ARTICLE
12 August 2025
Optimization Strategies for Performance Management of Knowledge Workers in EH Intelligent Company
Xiaoshi Chen Jin Peng Zhenfeng Zhu
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1 Guangdong University of Science and Technology, Dongguan 523083, Guangdong, China,
ssr 2025 , 7(7), 48–53; https://doi.org/10.26689/ssr.v7i7.11600
© 2025 by the Authors. Licensee: Bio-Byword Scientific Publishing Pty Ltd, Australia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract

In the context of globalization and informatization, knowledge-based employees have emerged as the primary drivers of enterprise innovation. Consequently, traditional performance management systems are encountering significant challenges in the context of intelligent enterprises. This article utilizes the EH Intelligent Company as a case study to assess the current state of performance management for its knowledge-based employees. The analysis identifies challenges such as ambiguous performance goals and standards, delayed feedback, ineffective incentives, and suboptimal cross-departmental collaboration mechanisms. Consequently, this study proposes targeted optimization measures, including the establishment of a flexible and personalized evaluation system, the enhancement of two-way communication, the construction of diversified incentive strategies, and the improvement of team collaboration assessment. The implementation of these measures is expected to enhance the performance of knowledge-based employees, boost enterprise competitiveness, and serve as a reference for analogous enterprises.

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