Data-driven Value-enhancing Strategies: How to Increase Firm Value Using Data Science

초록

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.

키워드

Architectural Innovation; A Behavioral Theory of the Firm; Data-driven Strategy; Knowledge-based View
제목
Data-driven Value-enhancing Strategies: How to Increase Firm Value Using Data Science
저자
강형구; 장가영; 최문경
DOI
10.14329/apjis.2022.32.3.477
발행일
2022-09
저널명
Asia Pacific Journal of Information Systems
권
32
호
3
페이지
477 ~ 495