Architectural Innovation; A Behavioral Theory of the Firm; Data-driven Strategy; Knowledge-based View
Issue Date
2022-09
Publisher
한국경영정보학회
Citation
Asia Pacific Journal of Information Systems, v. 32, NO. 3, Page. 477-495
Abstract
This paper proposes how to design and implement data-driven strategies by investigating how a firm can increase its value using data science. Drawing on prior studies on architectural innovation, a behavioral theory of the firm, and the knowledge-based view of the firm as well as the analysis of field observations, the paper shows how data science is abused in dealing with meso-level data while it is underused in using macro-level and alternative data to accomplish machine-human teaming and risk management. The implications help us understand why some firms are better at drawing value from intangibles such as data, data-science capabilities, and routines and how to evaluate such capabilities.