Abstract
The exhibition industry has been a part of the ‘smart tourism’ context, using smart information technology. Near field communication (NFC) allows exhibition attendees to acquire information and experience various services, which enhance their experience. However, which factors out of visitors’ determinants using NFC are crucial and how these factors affect their actual usage with real data have not been sufficiently investigated. Therefore, current study empirically examined how visitor’s self-efficacy and organizer’s support for NFC affect actual use through post-confirmation, NFC quality, NFC satisfaction and planned behaviour based on Expectation-Confirmation Model. We collected sample data from 387 exhibition attendees using NFC in the Cosmetic and Beauty Expo, Korea 2013. This study found that self-efficacy and organizational support affected their confirmation, which had effect on NFC actual use via NFC quality, NFC satisfaction and planned behaviour. Based on these results, this study presented theoretical and practical implications.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32(1), 1–20.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.
Au, N., Ngai, E. W., & Cheng, T. E. (2008). Extending the understanding of end user information systems satisfaction formation: An equitable needs fulfillment model approach. MIS Quarterly, 43–66.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.
Bandura, A. (1995). Exercise of personal and collective efficacy in changing societies. In A. Bandura (Ed.), Self-efficacy in changing societies. New York: Cambridge University Press.
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370.
Casaló, L. V., Flavián, C., & Guinalíu, M. (2010). Antecedents and consequences of consumer participation in on-line communities: The case of the travel sector. International Journal of Electronic Commerce, 15(2), 137–167.
Chen, K. Y., & Chang, M. L. (2013). User acceptance of ‘near field communication’ mobile phone service: An investigation based on the ‘unified theory of acceptance and use of technology’ model. The Service Industries Journal, 33(6), 609–623.
Chen, S. C., Liu, M. L., & Lin, C. P. (2013). Integrating technology readiness into the expectation–confirmation model: An empirical study of mobile services. Cyberpsychology, Behavior and Social Networking, 16(8), 604–612.
Chen, Y. Y., Huang, H. L., Hsu, Y. C., Tseng, H. C., & Lee, Y. C. (2010). Confirmation of expectations and satisfaction with the Internet shopping: The role of Internet self-efficacy. Computer and Information Science, 3(3), 14–22.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 298–336). Mahwah, NJ: Erlbaum.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Egger, R. (2013). The impact of near field communication on tourism. Journal of Hospitality and Tourism Technology, 4(2), 119–133.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. Upper Saddle River, NJ: Pearson Education.
Hossain, M. A., & Quaddus, M. (2012). Expectation–confirmation theory in information system research: A review and analysis. In Information systems theory (pp. 441–469). Springer: New York.
Igbaria, M., Parasuraman, S., & Baroudi, J. J. (1996). A motivational model of microcomputer usage. Journal of Management Information Systems, 13(1), 127–143.
Kim, H. W., & Kankanhalli, A. (2009). Investigating user resistance to information systems implementation: A status quo bias perspective. Management Information Systems Quarterly, 33(3), 567–582.
Lee, K. C., & Chung, N. (2009). Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean’s model perspective. Interacting with Computers, 21(5), 385–392.
Lee, Y., & Kwon, O. (2011). Intimacy, familiarity and continuance intention: An extended expectation–confirmation model in web-based services. Electronic Commerce Research and Applications, 10(3), 342–357.
Lee, D., Lee, S. M., Olson, D. L., & Chung, S. H. (2010). The effect of organizational support on ERP implementation. Industrial Management and Data Systems, 110(2), 269–283.
Lee, F. H., & Wu, W. Y. (2011). Moderating effects of technology acceptance perspectives on e-service quality formation: Evidence from airline websites in Taiwan. Expert Systems with Applications, 38(6), 7766–7773.
Li, H., & Liu, Y. (2014). Understanding the post-adoption behaviours of e-service users in the context of online travel services. Information and Management. doi:10.1016/j.im.2014.07.004.
López-de-Ipiña, D., Vazquez, J. I., & Jamardo, I. (2007). Touch computing: Simplifying human to environment interaction through NFC technology. In 1as Jornadas Científicas sobre RFID, 21.
Luarn, P., & Juo, W. J. (2010). The role of trust in technology within the TAM in the context of NFC mobile payment. Journal of Information and Optimization Sciences, 31(4), 875–896.
Muñoz, F. F., & Encinar, M. I. (2014). Intentionality and the emergence of complexity: An analytical approach. Journal of Evolutionary Economics, 24(2), 317–334.
Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460–469.
Oliver, R. L. (1999). Whence consumer loyalty? Journal of Marketing, 63, 33–44.
Subramanian, N., Gunasekaran, A., Yu, J., Cheng, J., & Ning, K. (2014). Customer satisfaction and competitiveness in the Chinese E-retailing: Structural equation modeling (SEM) approach to identify the role of quality factors. Expert Systems with Applications, 41(1), 69–80.
Tzeng, J. Y. (2011). Perceived values and prospective users’ acceptance of prospective technology: The case of a career eportfolio system. Computers and Education, 56(1), 157–165.
Tojib, D., & Tsarenko, Y. (2012). Post-adoption modeling of advanced mobile service use. Journal of Business Research, 65(7), 922–928.
Yang, Z., Cai, S., Zhou, Z., & Zhou, N. (2005). Development and validation of an instrument to measure user perceived service quality of information presenting web portals. Information and Management, 42(4), 575–589.
Acknowledgements
This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2013S1A3A2043345).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Han, H., Chung, N., Koo, C., Lee, K.J. (2015). Exhibition Attendees’ Smart Technology Actual Usage: A Case of Near Field Communications. In: Tussyadiah, I., Inversini, A. (eds) Information and Communication Technologies in Tourism 2015. Springer, Cham. https://doi.org/10.1007/978-3-319-14343-9_33
Download citation
DOI: https://doi.org/10.1007/978-3-319-14343-9_33
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14342-2
Online ISBN: 978-3-319-14343-9
eBook Packages: Business and EconomicsBusiness and Management (R0)