Factors Impacting Satisfaction and Continuance Intention of Art and Design Students to Study with Online Education in Chengdu, China

Authors

  • Hong Dong

DOI:

https://doi.org/10.14456/shserj.2024.2
CITATION
DOI: 10.14456/shserj.2024.2
Published: 2024-03-01

Keywords:

System Quality, Service Quality, Information Quality, Satisfaction, Continuance Intention

Abstract

Purpose: This research aims to investigate factor impacting satisfaction and continuance intention of undergraduates majoring in art and design on online learning of handicrafts in four public universities in Chengdu, China. The key variables are perceived ease of use, perceived usefulness, system quality, service quality, information quality, satisfaction, and continuance intention. Research design, data, and methodology: Questionnaires were distributed to 500 target population, and 487 is valid after the data screening. The sampling method involves judgmental, quota and convenience sampling. The main statistical analysis tools are confirmatory factor analysis (CFA) and structural equation modeling (SEM). Results: The results support all hypotheses in this study. Perceived ease of use significantly impacts perceived usefulness. System quality, information quality and service quality significantly impact satisfaction. Perceived usefulness has a significant impact on satisfaction and continuance intention. Satisfaction significantly impacts continuance intention. Conclusions: Teaching workers must explore online teaching methods that combine perceived ease of use and perceived usefulness, design systematic theoretical and practical courses according to different disciplinary backgrounds, and enhance the relevance and synergy of relevant knowledge and skills in different courses. The Continuance Intension of online learning can be effectively enhanced by enabling students to master new knowledge and skills in online learning truly.

Author Biography

Hong Dong

School of Fine Arts and Design, Chengdu University, China.

References

Ahn, T., Ryu, S., & Han, I. (2007). The impact of Web quality and playfulness on user acceptance of online retailing. Information & Management, 44(3), 263-275. https://doi.org/10.1016/j.im.2006.12.008

Al-dweeri, R. M., Moreno, A. R., Montes, F. J. L., Obeidat, Z. M., & Al-Dwairi, K. M. (2019). TheEffect of E-Service Quality on Jordanian Student’s E-Loyalty: An Empirical Study in Online Retailing. Industrial Management and Data Systems, 119(4), 902-923. https://doi.org/10.1108/imds-12-2017-0598

Alrousan, M. K., Al-Madadha, A., Al Khasawneh, M. H., & Adel Tweissi, A. (2022). Determinants of virtual classroom adoption in Jordan: the case of princess Sumaya university for technology. Interactive Technology and Smart Education, 19(2), 121-144. https://doi.org/10.1108/ITSE-09-2020-0211

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. https://doi.org/10.1037/0033-2909.103.3.411

Bagozzi, R., & Yi, Y. (1988). On the Evaluation of Structural Equation Models. Journal of the Academy of Marketing Sciences, 16, 74-94.

Balog, A. (2011). Testing A Multidimensional and Hierarchical Quality Assessment Model for Digital Libraries. Studies in Informatics and Control, 20(3), 233-246. https://doi.org/10.24846/v20i3y201104

Bentler, P. M., & Bonett, D. G. (1980). Significance Tests and Goodness of Fit in the Analysis of Covariance Structures. Psychological Bulletin, 88(3), 588-606. https://doi.org/10.1037/0033-2909.88.3.588

Bhattacherjee, A. (2001). Understanding Information Systems Continuance: An Expectation - Confirmation Model. MIS Quarterly, 25(3), 351. https://doi.org/10.2307/3250921

Blessinger, P., & Wankel, C. (2013). Novel Approaches in Higher Education: An Introduction to Web 2.0 and Blended Learning Technologies. In C. Wankel & P. Blessinger (Eds.), Increasing Student Engagement and Retention in e-learning Environments: Web 2.0 and Blended Learning Technologies (pp. 3-16). Emerald Group Publishing Limited. https://doi.org/10.1108/S2044-9968(2013)000006G003

Brown, M. W., & Cudeck, R. (1992). Alternative Ways of Assessing Model Fit. Sociological Methods & Research, 21(2), 230-258. https://doi.org/10.1177/0049124192021002005

Byrne, B. M. (2010). Structural Equation Modeling With AMOS: Basic Concepts, Applications, And Programming (2nd ed.). Routledge Taylor & Francis Group.

Cao, M., Zhang, Q., & Seydel, J. (2005). B2C E-Commerce Web Site Quality: An Empirical Examination. Industrial Management & Data Systems,105(5), 645-661. https://doi.org/10.1108/02635570510600000

Cao, Y., & Jittawiriyanukoon, C. (2022). Factors Impacting Online Learning Usage during Covid-19 Pandemic Among Sophomores in Sichuan Private Universities. AU-GSB E-JOURNAL, 15(1), 152-163. https://doi.org/10.14456/augsbejr.2022.52

Chen, H.-J. (2010). Linking employees' e-learning system use to their overall job outcomes: An empirical study based on the IS success model. Computers & Education, 55(4), 1628-1639. https://doi.org/10.1016/j.compedu.2010.07.005

Cheng, Y.-M. (2014). Extending the expectation-confirmation model with quality and flow to explore nurses' continued blended e-learning intention. Information Technology & People, 27(3), 230-258. https://doi.org/10.1108/itp-01-2013-0024

Chin, W. W. (1998). The Partial Least Squares Approach to Structural Equation Modeling. Modern Methods for Business Research, 295(2), 295-336.

Churchill, G. A. (1979). A Paradigm for Developing Better Measures of Marketing Constructs, Journal of Marketing Research, 16(1), 64-73. https://doi.org/10.2307/3150876

Clark-Carter, D. (2018). Quantitative Psychological Research: The Complete Student’s Companion. Taylor & Francis Ltd, 7(10), 1-10.

Cooper, D. R., & Schindler, P. S. (2011). Business Research Methods (11th ed.). Sage Publications Inc.

Davis, F. D. (1993). User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts. International Journal of Man-Machine Studies, 38(3), 475-487. https://doi.org/10.1006/imms.1993.1022

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. https://doi.org/10.1287/mnsc.35.8.982.

DeLone, W. H., & McLean, E. R. (2003). The DeLone and Mclean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems, 19(4), 9-30.

Filippini, R., Forza, C., & Vinelli, A. (1998). Trade-off and compatibility between performance: Definitions and empirical evidence. International Journal of Production Research, 36(12), 3379-3406. https://doi.org/10.1080/002075498192111

Gu, L., & Wang, J. (2015). A Task Technology Fit Model on E-Learning. Information Systems,16(1), 163-169.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th ed.). Prentice-Hall.

Hair, J. F., Celsi, M. W., Oritinau, D. J., & Bush, R. P. (2013). Essentials of Marketing Research (1st ed.). John Wiley & Sons Ltd.

Hassanzadeh, A., Kanaani, F., & Elahi, S. (2012). A Model for Measuring E-Learning Systems Success in Universities. Expert Systems with Applications, 39(12), 10959-10966. https://doi.org/10.1016/j.eswa.2012.03.028

Hu, L. T., & Bentler, P. M. (1999). Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55. https://doi.org/10.1080/10705519909540118

Hulland, J. (1999). Use of Partial Least Squares (PLS) in Strategic Management Research: A Review of Four Recent Studies. Strategic Management Journal, 20(2), 195-204.

Islam, A. Y. M. A. (2011). Viability of the Extended Technology Acceptance Model: An Empirical Study. Journal of ICT, 10, 85-98.

Kettinger, W. J., & Lee, C. C. (1994). Perceived Service Quality and User Satisfaction with the Information Services Function. Decision Sciences, 25(5-6), 737-766. https://doi.org/10.1111/j.1540-5915.1994.tb01868.x

Kumar, A., Lee, H. J., & Kim, Y. K. (2009). Indian Consumers’ Purchase Intention toward a United States versus Local Brand. Journal of Business Research, 62(5), 521-527. https://doi.org/10.1016/j.jbusres.2008.06.018

Kurt, O. E. (2019). Examining an E-Learning System Through the Lens of the Information Systems Success Model: Empirical Evidence from Italy. Education and Information Technologies, 24(2), 1173-1184. https://doi.org/10.1007/s10639-018-9821-4

Laukkanen, T. (2007). Internet vs Mobile Banking: Comparing Customer Value Perceptions, Business Process Management Journal, 13(6), 788-797. https://doi.org/10.1108/14637150710834550

Liang, J.-C., Wu, S.-H., & Tsai, C.-C. (2011). Nurses’ Internet Self-Efficacy and Attitudes toward Web-Based Continuing Learning. Nurse Education Today, 31(8), 768-773. https://doi.org/10.1016/j.nedt.2010.11.021

Liao, Y.-W., Huang, Y.-M., & Wang, Y.-S. (2015). Factors Affecting Students' Continued Usage Intention Toward Business Simulation Games: An Empirical Study. Journal of Educational Computing Research, 53(2), 260-283. https://doi.org/10.1177/0735633115598751

Lin, K.-M., Chen, N.-S., & Fang, K. (2011). Understanding e-learning continuance intention: a negative critical incidents perspective. Behaviour & Information Technology, 30(1), 77-89. https://doi.org/10.1080/01449291003752948

Mathwick, C., Malhotra, N. K., & Rigdon, E. (2002). The Effect of Dynamic Retail Experiences on Experiential Perceptions of Value: An Internet and Catalog Comparison, Journal of Retailing, 78(1), 51-60.

Mertens, D. M. (2015). Research and Evaluation in Education and Psychology (1st ed.). SAGE Publications Ltd.

Mtebe, J. S., & Raphael, C. (2018). Key factors in learners' satisfaction with the e-learning system at the University of Dar es Salaam, Tanzania. Australasian Journal of Educational Technology, 34(4). https://doi.org/10.14742/ajet.2993

O’Leary, Z. (2017). The Essential Guide to Doing Yours Research Project (1st ed.). Sage Publications Inc.

Ojo, A. I. (2017). Validation of the DeLone and McLean Information Systems Success Model. Healthcare Informatics Research, 23(1), 60. https://doi.org/10.4258/hir.2017.23.1.60

Ozkan, S., & Koseler, R. (2009). Multi-Dimensional Students’ Evaluation of E-Learning Systems in the Higher Education Context: An Empirical Investigation. Computers & Education, 53(4), 1285-1296. https://doi.org/10.1016/j.compedu.2009.06.011

Panigyrakis, G. G., & Chatzipanagiotou, K. C. (2006). The Impact of Design Characteristics and Support Services on the Effectiveness of Marketing Information Systems: An Empirical Investigation. Review of Business Information Systems, 10(2), 91-104. https://doi.org/10.19030/rbis.v10i2.5328

Peter, C. S., Suan, M. S., Donald, A.-D., & Richard, S. (2009). Primary Care Validation of a Single-Question Alcohol Screening Test. Journal of General Internal Medicine, 24, 783-788.

Ramlall, I. (2017). Applied Structural Equation Modelling for Researchers and Practitioners (1st ed.). Emerald Group Publishing Limited.

Ritanjali, P., Praveen, R. S., & Prabin, K. P. (2019). Effectiveness of E-Learning: The Mediating Role of Student Engagement on Perceived Learning Effectiveness. Information Technology & People, 34(7), 1840-1862.

Robey, D., & Farrow, D. (1982). User Involvement in Information System Development: A Conflict Model and Empirical Test, Management Science, 28(1), 73-85. https://doi.org/10.1287/mnsc.28.1.73

Roca, J. C., & Gagne, M. (2008). Understanding E-Learning Continuance Intention in the Workplace: A Self-Determination Theory Perspective, Computers in Human Behavior, 24(4), 1585-1604. https://doi.org/10.1016/j.chb.2007.06.001.

Roca, J. C., Chiu, C.-M., & Martínez, 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. https://doi.org/10.1016/j.ijhcs.2006.01.003

Rogers, E. M. (1962). Diffusion of Innovations (1st ed.). Free Press.

Rotchanakitumnuai, S., & Speece, M. (2009). Modeling Electronic Service Acceptance of an E-Securities Trading System. Industrial Management & Data Systems, 109(8), 1069-1084. https://doi.org/10.1108/02635570910991300

Rust, R. T., & Oliver, R. L. (1994). Service Quality: Insights and Managerial Implication from the Frontier, in Rust, T. R. and Oliver, R. L. (Eds), Service Quality: New Directions in Theory and Practice (pp. 1-19). Sage. https://doi.org/10.4135/9781452229102.n1

Samarasinghe, S. M. (2012). E-Learning Systems Success in an Organizational Context: A Thesis Presented in Partial Fulfilment of the Requirements for the Degree of Doctor of Philosophy in Management Information Systems at Massey University (1st ed.). Doctoral dissertation.

Sandjojo, N., & Wahyuningrum, T. (2015). Measuring E-learning Systems Success: Implementing D&M is Success Model. 2015 4th International Conference on Interactive Digital Media (ICIDM), 1-6. https://doi.org/10.1109/idm.2015.7516343

Santos, J. (2003). E-service Quality: A Model of Virtual Service Quality Dimensions, Managing Service Quality: An International Journal, 13(3), 233-246. https://doi.org/10.1108/09604520310476490

Seta, H. B., Wati, T., Muliawati, A., & Hidayanto, A. N. (2018). E-Learning Success Model: An Extension of DeLone and Mclean IS’ Success Model. Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 6(3), 281-291.

https://doi.org/10.52549/ijeei.v6i3.505

Shaikh, A. A., & Karjaluoto, H. (2015). Making the most of Information Technology and Ssystems Usage: A Literature Review, Framework and Future Research Agenda, Computers in Human Behavior, 49, 541-566. https://doi.org/10.1016/j.chb.2015.03.059

Shih, H.-P. (2004). An Empirical Study on Predicting User Acceptance of E-Shopping on the Web. Information and Management, 41, 351-368.

Sudin, B., Payel, A., & Md, A. I. (2022). Behavioral Intention of “Digital Natives” Toward Adapting the Online Education System in Higher Education. Journal of Applied Research in Higher Education, 14(1), 16-40.

Tan, M., & Teo, T. S. H. (2000). Factors Influencing the Adoption of Internet Banking. Journal of the Association for Information Systems, 1, 1-44.

Theng, Y. L., Duncker, E., Mohd Nasir, N., Buchanan, G., & Thimbleby, H. (1999). Design Guidelines and User-Centered Digital Libraries. Proceeding ECDL’99, Paris, September 22-24, 167-183. https://doi.org/10.1007/3-540-48155-9_12

Timothy, A. B., & Michael, T. M. (2012). Confirmatory Factor Analysis (6th ed). Department of Psychology.

Van Birgelen, M. J. H., Wetzels, M., & Vandolen, W. M. (2008). Effectiveness of Corporate Employment Web Sites: How Content and Form Influence Intentions to Apply. International Journal of Manpower, 29, 731-751. https://doi.org/10.1108/01437720810919323

Yang, Z., Caib, S., Zhouc, Z., & Zhou, N. (2005). Development and Validation of An Instrument to Measure User Perceived Service Quality of Information Presenting Web Portals. Information & Management, 42(4), 575-89.

Zeithaml, V. A., & Bitner, M. J. (2000). Services Marketing: Integrating Customer Focus Across the Firm (1st ed.). McGraw-Hill. https://doi.org/10.1002/9781444316568.wiem01055

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Published

2024-03-01

How to Cite

Dong, H. (2024). Factors Impacting Satisfaction and Continuance Intention of Art and Design Students to Study with Online Education in Chengdu, China. Scholar: Human Sciences, 16(1), 12-21. https://doi.org/10.14456/shserj.2024.2