How do subscription-based products hook users? SaaS user satisfaction and continued purchasing from information ecology perspective
Purpose Users’ requirements are becoming increasingly important for the sustainability of subscription-based software as a service (SaaS). However, scholars have rarely considered the reverse construction of SaaS technical architecture from a user perspective. Design/methodology/approach In this study, we constructed a sustainable SaaS use model based on a user-driven core, information ecology theory (IET), and the integration of the expectation–confirmation model (ECM) with the task–technology matching model. We further examined the impacts of SaaS risk, users’ digital literacy, task–technology fit, and SaaS providers’ ability images on SaaS users’ satisfaction and use continuance intentions according to four dimensions: information environment, information person, information technology, and information. Findings The data analysis results showed that task–technology fit and SaaS providers’ ability images affected users’ satisfaction and perceived value, respectively, further affecting SaaS use continuance. An interesting finding was that the business level relied more on corporate ability management and digital literacy to assess value and risk, whereas the management level focused more on the overall impact of risk and corporate ability management on decision-making. Originality/value The SaaS information ecology–expectation–confirmation model (IE-ECM) proposed in this study organically combines IET and post-reception behaviour theories. In addition, it provides an important basis for SaaS service providers’ customer relationship management and customer retention strategies.
Authors
- Cong Cao (ORCID: https://orcid.org/0000-0003-4163-2218)
- Shanshan Huang (ORCID: https://orcid.org/0000-0002-4018-820X)
- Xiuyan Shao (ORCID: https://orcid.org/0000-0001-6550-9025)
- Miaomiao Zheng
Institutions
- Zhejiang University of Science and Technology (CN)
- Southeast University (BD)
- Zhejiang University of Technology (CN)
Publication Details
- Journal
- Industrial Management & Data Systems
- Published
- 2025-08-18
- DOI
- https://doi.org/10.1108/imds-05-2024-0436
- Citations
- 2
- Primary Topic
- Technology Adoption and User Behaviour
- Type
- article
- Field-Weighted Citation Impact
- 8.34