Black, W., Babin, B., & Anderson, R. (2010). Multivariate Data Analysis (7th ed.). Pearson Prentice Hall. es_ES
dc.description.references Hair, J., Sarstedt, M., Hopkins, L., & Kuppelwieser, G., V (2014). Partial least squares structural equation modeling (PLS-SEM). European Business Review, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128. es_ES
dc.description.references Hall, D., & Lutsey, N. (2020). Charging infrastructure in cities: Metrics for evaluating future needs. es_ES
dc.description.references He, X., Zhan, W., & Hu, Y. (2018). Consumer purchase intention of electric vehicles in China: The roles of perception and personality. Journal of Cleaner Production, 204, 1060–1069. https://doi.org/10.1016/j.jclepro.2018.08.260. es_ES
dc.description.references Heinzl, A., Buxmann, P., Wendt, O., & Weitzel, T. (Eds.). (2011). Theory-guided modeling and Empiricism in Information Systems Research. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2781-1. es_ES
dc.description.references Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8. es_ES
dc.description.references Higueras-Castillo, E., Guillén, A., Herrera, L. J., & Liébana-Cabanillas, F. (2021). Adoption of electric vehicles: Which factors are really important? International Journal of Sustainable Transportation, 15(10), 799–813. https://doi.org/10.1080/15568318.2020.1818330. es_ES
dc.description.references Hoelter, J. W. (1983). The analysis of Covariance structures. Sociological Methods & Research, 11(3), 325–344. https://doi.org/10.1177/0049124183011003003. es_ES
dc.description.references Jain, N. K., Bhaskar, K., & Jain, S. (2022). What drives adoption intention of electric vehicles in India? An integrated UTAUT model with environmental concerns, perceived risk and government support. Research in Transportation Business & Management, 42, 100730. https://doi.org/10.1016/j.rtbm.2021.100730. es_ES
dc.description.references Jensen, A. F., Cherchi, E., & Mabit, S. L. (2013). On the stability of preferences and attitudes before and after experiencing an electric vehicle. Transportation Research Part D: Transport and Environment, 25, 24–32. https://doi.org/10.1016/j.trd.2013.07.006. es_ES
dc.description.references Jinliang, W., Chau, K. Y., Baei, F., Moslehpour, M., Nguyen, K. L., & Nguyen, T. T. H. (2023). Integrated perspective of eco-innovation, green branding, and sustainable product: A case of an emerging economy. Economic Research-Ekonomska Istraživanja, 36(3), https://doi.org/10.1080/1331677X.2023.2196690. es_ES
dc.description.references Junquera, B., Moreno, B., & Álvarez, R. (2016). Analyzing consumer attitudes towards electric vehicle purchasing intentions in Spain: Technological limitations and vehicle confidence. Technological Forecasting and Social Change, 109, 6–14. https://doi.org/10.1016/j.techfore.2016.05.006. es_ES
dc.description.references Kamboj, S., & Joshi, R. (2021). Examining the factors influencing smartphone apps use at tourism destinations: A UTAUT model perspective. International Journal of Tourism Cities, 7(1), 135–157. https://doi.org/10.1108/IJTC-05-2020-0094. es_ES
dc.description.references Kandemir, M. A., Franklin, T., Perkmen, S., & Yıldız, Y. (2022). Developing a Mobile Learning Acceptance Scale for Mathematics. Canadian Journal of Science Mathematics and Technology Education, 22(2), 392–404. https://doi.org/10.1007/s42330-022-00216-3. es_ES
dc.description.references Kapser, S., & Abdelrahman, M. (2020). Acceptance of autonomous delivery vehicles for last-mile delivery in Germany – extending UTAUT2 with risk perceptions. Transportation Research Part C: Emerging Technologies, 111, 210–225. https://doi.org/10.1016/j.trc.2019.12.016. es_ES
dc.description.references Lashari, Z. A., Ko, J., & Jang, J. (2021). Consumers’ intention to Purchase Electric vehicles: Influences of user attitude and perception. Sustainability, 13(12), 6778. https://doi.org/10.3390/su13126778. es_ES
dc.description.references Liu, R., Ding, Z., Wang, Y., Jiang, X., Jiang, X., Sun, W., Wang, D., Mou, Y., & Liu, M. (2021). The relationship between symbolic meanings and adoption intention of electric vehicles in China: The moderating effects of consumer self-identity and face consciousness. Journal of Cleaner Production, 288, 125116. https://doi.org/10.1016/j.jclepro.2020.125116. es_ES
dc.description.references Lohana, S., Imran, M., Harouache, A., Sadia, A., & Ur Rehman, Z. (2023). Impact of environment, culture, and sports tourism on the economy: A mediation-moderation model. Economic Research-Ekonomska Istraživanja, 36(3), https://doi.org/10.1080/1331677X.2023.2222306. es_ES
dc.description.references Madigan, R., Louw, T., Dziennus, M., Graindorge, T., Ortega, E., Graindorge, M., & Merat, N. (2016). Acceptance of Automated Road Transport systems (ARTS): An adaptation of the UTAUT Model. Transportation Research Procedia, 14, 2217–2226. https://doi.org/10.1016/j.trpro.2016.05.237. es_ES
dc.description.references Mahdiraji, H. A., Yaftiyan, F., Abbasi-Kamardi, A., Jafari-Sadeghi, V., Sahut, J. M., & Dana, L. P. (2023). A synthesis of boundary conditions with adopting digital platforms in SMEs: An intuitionistic multi-layer decision-making framework. The Journal of Technology Transfer, 48(5), 1723–1751. https://doi.org/10.1007/s10961-023-10028-8. es_ES
dc.description.references Manutworakit, P., & Choocharukul, K. (2022). Factors Influencing Battery Electric Vehicle Adoption in Thailand—Expanding the Unified Theory of Acceptance and Use of Technology’s variables. Sustainability, 14(14), 8482. https://doi.org/10.3390/su14148482. es_ES
dc.description.references Pagiaslis, A., & Krontalis, A. K. (2014). Green Consumption Behavior antecedents: Environmental concern, knowledge, and beliefs. Psychology & Marketing, 31(5), 335–348. https://doi.org/10.1002/mar.20698. es_ES
dc.description.references Palau-Saumell, R., Forgas-Coll, S., Sánchez-García, J., & Robres, E. (2019). User Acceptance of Mobile apps for restaurants: An expanded and extended UTAUT-2. Sustainability, 11(4), 1210. https://doi.org/10.3390/su11041210. es_ES
dc.description.references Palos-Sanchez, P., Saura, J. R., & Correia, M. B. (2021). Do tourism applications’ quality and user experience influence its acceptance by tourists? Review of Managerial Science, 15(5), 1205–1241. https://doi.org/10.1007/s11846-020-00396-y. es_ES
dc.description.references Patil, P., Tamilmani, K., Rana, N. P., & Raghavan, V. (2020). Understanding consumer adoption of mobile payment in India: Extending Meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal. International Journal of Information Management, 54, 102144. https://doi.org/10.1016/j.ijinfomgt.2020.102144. es_ES
dc.description.references Rogers, E. M. (1962). Bibliography on the diffusion of innovations. Department of Agricultural Economics and Rural Sociology. es_ES
dc.description.references Salari, N. (2022). Electric vehicles adoption behaviour: Synthesising the technology readiness index with Environmentalism values and instrumental attributes. Transportation Research Part A: Policy and Practice, 164, 60–81. https://doi.org/10.1016/j.tra.2022.07.009. es_ES
dc.description.references Sanaye, A., & Bahmani, E. (2012). Integrating TAM and TPB with perceived risk to measure customers’ Acceptance of Internet Banking. International Journal of Information Science and Management, 25–37. https://api.core.ac.uk/oai/oai:ojs.localhost:article/153. es_ES
dc.description.references Saura, J. R., Ribeiro-Soriano, D., & Palacios-Marqués, D. (2021). Setting B2B digital marketing in artificial intelligence-based CRMs: A review and directions for future research. Industrial Marketing Management, 98, 161–178. https://doi.org/10.1016/j.indmarman.2021.08.006. es_ES
dc.description.references Saura, J. R., Ribeiro-Soriano, D., & Palacios-Marqués, D. (2022). Assessing behavioral data science privacy issues in government artificial intelligence deployment. Government Information Quarterly, 39(4), 101679. https://doi.org/10.1016/j.giq.2022.101679. es_ES
dc.description.references Saura, J. R., Palacios-Marqués, D., & Ribeiro-Soriano, D. (2023a). Exploring the boundaries of open innovation: Evidence from social media mining. Technovation, 119, 102447. https://doi.org/10.1016/j.technovation.2021.102447. es_ES
dc.description.references Saura, J. R., Palacios-Marqués, D., & Ribeiro-Soriano, D. (2023b). Leveraging SMEs technologies adoption in the Covid-19 pandemic: A case study on Twitter-based user-generated content. The Journal of Technology Transfer, 48(5), 1696–1722. https://doi.org/10.1007/s10961-023-10023-z. es_ES
dc.description.references Saura, J. R., Ribeiro-Navarrete, S., Palacios-Marqués, D., & Mardani, A. (2023c). Impact of extreme weather in production economics: Extracting evidence from user-generated content. International Journal of Production Economics, 260, 108861. https://doi.org/10.1016/j.ijpe.2023.108861. es_ES
dc.description.references Schuitema, G., Anable, J., Skippon, S., & Kinnear, N. (2013). The role of instrumental, hedonic and symbolic attributes in the intention to adopt electric vehicles. Transportation Research Part A: Policy and Practice, 48, 39–49. https://doi.org/10.1016/j.tra.2012.10.004. es_ES
dc.description.references Sedigh, S., & Hurson, A. (2012). Introduction and Preface. In A. Hurson & A. Memon (Eds.), Advances in Computers, Volume 87 (pp. 1–6). Elsevier. https://doi.org/10.1016/B978-0-12-396528-8.00001-8. es_ES
dc.description.references Shukla, P. R., Dhar, S., Pathak, M., & Bhaskar, K. (2014). Promoting Low Carbon Transport in India: Electric vehicles scenarios and a roadmap for India. es_ES
dc.description.references Sinnappan, P., & Rahman, A. A. (2011). Antecedents of Green Purchasing Behavior among Malaysian consumers. International Business Management, 5(3), 129–139. https://doi.org/10.3923/ibm.2011.129.139. es_ES
dc.description.references Sovacool, B. K., Abrahamse, W., Zhang, L., & Ren, J. (2019). Pleasure or profit? Surveying the purchasing intentions of potential electric vehicle adopters in China. Transportation Research Part A: Policy and Practice, 124, 69–81. https://doi.org/10.1016/j.tra.2019.03.002. es_ES
dc.description.references Taylor, S., & Todd, P. (1995). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing, 12(2), 137–155. https://doi.org/10.1016/0167-8116(94)00019-K. es_ES
dc.description.references Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal Computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 125. https://doi.org/10.2307/249443. es_ES
dc.description.references Venkatesh, M., Davis, & Davis (2003). User Acceptance of Information Technology: Toward a unified view. MIS Quarterly, 27(3), 425. https://doi.org/10.2307/30036540. es_ES
dc.description.references Venkatesh, T., & Xu (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157. https://doi.org/10.2307/41410412. es_ES
dc.description.references Venkatesh, V., Thong, J., & Xu, X. (2016). Unified theory of Acceptance and Use of Technology: A synthesis and the Road ahead. Journal of the Association for Information Systems, 17(5), 328–376. https://doi.org/10.17705/1jais.00428. es_ES
dc.description.references Verma, M., Verma, A., & Khan, M. (2020). Factors influencing the Adoption of Electric Vehicles in Bengaluru. Transportation in Developing Economies, 6(2), 17. https://doi.org/10.1007/s40890-020-0100-x. es_ES
dc.description.references Wanasinghe, T. R., Galagedarage Don, M., Arunthavanathan, R., & Gosine, R. G. (2022). Industry 4.0 based process data analytics platform. In F. Khan, H. Pasman, & M. Yang (Eds.), Methods in Chemical Process Safety, Volume 6 (pp. 101–137). Elsevier. https://doi.org/10.1016/bs.mcps.2022.04.008. es_ES
dc.description.references Wang, S., Fan, J., Zhao, D., Yang, S., & Fu, Y. (2016). Predicting consumers’ intention to adopt hybrid electric vehicles: Using an extended version of the theory of planned behavior model. Transportation, 43(1), 123–143. https://doi.org/10.1007/s11116-014-9567-9. es_ES
dc.description.references Wang, S., Wang, J., Li, J., Wang, J., & Liang, L. (2018). Policy implications for promoting the adoption of electric vehicles: Do consumer’s knowledge, perceived risk and financial incentive policy matter? Transportation Research Part A: Policy and Practice, 117, 58–69. https://doi.org/10.1016/j.tra.2018.08.014. es_ES
dc.description.references Weldon, P., Morrissey, P., & O’Mahony, M. (2018). Long-term cost of ownership comparative analysis between electric vehicles and internal combustion engine vehicles. Sustainable Cities and Society, 39, 578–591. https://doi.org/10.1016/j.scs.2018.02.024. es_ES
dc.description.references Yakubu, M. N., Dasuki, S. I., Abubakar, A. M., & Kah, M. M. O. (2020). Determinants of learning management systems adoption in Nigeria: A hybrid SEM and artificial neural network approach. Education and Information Technologies, 25(5), 3515–3539. https://doi.org/10.1007/s10639-020-10110-w. es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem