Assessing the adoption barriers for the AI in food supply chain finance applying a hybrid interval-valued Fermatean fuzzy CRITIC-ARAS model
Abstract The identification and evaluation of barriers to artificial intelligence (AI) adoption in food supply chain finance (FSCF) can be addressed as a multiattribute decision-making problem. However, only a few studies have reported the application of decision models for evaluating barriers to th...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-11-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-79177-6 |
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| author | Wenyi Wang Yushuo Cao Yu Chen Chen Liu Xiao Han Bo Zhou Weizhong Wang |
| author_facet | Wenyi Wang Yushuo Cao Yu Chen Chen Liu Xiao Han Bo Zhou Weizhong Wang |
| author_sort | Wenyi Wang |
| collection | DOAJ |
| description | Abstract The identification and evaluation of barriers to artificial intelligence (AI) adoption in food supply chain finance (FSCF) can be addressed as a multiattribute decision-making problem. However, only a few studies have reported the application of decision models for evaluating barriers to the implementation of AI in FSCF, especially within an uncertain context. Hence, this work explores the evaluation issue of implementation barriers via an integrated decision model. In this model, the conventional additive ratio assessment (ARAS) model integrated with the Choquet integral and criteria importance through intercriteria correlation (CRITIC) is extended into the interval-valued Fermatean fuzzy (IVFF) setting for ranking the barriers. The IVFF weighted average operator based on the Choquet integral is introduced to form a group decision matrix. Then, the developed ARAS model with the IVFF-CRITIC method is proposed to evaluate the implementation barriers for AI in FSCF, which can depict the interactions between the barriers. Finally, a case of an FSCF, including four participants, is presented to illustrate the application of the reported model and demonstrate its reliability. The result shows that “Data privacy” ( $${c_{10}}$$ ) is the main barrier impeding AI adoption in FSCF, and the participant “small and medium-sized processing enterprises” ( $${a_3}$$ ) has the highest barrier level to AI adoption. |
| format | Article |
| id | doaj-art-79dc2b755a294c2bbe2d5bd07d136a5c |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-79dc2b755a294c2bbe2d5bd07d136a5c2024-11-17T12:25:29ZengNature PortfolioScientific Reports2045-23222024-11-0114111910.1038/s41598-024-79177-6Assessing the adoption barriers for the AI in food supply chain finance applying a hybrid interval-valued Fermatean fuzzy CRITIC-ARAS modelWenyi Wang0Yushuo Cao1Yu Chen2Chen Liu3Xiao Han4Bo Zhou5Weizhong Wang6School of Management and Engineering, Nanjing UniversitySchool of Economics and Management, Anhui Normal UniversitySchool of Economics and Management, Anhui Normal UniversityJiangsu Health Vocational CollegeSchool of Economics and Management, Anhui Normal UniversityJiangsu Xuzhou Higher Vocational Technology Academy of Finance and EconomicsSchool of Economics and Management, Anhui Normal UniversityAbstract The identification and evaluation of barriers to artificial intelligence (AI) adoption in food supply chain finance (FSCF) can be addressed as a multiattribute decision-making problem. However, only a few studies have reported the application of decision models for evaluating barriers to the implementation of AI in FSCF, especially within an uncertain context. Hence, this work explores the evaluation issue of implementation barriers via an integrated decision model. In this model, the conventional additive ratio assessment (ARAS) model integrated with the Choquet integral and criteria importance through intercriteria correlation (CRITIC) is extended into the interval-valued Fermatean fuzzy (IVFF) setting for ranking the barriers. The IVFF weighted average operator based on the Choquet integral is introduced to form a group decision matrix. Then, the developed ARAS model with the IVFF-CRITIC method is proposed to evaluate the implementation barriers for AI in FSCF, which can depict the interactions between the barriers. Finally, a case of an FSCF, including four participants, is presented to illustrate the application of the reported model and demonstrate its reliability. The result shows that “Data privacy” ( $${c_{10}}$$ ) is the main barrier impeding AI adoption in FSCF, and the participant “small and medium-sized processing enterprises” ( $${a_3}$$ ) has the highest barrier level to AI adoption.https://doi.org/10.1038/s41598-024-79177-6Food supply chainInterval-valued Fermatean fuzzy setARASBarrier analysisAI |
| spellingShingle | Wenyi Wang Yushuo Cao Yu Chen Chen Liu Xiao Han Bo Zhou Weizhong Wang Assessing the adoption barriers for the AI in food supply chain finance applying a hybrid interval-valued Fermatean fuzzy CRITIC-ARAS model Scientific Reports Food supply chain Interval-valued Fermatean fuzzy set ARAS Barrier analysis AI |
| title | Assessing the adoption barriers for the AI in food supply chain finance applying a hybrid interval-valued Fermatean fuzzy CRITIC-ARAS model |
| title_full | Assessing the adoption barriers for the AI in food supply chain finance applying a hybrid interval-valued Fermatean fuzzy CRITIC-ARAS model |
| title_fullStr | Assessing the adoption barriers for the AI in food supply chain finance applying a hybrid interval-valued Fermatean fuzzy CRITIC-ARAS model |
| title_full_unstemmed | Assessing the adoption barriers for the AI in food supply chain finance applying a hybrid interval-valued Fermatean fuzzy CRITIC-ARAS model |
| title_short | Assessing the adoption barriers for the AI in food supply chain finance applying a hybrid interval-valued Fermatean fuzzy CRITIC-ARAS model |
| title_sort | assessing the adoption barriers for the ai in food supply chain finance applying a hybrid interval valued fermatean fuzzy critic aras model |
| topic | Food supply chain Interval-valued Fermatean fuzzy set ARAS Barrier analysis AI |
| url | https://doi.org/10.1038/s41598-024-79177-6 |
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