Modelling the continuous innovation capability enablers in Indonesia’s manufacturing industry

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11 Citations (Scopus)


Purpose: The purpose of this paper is to identify and screen continuous innovation capability enablers (CICEs) in Indonesia’s manufacturing sectors, develop a relationship among these enablers and determine their driving power and dependence power in the sector. Design/methodology/approach: The initial CICEs identification process is based on a literature review, while a fuzzy Delphi method (FDM) was used for the screening process of CICEs. Total interpretive structural modelling (TISM) was used to develop contextual relationships among various CICEs. The results of the TISM are used as an input for the matrix of cross-impact multiplications applied to classification (MICMAC) to classify the driving power and dependence powers of the CICEs. Findings: This paper selected 16 CICEs classified in seven dimensions. TISM results and MICMAC analysis show that leadership, as well as climate and culture, are enablers with the highest driving power and lowest dependence powers; followed by information technology. The results of this study indicate that efforts to continuously develop innovation capabilities in the Indonesian manufacturing industries are strongly influenced by their leadership capability, climate and culture, also information technology-related capability. Practical implications: The framework assessed in this study provides business managers and policymakers to obtain a bigger picture in developing policies with evidence-based strategy and priority in regard to continuous innovation capability. Originality/value: The results will be useful for business managers and policymakers to understand the relationship between CICEs and identify key CICEs in Indonesia’s manufacturing sectors, which were previously non-existent.

Original languageEnglish
Pages (from-to)66-99
Number of pages34
JournalJournal of Modelling in Management
Issue number1
Publication statusPublished - 17 Feb 2022


  • Continuous innovation capability
  • Expert systems
  • Fuzzy
  • Indonesia
  • Innovation
  • Innovation enablers
  • Manufacturing
  • Modelling


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