Data-driven Value-enhancing Strategies: How to Increase Firm Value Using Data Science
- Authors
- 강형구; 장가영; 최문경
- Issue Date
- Sep-2022
- Publisher
- 한국경영정보학회
- Keywords
- Architectural Innovation; A Behavioral Theory of the Firm; Data-driven Strategy; Knowledge-based View
- Citation
- Asia Pacific Journal of Information Systems, v.32, no.3, pp.477 - 495
- Indexed
- SCOPUS
KCI
- Journal Title
- Asia Pacific Journal of Information Systems
- Volume
- 32
- Number
- 3
- Start Page
- 477
- End Page
- 495
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/173075
- DOI
- 10.14329/apjis.2022.32.3.477
- ISSN
- 2288-5404
- 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.
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