TITLE:
The Optimization of Talent Selection System of MCC Jiangxi Copper Aynak Mining CO., LTD.
AUTHORS:
Abdullah Burhani, Noorullah Rafiqee
KEYWORDS:
Talent Selection System, Talent Assessment, Human Resource
JOURNAL NAME:
Open Access Library Journal,
Vol.13 No.4,
April
22,
2026
ABSTRACT: The mining project of MCC Jiangxi Copper Aynak Mining Co., Ltd. in Afghanistan is of strategic and economic importance. However, the region’s long-term conflict has disrupted the local talent development system, creating a severe shortage of skilled mining professionals. Additionally, local universities’ outdated curricula and lack of practical training have hindered recruitment efforts. The company’s current talent selection system primarily focuses on professional skills and work experience, neglecting crucial factors such as cross-cultural communication, adaptability, and alignment with corporate strategy. This limits the company’s ability to navigate Afghanistan’s unique operational challenges, affecting both project progress and long-term growth. This study examines MCC Jiangxi Copper Aynak Mining Co., Ltd.’s talent selection system, utilizing theories in human resource management, talent assessment, and competency models. The research analyzes the company’s development in Afghanistan, talent distribution, and the limitations of the existing selection mechanism. It aims to clarify selection objectives, expand recruitment channels, and improve selection processes, ultimately creating a tailored talent selection system for the company’s needs in Afghanistan. The study proposes a multi-dimensional talent selection system that addresses various positions within the Afghanistan mining project. This system includes clear competency standards for roles in exploration, mining, and other key areas, while optimizing recruitment channels and decision-making processes. It is designed to meet the specific demands of transnational mining operations and local conditions in Afghanistan, enhancing the company’s ability to select highly skilled, adaptable talent. This will improve operational efficiency, resource development, and market competitiveness.