The goal of this study is to advance conceptual development and the growth of knowledge in the information systems (IS) field by placing the spotlight on a component of theory that is rarely discussed – the native IS concept. Beginning with the assertion that concepts are not the same as constructs, we build the argument that concepts, which are observable sets of ideas, should take priority over constructs which are unobservable fictions and hypothetical entities. Using natural language processing (NLP) based principles and techniques, we extract a sample of the most important concepts in the IS field from a corpus of 245 highly cited IS review articles and 1,293 citing articles from the Senior Scholars’ Basket of Journals to illustrate the extent to which the field agrees on their usage, their clarity and distinctiveness and how the field can move forward in enhancing its conceptual formation.
Hassan, Nik Rushdi; Prester, Julian; and Wagner, Gerit, "Seeking Out Clear And Unique Information Systems Concepts: A Natural Language Processing Approach" (2020). In Proceedings of the 28th European Conference on Information Systems (ECIS), An Online AIS Conference, June 15-17, 2020.
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