{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T21:51:13Z","timestamp":1776289873617,"version":"3.50.1"},"reference-count":32,"publisher":"SAGE Publications","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["KES"],"published-print":{"date-parts":[[2023,10,13]]},"abstract":"<jats:p>Supply chain finance has solved the problem of financing difficulties for small and medium-sized enterprises in the upstream and downstream of China\u2019s supply chain. However, with the development of the economy, traditional supply chain finance is gradually unable to meet the financing needs of enterprises. Enterprise financing pursues simplified processing time and process, simple operation methods and procedures. At the same time, the rapid development of information technology and the emergence and prosperity of new technologies such as e-commerce, big data, cloud computing also continue to promote the breeding of new models. Based on this background, a new type of supply chain finance has emerged \u2013 Internet supply chain finance. The risk assessment of internet supply chain finance is a classical multiple-attributed decision making (MADM) problems. In this paper, the cross-entropy method under type-2 neutrosophic numbers (T2NNs) is built based on the traditional cross-entropy method. Firstly, the T2NN is introduced. Then, combine the traditional fuzzy cross-entropy method with T2NNs information, the type-2 neutrosophic number cross-entropy (T2NN-CE) method is established for MADM under T2NNs. Finally, a numerical example for risk assessment of internet supply chain finance has been given and some comparisons is used to illustrate advantages of T2NN-CE method with T2NNs.<\/jats:p>","DOI":"10.3233\/kes-230112","type":"journal-article","created":{"date-parts":[[2023,9,5]],"date-time":"2023-09-05T15:52:29Z","timestamp":1693929149000},"page":"207-218","source":"Crossref","is-referenced-by-count":3,"title":["Modified cross-entropy method for multiple-attribute decision making with type-2 neutrosophic number and applications to risk assessment of internet supply chain finance"],"prefix":"10.1177","volume":"27","author":[{"given":"Xuanlin","family":"Li","sequence":"first","affiliation":[]}],"member":"179","reference":[{"issue":"9","key":"10.3233\/KES-230112_ref3","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1177\/1550147719874002","article-title":"Research on measurement of supply chain finance credit risk based on Internet of Things","volume":"15","author":"Abbasi","year":"2019","journal-title":"Int J Distrib Sens Netw."},{"key":"10.3233\/KES-230112_ref5","doi-asserted-by":"crossref","first-page":"53182","DOI":"10.1109\/ACCESS.2019.2909801","article-title":"Compressed sensing and its applications in risk assessment for internet supply chain finance under big data","volume":"7","author":"Lyu","year":"2019","journal-title":"IEEE Access."},{"key":"10.3233\/KES-230112_ref6","doi-asserted-by":"crossref","first-page":"53182","DOI":"10.1109\/ACCESS.2019.2909801","article-title":"Compressed sensing and its applications in risk assessment it for internet supply chain finance under big data","volume":"7","author":"Lyu","year":"2019","journal-title":"IEEE Access."},{"key":"10.3233\/KES-230112_ref7","first-page":"8","article-title":"New model of food supply chain finance based on the internet of things and blockchain","volume":"2021","author":"Hong","year":"2021","journal-title":"Mob Inf Syst."},{"key":"10.3233\/KES-230112_ref8","first-page":"10","article-title":"Development of internet supply chain finance based on artificial intelligence under the enterprise green business model","volume":"2021","author":"Zhang","year":"2021","journal-title":"Math Probl Eng."},{"issue":"1","key":"10.3233\/KES-230112_ref12","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1371\/journal.pone.0262222","article-title":"Internet-based supply chain financing-oriented risk assessment using BP neural network and SVM","volume":"17","author":"Fu","year":"2022","journal-title":"PLoS One."},{"key":"10.3233\/KES-230112_ref14","doi-asserted-by":"crossref","unstructured":"Zhang H, Zhang F, Gong B, Zhang X, Zhu Y. 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