Desarrollo de una escala de intención de uso del comercio móvil y su validación mediante análisis compuesto confirmatorio

Autores/as

  • Marina Isabel Sánchez-Sánchez Universidad Autónoma de Baja California, Facultad de Ciencias Administrativas y Sociales, Avenida Reforma s/n, Valle Dorado, Ensenada, Baja California, México, C. P. 22890. https://orcid.org/0000-0002-3363-5630
  • Virginia Guadalupe López-Torres Universidad Autónoma de Baja California, Facultad de Ciencias Administrativas y Sociales, Avenida Reforma s/n, Valle Dorado, Ensenada, Baja California, México, C. P. 22890. https://orcid.org/0000-0002-2795-8951

DOI:

https://doi.org/10.29059/cienciauat.v18i2.1788

Palabras clave:

comercio móvil, análisis compuesto confirmatorio, intención de uso, riesgo percibido, tradición

Resumen

La intención de comportamiento se ha estudiado desde la teoría de la acción razonada para predecir el comportamiento de los individuos. El objetivo de esta investigación fue desarrollar y validar una escala para medir la intención de uso del comercio móvil, a partir de las variables de la teoría unificada de aceptación y uso de tecnología como impulsores, y las variables riesgo percibido y tradición como inhibidores. El instrumento fue aplicado en línea a 211 consumidores del estado de Baja California, México. Se utilizó el análisis compuesto confirmatorio para verificar la fiabilidad del instrumento, así como la validez convergente, discriminante, nomológica y predictiva. Se obtuvo un instrumento válido y confiable para medir la influencia de las variables expectativa de rendimiento, influencia social, motivación hedónica, riesgo percibido, condiciones facilitadoras y tradición en la intención de uso del comercio móvil. La escala desarrollada satisface los criterios exigibles a un modelo de medición reflectivo.

Citas

Ajzen, I. and Fishbein, M. (1975). A Bayesian analysis of attribution processes. Psychological Bulletin. 82(2): 261-277.

Al-Adwan, A. S., Alrousan, M., Al-Soud, A., and Al-Yaseen, H. (2019). Revealing the black box of shifting from electronic commerce to mobile commerce: The case of Jordan. Journal of Theoretical & Applied Electronic Commerce Research. 14(1): 51-67.

Ali, F., Rasoolimanesh, S. M., Sarstedt, M., Ringle, C. M., and Ryu, K. (2018). An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research. International Journal of Contemporary Hospitality Management. 30(1): 514-538.

Arif, I., Aslam, W., and Hwang, Y. (2020). Barriers in adoption of internet banking: A structural equation modeling - Neural network approach. Technology in Society. 61: 101231.

Bagozzi, R. P. and Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science. 16(1): 74-94.

Bahaddad, A. A. (2021). The traditional influence on increasing acceptance of commercial smartphone applications in specific regions of the arabic world. Complexity. 1-16.

Barroso, C., Carrión, G. C., and Roldán, J. L. (2010). Applying Maximum Likelihood and PLS on Diffe-rent Sample Sizes: Studies on SERVQUAL Model and Employee Behavior Model. In V. Esposito Vinzi, W. W. Chin, J. Henseler and H. Wang (Eds.), Hand-book of Partial Least Squares: Concepts, Methods and Applications (pp. 427-447). Berlin, Heidelberg: Springer Berlin Heidelberg.

Blaise, R., Halloran, M., and Muchnick, M. (2018). Mobile commerce competitive advantage: A Quantitative Study of Variables that Predict M-Commerce Purchase Intentions. Journal of Internet Commerce. 17(2): 96-114.

Chimborazo, L. E., Frasquet, M., and Mollá, A. (2021). Explaining Mobile Commerce Usage Intention Based on Technology Acceptance Models in a Developing Market Context. Market / Trziste. 33(1): 25-40.

Chin, W.W. (2010). How to Write Up and Report PLS Analyses. In V. Esposito, Vinzi, W. W. Chin, J. Henseler, and H. Wang, (Eds.), Handbook of Partial Least Squares: Concepts, Methods and Applications. (pp. 655-690). Springer, Heidelberg, Dordrecht, London, New York.

Cruz, I. y Miranda, A. M. (2023). Factores determinantes de la adopción del m-commerce en consumidores de Tijuana. Estudios Gerenciales. 39(167). 192-206.

DeVellis, R. F. (2016). Scale Development: Theory and Applications. (Cuarta edición). Los Ángeles, U.S.A: Ed. SAGE. 280 Pp.

Do-Nascimento, J. and Da-Silva-Macedo, M. (2016). Modelagem de equações estruturais com mínimos quadrados parciais: um exemplo da aplicação do SmartPLS® em pesquisas em contabilidade. Revista de Educação e Pesquisa em Contabilidade. 10(3): 289-313.

Escobar-Pérez, J. y Cuervo-Martínez, Á. (2008). Validez de contenido y juicio de expertos: una aproximación a su utilización. Avances en Medición. 6(1): 27-36.

Faqih, K. M. S. (2016). An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: Does gender matter? Journal of Retailing and Consumer Services. 30: 140-164.

Gao, K. and Shao, X. (2019). Adoption research of the m-commerce application based on the perspective of supply chain management in shipping industry. Journal of Coastal Research. 83(10083): 839-845.

Grcić, A. and Mekić, E. (2019). Predictors of m-continuance intention: Case of users in Bosnia and Herzegovina. Economic Review: Journal of Eco-nomics & Business/Ekonomska Revija: Casopis Za Ekonomiju i Biznis. 17(2): 27-40.

Hair, J. F., Howard, M. C., and Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research. 109: 101-110.

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Castillo-Apraiz, J., Cepeda-Carrión, G., and Roldán, J. L. (2019). Manual de Partial Least Squares Structural Equation Modeling (pls-sem) (Second edition). Terrassa, España: OmniaScience.

Hair, J. F., Hult, G. T. M., Ringle, C. ..., and Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (Second edition). Los Ángeles, U.S.A: Sage publications. 384 Pp.

Hambleton, R. K. and Zenisky, A. L. (2011). Translating and adapting tests for cross-cultural assessments, in Cross-cultural research methods in psychology. [En línea]. Disponible en: https://psycnet.apa.org/record/2010-22491-003. Fecha de consulta: 6 de abril de 2022.

Henseler, J., Ringle, C. M., and Sarstedt, M. (2016). Testing measurement invariance of composites using partial least squares. International Marketing Review. 33(3): 405-431.

Henseler, J., Ringle, C. M., and Sinkovics, R. R. (2009). “The use of partial least squares path modeling in international marketing”. In R. R. Sinkovics and P. N. Ghauri (Eds.), New Challenges to International Marketing (pp. 277-319). Emerald Group Publishing Limited, Bingley.

Hew, J. J., Lee, V. H., Ooi, K. B., and Wei, J. (2015). What catalyses mobile apps usage intention: An empirical analysis, in Industrial Management & Da-ta Systems. [En línea]. Disponible en: https://doi.org/10.1108/IMDS-01-2015-0028. Fecha de consulta: 18 de mayo de 2022.

Iuga, I. C. and Wainberg, D. (2023). Factors That Influence the Implementation of M-Commerce by Romanian SMEs During the COVID-19 Pandemic. Journal of the Knowledge Economy. 1-34.

Imbachí, J. F. (2016). m-commerce: El comercio electrónico móvil y los pagos a través de dispositivos móviles. Revista Contexto. 46: 117-140.

Kalinic, Z. and Marinkovic, V. (2016). Determinants of users’ intention to adopt m-commerce: An empirical analysis. Information Systems and e-Busi-ness Management. 14(2): 367-387.

Kaur, P., Dhir, A., Singh, N., Sahu, G., and Almotairi, M. (2020). An innovation resistance theory pers-pective on mobile payment solutions. Journal of Re-tailing and Consumer Services. 55: 102059.

Kim, C., Li, W., and Kim, D. J. (2015). An empirical analysis of factors influencing m-shopping use. In-ternational Journal of Human-Computer Interaction. 31(12): 974-994.

Kwofie, M. and Adjei, J. K. (2019). Understanding the factors influencing mobile commerce adoption by traders in developing countries: Evidence from Ghana. En Y. Dwivedi, E. Ayaburi, R. Boateng, and J. Effah (Eds.), ICT Unbounded, Social Impact of Bright ICT Adoption (pp. 104-127). USA: Springer International Publishing.

Ledesma, R. D., Ferrando, P. J. y Tosi, J. D. (2019). Uso del análisis factorial exploratorio en RIDEP. Recomendaciones para Autores y Revisores. Revista Iberoamericana de Diagnóstico y Evaluación Psicológica. 52(52): 173-180.

Lee, W. O. and Wong, L. S. (2016). Determinants of mobile commerce customer loyalty in Malaysia. Procedia - Social and Behavioral Sciences. 224: 60-67.

Lira, M. T. y Caballero, E. (2020). Adaptación transcultural de instrumentos de evaluación en salud: historia y reflexiones del por qué, cómo y cuándo. Revista Médica Clínica Las Condes. 31(1): 85-94.

Lissitsa, S. and Kol, O. (2019). Four generational cohorts and hedonic m-shopping: Association between personality traits and purchase intention. Electronic Commerce Research. 21(2): 545-570.

Lloret-Segura, S., Ferreres-Traver, A., Hernández-Baeza, A. y Tomás-Marco, I. (2014). El análisis factorial exploratorio de los ítems: una guía práctica, revisada y actualizada. Anales de Psicología. 30(3): 1151-1169.

Máynez-Guaderrama, A. I. (2021). Apoyo del supervisor: su influencia en la autonomía, cohesión y percepción de apoyo organizacional en una dependencia del gobierno. Estudios Gerenciales. 37(160): 448-459.

Mehedintu, A. and Soava, G. (2022). A Hybrid SEM-Neural Network Modeling of Quality of M-Commerce Services under the Impact of the COVID-19 Pandemic. Electronics. 11(16): 299.

Moorthy, K., Suet-Ling, C., Weng-Fatt, Y., Mun-Yee, C., Ket-Yin, E. C., Sin-Yee, K., and Kok-Wei, L. (2017). Barriers of mobile commerce adoption intention: Perceptions of generation X in Malaysia. Journal of Theoretical & Applied Electronic Commerce Research. 12(2): 37-53.

Natarajan, T., Balasubramanian, S. A., and Kasilingam, D. L. (2017). Understanding the intention to use mobile shopping applications and its influence on price sensitivity. Journal of Retailing and Consumer Services. 37: 8-22.

Ntsafack, F. W., Kala, J. R., and Fosso, S. (2020). Mobile commerce adoption in a developing country: Driving factors in the case of Cameroon, in ICT for an Inclusive World. Lecture Notes in Information Systems and Organisation. [En línea]. Disponible en: https://doi.org/10.1007/978-3-030-34269-2_20. Fecha de consulta: 6 de abril de 2022.

Palos-Sanchez, P. R., Correia, M. B., and Saura, J. R. (2019). An empirical examination of adoption of mobile applications in Spain and Portugal, based in UTAUT. International Journal of Mobile Communications. 17(5): 579-603.

Pandey, S. and Chawla, D. (2019). Engaging m-commerce adopters in India: Exploring the two ends of the adoption continuum across four m-commerce categories. Journal of Enterprise Information Management. 32(1): 191-210.

Purohit, S., Arora, R., and Paul, J. (2022). The bright side of online consumer behavior: Continuance intention for mobile payments. Journal of Consumer Behaviour. 21(3): 523-542.

Ringle, C. M., Wende, S., and Becker, J. M. (2015). SmartPLS 3. SmartPLS GmbH, Boenningstedt. Journal of Service Science and Management. 10(3): 32-49.

Sair, S. A. and Danish, R. Q. (2018). Effect of performance expectancy and effort expectancy on the mobile commerce adoption intention through personal innovativeness among Pakistani consumers. Pakistan Journal of Commerce & Social Sciences. 12(2): 501-520.

Samad, N. S. A., Abdullah, F. A., Yaziz, M. F. A., and Bahari, N. (2021). The factors influencing the usage of mobile commerce among rural entrepreneurs in peninsular Malaysia. International Journal of Interactive Mobile Technologies. 16(20): 131-145.

Sánchez, M. I., López-Torres, V. G., Montes-de-Oca-Rojas, Y. M., and Leyva-Hernández, S. N. (2022). Mobile commerce usage explained by intention to use, price motivation, and COVID-19. Journal of Positive School Psychology. 5690-5709.

Shaw, N. and Sergueeva, K. (2019). The non-monetary benefits of mobile commerce: Extending UTAUT2 with perceived value. International Journal of Information Management. 45: 44-55.

Singh, S., Zolkepli, I. A., and Cheah, W. K. (2018). New wave in mobile commerce adoption via mobile applications in Malaysian market: Investigating the relationship between consumer acceptance, trust, and self efficacy. International Journal of Interactive Mobile Technologies. 12(7): 112-128.

Slade, E. L., Dwivedi, Y. K., Piercy, N. C., and Williams, M. D. (2015). Modeling consumers’ adoption intentions of remote mobile payments in the United Kingdom: Extending UTAUT with innovativeness, risk, and trust. Psychology & Marketing. 32(8): 860-873.

Soni, M., Jain, K. and Kumar, B. (2019). Factors affecting the adoption of fashion mobile shopping applications. Journal of Global Fashion Marketing. 10(4): 358-376.

Sujatha, R. and Sekkizhar, J. (2019). Determinants of m-commerce adoption in India Using technology acceptance model infused with innovation diffusion theory. Journal of Management Research. 19(3): 193-204.

Tarhini, A., Alalwan, A. A., Shammout, A. B., and Al-Badi, A. (2019). An analysis of the factors affecting mobile commerce adoption in developing countries: Towards an integrated model. Review of International Business and Strategy. 29(3): 157-179.

Trojanowski, M. and Kułak, J. (2017). The impact of moderators and trust on consumer’s intention to use a mobile phone for purchases. Central European Management Journal. 25(2): 91-116.

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

Venkatesh, V., Thong, J. Y. L., and Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly. 36(1): 157-178.

Verkijika, S. F. (2018). Factors influencing the adoption of mobile commerce applications in Cameroon. Telematics and Informatics. 35(6): 16651674.

Yadav, R., Sharma, S. K., and Tarhini, A. (2015). A multi-analytical approach to understand and predict the mobile commerce adoption. Journal of Enterprise Information Management. 29(2): 222-237.

Publicado

2023-11-30

Cómo citar

Sánchez-Sánchez, M. I., & López-Torres, . V. G. (2023). Desarrollo de una escala de intención de uso del comercio móvil y su validación mediante análisis compuesto confirmatorio. CienciaUAT, 18(2), 43-57. https://doi.org/10.29059/cienciauat.v18i2.1788

Número

Sección

Ciencias Sociales