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Harvesting big data to enhance supply chain innovation capabilities: an analytic infrastructure based on deduction graph

Tan, Kim Hua; Zhan, YuanZhu; Ji, Guojun; Ye, Fei; Chang, Chingter

Authors

KIM TAN kim.tan@nottingham.ac.uk
Professor of Operations and Innovation Management

YuanZhu Zhan

Guojun Ji

Fei Ye

Chingter Chang



Abstract

Today, firms can access to big data (tweets, videos, click streams, and other unstructured sources) to extract new ideas or understanding about their products, customers, and markets. Thus, managers increasingly view data as an important driver of innovation and a significant source of value creation and competitive advantage. To get the most out of the big data (in combination with a firm?s existing data), a more sophisticated way of handling, managing, analysing and interpreting data is necessary. However, there is a lack of data analytics techniques to assist firms to capture the potential of innovation afforded by data and to gain competitive advantage. This research aims to address this gap by developing and testing an analytic infrastructure based on the deduction graph technique. The proposed approach provides an analytic infrastructure for firms to incorporate their own competence sets with other firms. Case studies results indicate that the proposed data analytic approach enable firms to utilise big data to gain competitive advantage by enhancing their supply chain innovation capabilities.

Citation

Tan, K. H., Zhan, Y., Ji, G., Ye, F., & Chang, C. (2015). Harvesting big data to enhance supply chain innovation capabilities: an analytic infrastructure based on deduction graph. International Journal of Production Economics, 165, 223-233. https://doi.org/10.1016/j.ijpe.2014.12.034

Journal Article Type Article
Acceptance Date Dec 28, 2014
Online Publication Date Jan 5, 2015
Publication Date Jul 1, 2015
Deposit Date Apr 11, 2016
Publicly Available Date Mar 28, 2024
Journal International Journal of Production Economics
Print ISSN 0925-5273
Electronic ISSN 0925-5273
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 165
Pages 223-233
DOI https://doi.org/10.1016/j.ijpe.2014.12.034
Keywords Big data; Analytic infrastructure; Competence set; Deduction graph; Supply chain innovation
Public URL https://nottingham-repository.worktribe.com/output/983138
Publisher URL http://www.sciencedirect.com/science/article/pii/S0925527314004289

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