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A Belief Rule Based Expert System for Evaluating Technological Innovation Capability of High-Tech Firms Under Uncertainty
Department of Computer Science and Engineering, University of Chittagong, Bangladesh.
University of Chittagong, Bangladesh.ORCID iD: 0000-0002-7473-8185
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0002-3090-7645
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-0244-3561
2019 (English)In: Proceedings of the Joint 2019 8th International Conference on Informatics, Electronics & Vision (ICIEV), IEEE, 2019Conference paper, Published paper (Refereed)
Abstract [en]

Technological innovation capability (TIC) is a complicated and subtle concept which is based on multiple quantitative and qualitative criteria. The cores of a firm’s long-term competitive dominance are defined by technological innovation capability which is the incentive for a firm’s innovation. Various types of uncertainty can be noticed while considering multiple criteria for evaluating TIC. In order to evaluate TIC in a reliable way, a Belief Rule Base (BRB) Expert System can be used to handle both quantitative and qualitative data and their associated uncertainties. In this paper, a RESTful API-based BRB expert system is introduced to evaluate technological innovation capability by taking uncertainties into consideration. This expert system will facilitate firms’ managers to obtain a recapitulation of the TIC evaluation. It will help them to take essential steps to ensure corporate survival and strengthen their weak capabilities continuously to facilitate a competitive advantage. Other users can also use this API to apply BRB for a different domain. However, a comparison between the knowledge-driven approach (BRBES) and several data-driven models has been performed to find out the reliability in evaluating TIC. The result shows that the outcome of BRBES is better than other data-driven approaches.

Place, publisher, year, edition, pages
IEEE, 2019.
Keywords [en]
Technological Innovation Capability, Belief Rule Base, Uncertainty, RESTful API
National Category
Computer Sciences
Research subject
Pervasive Mobile Computing
Identifiers
URN: urn:nbn:se:ltu:diva-73309OAI: oai:DiVA.org:ltu-73309DiVA, id: diva2:1299001
Conference
Joint 2019 8th International Conference on Informatics, Electronics & Vision (ICIEV), 26 - 29 April 2019, Spokane, United States
Projects
A belief-rule-based DSS to assess flood risks by using wireless sensor networks
Funder
Swedish Research Council, 2014-4251Available from: 2019-03-25 Created: 2019-03-25 Last updated: 2019-04-02Bibliographically approved

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Islam, Raihan UlAndersson, Karl

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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Language
  • de-DE
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  • Other locale
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Output format
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