Abstract
Conventional data envelopment analysis (DEA) models assume that the inputs of a specific period are consumed to produce the outputs of the same period. However, in some applications, the inputs of a period can be thought to partially contribute to the outputs of several subsequent periods. This can be described as time lag effects for performance evaluation. A few researches have presented DEA models using the time lag weights of input or output factors to address the time lag effects. In those models, the weights for the time lag effects can vary by period. In this paper, we propose another DEA model with consistent weights for time lag effects throughout the periods. The proposed model is more realistic and more discriminative than the existing time lag model. We present the results of a case example for comparison of the proposed model and the existing time lag model.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.