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Evaluation of digital transformation programs for manufacturing enterprises based on D-S and intuitionistic fuzzy TOPSIS model

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ICBAR '23: Proceedings of the 2023 3rd International Conference on Big Data, Artificial Intelligence and Risk Management

Pages 201 - 204

https://doi.org/10.1145/3656766.3656801

Published: 01 June 2024 Publication History

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ICBAR '23: Proceedings of the 2023 3rd International Conference on Big Data, Artificial Intelligence and Risk Management

Evaluation of digital transformation programs for manufacturing enterprises based on D-S and intuitionistic fuzzy TOPSIS model

Pages 201 - 204

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Abstract

Before embarking on digital transformation, manufacturing enterprises evaluate different digital transformation programs. To address the conflicts in evidence and uncertainties during the evaluation process, this paper constructs modified evidence synthesis rules to integrate expert decision information. It then employs the intuitionistic fuzzy TOPSIS method for decision-making in evaluating digital transformation programs, and verifies the validity of the model through a case study.

References

[1]

Hess, T., Matt, C., Benlian, A., Wiesbock, F., "Options for formulating a digital transformation strategy," Mis Q Exec. 15(2),123–139, 2016.

Google Scholar

[2]

Nambisan, S., Lyytinen, K., Majchrzak, A., "Digital innovation management: reinventing innovation management research in a digital world," Manage Inform Syst Q. 41(1), 223-238, 2017.

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Google Scholar

[3]

Lin, M. C., Wang, C. C., Chen, M. S., "Using AHP and TOPSIS approaches in customer-driven product design process," Comput Ind. 59(1), 17–31, 2008.

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Google Scholar

[4]

Wang, P., Zhang, D. H., Cheng B., "Evaluation of multi-process plans based on fuzzy comprehensive evaluation and grey relational analysis," J Aero P. 27(9), 2075-2085, 2012.

Google Scholar

[5]

Li, S. F., Yang, N. D., Zhang, Y. Y., "New approaches of distinguishing the evidences importance and allocating the evidences conflict,"Syst. Engin T Prac. 33(7),1867-1872, 2013.

Google Scholar

[6]

Jiang, H. L., He, J. M., Zhuang, Y. M., "Approach to group decision making based on intuitionistic fuzzy sets and evidence theory," Control Decis. 2012, 27(5),752-756.

Google Scholar

[7]

Cheng, Q. Y., "Structure entropy weight method to confirm the weight of evaluationg index," Syst Engin T Prac.30(7),1225-1228, 2010.

Google Scholar

[8]

Dubois, D., Gottwald, S., Hajek P., "Terminological difficulties in fuzzy set theory—The case of “Intuitionistic Fuzzy Sets”," Fuzzy Set Syst. 156(3),485-491, 2005.

Digital Library

Google Scholar

[9]

Jousselme, A. L., Grenier, D., Éloi, Bossé., "A new distance between two bodies of evidence," Inform Fusion. 2(01), 91-101, 2001.

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Google Scholar

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Evaluation of digital transformation programs for manufacturing enterprises based on D-S and intuitionistic fuzzy TOPSIS model
1. Social and professional topics
  1. Computing / technology policy
    1. Commerce policy

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ICBAR '23: Proceedings of the 2023 3rd International Conference on Big Data, Artificial Intelligence and Risk Management

November 2023

1156 pages

ISBN:9798400716478

DOI:10.1145/3656766

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

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Published: 01 June 2024

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ICBAR 2023

ICBAR 2023: 2023 3rd International Conference on Big Data, Artificial Intelligence and Risk Management

November 24 - 26, 2023

Chengdu, China

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Intuitionistic Fuzzy Distance Based TOPSIS Method and Application to MADM

Circular intuitionistic fuzzy TOPSIS method: pandemic hospital location selection

Fuzzy multiattribute decision making based on transformation techniques of intuitionistic fuzzy values and intuitionistic fuzzy geometric averaging operators

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