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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM66885
Volume:
10 |
8 |
Aug 2026
Pages:
1-10
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
MANAGEMENT
IMS BUSINESS SCHOOL
MANAGEMENT
IMS BUSINESS SCHOOL
MANAGEMENT
IMS BUSINESS SCHOOL
MANAGEMENT
INSTITUTE OF MANAGEMENT STUDY
Digital trust is a key driver of interactions in platform ecosystems, where reputation systems and consumer feedback reduce uncertainty and shape user behaviour. While prior research highlights the influence of online reviews, credibility, and platform-based trust on user intentions and e-commerce adoption, studies often examine these elements in isolation, leaving a gap in integrating behavioural, technological, and ecosystem-level perspectives, particularly in emerging markets like India. This study addresses this gap by identifying key trust-building mechanisms and examining the influence of consumer feedback on user perceptions using a qualitative approach based on systematic literature synthesis and thematic analysis. The study develops an integrated Stimulus–Organism–Response (S-O-R) and Technology Acceptance Model (TAM) framework, where stimuli include ratings, reviews, and feedback credibility; organism factors comprise perceived usefulness, ease of use, trust, and risk; and responses involve usage, engagement, and loyalty, with governance mechanisms acting as moderating and mediating factors. Findings reveal that trust serves as a critical bridge between feedback systems and technology acceptance, as credible reviews, strong e-service quality, and transparent governance enhance perceived usefulness, reduce risk, and foster a self-reinforcing trust loop, leading to sustained engagement and platform success; these findings imply that platform managers should prioritize review authenticity, service quality, and robust governance to strengthen user trust and long-term performance.
KEYWORDS
Digital trust is a key driver of success in platform ecosystems, shaping user interaction, engagement, and decision-making. Reputation systems and consumer feedback reduce uncertainty by providing reliable information, enabling informed choices. The integration of the S-O-R and TAM models offers a comprehensive framework that captures both technological and behavioural aspects of trust formation. Trust is dynamic and evolves through ongoing interactions between platform features, user perceptions, and governance mechanisms. Factors such as perceived usefulness, ease of use, feedback credibility, and transparency collectively influence its development. Therefore, platforms must ensure authentic reviews, high service quality, and strong governance to build and sustain user confidence. Future research should focus on empirical validation, cross-cultural analysis, and advanced modelling to further test and refine this framework across diverse digital contexts.
1. Gefen, D., Karahanna, E., & Straub, D. (2003). Trust and TAM in online shopping. MIS Quarterly, 27(1), 51–90. 2. Pavlou, P. A. (2003). Consumer acceptance of electronic commerce. International Journal of Electronic Commerce, 7(3), 101–134. 3. Davis, F. D. (1989). Perceived usefulness and ease of use. MIS Quarterly, 13(3), 319–340. 4. Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3. Decision Sciences, 39(2), 273–315. 5. Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. MIT Press. 6. Resnick, P., Zeckhauser, R., Friedman, E., & Kuwabara, K. (2000). Reputation systems. Communications of the ACM, 43(12), 45–48. 7. Chevalier, J. A., & Mayzlin, D. (2006). Effect of word of mouth. Journal of Marketing Research, 43(3), 345–354. 8. Filieri, R. (2015). What makes online reviews helpful? Tourism Management, 46, 126– 138. 9. Mudambi, S. M., & Schuff, D. (2010). What makes a helpful review? MIS Quarterly, 34(1), 185–200. 10. Kim, J., & Lennon, S. (2013). Effects of reputation and website quality. Journal of Interactive Marketing, 27(1), 68–82.
Publication Date
8/21/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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