Makri, S; Blandford, A; (2012) Coming across information serendipitously: Part 2 - A classification framework. Journal of Documentation , 68 (5) 706 - 724. 10.1108/00220411211256049.

Preview

PDF 1341009_Makri & Blandford - Coming Across Information Serendipitously (Part 2).pdf Available under License : See the attached licence file. Download (309kB)

Abstract

Purpose: In ‘Coming across information serendipitously: Part 1 – A process model’ we identified common elements of researchers’ experiences of ‘coming across information serendipitously.’ These experiences involve a mix of unexpectedness and insight and lead to a valuable, unanticipated outcome. In this article, the elements of unexpectedness insight and value form a framework for subjectively classifying whether or not a particular experience might be considered serendipitous and, if so, just how serendipitous. Design/methodology/approach: The classification framework was constructed by analysing 46 experiences of coming across information serendipitously provided by 28 interdisciplinary researchers during Critical Incident interviews. ‘Serendipity stories’ were written to summarise each experience and to facilitate their comparison. The common elements of unexpectedness, insight and value were identified in almost all the experiences. Findings: The presence of different mixes of unexpectedness, insight and value in the interviewees’ experiences define a multi-dimensional conceptual space (which we call the ‘serendipity space’). In this space, different ‘strengths’ of serendipity exist. Our classification framework can be used to reason about whether an experience falls within the serendipity space and, if so, how ‘pure’ or ‘dilute’ it is. Originality/value: Our framework provides researchers from various disciplines with a structured means of reasoning about and classifying potentially serendipitous experiences.

Download activity - last month

Export as JSONXMLCSV

Download activity - last 12 months

Export as JSONXMLCSV

Downloads by country - last 12 months

Export as JSONCSVXML

Archive Staff Only

View Item