Open data capability architecture - An interpretive structural modeling approach

Abstract

Despite of increasing availability of open data as a vital organizational resource, large numbers of start-ups and organizations fail when it comes to utilizing open data effectively. This shortcoming is attributable to the poor understanding of what types of capabilities are required to successfully conduct data related activities. At the same time, research on open data capabilities and how they relate to one another remains sparse. Guided by extant literature, interviews of these organizations, and drawn from Interpretive Structural Modeling (ISM) approach which are pair comparison methods to evolve hierarchical relationships among a set of elements to convert unclear and unstructured mental models of systems into well-articulated models that act as base for conceptualization and theory building, this study explores open data capabilities and the relationships and the structure of the dependencies among these areas. Findings from this study reveal hitherto unknown knowledge regarding how the capability areas relate one another in these organizations. From the practical standpoint, the resulting architecture has the potential to transform capability management practices in open data organizations towards greater competitiveness through more flexibility and increased value generation. From the research point of you, this paper motivates theory development in this discipline.