{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T09:53:59Z","timestamp":1776419639343,"version":"3.51.2"},"reference-count":19,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T00:00:00Z","timestamp":1776384000000},"content-version":"vor","delay-in-days":106,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Applied Mathematics"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:p>In order to support responsible and executable decisions about people resources, this paper creates a unified math system that mixes many tasks\u2019 predictions, fair results, and costs into one decision\u2010making process. Instead of treating task losses and business restrictions as separate additions, the suggested formulation incorporates (i) task\u2010level empirical dangers for churn prediction, performance evaluation, and promotion suggestions, (ii) team\u2010fairness departure fines (such as limited subgroup AUC\/positive\u2010rate variances), and (iii) spending\/hazard limits on intervention strategies inside a solitary primary\u2010dual optimization objective. This coupling gives Pareto\u2010efficient solutions that cannot be reached by just using a set weight sum of task losses since Lagrange multipliers adjustively change objectives to meet feasibility and fairness needs. With IBM HR Analytics Public HR Benchmark (1470 records) as a reproducible testbed, we show better predictive performance compared to classical baselines and give SHAP\u2010based explanations along with subgroup diagnostics. In the whole document, \u201cbig data\u201d means the scalable data processing and feature engineering pipeline (multisource integration, standardized coding, and governed feature store), not just the number of samples in a benchmark dataset. The proposed framework provides a reusable applied mathematics template for HR decision\u2010making where accuracy, cost, risk, and fairness have to be optimized simultaneously.<\/jats:p>","DOI":"10.1155\/jama\/4911283","type":"journal-article","created":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T09:01:36Z","timestamp":1776416496000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Intelligent Decision\u2010Making Model for Human Resources Based on Data\u2010Driven Analytics"],"prefix":"10.1155","volume":"2026","author":[{"given":"Haiyang","family":"Guan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-7385-5928","authenticated-orcid":false,"given":"Jinhui","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Duntian","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fengjie","family":"Gong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2026,4,17]]},"reference":[{"key":"e_1_2_12_1_2","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/7345547"},{"key":"e_1_2_12_2_2","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/8325677"},{"key":"e_1_2_12_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/access.2021.3104147"},{"key":"e_1_2_12_4_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0303297"},{"key":"e_1_2_12_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbusres.2021.04.019"},{"key":"e_1_2_12_6_2","doi-asserted-by":"publisher","DOI":"10.1080\/09585192.2019.1674357"},{"key":"e_1_2_12_7_2","doi-asserted-by":"publisher","DOI":"10.1080\/08839514.2023.2198897"},{"key":"e_1_2_12_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/access.2022.3160725"},{"key":"e_1_2_12_9_2","doi-asserted-by":"publisher","DOI":"10.1177\/0008125619862257"},{"key":"e_1_2_12_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bushor.2021.02.008"},{"key":"e_1_2_12_11_2","doi-asserted-by":"publisher","DOI":"10.1108\/aaaj-09-2020-4934"},{"key":"e_1_2_12_12_2","first-page":"29","article-title":"Intelligent Modeling of Managers\u2019 Data-Driven Decisions in Empowering Human Resources","volume":"3","author":"Abbasi S. 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