仆人式领导
结构方程建模
业务
员工调查
独创性
价值(数学)
心理学
知识管理
验证性因素分析
营销
社会心理学
组织承诺
变革型领导
计算机科学
机器学习
创造力
服务(商务)
作者
Behrooz Ghlichlee,Mohsen Motaghed Larijani
出处
期刊:Leadership & organization development journal
[Emerald Publishing Limited]
日期:2024-02-11
卷期号:45 (3): 544-558
被引量:7
标识
DOI:10.1108/lodj-08-2023-0428
摘要
Purpose The purpose of this paper is to examine the relationship between servant leadership, employee innovative behavior and knowledge employee performance in knowledge-based firms. Design/methodology/approach A quantitative approach was used to conduct the present study. The respondents were sampled from knowledge-based firms in Iran. Overall, 726 knowledge employees in 121 firms were selected using convenience sampling. A confirmatory factor analysis was conducted to ascertain the validity and reliability of the observed items, and a structural equation model was employed for testing the hypotheses. Findings In the studied firms, servant leadership has a significant effect on employee innovative behavior. Moreover, the findings of this study show that firms that enhance their employees’ innovative behavior have higher knowledge employee performance. Research limitations/implications The study was conducted in knowledge-based firms in Iran. Therefore, our conclusions may not be applicable to other countries. Future studies should be carried out with samples from other contexts. Practical implications We found that servant leadership is conducive to employee innovative behaviors, and this effect leads to high knowledge employee performance. Accordingly, knowledge-based firms’ leaders should encourage employees’ innovative behavior through stimulating employee thriving at work, supporting employees’ development and empowering them with decision-making discretion. Originality/value This study contributes to advance research on servant leadership literature by linking servant leadership to knowledge employee performance in knowledge-based firms through employee innovative behavior as a mediator.
科研通智能强力驱动
Strongly Powered by AbleSci AI