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• W3177302034 abstract "Abstract Classification schemes are important groundwork for research on many topics of different business disciplines such as information systems (IS). They make investigating topics manageable by allowing researchers to delimit their work to certain taxa or types (e.g., of artifacts or firms) and provide a basis for generalization. Opposed to theoretically grounded typologies, taxonomies are empirically derived from entities of a phenomenon and therefore have several advantages, such as more detailed and exhaustive coverage. Initial guidelines for developing taxonomies in business have been proposed; however, research is still missing a clear set of applicable procedures to empirically build taxonomies. We tackle this topic by suggesting an inductive approach based on the procedures of content and cluster analysis. Each of the proposed six steps is amended with comprehensive state-of-the-art guidelines, suggestions, and formative measures of reliability and validity." @default.
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• W3177302034 date "2021-01-01" @default.
• W3177302034 modified "2023-09-24" @default.
• W3177302034 title "Taxonomy Development for Business Research: A Hands-On Guideline" @default.
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• W3177302034 doi "https://doi.org/10.1007/978-3-030-66661-3_4" @default.
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