The Determinants of Consumer Behaviour Influencing the Smart Technology Recognition and Acceptance

Authors

  • Rima Zitkiene Mykolas Romeris University
  • Germante Markeviciute Mykolas Romeris University
  • Monika Mickeviciene Lithuanian Police School

Keywords:

Keywords, consumer behaviour, smart technology, innovation, factors.

Abstract

Abstract. IT progress and development of innovations not only facilitate the increase of activity efficiency, but also contribute to the improvement of people’s life quality and the change of user’s habits. A new smart environment is formed, where a close interaction and mutual dependence upon a human being and IT exists. The paper analyzes the features of smart products and highlights theoretical aspects of consumers’ perception, recognition and adoption of smart technology. Methods used in the article: a comparative analysis of scientific literature, consumer survey and assessment. It includes references to the Innovation Diffusion Theory and Theory of Perceptual Level, Theory of Reasoned Action and the Planned Behaviour Theory that help to explain the consumer decision to become a regular user of the product. Factors that influence consumer’s behaviour and the decision process of innovation acceptance, as suggested by different authors, are emphasized.  As well the consumers’ of new technology classification categories are presented and factors determining the choice of innovation, when people are attracted to new technologies, are revealed. Survey’s empirical research results show that two groups dominate among the respondents: Early Adopters and Late Majority. Consumer is motivated to use the technology for its benefit, but the value and the price of technology remains a barrier for acquiring smart products.

Author Biographies

Rima Zitkiene, Mykolas Romeris University

Professor of Economics Institute

Monika Mickeviciene, Lithuanian Police School

Dr. Project Manager

References

Arts, J. W. C., Frambach, R. T., Bijmolt, T. H. A. (2011). Generalizations on consumer innovation adoption: A meta-analysis on drivers of intention and behavior. International Journal of Research in Marketing, 28, 134-144.

Bartl, M., Füller, J., Mühlbacher, H., Ernst, H. (2012). A Manager’s perspective on virtual customer integration for new product development. Journal of Product Innovation Management, 29(6), 1031-1046. Doi: 10.1111/j.1540-5885.2012.00946.x

Chang, Y. P., Dong, X. B., Sun, W. (2014). Influence of characteristics of the Internet of Things on consumer purchase intention. Social Behavior and Personality: An International Journal, 42(2), 321-330. Doi: 10.2224/sbp.2014.42.2.321

Dawid, H., Decker,R., Hermann, T., Jahnke, H., Klat, W., König, R., Stummer, C. (2016). Management science in the era of smart consumer products: challenges and research perspective. Central European Journal of Operations Research, 25(1), 203-230. Doi: 10.1007/s10100-016-0436-9.

Faiers, A., Neame, C. (2006). Consumer attitudes towards domestic solar power systems. Energy Policy, 34, 1797-1806.

Gartner (2013). Forecast: The internet of things, worldwide. Retrieved from http://www.gartner. com/newsroom/id/2636073

Haddon, L. (2006). The contribution of domestication research to in-home computing and media consumption. The Information Society: An International Journal, 22(4), 195-203. Doi: 10.1080/01972240600791325

Heidenreich, S., Kraemer, T., Handrich, M. (2016). Satisfied and unwilling: Exploring cognitive and situational resistance to innovations. Journal of Business Research, 69(7), 2440-2447. Doi: 10.1016/j.jbusres.2016.01.014

Heidenreich, S., Spieth, P. (2013). Why innovations fail - the case of passive and active innovation resistance. International Journal of Innovation Management, 17(5), 1350021-1350042. Doi: 10.1142/S1363919613500217

Hoffman, D. L., Novak, T. P. (2015). Emergent experience and the connected consumer in the smart home assemblage and the internet of things. Retrieved from https://postsocialgwu.files.wordpress.com/2015/08/hoffman-and-novak-2015-emergent-experience-in-the-iot.pdf

Hsu, C. L., Lin, C. C. (2016). An empirical examination of consumer adoption of internet of things services: Network externalities and concern for information privacy perspectives. Computers in Human Behavior, 62, 516-527. Doi: 10.1016/j.chb.2016.04.023

Jeyaraj, A., Rottman, J. W., Lacity, M. C. (2006). A review of the predictors, linkages, and biases in IT innovation adoption research. Journal of Information Technology, 21(1), 1–23.

Kim, K. J., Shin, D. H. (2015). An acceptance model for smart watches: Implications for the adoption of future wearable technology. Internet Research, 25(4), 527-541. Doi: 10.1108/IntR-05-2014-0126

Kleijnen, M., Lee, N. J., Wetzels, M. (2009). An exploration of consumer resistance to innovation and its antecedents. Journal of Economic Psychology, 30(3), 344–357. Doi: 10.1016/j. joep.2009.02.004.

Nguyen, B., De Cremer, D. (2016). The fairness challenge of the internet of things. The European Business Review. Retrieved from http://www.europeanbusinessreview.com/the-fairness-challenge-of-the-internet-of-things/

Porter, M. E., Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard Business Review, 92(11), 64-88.

Rogers, E. M. (1983). Diffusion of innovations. 3rd ed. New York: Free Press.

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

Schwarz, N., Ernst, A. (2008). Agent-based modelling of the diffusion of environmental innovations - an empirical approach. Technological Forecasting and Social Change, 76(4), 497-511. Doi: 10.1016/j.techfore.2008.03.024

Shin, D.H. (2010). Ubiquitous computing acceptance model: end user concern about security, privacy and risk. International Journal of Mobile Communications, 8(2), 169-186. Doi: 10.1504/IJMC.2010.031446

Sicari, S., Rizzardi, A., Grieco, L. A., Coen-Porisini, A. (2015). Security, privacy and trust in internet of things: The road ahead. Computer Networks, 76, 146-164. Doi:10.1016/j.comnet.2014.11.008.

Silverstone, R., Haddon, L. (2006). Design and the domestication of information and communication technologies: technical change and everyday life. In Silverstone, R., Mansell, R. (eds.). Communication by design. the politics of information and communication technologies. Oxford University Press, Oxford. 44-74.

Slettemeås, D. (2009). RFID-the “Next Step” in consumer-product relations or Orwellian nightmare? Challenges for research and policy. Journal of Consumer Policy, 32, 219-244. Doi: 10.1007/s10603-009-9103-z

Talke, K., Heidenreich, S. (2014). How to overcome pro-change bias: Incorporating passive and active innovation resistance in innovation decision models. Journal of Product Innovation Management, 31(5), 894-907. Doi: 10.1111/jpim.12130

Trope, Y., Liberman, N. (2003). Temporal construal. Psychological Review, 110, 403-421.

Venkatesh, V., Davis, F.D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46, 186-204. Doi: 10.1287/mnsc.46.2.186.11926

Verhoef, P. C., Langerak, F. (2001). Possible determinants of consumers’ adoption of electronic grocery shopping in the Netherlands. Journal of Retailing and Consumer, 8(5), 275–285. Doi: 10.1016/S0969-6989(00)00033-3

Wallden, S., Makinen, E. (2014). On accepting smart environments at user and societal levels. Universal Access in the Information Society, 13(4), 449-469. Doi: 10.1007/s10209-013-0327-y.

Wuenderlich, N. V., Heinonen, K., Ostrom, A. L., Patricio, L., Sousa, R., Voss, C., Lemmink, J. G. A. M. (2015). Futurizing smart service: Implications for service researchers and managers. Journal of Services Marketing, 29(6/7), 442-447. Doi: 10.1108/JSM-01-2015-0040.

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Published

2017-10-01

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Section

Section 2: Perspectives of Law