Diversity in IS research : a fictive metaphor analysis
Date
2011
Authors
Behrens, Sandy Hope
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Abstract
In striving to understand Information Systems phenomena Information Systems researchers frequently draw on a seemingly endless array of different disciplines to inform their studies. This act has drawn both the ire and admiration of those within the field as well as those outside its porous boundaries. On the one hand Information Systems researchers are berated for being chaotic and schizophrenic in their combined research endeavour - for producing a collective output that shows neither rhyme nor reason. On the other hand they are praised for being intellectually open and democratic in their approach. These reactions draw their strength from the many issues that stem from diversity in Information Systems research. These reactions are stimulated in part by the assertion that research in the Information Systems discipline is diverse. Despite this assertion not much is known or understood about diversity in Information Systems research. This thesis addresses this critical oversight by making research diversity the prime focus. The contributions it makes to current understandings of research diversity in Information Systems are philosophical, theoretical and empirical. Philosophically, this thesis relies on the novel approach of fictism - a blend of positivism and interpretivism. Theoretically, it explores diversity through the alternative lens of concepts. Empirically it examines the conceptual diversity of three key Information Systems concepts: organisations, technology and people. Grounded in Lakoff and Johnson's (1980) work with metaphors, the results show that Information Systems research may not be as diverse as was initially thought. Of the three primary views of key Information Systems concepts - machine, organism and culture - the study finds a distinct bias toward conceptualising these concepts as machines. This bias, one that exists at the very core of the Information Systems research endeavour, has important implications not only for individual researchers but the broader Information Systems community alike.
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