{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T05:45:46Z","timestamp":1782539146061,"version":"3.54.5"},"reference-count":62,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T00:00:00Z","timestamp":1781827200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Beijing Social Science Foundation Key Decision-Making Consultation Project","award":["24JCB026"],"award-info":[{"award-number":["24JCB026"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>In the digital era, intelligent applications play an increasingly pivotal role in restructuring supply chain cost management. Using panel data from Chinese-listed firms between 2010 and 2024, this study examines the impact of customers\u2019 Artificial Intelligence (AI) adoption on the cost stickiness of their suppliers. The findings indicate that customers\u2019 AI adoption mitigates suppliers\u2019 cost stickiness. This effect is more pronounced for larger suppliers, those with shorter geographic distance to customers, and those in highly competitive industries. Furthermore, customers\u2019 AI adoption alleviates suppliers\u2019 cost stickiness by promoting flexible production modes, enhancing production information flexibility, and raising production efficiency. Moreover, a two-stage model suggests that this alleviation of cost stickiness enhances suppliers\u2019 corporate resilience, offering directional insights for transmitting within supply chain systems. In summary, this paper expands the theoretical understanding of intelligent applications in supply chain systems, by substantiating cross-firm spillover effects and interactive behaviors among supply chain stakeholders.<\/jats:p>","DOI":"10.3390\/systems14060706","type":"journal-article","created":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T14:37:42Z","timestamp":1781879862000},"page":"706","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Unpacking the Spillover Effects of Customers\u2019 AI Adoption: How It Curbs Suppliers\u2019 Cost Stickiness"],"prefix":"10.3390","volume":"14","author":[{"given":"Jieying","family":"Gao","sequence":"first","affiliation":[{"name":"School of Finance, Capital University of Economics and Business, Beijing 100070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Duyang","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Finance, Capital University of Economics and Business, Beijing 100070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengjie","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Finance, Capital University of Economics and Business, Beijing 100070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"104758","DOI":"10.1016\/j.irfa.2025.104758","article-title":"Can the application of artificial intelligence technology and financial innovation drive the digital transformation of enterprises?","volume":"109","author":"Zou","year":"2025","journal-title":"Int. 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