Managing Big data for firm performance: A configurational approach

LeeAnn Kung, Hsiang Jui Kung, Allison Jones-Farmer, Yichuan Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations

Abstract

Big data are challenging organizations to find a thoughtful, holistic approach to data, analysis and information management to facilitate timely and sound decisions making, and in turn to gain competitive advantages. Managing big data is not a simple technical issue, but a complex managerial and strategic one. To achieve the vast potential of big data not only will enterprise IT architectures need to change, firms also need a new strategy, a new mind set, and a capability to deal with unexpected environmental turbulences. In this paper, we present a conceptual model and a novel analysis method, fuzzy set Qualitative Comparative Analysis to model and interpret interdependent non-linear relationships among elements and the outcome, performance. We posit that data management strategy, big data competence, IT capability and organization improvisational capability are interdependent and mutual reinforcing that form a network of nonlinear influential factors for firm decision quality and in turn, performance.

Original languageEnglish (US)
Title of host publication2015 Americas Conference on Information Systems, AMCIS 2015
PublisherAmericas Conference on Information Systems
ISBN (Electronic)9780996683104
StatePublished - Jan 1 2015
Event21st Americas Conference on Information Systems, AMCIS 2015 - Fajardo, Puerto Rico
Duration: Aug 13 2015Aug 15 2015

Other

Other21st Americas Conference on Information Systems, AMCIS 2015
Country/TerritoryPuerto Rico
CityFajardo
Period8/13/158/15/15

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems

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