Assessment of corporate innovation capability with a data-mining approach: industrial case studies

ALTUNTAŞ S., Dereli T., Kusiak A.

COMPUTERS & INDUSTRIAL ENGINEERING, vol.102, pp.58-68, 2016 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 102
  • Publication Date: 2016
  • Doi Number: 10.1016/j.cie.2016.10.018
  • Journal Name: COMPUTERS & INDUSTRIAL ENGINEERING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.58-68
  • Keywords: Innovation capability, Data mining, Fuzzy association rules, Case studies, KNOWLEDGE MANAGEMENT, FIRMS, PERFORMANCE, CAPACITY
  • Yıldız Technical University Affiliated: Yes

Abstract

The interest in assessment of innovation capability of manufacturing systems is fueled by the growing competition. At this time, there is no generally accepted model to evaluate innovation capability of manufacturing systems. In this paper, a fuzzy-logic based data-mining approach is proposed to assess innovation capability of manufacturing systems. The proposed algorithm is illustrated with two industrial case studies representing two different industry sectors. The results derived from these case studies demonstrate advantages of the proposed algorithm in assessing corporate innovation capability. (C) 2016 Elsevier Ltd. All rights reserved.