Consumer adoption of on‐demand digital platforms: An integrated model
Open accessAbstract
On‐demand digital platforms are omnipresent in the contemporary marketplace of the digital era. The purpose of this study was to assess the factors influencing consumers’ intention to adopt on‐demand digital platforms in the context of a developing country. Based on a modified integration of the unified theory of acceptance and use of technology (UTAUT) and the social influence theory, this study contended that electronic word‐of‐mouth (eWOM) about on‐demand digital platforms shapes consumers' perceived risk and subjective norms, which, along with the other elements of UTAUT, influence their intention to use on‐demand digital platforms. A self‐administered questionnaire was developed and distributed online, yielding a total of 226 responses, which were analyzed using partial least squares structural equation modelling. The findings revealed that performance expectancy, effort expectancy, subjective norms, and perceived risk significantly affect consumers’ intention, wherein eWOM reduces perceived risk and shapes subjective norms to adopt on‐demand digital platforms. Therefore, this study contributes to the literature on consumer adoption of new‐age digital products, and in this case, on‐demand digital platforms, with implications for theory and practice in this space.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Perceived risk is a critical factor in the adoption and use of platform economy because it reflects users' beliefs about potential losses and negative consequences associated with using these platforms.
“Perceived risk is a critical factor in the adoption and use of platform economy because it reflects users' beliefs about potential losses and negative consequences associated with using these platforms [59].”
Perceived risk significantly influences users' intentions and actual use of the platform economy.
“Our study found that perceived risk and privacy concerns significantly influence users' intentions and actual use of the platform economy [3,59].”
Privacy concerns significantly influence users' intentions and actual use of the platform economy.
“Our study found that perceived risk and privacy concerns significantly influence users' intentions and actual use of the platform economy [3,59].”
The citation lists haven’t been fetched yet
References 91 · Cited by 41
- Authors
- Lim, T., Lim, B. C., Leong, C., Phang, I. G., & Foong, W. H.
- Affiliations
- Faculty of Business, Design and Arts Swinburne University of Technology Kuching Malaysia
- UCSI University (MY)
- Faculty of Business, Economics and Accounting Universiti Malaysia Sabah Kota Kinabalu Malaysia
- Corresponding author
- Lim, Bibiana Chiu‐Yiong
- Venue
- Global Business and Organizational Excellence
- Publisher
- Wiley
- Published
- 2023-03-09
- Volume
- 42
- Issue
- 6
- Pages
- 75-88
- ISSN
- 1932-2054 (ISSN-L)
- 1932-2062
- OpenAlex
- W4323660529
- Cited by
- 41
- References
- 91
- Citations by year
- 2026: 10 · 2025: 4 · 2024: 15 · 2023: 12
- FWCI
- 10.55
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Global Business and Organizational Excellence (publishedVersion, cc-by-nc)
- UMS Institutional Repository (Universiti Malaysia Sabah) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
- Keywords
- consumer technology adoption, UTAUT, social influence theory, electronic word of mouth, risk perception, subjective norms, performance expectancy, effort expectancy, intention to use, developing countries
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review