Model Integratif TAM, Kepercayaan, dan Kelengkapan Fitur terhadap Volume Transaksi Saham Investor Ritel
-
Aloysius Agus Subagyo
*
Universitas Teknologi Digital Indonesia, Yogyakarta,
Indonesia
- Ivan Jaka Perdana Universitas Teknologi Digital Indonesia, Yogyakarta, Indonesia
- Heru Agus Triyanto Universitas Teknologi Digital Indonesia, Yogyakarta, Indonesia (*) Corresponding Author
Abstract
The number of stock investors on the Indonesia Stock Exchange grew steadily from 5.26 million Single Investor Identifications (SID) at the end of 2023 to 6.38 million at the end of 2024 and 8.59 million at the end of 2025, alongside a surge in total consolidated capital-market investors to 20.32 million SID; this growth was largely driven by mobile-based stock trading applications that lowered the barriers to entering the capital market. This study analyzes the influence of trading application quality on the stock transaction volume of retail investors through four user-experience dimensions: perceived ease of use, perceived usefulness, trust, and trading feature completeness. Transaction volume rather than investment intention was chosen as the dependent variable because it represents actual trading behavior more closely tied to market liquidity and real economic impact. A quantitative explanatory approach was applied by distributing online questionnaires to 312 retail investors using trading applications in Indonesia through purposive sampling, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The results indicate that all four variables have a positive and significant effect on transaction volume (p < 0.05), with trading feature completeness as the strongest predictor (β = 0.341; t = 5.213), followed by perceived usefulness (β = 0.287; t = 4.125), trust (β = 0.218; t = 3.412), and perceived ease of use (β = 0.176; t = 2.847); the model explains 62.4% of the variance in transaction volume (R² = 0.624; Q² = 0.387). The novelty of this study lies in developing an integrative TAM–Trust–Feature Completeness model relevant to the Indonesian e-brokerage context during the 2023–2025 digital maturation phase. Practically, the findings direct securities firms to prioritize analytical-feature development and to strengthen security and transparency, while for regulators (OJK and BEI) they underscore the urgency of minimum feature standards, fee transparency, and digital literacy to protect retail investors from noise-trading risks.
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