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<p>This paper presents a comprehensive multi-criteria group decision-making (MCGDM) framework for evaluating knowledge management (KM) solutions, with a particular focus on the critical success factors (CSFs) that influence organizational efficacy. The approach integrates the MOWSCER and MARCOS methods, operating within an interval type-2 fuzzy sets (IT2FS) framework to address the underlying uncertainty in expert evaluations. Unlike the DEMATEL method, MOWSCER not only considers cause-and-effect relationships but also assigns weights to CSFs, thereby offering a more robust analysis. Additionally, the MARCOS method has been enhanced by applying the border approximation area concept, enabling it not only to assess KM solutions effectively but also to allocate weights to the participating experts, which adds depth to the decision-making process. To manage the inherent ambiguity in human judgments, IT2FSs are employed for greater precision in capturing linguistic variables and subjective opinions. The proposed model’s practical utility is demonstrated through a case study conducted in a steel manufacturing facility, showcasing its capability to pinpoint actionable KM strategies aligned with organizational needs. Sensitivity analysis highlights the importance of expert weighting in the decision-making process, revealing notable shifts when experts 2 and 5 are replaced. The reliability of this methodology has been affirmed through comparative analyses with established approaches from the literature. Among the key KM solutions identified are creating a transparent workflow or open-door policy, developing employees’ awareness of KM, encouraging teamwork, and awarding group-based rewards. The research also explores the managerial and theoretical implications, offering valuable insights into both the academic and practical applications of KM optimization strategies.</p>

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An Integrated decision-making framework for evaluating knowledge management solutions through critical success factors: a combination of MARCOS and MOWSCER methods under interval type-2 fuzzy sets

  • 期刊论文

  • 发表日期：

    2026年5月6日

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  • Mostafa Jafari,
  • Shayan Naghdi Khanachah

摘要

This paper presents a comprehensive multi-criteria group decision-making (MCGDM) framework for evaluating knowledge management (KM) solutions, with a particular focus on the critical success factors (CSFs) that influence organizational efficacy. The approach integrates the MOWSCER and MARCOS methods, operating within an interval type-2 fuzzy sets (IT2FS) framework to address the underlying uncertainty in expert evaluations. Unlike the DEMATEL method, MOWSCER not only considers cause-and-effect relationships but also assigns weights to CSFs, thereby offering a more robust analysis. Additionally, the MARCOS method has been enhanced by applying the border approximation area concept, enabling it not only to assess KM solutions effectively but also to allocate weights to the participating experts, which adds depth to the decision-making process. To manage the inherent ambiguity in human judgments, IT2FSs are employed for greater precision in capturing linguistic variables and subjective opinions. The proposed model’s practical utility is demonstrated through a case study conducted in a steel manufacturing facility, showcasing its capability to pinpoint actionable KM strategies aligned with organizational needs. Sensitivity analysis highlights the importance of expert weighting in the decision-making process, revealing notable shifts when experts 2 and 5 are replaced. The reliability of this methodology has been affirmed through comparative analyses with established approaches from the literature. Among the key KM solutions identified are creating a transparent workflow or open-door policy, developing employees’ awareness of KM, encouraging teamwork, and awarding group-based rewards. The research also explores the managerial and theoretical implications, offering valuable insights into both the academic and practical applications of KM optimization strategies.