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Key Factors Identification and Path Selection of Enterprise Digital Transformation under Multicriteria Interaction

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  • Chunmei Liu
  • Zaoli Yang

Abstract

Enterprise digital transformation is a must-go phase in today’s market, for both large and small businesses. This is determined by the development of the market economy and people’s consumption concept. However, enterprises will face many challenges and factors in the process of digital transformation. For enterprise managers, it is more difficult to deal with these complex data and factors. Moreover, the digital transformation of enterprises needs to consider more development goals. For small businesses, the digital transformation of a business is even more difficult. This requires a full understanding of the key factors and development paths of the enterprise in the process of enterprise digital transformation. If the key factors of the enterprise and the reasonable development path of the enterprise cannot be fully grasped in the process of digital transformation of the enterprise, it will easily lead to the failure of the transformation of the enterprise. Therefore, in the process of enterprise transformation, it is necessary to fully consider the key factors faced by the enterprise and the reasonable development path of the enterprise. This study uses the multicriteria optimization algorithm and ConvLSTM method to study the key factors and paths in the digital transformation of enterprises. The research results show that the multicriteria optimization algorithm can efficiently handle multiple development goals in the digital transformation of enterprises, and the ConvLSTM algorithm can also accurately predict the key factors in the digital transformation of enterprises.

Suggested Citation

  • Chunmei Liu & Zaoli Yang, 2022. "Key Factors Identification and Path Selection of Enterprise Digital Transformation under Multicriteria Interaction," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-9, August.
  • Handle: RePEc:hin:jnlmpe:2894156
    DOI: 10.1155/2022/2894156
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