Abstract
This study used a dynamic data envelopment analysis (DEA) model to investigate the learning carry-over effect on the performance of Taiwan’s municipal solid waste (MSW) recycling systems. Regression analysis was used to estimate the latent learning effect in the MSW recycling systems of 23 local governments during 2002–2011. The results were incorporated into a dynamic DEA model that evaluated the relative performance of local government systems. This research makes three major contributions to the field. Firstly, it develops an approach that incorporates the carry-over effects of organizational learning into a dynamic DEA model. Secondly, it evaluates the influence of those carry-over effects on the MSW recycling performance of Taiwan’s local governments. Finally, it identifies policies to help local governments with inefficient MSW recycling systems as they seek to improve and promote recycling activities. In addition, local government should continue to promote its recycling policies.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
