Big Data Analytics Affordances for Social Innovation: A Theoretical Framework
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2021Metadata
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Pappas I. O., & Thapa D. (2021). Big Data Analytics Affordances for Social Innovation: A Theoretical Framework. I D. Dennehy, A. Griva, N. Pouloudi, Y. K. Dwivedi, I. Pappas, & M. Mäntymäki (Red.), Responsible AI and Analytics for an Ethical and Inclusive Digitized Society (Bd. 12896, s. 144-149). Springer. https://doi.org/10.1007/978-3-030-85447-8_13Abstract
This paper proposes a theoretical framework to identify the mechanisms by which actors perceive the affordances of big data analytics (BDA) and how institutional voids and supports enable or hinder the actualisation of those perceived affordances. In doing so, we contribute to identifying the missing link needed to understand the social innovation process in relation to BDA. The framework paves the ground towards understanding the institutionalization process of social innovation and its implications for research and practice.