This paper introduces a dynamic Data Envelopment Analysis (DEA) model, called Dynamic Slacks-Based Measure (DSBM), which extends the dynamic DEA model proposed by Färe and Grosskopf. The DSBM model is developed within the slacks-based measure (SBM) framework, allowing for non-radial analysis and individual treatment of inputs and outputs. The model categorizes carry-over activities into four types: desirable, undesirable, free, and fixed, reflecting their actual characteristics. The paper presents the mathematical formulation of the DSBM model, including the production possibility set and the objective functions for input-oriented, output-oriented, and non-oriented efficiency measures. An empirical study on the generation division of fifty U.S.-Japan electric utilities is conducted to illustrate the application of the DSBM model. The results show that the classification of carry-over types significantly affects efficiency measurement, and the dynamic model outperforms traditional separate models in capturing long-term investment trends. The paper concludes with future research directions, including decomposition of inefficiency, dynamic cost and profit efficiencies, and further comparisons with other methods.This paper introduces a dynamic Data Envelopment Analysis (DEA) model, called Dynamic Slacks-Based Measure (DSBM), which extends the dynamic DEA model proposed by Färe and Grosskopf. The DSBM model is developed within the slacks-based measure (SBM) framework, allowing for non-radial analysis and individual treatment of inputs and outputs. The model categorizes carry-over activities into four types: desirable, undesirable, free, and fixed, reflecting their actual characteristics. The paper presents the mathematical formulation of the DSBM model, including the production possibility set and the objective functions for input-oriented, output-oriented, and non-oriented efficiency measures. An empirical study on the generation division of fifty U.S.-Japan electric utilities is conducted to illustrate the application of the DSBM model. The results show that the classification of carry-over types significantly affects efficiency measurement, and the dynamic model outperforms traditional separate models in capturing long-term investment trends. The paper concludes with future research directions, including decomposition of inefficiency, dynamic cost and profit efficiencies, and further comparisons with other methods.