Abstract
Continuance intention is defined as ones intention to continue using a technology or long term usage intention of a technology. Although initial acceptance is important in identifying the success of an information system but continued usage is even more significant in ensuring the long-term viability of technology innovations and also to enhance the financial and quality performance of an organization. Unlike initial acceptance decision, continuance intention is important, depends on various factors that affect the individuals’ decision to continue using a particular system with one of the most important emotion that is the satisfaction. Therefore, this case study aims to examine the e-filing usage by taxpayers in Malaysia based on the Expectation Confirmation Model. The data were collected from 116 taxpayers in Penang, Malaysia using survey method. Data was analyzed using Partial Least Square (PLS) method version 2.0. The result shows a significant relationship between the entire variable in the study. Perceived usefulness and satisfaction were found to be significantly related to the continuance usage intention, explaining 54.2 % of the variance in continuance usage intention. Surprisingly, perceived usefulness was found to be the strongest predictor of continuance usage intention. The implications of these findings to the Inland Revenue Board of Malaysia are also elaborated.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Al-maghrabi, T., Dennis, C., & Halliday, S. V. (2011). understanding the factors that derive continuance intention of e-shopping in saudi arabia: Age group differences in behaviour. Journal of Enterprise Information Management, 24(1), 85–111.
Alsaghier, H., Ford, M., Nguyen, A., & Hexel, R. (2009). Conceptualising citizens trust in e-Government: Application of Q methodology. Electronic Journal of e-Government, 7(4), 295–310.
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.
Annual Report Inland Revenue Board of Malaysia. (2010). Retrieved April 20, 2012 from http://www.hasil.org.my/pdf/pdfam/AR2010_2.pdf.
Annual Report Inland Revenue Board of Malaysia. (2009). Retrieved April 5, 2011 from http://www.hasil.gov.my/pdf/pdfam/AR2009_2.pdf.
Annual Report Inland Revenue Board of Malaysia. (2007). Retrieved April 5, 2011 from http://www.hasil.gov.my/pdf/pdfam/AR2007_2.pdf.
Atchariyachanvanich, K., Okada, H., & Sonehara, N. (2006). What keeps online customers repurchasing through the internet? ACM SIGecom Exchanges, 6(2), 47–57.
Aziz, S. A., & Idris, K. M. (2012). The determinants of tax e-filing among tax preparers in Malaysia. World Journal of Social Sciences, 2(3), 182–188.
Bhatnagar, S. (2009). Unlocking e-Government potential: Concepts, cases and practical insights. 1st (Ed.) SAGE Publications India Pvt Ltd.
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370.
Chea, S., & Luo, M.M. (2007). Cognition, emotion, satisfaction, and post-adoption behaviors of e-service customers. Proceedings of the 40th Annual Hawaii International Conference on System Sciences (HICSS), 154. January 2007.
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.
Chen, S. C., Chen, H. H., & Chen, M. F. (2009). Determinants of satisfaction and continuance intention towards self-service technologies. Industrial Management and Data Systems, 109(9), 1248–1263.
Chin, W.W. (2010). How to write up and report PLS Analyses. Handbook of partial least squares: Concepts, methods and applications In V. Esposito Vinzi et al. (Eds.), Springer Handbooks of Computational Statistics (pp. 655–689). Berlin: Springer.
Chin, W.W. (1998). Commentary: Issues and opinion on structural equation modeling. Management Information Systems Quarterly, 22(1), 7–16.
Chiu, C. M., Hsu, M. H., Sun, S. Y., Lin, T. C., & Sun, P. C. (2005). Usability, quality, value and e-learning continuance decisions. Computers and Education, 45(4), 399–416.
Chou, S. W., & Chen, P. Y. (2009). The Influence of individual differences on continuance intentions of enterprise resource planning (ERP). International Journal of Human Computer Studies, 67(6), 484–496.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 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, 15(8), 982–1003.
Deng, L., Turner, D. E., Gehling, R., & Prince, B. (2010). User experience, satisfaction, and continual usage intention of IT. European Journal of Information Systems, 19, 60–75.
Doong, H.S., Wang, H.C., & Chen, P.H. (2007). An empirical study of online reputation system continuance. International Conference on Wireless Communications, Networking and Mobile Computing, 3816–3819.
Eriksson, K., & Nilsson, D. (2007). Determinants of the continued use of self-service technology: The Case of internet banking. Technovation, 27(4), 159–167.
Fornell, C., & Cha, J. (1994). Partial least squares. In R. P. Bagoozi (Ed.), Advanced methods of marketing research (pp. 52–78). Cambridge: Blackwell.
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, Jr, Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). New Jersey: Pearson Prentice Hall.
Hasmah, A. (2009). E-filing pays. Retrieved April 12, 2010 from http://www.intanbk.intan.my/i-portal/nict/nict/DAY1/SESSION3PARALLEL1(SESSION3A)/Dato_hasmah_e-filing_Pays.pdf.
Hayashi, A., Chen, C., Ryan, T., & Wu, J. (2004). The role of social presence and moderating role of computer self efficacy in predicting the continuance usage of e-learning systems. Journal of Information Systems Education, 15(2), 139–154.
Hesson, M., & Al-Ameed, H. (2007). Online security evaluation process for new e-services. Journal of Business Process Management, 13(2), 223–245.
Hung, M. C., Chang, I. C., & Hwang, H. G. (2011). Exploring academic teachers continuance toward the web-based learning system: The role of causal attributions. Computers and Education, 57(2), 1530–1543.
Hussein, R., Mohamed, N., Ahlan, A.R., Mahmud, M., & Aditiawarman, U. (2010). An integrated model on online tax adoption in Malaysia. European, Mediterranean & Middle Eastern Conference on Information Systems (EMCIS), 1–16.
Hsu, M. H., & Chiu, C. M. (2004). Predicting electronic service continuance with a decomposed theory of planned behaviour. Behaviour and Information Technology, 23(5), 359–373.
Hwang, Y.E., Suh, H.J., & Suh, H.S. (2007). An empirical research on factors affecting continued intention to use mobile internet services in Korea. Proceedings of the International Conference on Management of Mobile Business, 56(1), 31–39.
Islam, A. K. M. N. (2012). The role of perceived system quality as educators motivation to continue e-learning system use. AIS Transactions on Human-Computer Interaction, 4(1), 25–43.
Jiang, X. (2011). Enhancing users continuance intention to e-government portals: An empirical study. International Conference on Management and Service Science (MASS), China, 1–4, August 12–14.
Kaliannan, M., Awang, H., & Raman, M. (2010). Public-private partnerships for e-Government services: Lessons from Malaysia. International Journal of Institutions and Economies, 2(2), 201–220.
Kang, Y. S., & Lee, H. (2010). Understanding the role of an IT artifact in online service continuance: An extended perspective of user satisfaction. Computers in Human Behavior, 26(3), 353–364.
Kim, B. (2010). An empirical investigation of mobile data service continuance: Incorporating the theory of planned behavior into the expectation–confirmation model. Expert Systems with Applications, 37(10), 7033–7039.
Kim, H. W., Chan, H. C., & Chan, Y. P. (2007). A balanced thinking-feelings model of information systems continuance. International Journal of Human Computer Studies, 65(6), 511–525.
Lee, M. C. (2010). Explaining and predicting users continuance intention toward e-learning: An extension of the expectation-confirmation model. Computers and Education, 54(2), 506–516.
Lee, Y., & Kwon, O. (2010). Intimacy, familiarity and continuance intention: An extended expectation–confirmation model in web-based services. Electronic Commerce Research and Applications, Article in press.
Liao, C., Palvia, P., & Chen, J. L. (2009). Information technology adoption behavior life cycle: Toward a technology continuance theory (TCT). International Journal of Information Management, 29(4), 309–320.
Limayem, M., & Cheung, C. M. K. (2008). Understanding information system continuance: The case of internet-based learning technologies. Information and Management, 45(4), 227–232.
Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intention: The case of information system continuance. MIS Quarterly, 31(4), 705–737.
Limayem, M., Hirt, S.G., & Chin, W.W. (2001). Intention does not always matter: The contingent role of habit on IT usage behavior. The 9th European Conference on Information Systems, 274–286.
Lin, C. S., Wu, S., & Tsai, R. J. (2005). Integrating perceived playfulness into expectation-confirmation model for web portal context. Information and Management, 42(5), 683–693.
Min, Q., & Shenghua, X. (2007). An extended expectation confirmation model for information systems continuance. Proceeding of the International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM), 21–25 September, 3879–3882.
Muhammad Rais, A.K., & Nazariah, M.K. (2003). E-Government in Malaysia. Pelanduk publications (M) Sdn Bhd.
New Straits Times (NST). (2012). 15 % increase in e-filing, says LHDN. Retrieved February 14, 2013 from http://www.nst.com.my/latest/15-per-cent-increase-in-e-filing-says-lhdn-1.91623.
Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460–469.
Ong, C.S., & Day, M.Y. (2010). An integrated evaluation model of user Satisfaction with social media services. Proceeding of the International Conference on Information Reuse and Integration (IRI), 4–6 August, 195–200.
Roca, J. C., Chiu, C. M., & Martinez, F. J. (2006). Understanding e-Learning continuance intention: An extension of the technology acceptance model. International Journal of Human-Computer Studies, 64(8), 683–696.
Shiau, W. L., Huang, L. C., & Shih, C. H. (2011). Understanding continuance intention of blog users: A perspective of flow and expectation confirmation theory. Journal of Convergence Information Technology, 6(4), 306–317.
Spreng, R. A., MacKenzie, S. B., & Olshavsky, R. W. (1996). A reexamination of the determinants of consumer satisfaction. Journal of Marketing, 60(3), 15–32.
Thong, J. Y. L., Hong, S. J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human Computer Studies, 64(9), 799–810.
Wang, T., Oh, L.B., Wang, K., & Zhang, B. (2010). An empirical study of the impact of trial experiences on the continued usage of mobile newspapers. Proceeding of the Pacific Asia Conference on Information Systems (PACIS), Paper 112, 1148–1159.
Wangpipatwong, S., Chutimaskul, W., & Papasratorn, B. (2008). Understanding citizens continuance intention to use e-government website: A composite view of technology acceptance model and computer self-efficacy. The Electronic Journal of e-government, 6(1), 55–64.
Wetzels, M., Schroder, G. O., & Oppen, Cv. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quarterly, 33(1), 177–195.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendix
Appendix
Measures
-
(1)
Confirmation
-
(a)
My experience with using e-filing was better than what I expected
-
(b)
The service level provided by e-filing was better than what I expected
-
(c)
Overall, most of my expectation from using e-filing were confirmed.
-
(a)
-
(2)
Perceived Usefulness
-
(a)
Using e-filing enables me to file my tax more quickly
-
(b)
Using e-filing enhances my effectiveness in filing my taxes
-
(c)
Using e-filing saves my time in filing my taxes
-
(d)
I finds that e-filing is useful in filing my taxes.
-
(a)
-
(3)
Satisfaction
-
(a)
My overall experience with e-filing usage was: very satisfied
-
(b)
My overall experience with e-filing usage was: very pleased
-
(c)
My overall experience with e-filing usage was: very contended
-
(d)
My overall experience with e-filing usage was: absolutely delighted.
-
(a)
-
(4)
Continuance Intention
-
(a)
I will use the e-filing system in the future
-
(b)
I intend to continue using the e-filing rather than discontinue its use
-
(c)
My intentions are to continue using e-filing than use any alternative means (manual filing)
-
(d)
If I could, I would like to continue using e-filing as much as possible.
-
(a)
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media New York
About this chapter
Cite this chapter
Santhanamery, T., Ramayah, T. (2014). Explaining the e-Government Usage Using Expectation Confirmation Model: The Case of Electronic Tax Filing in Malaysia. In: Anthopoulos, L., Reddick, C. (eds) Government e-Strategic Planning and Management. Public Administration and Information Technology, vol 3. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8462-2_15
Download citation
DOI: https://doi.org/10.1007/978-1-4614-8462-2_15
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-8461-5
Online ISBN: 978-1-4614-8462-2
eBook Packages: Business and EconomicsEconomics and Finance (R0)