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生成式AI接受与持续使用:TAM-ECM整合机制

Generative AI Use Beyond Initial Adoption: Linking TAM and ECM Across Continued Use, Pauses, and Return

作者:王晨
单位:江西枫林涉外经贸职业学院
卷期:2026年11月-2卷11期
通讯作者:王晨
页码:30-37
发布时间:2026-11-05
总浏览量:124

摘要

生成式人工智能进入日常学习和知识工作的速度很快,但“开始使用”并不能说明用户之后会怎样选择。本文据此把研究视线由首次采纳向使用后的行为变化延伸,并以技术接受模型(TAM)和期望确认模型(ECM)为主要分析线索,对相关研究作叙述性梳理。文章先讨论用户接触技术时对有用性、易用性、风险、AI素养和信任的判断,再考察真实任务经验如何改变这些认识。实际使用后,模型表现是否符合预期、核验需要付出多少成本以及任务结果是否可接受,都会进入下一轮评价,并影响满意度及后续选择。由此,本文不把持续使用视为唯一结果,而将继续使用、阶段性停用和重新采用置于同一过程之中,同时讨论任务—技术匹配、AI疲劳与认知卸载可能造成的差异。本文提出的是概念框架,其关系仍需通过纵向追踪、行为日志等资料验证。

关键词

生成式人工智能;技术接受模型;期望确认模型;持续使用;中辍行为;用户行为

Abstract

This conceptual paper examines generative AI use as a sequence of judgments rather than a one-time adoption decision. TAM is used to describe how users approach the technology before or during early use, whereas ECM is used to interpret evaluation after experience has accumulated. The analysis distinguishes expectations formed before substantial use from judgments made after users complete real tasks. At the earlier stage, perceived usefulness, ease of use, risk, AI literacy, and calibrated trust are relevant to adoption. Later, users reassess the technology in light of whether expectations were met, how useful the tool proved in practice, how satisfied they were, and how much checking or correction was required. Continued use is therefore treated alongside temporary discontinuance and subsequent return. Task-technology fit, AI fatigue, and cognitive offloading are discussed as conditions that may change these transitions. The framework remains conceptual and should be tested with longitudinal observations and behavioral records.

Keywords

generative artificial intelligence; technology acceptance model; expectation-confirmation model; continuance use; discontinuance; user behavior

引用本文

王晨. 生成式AI接受与持续使用:TAM-ECM整合机制[J]. 人文与社会科学学刊. 2026, 2 (11): 30-37. DOI: 10.70693/202610077735.

APA引用

王晨. (2026). 生成式AI接受与持续使用:TAM-ECM整合机制. 人文与社会科学学刊, 2 (11), 30-37. https://doi.org/10.70693/202610077735

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CC BY 本文依据 知识共享署名 4.0 国际许可协议 授权发布。允许他人在署名原作者及来源的前提下复制、传播和使用本文。

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