Eco-efficiency in greenhouse emissions among manufacturing industries: A range adjusted measure

Ramli, Noor Asiah; Munisamy, Susila

doi:10.1016/j.econmod.2015.02.034

Cited by 47 publications

(21 citation statements)

References 56 publications

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“…As will be shown below, this summation of all slacks in the objective function departs from the ratio form of ratio 1. However, it is consistent with the idea of maximizing output while minimizing EIs and thus has been adopted in past eco-efficiency studies (see Ramli and Munisamy, 2015 and the related studies they cite). This study employed the RAM additive model (Cooper et al, 1999), presented below.…”

Section: Datasupporting

confidence: 70%

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An approach to holistically assess (dairy) farm eco-efficiency by combining Life Cycle Analysis with Data Envelopment Analysis models and methodologies

Soteriades

Faverdin

Moreau

et al. 2016

Animal

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Eco-efficiency is a useful guide to dairy farm sustainability analysis aimed at increasing output (physical or value added) and minimizing environmental impacts (EIs). Widely used partial eco-efficiency ratios (EIs per some functional unit, e.g. kg milk) can be problematic because (i) substitution possibilities between EIs are ignored, (ii) multiple ratios can complicate decision making and (iii) EIs are not usually associated with just the functional unit in the ratio's denominator. The objective of this study was to demonstrate a 'global' eco-efficiency modelling framework dealing with issues (i) to (iii) by combining Life Cycle Analysis (LCA) data and the multiple-input, multiple-output production efficiency method Data Envelopment Analysis (DEA). With DEA each dairy farm's outputs and LCA-derived EIs are aggregated into a single, relative, bounded, dimensionless eco-efficiency score, thus overcoming issues (i) to (iii). A novelty of this study is that a model providing a number of additional desirable properties was employed, known as the Range Adjusted Measure (RAM) of inefficiency. These properties altogether make RAM advantageous over other DEA models and are as follows. First, RAM is able to simultaneously minimize EIs and maximize outputs. Second, it indicates which EIs and/or outputs contribute the most to a farm's eco-inefficiency. Third it can be used to rank farms in terms of eco-efficiency scores. Thus, non-parametric rank tests can be employed to test for significant differences in terms of eco-efficiency score ranks between different farm groups. An additional DEA methodology was employed to 'correct' the farms' eco-efficiency scores for inefficiencies attributed to managerial factors. By removing managerial inefficiencies it was possible to detect differences in eco-efficiency between farms solely attributed to uncontrollable factors such as region. Such analysis is lacking in previous dairy studies combining LCA with DEA. RAM and the 'corrective' methodology were demonstrated with LCA data from French specialized dairy farms grouped by region (West France, Continental France) and feeding strategy (regardless of region). Mean eco-efficiency score ranks were significantly higher for farms with <10% and 10% to 30% maize than farms with >30% maize in the total forage area before correcting for managerial inefficiencies. Mean eco-efficiency score ranks were higher for West than Continental farms, but significantly higher only after correcting for managerial inefficiencies. These results helped identify the eco-efficiency potential of each region and feeding strategy and could therefore aid advisors and policy makers at farm or region/sector level. The proposed framework helped better measure and understand (dairy) farm eco-efficiency, both within and between different farm groups.

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Section: Datasupporting

confidence: 70%

“…This study employed the RAM additive model (Cooper et al, 1999), presented below. RAM and its variants have been used in several eco-efficiency studies of industries other than dairy, see Ramli and Munisamy (2015).…”

Section: Datamentioning

confidence: 99%

An approach to holistically assess (dairy) farm eco-efficiency by combining Life Cycle Analysis with Data Envelopment Analysis models and methodologies

Soteriades

Faverdin

Moreau

et al. 2016

Animal

View full text Add to dashboard Cite

show abstract

“…In addition, it calculates efficiency by considering economic and environmental outcomes to understand undesirable factors in efficiency evaluation [59,60]. Indeed, we consider eco-innovation by adding further sustainability attributes of innovations that allow bioenergy policies to reduce the environmental burden in the evaluation [61,62]. Further, this study measures the eco-efficiency of bioenergy technology policy based on Smith and Street's [63] notion of dynamic effects (i.e., path dependence), which means that contemporary inputs are, to some extent, invested for future outputs.…”

Section: Theoretical Background and Research Methodologymentioning

confidence: 99%

“…DEA can easily handle multiple inputs and outputs and does not require assumptions about the specific functional form of the production function [69]. To estimate eco-efficiency, we use two policy input factors, namely technology-push and demand-pull activities [2,53], and two output factors, namely innovation outcomes [25,27,64] and the reduction in greenhouse gas (GHG) emissions [61,62]. Moreover, R&D expenditure, the contribution of bioenergy to total energy supply, and the number of patent applications are the respective proxies for technology-push policy [12,23,25,70], demand-pull policy [12,23], and innovation outcomes [27,71,72].…”

Section: Data Measurement and Sourcesmentioning

confidence: 99%

Eco-Efficiency of Government Policy and Exports in the Bioenergy Technology Market

2017

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This study investigates how the eco-efficiency of government policy-continuously implementing innovation-friendly policy based on both environmental and economic considerations-affects the export performance of bioenergy technologies, using panel data from 16 countries during 1995-2012. Various heterogeneous panel framework tests are conducted. Our panel unit root and co-integration tests, which allow for cross-sectional dependence in the panel, show that the time series data on the eco-efficiency of public support, exports, and gross domestic product (GDP) are integrated and co-integrated. We set up a panel vector error correction model (VECM) to empirically test the casual relationship among the variables examined. The long-term parameters of the variables were calculated using dynamic ordinary lease squares (DOLS). Panel difference generalized method of moments (GMM) estimations were conducted to test the short-term relationship among the variables. The results of this study therefore show that the eco-efficiency of government policy positively influences export performance in the long run, but not in the short run. The presented findings also indicate that efficiently implemented government policy plays a crucial role in achieving environmentally sound and sustainable development, showing path dependence among the eco-efficiency of government policy, exports, and GDP. We finally suggest policy implications based on the results.

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“…This method can be used to evaluate the environmental performance of the system; (iii) Models for assessing efficiency, such as the Range Adjusted Measure (RAM) model. These models explain desirable and undesirable outputs in the production process [25] and positive matrix factorization [26]. In recent years, various studies have used DEA to calculate efficiency using different models with multiple inputs and outputs [27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Development and Urban Sustainability: An Analysis of Efficiency Using Data Envelopment Analysis

Piña

Martínez

2016

Sustainability

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Abstract:In recent decades, the majority of cities in developing countries have grown rapidly and have experienced increasing environmental problems. These changes have generated a broad discussion on urban sustainability and development. In this discussion, it is fundamental to establish methods for measuring urban sustainability using a quantitative approach. This research seeks to estimate and evaluate the environmental, social, and economic efficiency of cities in a developing country, Colombia, using data envelopment analysis to determine the changes that occurred between 2005 and 2013. In this study, indicators related to economic, environmental, and social performance are used with the objective of analyzing efficiency from urban sustainability. The results indicate differences among cities, where the efficient cities show adequate resource use, lower environmental impacts, improved social conditions, and guaranteed economic growth and development. Moreover, as the city scale increases, urban sustainability declines. All these findings are important in the formulation and design of adequate urban policies to improve and strengthen sustainability and social welfare over the long term, particularly in cities in developing countries.

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Eco-efficiency in greenhouse emissions among manufacturing industries: A range adjusted measure

Cited by 47 publications

References 56 publications

An approach to holistically assess (dairy) farm eco-efficiency by combining Life Cycle Analysis with Data Envelopment Analysis models and methodologies

An approach to holistically assess (dairy) farm eco-efficiency by combining Life Cycle Analysis with Data Envelopment Analysis models and methodologies

Eco-Efficiency of Government Policy and Exports in the Bioenergy Technology Market

Development and Urban Sustainability: An Analysis of Efficiency Using Data Envelopment Analysis

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