A Ranking Approach for Decision Making Units with Interval Data using Multi-Objective IDEA Model and Relative Closeness Coefficient Method
DOI:
https://doi.org/10.14456/jeit.2023.25Keywords:
Data Envelopment Analysis, Interval Data Envelopment Analysis, Multi-Objective IDEA Model, Relative Closeness Coefficient MethodAbstract
The traditional Data Envelopment Analysis (DEA) model can assess the relative efficiency of decision-making units (DMUs) with precise data. However, it cannot be applied to evaluate the efficiency of production units with imprecise data. Imprecise data can take various forms, such as interval data or fuzzy data. This research aims to introduce a ranking method for DMUs with interval data using a Multi-Objective IDEA Model (MOIDEA model) and the Relative Closeness Coefficient method (RCC). In the first step, the MOIDEA model is used to assess interval efficiency. Subsequently, the interval efficiency scores were transformed into precise efficiency scores using the Relative Closeness Coefficient (RCC) method. Testing the proposed method against problem in the literature reveals that it achieves a high Spearman rank correlation (r > 0.999) when compared to a method in the literature. Therefore, the proposed method is reliable and can serve as one approach for assessing and ranking DMUs that possess interval data.
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เนื้อหาและข้อมูลในบทความที่ลงตีพิมพ์ในวารสารศูนย์ดัชนีการอ้างอิงวารสารไทย ถือเป็นข้อคิดเห็นและความรับผิดชอบของผู้เขียนบทความโดยตรงซึ่งกองบรรณาธิการวารสาร ไม่จำเป็นต้องเห็นด้วย หรือร่วมรับผิดชอบใด ๆ
บทความ ข้อมูล เนื้อหา รูปภาพ ฯลฯ ที่ได้รับการตีพิมพ์ในวารสารศูนย์ดัชนีการอ้างอิงวารสารไทย ถือเป็นลิขสิทธิ์ของวารสารศูนย์ดัชนีการอ้างอิงวารสารไทย หากบุคคลหรือหน่วยงานใดต้องการนำทั้งหมดหรือส่วนหนึ่งส่วนใดไปเผยแพร่ต่อหรือเพื่อกระทำการใด จะต้องได้รับอนุญาตเป็นลายลักอักษรจากวารสารศูนย์ดัชนีการอ้างอิงวารสารไทยก่อนเท่านั้น
