Positive weights in data envelopment analysis
نویسندگان
چکیده
Abstract Data Envelopment Analysis (DEA) models give each decision making unit freedom to assign values the input-output weights maximising its efficiency score. However, there is no guarantee that optimal obtained from a DEA model are always positive which poses problem, in both theory and practice. This paper offers new linear programming deal with zero problem without restricting or placing prior value judgments on them while maintaining original frontier. These generate profile of maximum number applicable envelopment multiplier settings. programs still allow weight flexibility independent solver. We show how these can be modified provide unit-specific weights. illustrate relevance our approach using artificial real world data.
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ژورنال
عنوان ژورنال: Journal of Productivity Analysis
سال: 2023
ISSN: ['0895-562X', '1573-0441']
DOI: https://doi.org/10.1007/s11123-023-00682-3