Staggered Shifts policy is increasingly becoming one of the effective methods to solve the commute travel congestion problem in the AM and PM peak periods. In order to implement the policy effectively, it is necessary to evaluate its influence on commuters' travel decisions through travel demand behavior forecasting. By analyzing the commute travel data, a Binary Logit model was developed to predict the employees' commuting preference. Then the acceptability of the Staggered Shifts policy in Beijing city was evaluated. The results indicate that the feasibility of the Staggered Shifts strategy is mainly related to commuters' occupation, work schedules, travel behaviors and some basic socioeconomic attributes. Therefore, it's necessary for government to choose the most suitable job categories and work arrangements, cooperate with related enterprises and departments, and build some corresponding guarantees for the implementing of the policy.