医科大学知识管理成熟度评估:克尔曼沙医科大学的横断面研究

Soleiman Shafiee, Ardavan Hariri, Feizollah Foroghi
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引用次数: 1

摘要

目的:知识是企业发展服务和获得竞争优势的战略资源,对知识活动的及时评价将成为企业绩效卓越的重要因素。摘要本研究旨在评估克尔曼沙医科大学管理成熟度和知识水平及其对卓越绩效的影响。方法:研究方法为调查法,采用类型法。研究人群包括克尔曼沙阿医学院的管理人员和工作人员。该研究于2021年进行。抽样为简单分层随机抽样。样本量为320人。数据收集工具为亚洲生产力组织标准问卷(问卷信度系数:0.83)。问卷包括7项主要标准和46个问题。统计软件为SPSS 26。方差分析、t检验和简单线性回归分析了数据并检验了假设。结果:研究表明,学校处于知识管理成熟度发展水平,得分为141.16。回归结果表明,知识过程指数(0.69)对知识管理成熟度的影响最大,员工指数(0.67)对知识管理成熟度的影响最小。知识成熟度指标(技术、知识过程、领导力、过程、学习与创新、知识管理结果)除员工水平< 0.05外,其余各指标的t统计量均显著。结论:数据分析结果证明了亚洲生产力组织知识管理成熟度模型与绩效改善之间的关系。因此,该模型具有一定的可靠性,其结果可推广到高校。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing the maturity of knowledge management in medical universities: A cross-sectional study in Kermanshah University of Medical Sciences
Aim: Knowledge is a strategic resource for developing services and gaining a competitive advantage, and timely evaluation of knowledge activities will be an important factor for organizational performance excellence. The aim of this study was to evaluate the level of management maturity and knowledge of Kermanshah University of Medical Sciences and its effect on performance excellence. Methods: The research method is a survey, and its type is applied. The study population included managers and staff of Kermanshah University of Medical Sciences. The research was conducted in 2021. Sampling was simple stratified random sampling. The sample size was 320 people. The data collection tool was the standard questionnaire of the Asian Productivity Organization (reliability coefficient of the questionnaire: 0.83). The questionnaire consisted of seven main criteria and 46 questions. The statistical software used was SPSS version 26. ANOVA, t-test, and simple linear regression analyzed the data and tested the hypotheses. Results : The research showed that the university was at the level of development of knowledge management maturity with a score of 141.16. The regression results showed that the knowledge processes index with a value of 0.69 had the highest effect, and the staff index with a value of 0.67 had the lowest effect on knowledge management maturity. The value of t-statistic was significant for indicators of knowledge maturity (technology, knowledge processes, leadership, process, learning and innovation, and knowledge management results) except employees at the level of less than 0.05. Conclusion : The results of data analysis proved the relationship between the Asian Productivity Organization knowledge management maturity model and performance improvement. Therefore, the mentioned model can be relied on, and the results can be generalized to the university.
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