A data-driven design module development for enhancing multi-attribute decision-making (MADM) efficacy - Mohd Zulfadli Rozali, Mohd Zulfadli Rozali; Zakaria, Anies Fazihan (2024)
The development of decision-making modules that leverage data-driven design principles is crucial for enhancing the efficacy of multi-attribute decision-making (MADM) systems. This paper discussed modules, focusing on the integration of diverse attributes into the decision-making process. Five distinct modules are proposed within this framework, each tailored to address specific aspects of MADM, thereby offering a comprehensive approach to decision support. The proposed modules are conceptualized based on a thorough analysis of existing datadriven design methodologies and MADM theories, ensuring their relevance and applicability to real-world decision-making scenarios. The effectiveness and validity of the proposed framework and its modules are assessed through expert reviews. These reviews involve subject matter experts evaluating the content structure, usability, and applicability of the modules in various decisionmaking contexts. The feedback obtained from these reviews is integral to refining the modules, ensuring their alignment with the needs and expectations of end-users. For practitioners, the framework provides a structured approach to developing decision-making modules that are both robust and adaptable, capable of accommodating a wide range of decision attributes. For researchers, it offers a conceptual and methodological foundation for further exploration into data-driven design and its application in MADM. This paper contributes to the evolving field of decision support systems, highlighting the importance of structured content development in enhancing the decisionmaking capabilities of organizations and individuals alike.