Influence of social networks on the purchase decisions of university students
DOI:
https://doi.org/10.1229/tecempresarialjournal.v14i1.3Keywords:
Trust, purchase decisions, information, marketing, social networksAbstract
The emergence of social networks has not just had a great impact in the way companies promote their products and services, but also in the decision-making process of consumers regarding their purchases. Using the application and extension of the models proposed by Okazaki et al. (2012), the present study tries to understand the factors that motivate the use of social networks in the purchase decisions of young university students, for this a self-administered questionnaires were applied to 224 university students. Some limitations were found at the time of evaluating the adjustment of the model through a structural equations method, due to the number of indicators per construct. However, the results show that the proposed model presents a good adjustment. Therefore, it can be concluded that the study develops an appropriate approach to the knowledge of the factors that can influence university students, who intend to use social networks to buy, validating the conclusions drawn by Okazaki et al. (2012) in their study. At last, it is recommended for companies that wish to promote their products through social networks to look out for strategies that combine information transparency and stimulation of word-of-mouth communication among users, generating a larger impact on the purchase decisions of clients.
References
Abascal, E. and Esteban, I.G., 2005. Análisis de encuestas. Madrid: ESIC Editorial. Acar, A.S. and Polonsky, M., 2007. Online social networks and insights into marketing communications. Journal of Internet Commerce, 6(4), 55-72.
Ajzen, I., 1991. The theory of planned behavior. Organizational behavior and human de-cision processes, 50 (2), 179-211.
Akar, E. and Topçu, B., 2011. An examination of the factors influencing consumers’ at-titudes toward social media marketing. Journal of Internet Commerce, 10 (1), 35-67.
Alvarado, P.A., 2012. Impacto de las redes sociales sobre las variables de decisiones de los agentes. Universidad Nacional de Colombia, Facultad de Ciencias Económicas, Colombia. Available at: http://www.fce.unal.edu.co/wiki/images/0/04/Impacto_de_ las_redes_sociales_en_las_decisiones_de_los_agentes.pdf. [Accessed: 20 December 2014].
Anderson, J.C. and Gerbing, D.W., 1988. Structural equation modeling in practice: A re-view and recommended two-step approach. Psychological bulletin, 103 (3), 411-423.
Arcos, V.A., Gutiérrez, S.S.M. and Hernanz, R.J.P., 2014. La aplicación empresarial del marketing viral y el efecto boca-oreja electrónico: opiniones de las empresas. Cuader-nos de gestión, 14 (1), 15-31.
Ajzen, I. and Fishbein, M., 1980. Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs, NJ: Prentice Hall.
Bermudez, J., Chalela, S., Valencia, J. and Valencia, A., 2017. Research Trends in the Study of ICT Based Learning Communities: A Bibliometric Analysis. Eurasia Journal of Mathematics, Science and Technology Education, 13 (5), 1539-1562. DOI: 10.12973/ eurasia.2017.00684a
Bolotaeva, V. and Cata, T., 2010. Marketing opportunities with social networks. Journal of Internet Social Networking and Virtual Communities, 1-8.
Bran, L., Romero, K., Echeverri, L., Peña, J., Vasquez, S., Aguilera, M., Herazo, C. and Valencia, A., 2017. Information and Communication Technologies Influence on Family Relationship. Global Journal of Health Science, 9 (6), 204-213. DOI:10.5539/gjhs. v9n6p204.
Bryant, C.L., Maarouf, S., Burcham, J. and Greer, D., 2016. The examination of a teacher candidate assessment rubric: A confirmatory factor analysis. Teaching and Teacher Ed-ucation, 57, 79-96.
Brown, J., Broderick, A.J. and Lee, N., 2007. Word of mouth communication within online communities: Conceptualizing the online social network. Journal of interactive mar-keting, 21 (3), 2-20.
Calvo-Porral, C., Martínez-Fernández, V.A. and Juanatey-Boga, O., 2013. Análisis de dos modelos de ecuaciones estructurales alternativos para medir la intención de compra. Revista Investigación Operacional, 34 (3), 230 – 243.
Cartagena, C., Vasquez, A., Benjumea-Arias, M. and Valencia-Arias, A., 2017. Proposed Model for Measuring Customer Satisfaction with Telecommunications Services. Med-iterranean Journal of Social Sciences, 8 (2), 15-26. DOI: 10.5901/mjss.2017.v8n2p15.
Cheung, C.M. and Lee, M.K., 2010. A theoretical model of intentional social action in online social networks. Decision support systems, 49 (1), 24-30.
ComScore, 2013. Futuro Digital Colombia 2013. Available at: http://www.comscore. com/esl/Prensa-y-Eventos/Presentaciones-y-libros-blancos/2014/2014-Digital-Fu-ture-in-Focus-Colombia. [Accessed: 12 August 2015].
Davis, F.D., Bagozzi, R. and Warshaw, P., 1989. User acceptance of computer technology:
A comparison of two theoretical models. Management Science, 35 (8), 982–1003.
De la Fuente, J. and Justicia, F.J., 2003. Escala de estrategias de aprendizaje ACRA-Abre-viada para alumnos universitarios. Electronic journal of research in educational psy-chology, 1 (2), 139-158.
Dholakia, U.M., Bagozzi, R.P. and Pearo, L.K., 2004. A social influence model of consum-er participation in network-and small-group-based virtual communities. International journal of research in marketing, 21 (3), 241-263.
Fishbein, M. and Ajzen, I., 1975. Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Frías-Navarro, D., 2013. Alfa de Cronbach y consistencia interna de los ítems de un in-strumento de medida. Available at: http://www.uv.es/~friasnav/AlfaCronbach.pdf. [Ac-cessed: 10 May 2015].
Gatautis, R. and Kazakevičiūtė, A., 2012. Consumer behavior in online social networks: review and future research directions. Economics and Management, 17 (4), 1457-1463
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