Designing the adaptive fuzzy-neural inference system to measure the benefits of knowledge management in the organization
In recent years, knowledge management has become a fundamental principle in the field of management. Since the introduction of knowledge management, many institutions have tried to measure the benefits of using this concept. Success in implementing knowledge management and continuing its usage large...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | fas |
| Published: |
Iranian Research Institute for Information and Technology
2021-09-01
|
| Series: | Iranian Journal of Information Processing & Management |
| Subjects: | |
| Online Access: | http://jipm.irandoc.ac.ir/article-1-4615-en.html |
| _version_ | 1818731490630959104 |
|---|---|
| author | Hossein Yekkeh Seyed Mohammadbagher Jafari Seyed Mohammad Mahmoudi Mehdi ShamiZanjani |
| author_facet | Hossein Yekkeh Seyed Mohammadbagher Jafari Seyed Mohammad Mahmoudi Mehdi ShamiZanjani |
| author_sort | Hossein Yekkeh |
| collection | DOAJ |
| description | In recent years, knowledge management has become a fundamental principle in the field of management. Since the introduction of knowledge management, many institutions have tried to measure the benefits of using this concept. Success in implementing knowledge management and continuing its usage largely depends on measuring knowledge management benefits. However, few studies were conducted on this issue. This study, by using the adaptive neural fuzzy inference method (ANFIS) via Matlab 2017 software, tried to provide a predictive model to measure the benefits of knowledge management in the organization. The study population consists of scientists and experts working in 15 branches of the Social Security Organization, with a minimum of five years of experience in knowledge management related tasks. Based on the results, the degree of compatibility of the estimates with the actual results and the predictability and accuracy of the results were discussed, and at the end, based on the results, guidelines were provided to the studied organization. |
| first_indexed | 2024-12-17T23:18:31Z |
| format | Article |
| id | doaj.art-41abd918ad3b4816be6be8df4af120aa |
| institution | Directory Open Access Journal |
| issn | 2251-8223 2251-8231 |
| language | fas |
| last_indexed | 2024-12-17T23:18:31Z |
| publishDate | 2021-09-01 |
| publisher | Iranian Research Institute for Information and Technology |
| record_format | Article |
| series | Iranian Journal of Information Processing & Management |
| spelling | doaj.art-41abd918ad3b4816be6be8df4af120aa2022-12-21T21:28:58ZfasIranian Research Institute for Information and TechnologyIranian Journal of Information Processing & Management2251-82232251-82312021-09-01371288303Designing the adaptive fuzzy-neural inference system to measure the benefits of knowledge management in the organizationHossein Yekkeh0Seyed Mohammadbagher Jafari1Seyed Mohammad Mahmoudi2Mehdi ShamiZanjani3 College of Farabi; University of Tehran; Qom, Iran; Employee of the Social Security Organization College of Farabi; University of Tehran; Qom, Iran; College of Farabi; University of Tehran; Qom, Iran; Department of Information Technology Management; Faculty of Management; University of Tehran; Tehran, Iran In recent years, knowledge management has become a fundamental principle in the field of management. Since the introduction of knowledge management, many institutions have tried to measure the benefits of using this concept. Success in implementing knowledge management and continuing its usage largely depends on measuring knowledge management benefits. However, few studies were conducted on this issue. This study, by using the adaptive neural fuzzy inference method (ANFIS) via Matlab 2017 software, tried to provide a predictive model to measure the benefits of knowledge management in the organization. The study population consists of scientists and experts working in 15 branches of the Social Security Organization, with a minimum of five years of experience in knowledge management related tasks. Based on the results, the degree of compatibility of the estimates with the actual results and the predictability and accuracy of the results were discussed, and at the end, based on the results, guidelines were provided to the studied organization.http://jipm.irandoc.ac.ir/article-1-4615-en.htmlknowledge managementknowledge management benefitsadaptive neural fuzzy inference systemanfis |
| spellingShingle | Hossein Yekkeh Seyed Mohammadbagher Jafari Seyed Mohammad Mahmoudi Mehdi ShamiZanjani Designing the adaptive fuzzy-neural inference system to measure the benefits of knowledge management in the organization Iranian Journal of Information Processing & Management knowledge management knowledge management benefits adaptive neural fuzzy inference system anfis |
| title | Designing the adaptive fuzzy-neural inference system to measure the benefits of knowledge management in the organization |
| title_full | Designing the adaptive fuzzy-neural inference system to measure the benefits of knowledge management in the organization |
| title_fullStr | Designing the adaptive fuzzy-neural inference system to measure the benefits of knowledge management in the organization |
| title_full_unstemmed | Designing the adaptive fuzzy-neural inference system to measure the benefits of knowledge management in the organization |
| title_short | Designing the adaptive fuzzy-neural inference system to measure the benefits of knowledge management in the organization |
| title_sort | designing the adaptive fuzzy neural inference system to measure the benefits of knowledge management in the organization |
| topic | knowledge management knowledge management benefits adaptive neural fuzzy inference system anfis |
| url | http://jipm.irandoc.ac.ir/article-1-4615-en.html |
| work_keys_str_mv | AT hosseinyekkeh designingtheadaptivefuzzyneuralinferencesystemtomeasurethebenefitsofknowledgemanagementintheorganization AT seyedmohammadbagherjafari designingtheadaptivefuzzyneuralinferencesystemtomeasurethebenefitsofknowledgemanagementintheorganization AT seyedmohammadmahmoudi designingtheadaptivefuzzyneuralinferencesystemtomeasurethebenefitsofknowledgemanagementintheorganization AT mehdishamizanjani designingtheadaptivefuzzyneuralinferencesystemtomeasurethebenefitsofknowledgemanagementintheorganization |