The technology acceptance scale (TAS) by van der Laan, Heino, and De Waard (1997) measures the psychological construct of the same term as a sum of attitudes of an operator toward a specific complex sociotechnical system. The TAS has been claimed to comprise two subscales, usefulness and satisfaction. However, recent empirical work has found evidence for only one underlying factor. To provide further insight into the factor structure of the TAS, this study adopts a Bayesian exploratory factor analysis (BEFA) to analyse the data of a flight simulation study regarding single pilot operations. A series of Markov chain Monte Carlo (MCMC) models is used to assess the latent factor structure of the TAS for the two different crewing conditions and their corresponding workstation and cockpit setups of the copilot. A reliable step-by-step data analysis of the MCMC models provides evidence for a one-factor solution of the scale. The divergence to the previous studies which claim two factors can be due to the different applications as well as due to different statistical paradigms and methodological issues in exploratory factor analysis.

中文翻译：

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技术接受量表：通过马尔可夫链蒙特卡罗模型在因子分析中评估其贝叶斯心理测量学

van der Laan、Heino 和 De Waard (1997)的技术接受量表(TAS) 测量同一术语的心理构造，作为操作员对特定复杂社会技术系统的态度总和。据称 TAS 包括两个分量表，有用性和满意度. 然而，最近的实证工作仅发现了一个潜在因素的证据。为了进一步了解 TAS 的因子结构，本研究采用贝叶斯探索性因子分析 (BEFA) 来分析有关单个飞行员操作的飞行模拟研究数据。一系列马尔可夫链蒙特卡罗 (MCMC) 模型用于评估 TAS 的潜在因素结构，用于两种不同的机组人员条件及其相应的副驾驶工作站和驾驶舱设置。对 MCMC 模型进行可靠的逐步数据分析为规模的单因素解决方案提供了证据。与先前声称两个因素的研究的分歧可能是由于不同的应用以及由于探索性因素分析中的不同统计范式和方法论问题。