2015/07/02 by Mahmood Mehdiloozad, Mehdiloozad, Mahmood, Kaoru Tone +3
Decision Sciences · Economics, Econometrics and Finance · Engineering · #Economic Growth and Productivity #Economic Theory and Policy #Economic theories and models #Efficiency Analysis Using DEA #FOS: Mathematics #Optimization and Control (math.OC) #Optimization and Mathematical Programming
paper · pdf · doi:10.48550/arxiv.1507.00705
openalex publication_date 2015/07/02 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
While measuring returns to scale in data envelopment analysis (DEA), the\noccurrence of multiple supporting hyperplanes has been perceived as a crucial\nissue. To deal effectively with this in weigh restrictions (WR) framework, we\nfirst precisely identify the two potential sources of its origin in the\nnon-radial DEA setting. If the firm under evaluation P is WR-efficient, the\nnon-full-dimensionality of its corresponding P-face-a face of minimum dimension\nthat contains P-is the unique source of origin (problem Type I). Otherwise, the\noccurrence of multiple WR-projections or, correspondingly, multiple P-faces\nbecomes the other additional source of origin (problem Type II). To the best of\nour knowledge, while problem Type I has been correctly addressed in the\nliterature, the simultaneous occurrences of problems Types I and II have not\neffectively been coped with. Motivated by this, we first show that problem Type\nII can be circumvented by using a P-face containing all the P-faces. Based on\nthis finding, we then devise a two-stage linear programming based procedure by\nextending a recently developed methodology by [Mehdiloozad, M., Mirdehghan, S.\nM., Sahoo, B. K., & Roshdi, I. (2015). On the identification of the global\nreference set in data envelopment analysis. European Journal of Operational\nResearch, 245, 779-788]. Our proposed method inherits all the advantages of the\nrecently developed method and is computationally efficient. The practical\napplicability of our proposed method is demonstrated through a real-world data\nset of 80 Iranian secondary schools.\n