Consumer Behavior Towards Technological Innovations: A Systematic Review

Kelly Carvalho Vieira, Guilherme Alcântara Pinto, Joel Yutaka Sugano


One of the biggest challenges facing technology innovation companies is how to jump from a small group of enthusiasts and achieve mass sales. For this, many theories are extended trying to explain the different behavioral profiles. Therefore, the objective of this article is to analyze the studies on consumer behavior of technological innovations, synthesize the main concepts on this theme, and outline an overview of how this field is configured. To this end, a systematic review, first in the research front and then in the intellectual base was performed. The results indicate a dynamic of articles with more than one model or hybrids that seems to be a trend towards complementing the already consolidated factor theoretical models. This fact implies that these theories are failing to accurately explain the factors that influence a technology to push visionary customers to mass demand.


Technology Acceptance Model, Innovation Adoption, Innovation Diffusion, Research Front, Intellectual Base

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Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information systems research, 9(2), 204-215.

Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.

Bartels, J., & Reinders, M. J. (2011). Consumer innovativeness and its correlates: A propositional inventory for future research. Journal of Business Research, 64(6), 601-609.

Chang, M. K., Cheung, W., & Lai, V. S. (2005). Literature derived reference models for the adoption of online shopping. Information & Management, 42(4), 543-559.

Chen, C. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for information Science and Technology, 57(3), 359-377.

Chen, Y. H., & Corkindale, D. (2008). Towards an understanding of the behavioral intention to use online news services: An exploratory study. Internet Research, 18(3), 286-312.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), 982-1003.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.

Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online consumers: an extended technology acceptance perspective. Information & management, 39(8), 705-719.

Keung, J., Jeffery, R., & Kitchenham, B. (2004, April). The challenge of introducing a new software cost estimation technology into a small software organisation. In null (p. 52). IEEE.

Lee, E. J., Lee, J., & Schumann, D. W. (2002). The influence of communication source and mode on consumer adoption of technological innovations. Journal of Consumer Affairs, 36(1), 1-27.

Lu, H. P., & Yu-Jen Su, P. (2009). Factors affecting purchase intention on mobile shopping web sites. Internet Research, 19(4), 442-458.

Mick, D. G., & Fournier, S. (1998). Paradoxes of technology: Consumer cognizance, emotions, and coping strategies. Journal of Consumer research, 25(2), 123-143.

Miller, T. W., & Dickson, P. R. (2001). On-line market research. International Journal of Electronic Commerce, 5(3), 139-167.

Moore, G. A. (2002). Crossing the chasm, revised edition. New York: HarperBusiness Essentials.

Parasuraman, A. (2000). Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. Journal of service research, 2(4), 307-320.

Parasuraman, A., & Colby, C. L. (2007). Techno-ready marketing: How and why your customers adopt technology. The Free Press.

Poon, W. C. (2007). Users' adoption of e-banking services: the Malaysian perspective. Journal of Business & Industrial Marketing, 23(1), 59-69.

Prado, J. al. (2016). Multivariate analysis of credit risk and bankruptcy research data: a bibliometric study involving different knowledge fields (1968–2014). Scientometrics, 106(3), 1007-1029.

Rogers, E. M. (2003). Diffusion of innovations, (5th ed). New York: Free Press.

Taherdoost, H. (2018). A review of technology acceptance and adoption models and theories. Procedia Manufacturing, 22, 960-967.

Thakur, R., & Srivastava, M. (2014). Adoption readiness, personal innovativeness, perceived risk and usage intention across customer groups for mobile payment services in India. Internet Research, 24(3), 369-392.

Turner, M., Kitchenham, B., Brereton, P., Charters, S., & Budgen, D. (2010). Does the technology acceptance model predict actual use? A systematic literature review. Information and Software Technology, 52(5), 463-479.

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.

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

Wang, S., & Cheung, W. (2004). E-business adoption by travel agencies: prime candidates for mobile e-business. International Journal of Electronic Commerce, 8(3), 43-63.

Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model. Information & management, 42(5), 719-729.

Xu, X., Venkatesh, V., Tam, K. Y., & Hong, S. J. (2010). Model of migration and use of platforms: role of hierarchy, current generation, and complementarities in consumer settings. Management Science, 56(8), 1304-1323.

Zenobia, B., Weber, C., & Daim, T. (2009). Artificial markets: A review and assessment of a new venue for innovation research. Technovation, 29(5), 338-350.


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