Understanding Impact of Information System Quality on Software as a Service: An Empirical Study

  • Taqwa Hariguna Southern Taiwan University of Science Taiwan
  • Min Tsai Lai Southern Taiwan University of Science Taiwan
  • Shih Chih Chen Southern Taiwan University of Science Taiwan

Abstract

 Cloud computing specially on Software as a Service (SaaS) is currently powerful instrument and has attracted substantial attention from industrial, practitioners and academics. This paper aimed to develop an integrated model designed to predict, to examine and to understand information system quality on Software as a Service during the formation of sustainable of continuous intention of customers in cloud computing contexts. The participants were from 144 samples, most of respondents were CIOs and CEOs. Structural equation modeling was applied to demonstrate the stability of the proposed model and the results of hypotheses testing. The analysis results demonstrated that customers’ continuous intention and customers’ satisfaction were determined significantly by SaaS Quality. Satisfaction was also the significant motivator of customers’ continuous intention. The differences among various types of SaaS application were not analyzed. This study suggests that future studies should extend research including users of various SaaS applications such as office application software, enterprise resource plan, customer relationship management system and so on. This paper proposed a comprehensive model to synthesize the essence of SaaS quality for explaining customers’ satisfaction and customers’ continuous intention of SaaS.

References

[1] Chou, D., Chou, A. (2007). Analysis of a new information systems outsourcing practice: Software-as-a-service business model. International Journal of Information Systems and Change Management, 2 (4) 392–405. [2] DeLone,W.H., McLean, E. R. (2003). The DeLone and McLean model of information system success: A ten-year update. Journal of Management Information Systems, 19 (4) 9–30. [3] DeLone, W. H., McLean, E. R. (1992). Information system success: The quest for the dependent variable. Information Systems Research, 3 (1) 60–95. [4] Pitt, L. F., Watson, R. T., Kavan, C. B. (1995). Service quality: Ameasure of informa- tion systems effectiveness. MIS Quarterly, 19 (2) 173–188. [5] Seddon, P. B. (1997). A respecification and extension of the DeLone and McLean model of IS success. Information Systems Research, 8 (3) 240–253. [6] Rai, A., Lang, S. S., Welker, R. B. (2002). Assessing the validity of IS success models: An empirical test and theoretical analysis. Information Systems Research, 13 (1) 50–69. [7] DeLone, W. H., McLean, E. R. (2004). Measuring e-commerce success: Applying the DeLone & McLean information system success model. International Journal of Electronic Commerce, 9(1) 31–47. [8] Bradley, R. V., Pridmore, J. L.,Byrd, T. A. (2006). Information systems success in the context of different corporate cultural types: An empirical investigation. Journal of Management Information Systems, 23(2) 267–294. [9] Liu, C., Arnett, K. P. (2000). Exploring the factors associated with web site success in the context of electronic commerce. Information & Management, 38 (1) 23–33. [10] Kim, C., Oh, E., Shin, N., Chae, M. (2009). An empirical investigation of factors affecting ubiquitous computing use and Ubusiness value. International Journal of Information Management, 29(6) 436–448. [11] Chen, C. W. (2010). Impact of quality antecedents on taxpayer satisfaction with online tax-filing systems-An empirical study. Information and Management. 47, 308–315. [12] Yang, Z., Sun, J., Zhang, Y., Wang, Y. (2015). Computers in Human Behavior Understanding SaaS adoption from the perspective of organizational users : A tripod readiness model. Computers in Human Behavior, 45, 254–264. [13] Noura Limam, R. B. (2010). Assessing Software Service Quality and Trustworthiness at Selection Time. IEEE Transactions on Software Engineering, 36 (4). [14] Du, J., Dean, D. J., Tan, Y., Gu, X., Yu, T. (2014). Scalable Distributed Service Integrity Attestation for Software-as-a-Service Clouds. IEEE Transactions on Parallel and Distributed Systems, 25 (3) 730–739. [15] Ma, D., Kauffman, R. J. (2014). Competition Between Software-as-a-Service Vendors, 61 (4) 717–729. [16] Rohitratana, J., Altmann, J. (2012). Impact of pricing schemes on a market for Software-as-a-Service and perpetual software. Future Generation Computer Systems, 28 (8) 1328–1339. [17] Wu, L., Kumar Garg, S., Buyya, R. (2012). SLA-based admission control for a Software-as-a-Service provider in Cloud computing environments. Journal of Computer and System Sciences, 78(5) 1280–1299. [18] Du, J., Lu, J., Wu, D., Li, H., Li, J. (2013). User acceptance of software as a service: Evidence from customers of China’s leading e-commerce company, Alibaba. Journal of Systems and Software, 86 (8) 2034–2044. [19] Chou, S. W., Chiang, C. H. (2013). Understanding the formation of software-as-a-service (SaaS) satisfaction from the perspective of service quality. Decision Support Systems, 56 (1) 148–155. [20] Goode, S., Lin, C., Tsai, J. C., Jiang, J. J. (2015). Rethinking the role of security in client satisfaction with Software-as-aService (SaaS) providers. Decision Support Systems, 70, 73–85.[21] Lee, S. G., Chae, S. H., Cho, K. M. (2013). Drivers and inhibitors of SaaS adoption in Korea, International Journal of Information Management, 33 (3) 429–440. [22] Benlian, A., Koufaris, M., Hess, T. (2012). Service Quality in Software-as-a-Service: Developing the SaaS-Qual Measure and Examining Its Role in Usage Continuance. Journal of Management Information Systems, 28 (3) 85–126. [23] Benlian, A., Hess, T. (2011). Opportunities and risks of software-as-a-service: Findings from a survey of IT executives. Decision Support Systems, 52(1) 232–246. [24] Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation confirmation model, MIS Quarterly, 25 351–370. [25] Premkumar, G., Bhattacherjee, A. (2008). Explaining information technology usage: A test of competing models. The International Journal of Management Science, 36(1) 64–75. [26] Abdelmaboud, A., Jawawi, D. N. a., Ghani, I., Elsafi, A., & Kitchenham, B. (2014). Quality of service approaches in cloud computing: A systematic mapping study. Journal of Systems and Software, 101, 159–179. [27] Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17 (4) 460-469. [28] Hong, W.Y., Thong, J.Y.L., Wong, W.M., Tam, K.Y. (2001). Determinants of user acceptance of digital libraries: an empirical examination of individual differences and system characteristics. Journal of Management Information Systems 18 (3) 97–124. [29] 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. [30] Bhattacherjee, A., Perols, J., Sanford, C. (2008). Information technology continuance: a theoretic extension and empirical test. Journal of Computer Information Systems, 49. 17–26. [31] Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295 (2) 295–336. [32] Chin, W.W., Newsted, P.R. (1999). Structural equation modelling analysis with samples using partial least squares. In: Hoyle, R. (Ed.), Statistical Strategies for Small Sample Research. Sage, Thousand Oaks, CA, p. 307–341. [33] Urbach, N., Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. J. Inf. Technol. Theory Appl. 11, 5–40. [34] Fornell, C., Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18 (1) 39-50. [35] Hair, J.F., Ringle, C.M., Sarstedt, M. (2011a). PLS-SEM: indeed a silver bullet. Journal of Marketing Theory and Practice, 19 (2) 139-151. [36] Sobel, M.E. (1982). Asymptotic intervals for indirect effects in structural equations models. In: Leinhart, S. (Ed.) Sociol. Methodol.Jossey-Bass, San Francisco, 290–312. [37] Komppula, R., Gartner, W.C. (2012). Hunting as a travel experience: an auto-ethnographic study of hunting tourism in Finland and the USA. Tour. Manag. 35, 168–180.
Published
2025-01-31
How to Cite
HARIGUNA, Taqwa; LAI, Min Tsai; CHEN, Shih Chih. Understanding Impact of Information System Quality on Software as a Service: An Empirical Study. International Journal of Information Studies, [S.l.], v. 8, n. 4, jan. 2025. ISSN 2278-6511. Available at: <https://dline.info/ojs/index.php/ijis/article/view/520>. Date accessed: 23 apr. 2026.