消费者特质与情境因素对技术接受的影响

Jon M. Martin
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引用次数: 0

摘要

本研究考察了基本技术接受模型(TAM)结构的内部关系及其与外部预测因子的关系:1)人口统计学(年龄、性别、收入、教育程度和种族);B)心理技术准备方面(乐观、创新、不适、不安全感);C)情景因素(等待时间和拥挤程度)。分析发现,年龄、等待时间和拥挤程度与三个TAM变量均有显著相关,而心理技术准备度变量与TAM的关系不显著。年龄、等待时间和拥挤程度与TAM变量(感知有用性、感知易用性和行为意图)之间的关系似乎是有效的和可推广的,并对SST采用研究具有影响。探索性研究省略了TAM的调节变量(感知有用性和感知易用性),并将年龄、等待时间和拥挤程度直接与行为意图进行回归,结果得出一个简单的4变量模型,该模型与行为意图具有显著的、中等强度的关系。这种替代模型为实践者提供了重要的机会和分支,值得额外的实证应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Consumer Trait and Situational Factor Determinants of Technology Acceptance
This study examines the internal relationships of the basic technology acceptance model (TAM) constructs and their respective relationships with external predictors from: a) demographics (age, gender, income, education, and ethnicity); b) psychographic tech readiness facets (optimism, innovativeness, discomfort, insecurity); c) situational factors (wait time and crowding).  Analysis concludes that age, wait time, and crowding have significant relationships with all three TAM variables, while psychographic tech readiness variables cannot be concluded to have significance with TAM.  The relationship of age, wait time, and crowding with TAM’s variables (perceived usefulness, perceived ease-of-use, and behavioral intention) appears valid and generalizable, and has implications for SST adoption research.  Exploratory research that omits TAM’s moderating variables (perceived usefulness and perceived ease-of-use) and that regresses age, wait time, and crowding directly with behavioral intention results in a simple 4-variable model that has significant, moderately strong relationships with behavioral intent.  This alternative model offers significant opportunities and ramifications for practitioners and deserves additional empirical applications.
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