THE EFFECTS OF PERCEIVED RISK ON THE USE INTENTION OF AUTONOMOUS VEHICLES.

Cristina Maria Alcântara de Brito Vieite; Alexandre Luzzi Las Casas; Belmiro do Nascimento João; Paulo Sergio Gonçalves de  Oliveira

doi:10.5585/remark.v22i4.23746

Autores

Cristina Maria Alcântara de Brito Vieite Pontifícia Universidade Católica - PUC-SP https://orcid.org/0000-0001-8385-7517
Alexandre Luzzi Las Casas Pontifícia Universidade Católica PUC-SP https://orcid.org/0000-0003-2098-0969
Belmiro do Nascimento João Pontifícia Universidade Católica de São Paulo – PUC/SP https://orcid.org/0000-0002-7994-9934
Paulo Sergio Gonçalves de Oliveira MP em Gestão de Alimentos e Bebidas – Anhembi-Morumbi https://orcid.org/0000-0001-9122-4904

DOI:

https://doi.org/10.5585/remark.v22i4.23746

Palavras-chave:

Risco percebido, Intenção de uso, Veículos autônomos, Risco psicológico, Novidade, Ansiedade

Resumo

Objetivos: Este estudo procurou verificar os efeitos do risco percebido na intenção de usar veículos autônomos (AV) e a possível influência da "novidade" e da "ansiedade".

Metodologia/abordagem: A amostra da pesquisa, composta por 340 estudantes de Administração de Empresas de uma universidade brasileira, foi desenvolvida como um quase-experimento, pois a amostra não foi escolhida de forma aleatória. A amostra foi dividida em dois grupos: um grupo experimental com acesso a um vídeo que explica os benefícios dos veículos autônomos e outro grupo sem nenhuma informação.

Resultados: Para o grupo experimental, a informação é um fator atenuante para o risco psicológico percebido, que é o que mais influencia a intenção de usar um veículo autônomo. Por outro lado, a novidade afeta a intenção do consumidor de usar o veículo autônomo, o mesmo questionário foi aplicado para ambos os grupos.

Contribuições teóricas/metodológicas: A principal contribuição deste estudo é uma abordagem inovadora do comportamento do consumidor, que propõe um modelo teórico para analisar a influência da "novidade" e do "risco psicológico" como a "ansiedade", na intenção de usar um AV.

Relevância/originalidade: uma proposta de modelo teórico para analisar a influência da "novidade" e do "risco psicológico" como a "ansiedade" na intenção de usar o AV.

Implicações para a gestão: ajudará os profissionais de marketing a direcionar suas mensagens incorporando o modelo teórico e, consequentemente, reduzindo a ansiedade do consumidor em relação ao uso de carros autônomos.

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Biografia do Autor

Cristina Maria Alcântara de Brito Vieite, Pontifícia Universidade Católica - PUC-SP

Departmento de Administração - área de marketing

Alexandre Luzzi Las Casas, Pontifícia Universidade Católica PUC-SP

Professor de marketing na FEA , deartamento de Administração , área de marketing

Belmiro do Nascimento João, Pontifícia Universidade Católica de São Paulo – PUC/SP

Dr. Comunicação e Semiótica – PUC/SP

Paulo Sergio Gonçalves de Oliveira, MP em Gestão de Alimentos e Bebidas – Anhembi-Morumbi

Dr. Engenharia de Produção - UNIMEP

Referências

Aleem Raza, Muhammad Asif, & Mubasher Akram. (2023). Give your hunger a new option: Understanding consumers’ continuous intention to use online food delivery apps using trust transfer theory. International Journal of Consumer Studies, 47(2), 474–495. https://doi.org/10.1111/ijcs.12845

Alloulbi, A., Öz, T., & Alzubi, A. (2022). The Use of Artificial Intelligence for Smart Decision-Making in Smart Cities: A Moderated Mediated Model of Technology Anxiety and Internal Threats of IoT. Mathematical Problems in Engineering, 1–12. https://doi.org/10.1155/2022/6707431

Ayyildiz, S., Çandereli̇, Z. Ö., Kiliç Aksu, P., Çatar, R. Ö., Ki̇tapçi, O. C., Şi̇şman Ki̇tapçi, N., Köksal, L., Demi̇rgöz Bal, M., & Mumcu, G. (2022). Assessment of Students’ Anxiety Level and Technology Readiness in a Simulation-Based Obstetrics Training: Simülasyona Dayalı Doğum Eğitimi Uygulanmasında Öğrencilerin Kaygı Durumları ve Teknolojik Hazırbulunuşluklarının İncelenmesi. Journal of Hacettepe University Faculty of Nursing, 9(3), 264–273. https://doi.org/10.31125/hunhemsire.1229918

American Psychiatric Association, D., & American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders: DSM-5 (Vol. 5, No. 5). Washington, DC: American psychiatric association.

Bauer, R. A. (1960). Consumer behavior as risk-taking. In R. S. Hancock (Ed.), Dynamic marketing for a changing world. Chicago: American Marketing Association, 389-398.

Bhukya, R., & Singh, S. (2015). The effect of perceived risk dimensions on purchase intention: An empirical evidence from Indian private labels market. American Journal of Business, 30(4), 218-230.

Bido, D. D. S., & Da Silva, D. (2019). SmartPLS 3: especificação, estimação, avaliação e relato. Administração: Ensino E Pesquisa, 20(2). https://doi.org/10.13058/raep.2019.v20n2.1545

Bido, D., da Silva, D., & Ringle, C. (2014). Structural Equation Modeling with the Smartpls. Brazilian Journal Of Marketing, 13(2).

Campbell, Stanley, J. C., & Gage, N. L. (1963). Experimental and quasi-experimental designs for research. Em N. L. Gage (Ed.) Handbook of research on teaching (p. 1-76). Chicago: Rand Mc-Nally.

Cai, J., Wu, J., Zhang, H., & Cai, Y. (2023). Research on the Influence Mechanism of Fashion Brands’ Crossover Alliance on Consumers’ Online Brand Engagement: The Mediating Effect of Hedonic Perception and Novelty Perception. Sustainability (2071-1050), 15(5), 3953. https://doi.org/10.3390/su15053953

Celik, H. (2016). Customer online shopping anxiety within the Unified Theory of Acceptance and Use Technology (UTAUT) framework. Asia Pacific Journal of Marketing and Logistics, 28(2), 278-307. https://doi.org/10.1108/APJML-05-2015-0077

Cohen, J. (1988). Statistical power analysis for the behavioural sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.

Cooper, D.R. & Schindler, P.S. (2003). Business Research Methods. 8th Edition, McGraw-Hill Irwin, Boston.

Cox, D.F., & Rich, S.V. (1964), Perceived risk and consumer decision making – the case of telephone shopping Journal of Market Research, 1(4), 32-9.

Dabholkar, P. A. (1996). Consumer evaluations of new technology-based self-service options: An investigation of alternative models of service quality. International Journal of Research in Marketing, 13(1), 29–51.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-341.

Dijk, M., Wells, P., & Kemp, R. (2016). Will the momentum of the electric car last? Testing a hypothesis on disruptive innovation? Testing a hypothesis on disruptive innovation. Technological Forecasting and Social Change, 105, 77-88.

https://doi.org /10.1016/j.techfore.2016.01.013

Dimitriadis, S., & Kyrezis, N. (2010). Linking trust to use intention for technology‐enabled bank channels: The role of trusting intentions. Psychology & Marketing, 27(8), 799-820.

Dowling, G. R., & Staelin, R. (1994). A model of perceived risk and intended risk-handling activity. Journal of consumer research, 21(1), 119-134.

Dubey, S., Sharma, I., Mishra, S., Cats, O., & Bansal, P. (2022). A general framework to forecast the adoption of novel products: A case of autonomous vehicles. Transportation research part B: methodological, 165, 63-95.

Elhai, J. D., Levine, J. C. & Hall, B. J. (2017). Anxiety about electronic data hacking: Predictors and relations with digital privacy protection behaviour. Internet Research, 27(3), 631-649.

Ferràs-Hernández, X., Tarrats-Pons, E., & Arimany-Serrat, N. (2017). Disruption in the automotive industry: A Cambrian moment. Business Horizons, 60(6), 855–863. https://doi.org/10.1016/j.bushor.2017.07.011.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behaviour: an introduction to theory and research. Addison-Wesley Publishing Company.

Fornell, C., Larcker, D.F. (1981). Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. Journal of Marketing Research; 18(3):382-388. https://doi.org/10.1177/002224378101800313

Garson, G. D. (2016). Partial least squares: Regression and structural equation models. Asheboro, NC: Statistical Associates Publishers Asheboro.

Goedertier, F., Dawar, N., Geuens, M., & Weijters, B. (2015). Brand typicality and distant novel extension acceptance: How risk-reduction counters low category fit. Journal of Business Research, 68(1), 157–165 https://doi.org/10.1016/j.jbusres.2014.04.005

Hair Jr, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modelling. Sage Publications.

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. Journal of the Academy of marketing science, 43(1), 115-135.

Ho, J. S., Tan, B. C., Lau, T. C., & Oo, N. K. T. (2023). A Review of Perceived Risk Role in Autonomous Vehicles Acceptance. International Journal of Management, Finance and Accounting, 4(1), 22-36.

Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modelling: a multidisciplinary journal, 6(1), 1-55.

Jordan, G., Leskovar, R., & Marič, M. (2018). Impact of Fear of Identity Theft and Perceived Risk on Online Purchase Intention. Organizacija, 51(2), 146-155.

Kim, L.H., Qu, H. and Kim, D.J. (2009), "A study of perceived risk and risk reduction of purchasing air- tickets online", Journal of Travel & Tourism Marketing, Vol. 26 No. 3, pp. 203-224.

Kotzé, T. G., Anderson, O., & Summerfield, K. (2016). Technophobia: Gender differences in the adoption of high-technology consumer products. South African Journal of Business Management, 47(1), 21–28. https://doi.org/10.4102/sajbm.v47i1.49.

Las-Casas, Alexandre Luzzi. (2012). Administração de marketing: conceitos, planejamento e aplicações à realidade brasileira. 1. ed. São Paulo: Atlas.

Likert, R. (1932). Technique for the Measurement of Attitudes Archives of Psychology, 140, 1–55. Google Scholar.

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.

Mello, S. C. B. de, Bastos, A. F. de S., & Mello, G. B. de. (2020). [Im]Mobility and trucking disruption: what happened to isolated cities and individuals in Brazil after a supply blockage. Applied Mobilities, 1–22. https://doi.org/10.1080/23800127.2020.1809157.

Meyer-Waarden, L., & Cloarec, J. (2022). “Baby, you can drive my car”: Psychological antecedents that drive consumers’ adoption of AI-powered autonomous vehicles. Technovation, 109, 102348.

MacKenzie, S. B., & Podsakoff, P. M. (2012). Common method bias in marketing: Causes, mechanisms, and procedural remedies. Journal of Retailing, 88(4), 542-555.

Mitchell V. W. (1999). Consumer perceived risk: conceptualizations and models. European Journal of Marketing, 33 (1/2), 163–195.

Nunnally J. Psychometric theory (1978). New York: McGraw-Hill.

Park, J., Ahn, J., Thavisay, T., & Ren, T. (2019). Examining the role of anxiety and social influence in multi-benefits of mobile payment service. Journal of Retailing and Consumer Services, 47, 140-149.

Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International journal of electronic commerce, 7(3), 101-134.

Pettersson, I., & Karlsson, I. C. M. (2015). Setting the stage for autonomous cars: a pilot study of future autonomous driving experiences. IET intelligent transport systems, 9(7), 694-701.

Quintal, V., Phau, I., Sims, D., & Cheah, I. (2016). Factors influencing Generation Y's purchase intentions of prototypical versus me-too brands. Journal of Retailing and Consumer Services, 30, 175-183.

Rogers, E. M. (1995). Diffusion of Innovations. 4th ed., New York: Free Press.

Rundmo, T., & Nordfjærn, T. (2017). Does risk perception really exist? Safety Science, 93, 230-240.

Schaffer, R. H. (1971). The psychological barriers to management effectiveness. Business Horizons, 14(2), 17–25. https://doi.org/10.1016/0007-6813(71)90003-6.

Silva, D., Cunha, L., Barros, C., & Baylina, P. (2019). Preparing the future scenario of automated vehicles: recommendations drawn from the analysis of the work activity of road transport workers. In Health and Social Care Systems of the Future: Demographic Changes, Digital Age and Human Factors: Proceedings of the Healthcare Ergonomics and Patient Safety, HEPS, 3-5 July 2019 Lisbon, Portugal (pp. 301-310). Springer International Publishing.

Stollery, A., & Jun, S. H. (2017). The antecedents of perceived value in the Airbnb context. Asia Pacific Journal of Innovation and Entrepreneurship, 11(3), 391– 404. https://doi.org/10.1108/apjie-12-2017-040.

Subiyakto, A., Nurrachman, G. R., Nuryasin, N., Muslimin, J. m., Yuniarto, D., & Kartiwi, M. (2023). Network Externality Effects on Behavioral Intention to Use Consumer Internet of Things Among Urban Citizens in Indonesia. Management Systems in Production Engineering, 31(2), 223–229. https://doi.org/10.2478/mspe-2023-0024

Suryani, A., Rahayu, A., & Dirgantari, P. D. (2023). Measuring The Impact of Hedonic Motivation, Smart Shopper Perception, Location-Based Coupon Attitude on Intention of Use Location-Based Coupon. Dinasti International Journal of Management Science (DIJMS), 4(3), 413–419. https://doi.org/10.31933/dijms.v4i3

Theeke, M., Polidoro, F., & Fredrickson, J. W. (2018). Path-dependent Routines in the Evaluation of Novelty: The Effects of Innovators’ New Knowledge Use on Brokerage Firms’ Coverage. Administrative Science Quarterly, 63(4), 910–942. https://doi.org/10.1177/0001839217747269

Transportation Research Board (2015). Transport Research International Documentation - TRID." http://trid.trb.org/

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425-478.

Waung, M., McAuslan, P., & Lakshmanan, S. (2021). Trust and intention to use autonomous vehicles: Manufacturer focus and passenger control. Transportation research part F: traffic psychology and behaviour, 80, 328-340.

Wells, J. D., Campbell, D. E., Valacich, J. S., & Featherman, M. (2010). The effect of perceived novelty on the adoption of information technology innovations: a risk/reward perspective. Decision Sciences, 41(4), 813-843.

Wilson, M. L., Huggins-Manley, A. C., Ritzhaupt, A. D., & Ruggles, K. (2023). Development of the Abbreviated Technology Anxiety Scale (ATAS). Behaviour research methods, 55(1), 185–199. https://doi.org/10.3758/s13428-022-01820-9

Wu, J. H., Wu, C. W., Lee, C. T., & Lee, H. J. (2015). Green purchase intentions: An exploratory study of the Taiwanese electric motorcycle market. Journal of Business Research, 68(4), 829-833.

Zhang, S., Xia, Z., Zhang, C., Tian, X., & Xie, J. (2023). Green illusions in self-reporting? Reassessing the intention-behaviour gap in waste recycling behaviours. Waste Management, 166, 171-180.