Springer Verlag;Berlin/Heidelberg: Springer Berlin Heidelberg
摘要:
摘要： 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. 其他題名： Clean Techn Environ Policy 出版者： Berlin/Heidelberg: Springer Berlin Heidelberg 出版日期： 2016-06-01 出處： Clean technologies and environmental policy, 2016-06, Vol.18 (5), p.1535-1550 資源來源： ABI/INFORM Collection 版權： Springer-Verlag Berlin Heidelberg 2016 版權： Clean Technologies and Environmental Policy is a copyright of Springer, (2016). All Rights Reserved. 識別號： ISSN: 1618-954X 識別號： EISSN: 1618-9558 識別號： DOI: 10.1007/s10098-016-1135-x
