A decision-making model for predicting technology adoption success

Tahriri, Farzad and Mousavi, Maryam and Galavi, Hadi and Sorooshian, Shahryar (2022) A decision-making model for predicting technology adoption success. Processes, 10 (11). ISSN 2227-9717, DOI https://doi.org/10.3390/pr10112261.

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Advanced manufacturing technology (AMT) has the potential to significantly improve manufacturing performance and boost competitiveness in the global market. Investment in AMT remains a promising but potentially risky venture due to the numerous factors that must be considered before the full benefits of implementing a new technology can be realized. To respond to the reported risks and uncertainties, such as those revealed in the recent industrial revolution, it is very important to identify and classify the critical factors that can influence the success of AMT adoption early in the planning stage. Based on an extensive review of relevant literature, 32 critical factors are identified and classified into ten categories in this paper. A new multiple-input single-output (MISO) model is developed by combining the fuzzy Delphi method (FDM) and the fuzzy inference system (FIS) based on the objectives defined. The FDM is used to determine the critical factors, and the FIS addresses the general fuzzy multi-attribute decision-making (MADM) problem in order to evaluate and predict the percentage of AMT adoption success with an existing system. The model is validated using a numerical test bed, and the results show that the model is a proper tool for risk management in AMT implementation.

Item Type: Article
Funders: None
Uncontrolled Keywords: Advanced manufacturing technology (AMT); Fuzzy delphi method (FDM); Fuzzy inference system (FIS); Flexible manufacturing technology (FMT); Multiple-attribute decision-making (MADM) model
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 10 Nov 2023 05:32
Last Modified: 10 Nov 2023 05:33
URI: http://eprints.um.edu.my/id/eprint/40756

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