Although measurement is central to knowledge production, little is known about the process by which a dataset becomes accepted by academics as an appropriate way of measuring a phenomenon. Relying on actor-network theory and prior studies of the construction of organizational knowledge, and using the Kinder Lydenberg and Domini database as a case, we analyze the activities that enabled the adoption of this dataset. Informed by a systematic content analysis of 573 articles referring to KLD and interviews with KLD experts, we develop a process model that explains how datasets become accepted in academia and linked to theoretical concepts. In making visible the practical, symbolic and conceptual work that underlie a dataset adoption in academia, we show how academics can potentially be influenced by practitioners through metrics. Our findings also highlight the importance of reflexivity and mindfulness in the use of datasets.
Keywords Business and Professional Ethics  Conference Proceedings  Social Science
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ISBN(s) 2155-2568
DOI 10.5840/iabsproc2017289
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