A Content Validity Study for Big Data Analytics Implementation Model

Cecilia Adrian, R. Abdullah, Y. Y. Jusoh, R. Atan
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引用次数: 1

Abstract

Despite the vast investigations that had assessed the capabilities of big data analytics (BDA), studies regarding the influential factors of BDA implementation (BDAI) are in scarcity, particularly within the organisational context. The paucity of studies on BDAI evaluation has partly motivated this study. As such, this study performed content validation in developing a BDAI model. Validation of survey instrument is essential in a quantitative research. Data were retrieved from a panel of seven big data experts, both from industries and academic. Next, the scores were analysed by incorporating item-content validity index (I-CVI) and modified kappa (K) statistics. From a set of 64 items, the content validity process discarded 9 items and retained 55 items, with the revised items proceeded for further analysis. This particular content validity study revealed that the assessed instrument can be used to develop a viable level of content validity. This study may serve as a guide amidst Information Systems (IS) researchers, especially the big data domain in devising valid and reliable instruments.
大数据分析实施模型的内容效度研究
尽管进行了大量调查,评估了大数据分析(BDA)的能力,但关于实施大数据分析(BDA)的影响因素的研究很少,特别是在组织背景下。BDAI评价研究的缺乏是本研究的部分动机。因此,本研究在开发BDAI模型时进行了内容验证。在定量研究中,测量仪器的验证是必不可少的。数据来自一个由七位大数据专家组成的小组,这些专家既有工业界的,也有学术界的。接下来,通过纳入项目内容效度指数(I-CVI)和修正kappa (K)统计来分析得分。在64个项目中,内容效度过程丢弃了9个项目,保留了55个项目,并对修改后的项目进行了进一步分析。这个特定的内容效度研究表明,评估的工具可以用来开发一个可行的水平的内容效度。本研究可为信息系统(IS)研究者,特别是大数据领域研究者设计有效可靠的工具提供指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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