Energy Efficiency of Intensive Rice Production in Japan: An Application of Data Envelopment Analysis

Aims: To correlate the energy and carbon emission efficiency relative to research income, gross internal area, and population for all the Higher Education Institutions (HEIs) in the UK and to assess the comparative carbon emission efficiency of HEIs relative to economic metrics. Study Design: Analytical panel data study. Place and Duration of Study: This paper evaluates the energy efficiency of 131 HEIs in the UK subdivided into Russell and non-Russell groups from 2008 to 2015. Methodology: Data Envelopment Analysis (DEA) and Malmquist productivity indexes (MPI) are used for the efficiency calculations. Results: The empirical results indicate that UK HEIs have relatively high energy efficiency scores of 96.9% and 77.6% (CRS) and 98.5%, 86.3% (VRS) for Russell and non-Russell groups respectively. Conclusion: The evidence from this study reveals that HEIs are not significantly suffering from scale effects, hence, an increase in energy efficiency of these institutions is feasible with the present operating scale but would need to work on their technical improvements in energy use. Malmquist index analysis confirms the lack of substantial technological innovation, which impedes their energy efficiency and productivity gain. Findings show that pure technical efficiency accounts for the annual efficiency obtained in the DEA model, the technological progress in contrast is the source of their energy inefficiency.

Download Full-text

An Improved Data Envelopment Analysis (DEA) Model to Measure China's Energy Efficiency

Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science ◽

10.2991/lemcs-15.2015.148 ◽

2015 ◽

Author(s):

Xiaqing Liu ◽

Lusi Liu ◽

Xiao Liu ◽

Guixian Liu

Keyword(s):

Energy Efficiency ◽

Data Envelopment Analysis ◽

Data Envelopment ◽

Dea Model

Download Full-text

Copula Approach to Multivariate Energy Efficiency Analysis

Asia Pacific Journal of Operational Research ◽

10.1142/s0217595921500421 ◽

2021 ◽

Author(s):

Mervenur Sözen ◽

Mehmet Ali Cengiz

Keyword(s):

Energy Efficiency ◽

Data Envelopment Analysis ◽

Joint Probability ◽

Joint Probability Distribution ◽

Data Envelopment ◽

Network Dea ◽

Dependency Structure ◽

Optimal Weights ◽

Joint Efficiency ◽

Copula Approach

Data envelopment analysis (DEA) is a method that finds the effectiveness of an existing system using a number of input and output variables. In this study, we obtained energy efficiencies of construction, industrial, power, and transportation sectors in OECD countries for 2011 using DEA. It is possible to achieve the efficiencies in different sectors. However, we aim to find joint energy efficiency scores for all sectors. One of the methods proposed in the literature to obtain joint efficiency is network data envelopment analysis (network DEA). Network DEA treats sectors as sub-processes and obtains system and process efficiencies through optimal weights. Alternatively, we used a novel copula-based approach to achieve common efficiency scores. In this approach, it is possible to demonstrate the dependency structure between the efficiency scores of similar qualities obtained with DEA by copula families. New efficiency scores are obtained with the help of joint probability distribution. Then, we obtained joint efficiency scores through the copula approach using these efficiency scores. Finally, we obtained the joint efficiency scores of the same sectors through network DEA. As a result, we compared network DEA with the copula approach and interpreted the efficiencies of each energy sector and joint efficiencies.

Download Full-text