Data envelopment analysis (DEA) is a representative method to estimate efficient frontiers and derive efficiency. However, in a situation with weight restrictions on individual input-output pairs, its suitability has been questioned. Therefore, the main purpose of this paper is to develop a mathematical method, which we call the input-oriented ratio-based comparative efficiency model, DEA-R-I, to derive the input-target improvement strategy in situations with weight restrictions. Also, we prove that the efficiency score of DEA-R-I is greater than that of CCR-I, which is the first and most popular model of DEA, in input-oriented situations without weight restrictions to claim the DEA-R-I can replace the CCR model in these situations. We also show an example to illustrate the necessity of developing the new model. In a nutshell, we developed DEA-R-I to replace CCR-I in all input-oriented situations because it sets a more accurate weight restriction and yields a more achievable strategy.