A Fuzzy Inference System for Evaluating the Performance of Knowledge Management System in Software Development Industry
In this research, for the purpose of evaluating the performance of knowledge management systems as an improving infrastructure for organizational learning and performance in software development industry, a fuzzy inference system is designed and evaluated. At first, input variables were extracted as...
| Main Authors: | , , |
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| Format: | Article |
| Language: | fas |
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Allameh Tabataba'i University Press
2018-08-01
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| Series: | مطالعات مدیریت کسب و کار هوشمند |
| Subjects: | |
| Online Access: | https://ims.atu.ac.ir/article_8890_b8f5c75741c599d4d37360a481b909e4.pdf |
| _version_ | 1797386079671681024 |
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| author | Imani Raeesi Vanan Mohammad Reza Taghva Delnia Amir Ashayeri |
| author_facet | Imani Raeesi Vanan Mohammad Reza Taghva Delnia Amir Ashayeri |
| author_sort | Imani Raeesi Vanan |
| collection | DOAJ |
| description | In this research, for the purpose of evaluating the performance of knowledge management systems as an improving infrastructure for organizational learning and performance in software development industry, a fuzzy inference system is designed and evaluated. At first, input variables were extracted as the performance evaluators of knowledge management system. Then, if-then rules were identified through the utilization of experts’ opinions and inserted to the fuzzy rule-base. The output of inference system was also designed for performance evaluation of knowledge management system. The designed system, through a comprehensive assessment of knowledge management systems, can enable organizations to identify the strengths, weaknesses, current condition, and future decisions making for the purpose of performance improvement. For the validation of fuzzy inference system, a comparison was made between system outputs and experts viewpoints. Considering the very small difference between the average of experts’ opinions and system output, it can be stated that the system has an appropriate precision and validity for future assessment. |
| first_indexed | 2024-03-08T22:04:46Z |
| format | Article |
| id | doaj.art-f52da76d3c3e4367a7596d54161fb1a1 |
| institution | Directory Open Access Journal |
| issn | 2821-0964 2821-0816 |
| language | fas |
| last_indexed | 2024-03-08T22:04:46Z |
| publishDate | 2018-08-01 |
| publisher | Allameh Tabataba'i University Press |
| record_format | Article |
| series | مطالعات مدیریت کسب و کار هوشمند |
| spelling | doaj.art-f52da76d3c3e4367a7596d54161fb1a12023-12-19T10:33:20ZfasAllameh Tabataba'i University Pressمطالعات مدیریت کسب و کار هوشمند2821-09642821-08162018-08-0162453610.22054/ims.2018.88908890A Fuzzy Inference System for Evaluating the Performance of Knowledge Management System in Software Development IndustryImani Raeesi Vanan0Mohammad Reza Taghva1Delnia Amir Ashayeri2Assistant Professor, Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, TehranAssociate Professor, Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran MA, Information Technology Management, Faculty of Management and Accounting, Allameh Tabataba’i University, TehranIn this research, for the purpose of evaluating the performance of knowledge management systems as an improving infrastructure for organizational learning and performance in software development industry, a fuzzy inference system is designed and evaluated. At first, input variables were extracted as the performance evaluators of knowledge management system. Then, if-then rules were identified through the utilization of experts’ opinions and inserted to the fuzzy rule-base. The output of inference system was also designed for performance evaluation of knowledge management system. The designed system, through a comprehensive assessment of knowledge management systems, can enable organizations to identify the strengths, weaknesses, current condition, and future decisions making for the purpose of performance improvement. For the validation of fuzzy inference system, a comparison was made between system outputs and experts viewpoints. Considering the very small difference between the average of experts’ opinions and system output, it can be stated that the system has an appropriate precision and validity for future assessment.https://ims.atu.ac.ir/article_8890_b8f5c75741c599d4d37360a481b909e4.pdfknowledge management systemfuzzy inference systemperformance evaluationsoftware development industry |
| spellingShingle | Imani Raeesi Vanan Mohammad Reza Taghva Delnia Amir Ashayeri A Fuzzy Inference System for Evaluating the Performance of Knowledge Management System in Software Development Industry مطالعات مدیریت کسب و کار هوشمند knowledge management system fuzzy inference system performance evaluation software development industry |
| title | A Fuzzy Inference System for Evaluating the Performance of Knowledge Management System in Software Development Industry |
| title_full | A Fuzzy Inference System for Evaluating the Performance of Knowledge Management System in Software Development Industry |
| title_fullStr | A Fuzzy Inference System for Evaluating the Performance of Knowledge Management System in Software Development Industry |
| title_full_unstemmed | A Fuzzy Inference System for Evaluating the Performance of Knowledge Management System in Software Development Industry |
| title_short | A Fuzzy Inference System for Evaluating the Performance of Knowledge Management System in Software Development Industry |
| title_sort | fuzzy inference system for evaluating the performance of knowledge management system in software development industry |
| topic | knowledge management system fuzzy inference system performance evaluation software development industry |
| url | https://ims.atu.ac.ir/article_8890_b8f5c75741c599d4d37360a481b909e4.pdf |
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