A new slacks-based measure of Malmquist-Luenberger index in the presence of undesirable outputs

In the majority of production processes, noticeable amounts of bad byproducts or bad outputs are produced. The negative effects of the bad outputs on efficiency cannot be handled by the standard Malmquist index to measure productivity change over time. Toward this end, the Malmquist-Luenberger index (MLI) has been introduced, when undesirable outputs are present. In this paper, we introduce a Data Envelopment Analysis (DEA) model as well as an algorithm, which can successfully eliminate a common infeasibility problem encountered in MLI mixed period problems. This model incorporates the best endogenous direction amongst all other possible directions to increase desirable output and decrease the undesirable outputs at the same time. A simple example used to illustrate the new algorithm and a real application of steam power plants is used to show the applicability of the proposed model

Power industry restructuring and eco-efficiency changes:a new slacks-based model in Malmquist-Luenberger Index measurement

Measuring variations in efficiency and its extension, eco-efficiency, during a restructuring period in different industries has always been a point of interest for regulators and policy makers. This paper assesses the impacts of restructuring of procurement in the Iranian power industry on the performance of power plants. We introduce a new slacks-based model for Malmquist-Luenberger (ML) Index measurement and apply it to the power plants to calculate the efficiency, eco-efficiency, and technological changes over the 8-year period (2003-2010) of restructuring in the power industry. The results reveal that although the restructuring had different effects on the individual power plants, the overall growth in the eco-efficiency of the sector was mainly due to advances in pure technology. We also assess the correlation between efficiency and eco-efficiency of the power plants, which indicates a close relationship between these two steps, thus lending support to the incorporation of environmental factors in efficiency analysis

Testing the theory of performance frontiers in the era of Industry 4.0

info:eu-repo/semantics/publishedVersio

Eco-efficiency considering the issue of heterogeneity among power plants

One of the main objectives in restructuring power industry is enhancing the efficiency of power facilities. However, power generation industry, which plays a key role in the power industry, has a noticeable share in emission amongst all other emission-generating sectors. In this study, we have developed some new Data Envelopment Analysis models to find efficient power plants based on less fuel consumption, combusting less polluting fuel types, and incorporating emission factors in order to measure the ecological efficiency trend. We then applied these models to measuring eco-efficiency during an eight-year period of power industry restructuring in Iran. Results reveal that there has been a significant improvement in eco-efficiency, cost efficiency and allocative efficiency of the power plants during the restructuring period. It is also shown that despite the hydro power plants look eco-efficient; the combined cycle ones have been more allocative efficient than the other power generation technologies used in Iran

Eco-efficiency measurement and material balance principle:an application in power plants Malmquist Luenberger Index

Incorporating Material Balance Principle (MBP) in industrial and agricultural performance measurement systems with pollutant factors has been on the rise in recent years. Many conventional methods of performance measurement have proven incompatible with the material flow conditions. This study will address the issue of eco-efficiency measurement adjusted for pollution, taking into account materials flow conditions and the MBP requirements, in order to provide ‘real’ measures of performance that can serve as guides when making policies. We develop a new approach by integrating slacks-based measure to enhance the Malmquist Luenberger Index by a material balance condition that reflects the conservation of matter. This model is compared with a similar model, which incorporates MBP using the trade-off approach to measure productivity and eco-efficiency trends of power plants. Results reveal similar findings for both models substantiating robustness and applicability of the proposed model in this paper

Modeling eco-efficiency changes of heterogeneous firms with an application in power plants / Behrouz Arabi

The objective of power industry restructuring worldwide has been to enhance efficiency, hence providing an increased focus on efficiency measurement in power industries. Power generation which plays a key role in the power industry accounts for a noticeable share of emission generation amongst all power industry sectors. This would be costly not only for the sector itself, but also for the entire economy. Thus, the ecological impact of power generation should not be neglected in efficiency measurement. In addition, the non-homogeneous nature of power generation technologies has always been a barrier to drawing a complete picture of power generation industry efficiency or to compare the relative efficiency of different power plant technologies using methodologies such as Data Envelopment Analysis (DEA). In view of the above, this research aims for introducing a more comprehensive DEA method to measure the ecological efficiency or eco-efficiency trend of heterogeneous power plants during an eight-year period of power industry restructuring in Iran using a popular measure known as the Malmquist-Luenberger index (MLI). Toward this aim, the study tackles a prevalent infeasibility problem which occurs when the traditional Directional Distance Function (DDF) or slack-based DEA models are adopted to measure MLI. This study introduces an algorithm accompanied by a slack-based model to tackle the infeasibility problem. In addition, to represent thermodynamic realities of mechanical systems more accurately, the study incorporates the Materials Balanced Principle (MBP) requirement in the measurement of efficiency by adopting a slack-based DEA model. As fuel rotation is an approach to generate the same amount of energy with less emission or cost, a fuel control constraint has been introduced to all MBP-enabled DEA models. Furthermore, to measure the trend of ecological efficiency during the eight-year period of restructuring across the Iranian power industry, in addition to conventional technical PhD Thesis Modeling Eco-efficiency Changes of Heterogeneous Firms with an Application in Power Plants efficiency measures, some DEA models are also introduced and adopted to identify efficient power plants based on a number of factors; namely, less fuel consumption, combustion of less polluting fuel types, and incorporating emission factors. In addition, to see the effects of restructuring on the efficiency measures, rather than on the factors conventionally used for eco-efficiency and cost efficiency measurement, values of inputs and outputs are calculated using a new set of rules and regulations affected by restructuring. Due to the non-homogenous nature of different power plant technologies, in the studies undertaken so far, efficiency and eco-efficiency measurements have been carried out within the homogenous power plant categories. However, in order to provide more comprehensive information for future planning and budgeting and to draw a complete picture of the performance delivered by heterogeneous power plants, this study introduces models which can handle heterogeneous firms and are deployed to measure cost and allocative efficiency in addition to the eco-efficiency of power plants. Results reveal improvements in the eco-efficiency, cost efficiency and allocative efficiency of power plants during the restructuring period. It is also shown that although hydro power plants may look more eco-efficient, in Iran, the combined-cycle ones have been more allocatively efficient than those of other power generation technologies. Furthermore, results have exhibited that gas is the most cost-efficient, but less allocatively efficient technology in Iran

Eco-efficiency change in power plants: Using a slacks-based measure for the meta-frontier Malmquist-Luenberger productivity index

Malmquist–Luenberger index is a popular index deployed for evaluating eco-efficiency and productivity change over a certain period when both desirable and undesirable factors are jointly produced in some production processes. However, conventional data envelopment analysis (DEA) models used for computing this index are unable to distinguish the various technologies employed by the decision making units. When heterogeneity exists in the technology, the meta-frontier Malmquist–Luenberger approach is adopted to evaluate eco-efficiency and productivity change over a period when undesirable outputs are incorporated in the analysis of efficiency. In this paper, a new slacks-based DEA measure is developed and used to compute the meta-frontier Malmquist–Luenberger productivity index. This approach is then deployed to evaluate 48 Iranian thermal power plants productivity change in three different categories – steam, gas, and combined cycle – over an eight year period of restructuring in the power industry. This technique enables the calculation of eco-efficiency change of thermal power plants operating under different technologies as well as the technology gap ratios and measures the extent to which the efficiency frontiers of individual categories of power plants deviate from the meta-frontier. The results reveal that the last years of the restructuring period saw a greater rate of productivity growth compared to the initial years; and evidence of significant eco-efficiency improvements over the period in all the three types of the thermal power plants. Finally, it is expected that the findings in this study aid policy makers and power industry regulators in developing sustainable energy policies towards environmental protection and planning power plant operations

Scale directional distance function and its application to the measurement of eco-efficiency in the manufacturing sector

Directional distance function (DDF) is a recognized technique for measuring efficiency while incorporating undesirable outputs. This approach allows for desirable outputs to be expanded while undesirable outputs are contracted simultaneously. A drawback of the DDF approach is that the direction vector to the production boundary is fixed arbitrarily, which may not provide the best efficiency measure. Therefore, this study extends the previous framework of efficiency analysis to introduce a new slacks-based measure of efficiency called the scale directional distance function (SDDF) approach. This new approach determines the optimal direction to the frontier for each unit of analysis and provides dissimilar expansion and contraction factors to achieve a more reasonable eco-efficiency score. This new approach is employed to measure the eco-efficiency of the Malaysian manufacturing sector. In addition, the paper demonstrates the use of the new approach to establish target values for the reduction/expansion of outputs in order for the inefficient DMUs to achieve full eco-efficiency. The results indicate that Melaka, Pulau Pinang, Negeri Sembilan, Sabah, Sarawak and Labuan have attained full eco-efficiency while Terengganu is the least eco-efficient. The overall eco-efficiency of the manufacturing sector in Malaysia is 80.5 % with wide variations across the states.</p

A non-parametric Data Envelopment Analysis approach for improving energy efficiency of grape production

Grape is one of the world's largest fruit crops with approximately 67.5 million tonnes produced each year and energy is an important element in modern grape productions as it heavily depends on fossil and other energy resources. Efficient use of these energies is a necessary step toward reducing environmental hazards, preventing destruction of natural resources and ensuring agricultural sustainability. Hence, identifying excessive use of energy as well as reducing energy resources is the main focus of this paper to optimize energy consumption in grape production.In this study we use a two-stage methodology to find the association of energy efficiency and performance explained by farmers' specific characteristics. In the first stage a non-parametric Data Envelopment Analysis is used to model efficiencies as an explicit function of human labor, machinery, chemicals, FYM (farmyard manure), diesel fuel, electricity and water for irrigation energies. In the second step, farm specific variables such as farmers' age, gender, level of education and agricultural experience are used in a Tobit regression framework to explain how these factors influence efficiency of grape farming.The result of the first stage shows substantial inefficiency between the grape producers in the studied area while the second stage shows that the main difference between efficient and inefficient farmers was in the use of chemicals, diesel fuel and water for irrigation. The use of chemicals such as insecticides, herbicides and fungicides were considerably less than inefficient ones. The results revealed that the more educated farmers are more energy efficient in comparison with their less educated counterparts

Best practices, performance advantage and trade-offs:new insights from frontier analysis

There are still important theoretical and empirical gaps in understanding the role of best practices (BPs), such as quality management, lean and new product development, in generating firm’s performance advantage and overcoming trade-offs across distinct performance dimensions. We examine these issues through the perspective of performance frontiers, integrating in novel ways the resource-based theory with the emergent practice-based view. Hypotheses on relationships between BPs, performance advantage, and trade-offs are developed and tested with stationary and longitudinal (recall) data from a global survey of manufacturing firms. We use data envelopment analysis, which overcomes limitations of mainstream methods based on central tendency. Our findings support the view that BPs may serve as a source of enduring competitive advantage, based on their ability to lead to a heterogeneous range of dominant and difficult-to-imitate competitive positions. The study provides new insights on contemporary debates about the role of BPs in generating performance advantage and how practitioners can sustain internal support and extract benefits from them.</p