Slacks-based Measure Data Envelopment Research Articles

An efficiency analysis of municipal solid waste collection in Italy between 2010 and 2019

This paper presents an efficiency analysis of the collection of municipal solid waste in Italian provinces between 2010 and 2019. Particularly, the waste service efficiency of the 110 provinces was measured by implementing non-parametric Slack Based Measure Data Envelopment Analysis (SBM-DEA). A dynamic distributional analysis of efficiencies from 2010 to 2019 was also performed to investigate the behavior of the provinces efficiency in the analysed period specifically considering their size as a discriminant factor influencing it. To this aim a kernel-based method was used. Results show that the efficiency of the MSW collection service in the Italian provinces has increased steadily. The average efficiency grew from 44.7% to 53.0% during the period from 2010 to 2019, following the improvement in the sorted waste collection rate. Furthermore, smaller provinces performed better than larger ones.

Sustainability Performance of European Smart Cities: A Novel DEA Approach with Double Frontiers

Sustainability is the crux of urban renaissance. Imbibed with utopian technological planning, understanding the convergence between smart development and sustainable practices for city development is necessary. Smart cities have succeeded in bringing high standards of living to its residents. This article evaluates the long-term sustainability performance of 35 leading European smart cities over time from 2015 till 2020 to understand on how these cities address sustainability to make the concept of smart sustainable cities more actionable. A novel Double-Frontier Slack Based Measure Data Envelopment Analysis (DFSBM-DEA) model considering undesirable factors in the technology set is proposed for the assessment. An integrated relative sustainability performance assessment model considering both the optimistic and pessimistic viewpoint simultaneously, in terms of interval efficiency is used to determine the most efficient smart city under 6 various dimensions of sustainable development. These key dimensions include; Energy and Environmental Resource, Governance and Institution, Economic dynamism, Social cohesion and solidarity, Climate Change and, Safety and Security. A productivity progress assessment from a double frontier perspective using a modified Malmquist-DEA model is then used to capture the response of each smart city in terms of their productivity growth towards achieving sustainable development. Results show Dublin (ranked 1st) as the most smart and sustainable European city under all the proposed dimensions of sustainable development from the double-frontier perspective. Along with Dublin lies Oslo, Zurich and Amsterdam as the cities with high aggregate sustainability performance. The results also revealed significant difference in the productivity progress values from the optimistic and pessimistic viewpoint, thus exemplifying the significance for the proposed aggregate productivity progress measurement model. The findings of the present study contribute to knowledge and practice for smart city modellers, decision makers and urban planners, by aiding methodological clarity in assessing sustainable capacity of cities from a double frontier perspective and, in particular, by drawing attention to underlying assumptions about the role of sustainability in smart city development. This research stands as a breakthrough in the field of relative sustainability assessment using non-parametric approaches and a benchmark for global smart cities to shape their development in light of sustainability.

Productivity Analysis of Municipal Solid Waste Collection in Italy using SBM DEA Malmquist Index

This paper presents a productivity analysis of municipal solid waste collection in Italian provinces from 2010 to 2019. Particularly, the total factor productivity was measured by computing the non-parametric Global Malmquist Productivity Index implementing Slack Based Measure Data Envelopment Analysis (SBM-DEA). Findings show that the productivity of the sorted waste collection service slightly grew from 2010 to 2019. Such growth was due to an increase of the technical efficiency and an improvement of the service technology. However, in some years the efficiency changes and productivity increase were affected by the rise of the per capita production of waste.

旅游地生态效率测度的SBM-DEA模型及实证分析

旅游地生态效率测度的SBM-DEA模型及实证分析

Dynamic environmental efficiency evaluation of electric power industries: Evidence from OECD (Organization for Economic Cooperation and Development) and BRIC (Brazil, Russia, India and China) countries

As most power is consumed domestically, the environmental efficiencies of electric power industries in different countries may serve as a benchmark to evaluate their emission reduction efforts. Taking the power generated and carbon emissions as desirable and undesirable outputs respectively, this study adopts the environmental Malmquist index, which is based on a SBM-DEA (slack based measure data envelopment analysis) model, to investigate the environmental TFP (total factor productivity) index of electric power industries in 26 OECD (Organization for Economic Cooperation and Development) and BRIC (Brazil, Russia, India and China) countries from 1996 to 2010. In addition, we employ the Tobit regression model to analyze the influence of related factors on TFP and its decompositions. The empirical results indicate that the dynamic environmental efficiency or TFP provides a good perspective for evaluating emission reduction efforts of electric power industries in different countries. Fuel structure change and technological progress are the main driving forces to promote dynamic environmental efficiency. Furthermore, the economic situation and energy price changes also affect dynamic environmental efficiency significantly. Therefore, taking the energy structure and affordability into consideration, environmental TFP may indicate climate change mitigation efforts to a large extent.