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

Abstract

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.

Exploring the significant factors of reconfigurable manufacturing system adoption in manufacturing industries

“…Several researchers (Dubey et al , 2017; Yadav et al , 2020b) agreed on this during their research. The researchers Dubey et al (2017) attempted to develop a link between RMS and top management beliefs and discovered that if top management participation is higher, there is a higher likelihood of RMS adoption and is also supported by Lianto et al (2022). The researchers also concentrated on organizational culture, emphasizing the importance of management involvement, reconfigurability, etc.…”

The Role of Adaptive E-Learning Co-Design as Main Solution to Higher Education’s Marketing Performance

“…Qualitatively, the results show that e-learning can help in completing the three pillars of HE (lecturers) and the educational programs without reducing quality, as evidenced by the level of understanding and deepening the learning materials (Lianto et al, 2020). HE focuses more on digital innovation and adaptation towards a digital campus (Sorkun et al, 2022).…”

Modelling the Enablers for Branded Content as a Strategic Marketing Tool in the COVID-19 Era

“…Step 5: MICMACAnalysis: The purpose of MICMAC Analysis is to divide the identified factors into four different clusters as per the driving power and dependence of the factors. The four clusters thus identify and group the factors as autonomous, dependent, linkage, and independent factors [44,[60][61][62][63]. The grouping of factors in this study is presented in Figure 1 and discussed as below: Cluster I: This cluster groups together Autonomous Factors in the system.…”

“…In contrast, in TISM, the interpretive logic knowledge base matrix is prepared to provide logic for each linkage. TISM approach identifies the structural relationship between the variables [42][43][44][45], and DEMATEL further provides the strength of those relationships, along with providing the cause and effect relationship among the variables [46][47][48]. Further, in this section, the methodology for TISM and DEMATEL approaches are discussed.…”