{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:38:24Z","timestamp":1761176304874,"version":"build-2065373602"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>Negotiation is ubiquitous in business applications in general and in procurement operations in particular. Nevertheless, several studies have shown that the negotiation process is often inefficient and time-consuming. In this paper, we propose a novel automated negotiation framework for procurement focusing on delivery date adjustment negotiations between buyers and suppliers. These negotiations are one of the most repeated negotiations in industrial applications.Nevertheless, they are often complex and time-consuming, as they involve multiple parties and require careful consideration of various internal and external factors. The proposed method was evaluated in the field and was shown to provide a significant reduction in the time required to reach achievement and around 95% closure rate. The proposed method is expected to be widely applicable in various procurement operations, contributing to improved efficiency and effectiveness in business negotiations. We also discuss the potential for future research in this area, including the integration of various machine learning techniques to further enhance the negotiation process.<\/jats:p>","DOI":"10.3233\/faia251427","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T10:02:29Z","timestamp":1761127349000},"source":"Crossref","is-referenced-by-count":0,"title":["Automated Negotiation for Delivery Date Adjustment in Procurement"],"prefix":"10.3233","author":[{"given":"Tomohito","family":"Ando","sequence":"first","affiliation":[{"name":"NEC CORPORATION"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nozomoi","family":"Miki","sequence":"additional","affiliation":[{"name":"NEC CORPORATION"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Norio","family":"Yanagi","sequence":"additional","affiliation":[{"name":"NEC CORPORATION"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2272-7254","authenticated-orcid":false,"given":"Yasser","family":"Mohammad","sequence":"additional","affiliation":[{"name":"NEC CORPORATION"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251427","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T10:02:29Z","timestamp":1761127349000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251427"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251427","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}