As digital technologies increasingly reshape service use across sectors such as education, finance, healthcare, and hospitality, understanding technology acceptance and continued usage remains a central issue in information systems research. The Technology Acceptance Model (TAM) and its extensions have been widely applied in digital contexts; however, growing model complexity and construct proliferation have raised concerns regarding theoretical coherence and cumulative knowledge development. This study presents a structured narrative review of TAM and its foundational theories—the Theory of Reasoned Action (TRA) and the Theory of Planned Behavior (TPB)—based on empirical studies published between 2021 and 2025. Drawing on applications in digital banking, online learning, social media, artificial intelligence, and service automation, the review synthesizes how core acceptance constructs, including perceived usefulness, perceived ease of use, attitude, subjective norms, and perceived behavioral control, have been operationalized and extended. The findings show that while extended models such as TAM2, TAM3, and UTAUT improve predictive performance, their increasing complexity often results in limited theoretical advancement and inconsistent findings. This review highlights enduring core acceptance mechanisms and identifies key tensions between explanatory power and conceptual clarity, offering an integrated framework for future technology acceptance research in digital and educational contexts.
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