TAM理论测试方法比较测试对象是接受本Pontianak的E-Money技术

Irawan Wingdes, Sandy Kosasi, I. Yuliani
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引用次数: 1

摘要

作为研究人员,可以采用多种方法来分析技术接受模型(TAM)。这些方法包括总和量表回归、因子分析得分回归、基于协方差的扫描电镜和基于pls的扫描电镜。然而,在单个数据集中比较这些方法的估计差异的努力较少。因此,不同的估计可能导致第一类统计误差。本研究的目的是通过单一数据集客观地比较这些方法。测试的数据集来自Pontianak的电子货币研究,其中包括2020年5月,6月和7月在加油站收集的280个数据。这项研究有助于证明即使在相同的数据集上测试,方法选择如何产生不同的解释。总结量表回归和基于pls的SEM产生了相似的估计结果,但与因子分析评分回归和基于协方差的SEM不同。进一步的检验表明,不同的估计数是由于消除了具体方法的指标。因此,研究方法的合理性、研究报告的完整性和研究背景对所选择的方法的会计局限性至关重要。基于pls的SEM是一种适用于数据的方法,其有用性有50.3%的可变性,使用意图有58%的可变性,从研究模型中考虑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Perbandingan Metode Pengujian Teori TAM Pada Penerimaan Teknologi E-Money di Pontianak
As a researcher, one could analyze Technology Acceptance Model (TAM) by utilizing several methods. Such methods are summated scales regression, factor analysis score regression, covariance-based SEM, and PLS-based SEM. However, there exists less effort to compare the difference in estimates of these methods in a single dataset. The differing estimates could therefore lead to type I statistical errors. This research purpose was to compare these methods objectively with a single dataset. The dataset tested was derived from e-money research in Pontianak, with 280 data collected at refueling stations during May, June, July 2020. This research contributes to proofing how method choices will produce a differing interpretation even though tested on the same dataset. Summated scale regression and PLS-based SEM produced similar estimation results but differed from factor analysis score regression and covariance-based SEM. Further testing implies that the different estimates are due to the elimination of indicators, which is method-specific. Therefore, method justification, completeness of research report, and research context are crucial for accounting limitation of the method chosen. PLS-based SEM was a suitable method for data utilized with 50,3% variability in usefulness, 58% variability in intention to use is accounted for from the research model.  
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