A hybrid multi-criteria decision making model for technological innovation capabilities measurement in automotive parts industry

Abstract

Technological innovation capabilities (TICs) are currently one of the essential factors to enhance the competitiveness of enterprises. The measurement of TICs is a complicated decision making process and quite difficult to perform because its assessment involves multi-attribute criteria and the subjective judgements of experts. To solve these problems, this study provides a TICs evaluating model by employing a hybrid multi-criteria decision making (MCDM) technique. This method is an integration of four approaches, consisting of: 1) fuzzy Delphi; 2) fuzzy DEMATEL; 3) analytical network process; 4) technique for order preference by similarity to an ideal solution (TOPSIS). The final results showed the measurement criteria, the interrelationship and the relative important weights among criteria and the ranking of TICs of firms. An empirical study is also illustrated in Thai automotive parts firms as a case study. Furthermore, this study could assist industrial managers to efficiently evaluate TICs and its direction of improvement.

Evaluating the Renewal Degree for Expressway Regeneration Projects Based on a Model Integrating the Fuzzy Delphi Method, the Fuzzy AHP Method, and the TOPSIS Method

“…Based on expert opinions, Huang et al [36] used the FDM to determine the key input variables that had the deepest impact on blasting vibration. Sumrit et al [37] used the fuzzy function of triangular fuzzy numbers to screen the important factors to improve the competitiveness of enterprise technological innovation based on the existing research results. Chan et al [38] combined fuzzy Delphi and analytical network processing techniques to establish a postdisaster resilience index system for redeveloped urban areas in the Tansui River Basin in Taiwan.…”

A Novel Integration of IF-DEMATEL and TOPSIS for the Classifier Selection Problem in Assistive Technology Adoption for People with Dementia

“…Step 5-Computation of the convergence index: The convergence index, calculated using Equation ( 9), determines whether the decision makers were accurate when performing the judgments [61]. In Equation (9), n denotes the number of experts, and g ijp c and g ij(p−1) c represent the integration matrix of n and n − 1, experts respectively. If this index is less than 0.05, the convergence is satisfactory and the experts are therefore considered consistent in their preferences [61].…”

“…In fact, we aim to network with people from public health organizations to obtain their judgments regarding the importance of criteria influencing this decision. Note that the merger of these two methods has already been successfully adopted in other fields [8,9].…”