Using Fuzzy Logic in QCA for the Selection of Relevant IS Adoption Drivers in Emerging Economies

N. I. Alcivar, L. Houghton, L. Sanzogni
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Abstract

This paper argues that typical adoption studies fail to capture the nuances and realities of emerging economies in Latin American (LAT) regions. Existing research has a long list of factors that are based on studies outside of the LAT region, which is a problem because there are almost no studies that capture the unique perspective of the LAT context. These issues, in turn, creates uncertainty because the context in LAT varies widely from the economies where most of these studies are conducted. To begin to address this problem, the authors used a Qualitative Comparative Analysis (QCA) using fuzzy logic to refine the selection of drivers obtained from earlier studies. The study revealed fourteen themes as being relevant candidate drivers for comparative future research purposes. It is argued that these results provide local stakeholders with a set of drivers relating to IS adoption within a specific context, namely in LAT economies and provide a contextual frame to develop more meaningful studies in LAT economies.
在QCA中运用模糊逻辑选择新兴经济体的相关信息系统采用驱动因素
本文认为,典型的采用研究未能捕捉到拉丁美洲地区新兴经济体的细微差别和现实。现有的研究有一长串基于LAT区域以外的研究的因素,这是一个问题,因为几乎没有研究捕捉到LAT背景的独特视角。这些问题反过来又造成了不确定性,因为LAT的背景与进行大多数研究的经济体差别很大。为了开始解决这个问题,作者使用了定性比较分析(QCA),使用模糊逻辑来优化从早期研究中获得的驱动因素的选择。该研究揭示了14个主题作为未来比较研究目的的相关候选驱动因素。作者认为,这些结果为当地利益相关者提供了一套与特定背景下(即在LAT经济体中)采用信息系统相关的驱动因素,并为在LAT经济体中开展更有意义的研究提供了一个背景框架。
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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