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  • Please use this identifier to cite or link to this item: https://repositorio.uti.edu.ec//handle/123456789/5726
    Title: A decision support model for evaluating risks in the digital economy transformation of the manufacturing industry
    Authors: Shang, Chao
    Jiang, Jian
    Zhu, Lan
    Saedi, Parvaneh
    Issue Date: 2023
    Publisher: Journal of Innovation and KnowledgeOpen Access. Volume 8, Issue 3
    Abstract: In recent decades, digital technologies have seriously changed socioeconomic systems on a global scale. Unfortunately, consequential issues have remained mostly uninvestigated. The literature lacks research into the risks that may arise in the procedure of developing digital capabilities that have considerable impacts on firms’ innovative growth. In addition, inadequate research has been conducted on challenges that may arise when a business is being developed in the context of the digital economy. Moreover, the advent of new risks specific to the digital economy has not been addressed in the overall system of modern economic relations. As a result, the current study aims to investigate the major areas of relevance to transforming companies into the digital economy, considering the impacts of new risks encountered during such transitions. Along this line, this paper develops a decision support model for evaluating risks in the digital economy transformation of the manufacturing industry. This approach is applied to compute the weights and the study ranks the most important risks for digital economy transformation in the manufacturing industry. In addition, the proposed method model is implemented to find industries’ priorities of different risks for the digital economy transformation of the manufacturing industry. Finally, a case study is carried out to assess the most important risk for the digital transformation of the manufacturing industry. The results show that lack of top management involvement (f7), with a weight of 0.0563, an unstable market environment in terms of the uncertainty industry, and market volatility, with a weight of 0.0542, are the most considerable risks for the digital economy transformation (DET) of the manufacturing industry. Additionally, comparison and sensitivity analyses are made to illustrate the advantage of the presented approach.
    URI: https://doi.org/10.1016/j.jik.2023.100393
    https://repositorio.uti.edu.ec//handle/123456789/5726
    Appears in Collections:Artículos Científicos Indexados

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