Open AccessPredicting Job Performance Based on Knowledge Management
Author(s) -
Ebrahim Alijanzadeh,
Ali Asghar Razavi,
Safiyeh T Ahmasebi Limuni
Publication year - 2020
Publication title -
journal of management and accounting studies
Language(s) - English
Resource type - Journals
ISSN - 2693-8448
DOI - 10.24200/jmas.vol8iss4pp34-38
Subject(s) - cronbach's alpha , face validity , statistical population , reliability (semiconductor) , psychology , knowledge management , applied psychology , job performance , content validity , population , validity , medical education , descriptive statistics , computer science , job satisfaction , statistics , medicine , social psychology , mathematics , psychometrics , clinical psychology , power (physics) , physics , environmental health , quantum mechanics
The objective of this research is to predict job performance based on knowledge management. The methodology of this research was applied according to its objective and descriptive-correlational based on the execution method. The statistical population of this research is all the librarians from public libraries of Mazandaran province with 265 members by full-census manner. 179 questionnaires were turned back. The research tool was Hosseinzadeh (2019) personal knowledge management questionnaire and Hosseini job performance questionnaire (2013). Cronbach’s alpha coefficient was used to estimate the face and content validity, and reliability of the questionnaire was estimated according to professors and specialists’ ideas which were obtained higher than 0.7 in all questionnaires. Data was analyzed using SPSS 18 software. The results of this research showed that the components of knowledge management have a positive and significant effect on job performance (P<0.01). Moreover, 37.6% of changes caused by job performance are predicted by the components of knowledge management. According to the obtained results, some suggestions are offered to improve the research variables.