Efficiency, one of the important measures of business performance, is directly influenced by input and output factors and is also sometimes significantly affected by environmental variables. Examining the case of Fast-Food Company A described in this paper, the environmental characteristics of each store (commercial area vs. non-commercial area) had a substantial impact on business performance, giving rise to the problem that a store could receive a superior performance evaluation merely due to its favorable location. Therefore, consideration of such categorical environmental variables is required for fair efficiency evaluation. To enable fair evaluation and, furthermore, efficiency ranking, this study proposes an approach that simultaneously employs Data Envelopment Analysis (DEA) and Constrained Canonical Correlation Analysis (CCCA). The general procedure of this approach involves first selecting efficient observations using DEA, and then performing CCCA on the selected data to determine the efficient production frontier. If categorical variables are not considered, this approach does not differ significantly from existing studies. However, the question of whether categorical variables should be considered at the DEA stage or at the CCCA stage emerges as an important issue, and no guidelines exist on this matter. Therefore, this study compares and analyzes two possible methods to provide guidelines for the consideration of categorical variables. All analyses are based on actual data from Fast-Food Company A.