Purposive Selection and the Quality of Qualitative IS Research
Purposive Selection and the Quality of Qualitative IS Research
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有目的的选择和定性信息系统研究的质量
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Attila Márton
中科院分区：
文献类型：
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作者：
Attila Márton
随着定性研究在IS社区内得到广泛接受，方法论话语已将注意力转向有关定性研究质量的问题，主要强调如何制定良好实践的指导方针。相比之下，定性研究的评价标准虽然同样重要，但没有得到同等的重视。借鉴行为科学和社会科学的文献，本文讨论了评价定性研究的方法论概念，重点是有目的地选择数据进行分析的技术。特别是，将介绍语料库建设的技术，这是专门设计的定性研究的评价标准。从语言学改编，语料库建设提供了一种替代方法，在实证研究的质量方面，它在功能上等同于统计抽样技术。因此，本文贡献的目的性选择的概念作为评价标准的方法工具箱和术语的IS研究。
As qualitative research has found broad acceptance within the IS community, the methodological discourse has turned its attention to questions concerning the quality of qualitative research mostly emphasizing the development of how-to guidelines for good practice. By contrast, criteria for the evaluation of qualitative research, although equally important, have not received equal attention. Drawing on literature from behavioral and social science, this paper discusses methodological concepts of evaluating qualitative research by focusing on techniques to purposefully select data for analysis. In particular, the technique of corpus construction will be introduced, which was specifically designed as an evaluation criterion for qualitative research. Adapted from linguistics, corpus construction offers an alternative that is functionally equivalent to statistical sampling techniques in terms of the quality of empirical research. Hence, the paper contributes the concept of purposive selection as an evaluation criterion to the methodological tool-box and terminology of IS research.