Weak Disposability Assumption Research Articles

Efficiency analysis and CO2 emission reduction strategies in the US forest sector: a data envelopment analysis approach

Industrial economic activities produce pollutants and environmentally sustainable production systems in forestry aim to minimize these undesirable outputs while maintaining high production and economic growth. In this contribution, we assume that in addition to plot-specific inputs and outputs, there are some contextual variables that may be exogenously fixed or may be under the control of the decision-makers. In this sense, we first propose a novel and practical approach to calculate environmental efficiency by reducing undesirable products. Then, we utilize an inverse data envelopment analysis (IDEA) model to effectively manage and reduce CO2 emissions. In doing so, the applied models have been utilized to evaluate the efficiencies of 89 forest plots in the USA. Given our estimations in a real application to the forest plots, the study revealed that the average environmental efficiency score is nearly 0.75 (out of 1). However, there is potential for improvement by adjusting the impacts of contextual factors, which could raise the score to approximately 0.8. Furthermore, the analysis indicates a positive correlation between ownership and environmental efficiency, suggesting that increased ownership leads to higher environmental efficiency. Conversely, temperature exhibits a negative correlation with environmental efficiency. Finally, the results obtained from the IDEA indicate that in order to reduce undesirable outputs by a specific level of 5–10%, it is necessary to decrease other inputs and outputs. This is because, under the assumption of weak disposability, reducing the level of undesirable outputs requires a reduction in certain factors that influence production capacity. In other words, achieving the desired reduction in undesirable outputs inevitably involves diminishing certain aspects of the production process. As the major conclusion, the emergence of IDEA as a powerful tool for sensitivity analysis, along with its flexible nature, offers exciting opportunities for research and practical applications in various fields, including forestry activities. It has the potential to enhance overall environmental efficiency and enable better control over GHG emissions levels.

A material balance approach for modelling banks’ production process with non-performing loans

The aim of this to study is to examine how non-performing loans on the balance sheets of Japanese banks affect their performance by adopting a material balance principle. The paper outlines how the material balance conditions can be applied when modelling banks’ production process in the presence of non-performing loans. The paper utilizes the generalized weak G-disposability principle which accounts for the heterogeneity among banks’ input quality. We test how an input-oriented model (non-performing loans are treated as an input), the weak disposability assumption and the adopted material balance approach, affect banks’ performance levels. We apply our test on a sample of Japanese banks over the period 2013 to 2019. Our findings indicate that the input-oriented model and the material balance estimator even if they present similar distributions, they account differently the effect of non-performing loans’ fluctuations over the examined period. In addition, the results under the weak disposability assumption are found to be different compared to the material balance measures and less sensitive to banks’ non-performing loans variation levels. We also provide evidence that the generalized weak G-disposability assumption captures better banks’ performance fluctuations that has been caused by the restructuring of the Japanese banking industry.

Profitability assessment of two-stage feedback processes with undesirable factors

Naturally, managers are interested in analyzing the relative efficiency of the production systems with parametric or non-parametric methods. One of the non-parametric methods utilized in recent three decades is a data envelopment analysis (DEA) that can evaluate the relative efficiency of these structures and determine their strengths and weaknesses. In the real world, most production systems have a network structure. So, network data envelopment analysis (NDEA) is a suitable non-parametric method to evaluate the performance of production processes, which considers the internal processes. In addition to the importance of treating consumed waters and pollutants in environmental protection in today’s world, increasing the profitability of the production unit can be an important motivation to design the proper model to evaluate the performance of these structures in terms of profitability. In this sense, we first introduce a two-stage feedback structure including undesirable factors. Then, by applying the assumption of weak disposability for undesirable factors, a method for analyzing the relative performance of such network structures is given. The focus would be on profitability maximization. Moreover, to illustrate the proposed approach, a real case on the ecological system of 31 regions of China is used.

Directional sustainability assessment of the two-stage processes in the presence of undesirable factors

Network data envelopment analysis (NDEA) is an appropriate technique to evaluate the sustainability of network structures. In the current paper, based on the directional distance function, a model for evaluating the sustainability of two-stage structures in several periods is introduced. The mentioned two-stage structure includes undesirable factors, consequently, the weak disposability assumption is considered to handle them. Sustainability incorporates economic, social and environmental aspects. The proposed model can evaluate sustainability in each period, in addition to the sustainability assessment of the whole system. Simultaneous with the assessing of sustainability, the efficiency of the foregoing structure is examined from three economic, social and environmental aspects in all periods, and based on it, the processes sustainability is estimated from the economic, social and environmental perspectives. To analyze and illustrate the suggested model, a real application on 19 countries is used.

Allocating a fixed cost across decision-making units with undesirable outputs: A bargaining game approach

Allocating a fixed cost among a set of peer decision-making units (DMUs) is one of the most important applications of data envelopment analysis. However, almost all existing studies have addressed the fixed cost allocation (FCA) problem within a traditional framework while ignoring the existence of undesirable outputs. Undesirable outputs are neither scarce in various production activities in real world applications nor trivial in efficiency evaluation and subsequent decision making. Motivated by this observation, this article attempts to explicitly extend the traditional FCA problem to situations in which DMUs are necessarily involved with undesirable outputs. To this end, we first investigate the efficiency evaluation of DMUs considering undesirable outputs based on the joint weak disposability assumption. Then, flexible FCA schemes are considered to revisit the efficiency evaluation process. The results show that feasible allocation schemes exist such that all DMUs can be simultaneously efficient. Furthermore, we define the comprehensive satisfaction degree and develop a satisfaction degree bargaining game approach to determine a unique FCA scheme. Finally, the proposed approach is tested with an empirical study of banking activities based on real conditions.

Decomposing CO2 emission changes in thermal power sector: A modified production-theoretical approach

Carbon emission from the thermal power generation sector is one of the main contributors to global warming. It is critical to objectively evaluate the influence of relevant factors on carbon emissions, which may be beneficial for the implementation of policies and the formulation of development plans. However, the current decomposition approach based on production-theoretical decomposition analysis (PDA) and weak disposability may cause deviation on potential emission reduction. This paper proposes a modified PDA model under the assumption of semi-disposability and decomposes the carbon emission changes of China's thermal power generation sector accordingly. The results show that provinces, which have the highest non-disposal degrees during the study period, are mostly located along the east coast of China. The growth in installed capacity is identified as the largest contributor to the increase in national carbon emissions, while the decrease in capacity utilization rate significantly benefits the carbon emission reduction. A cluster analysis is also conducted to give policy implications for provinces with similar characteristics. Compared with traditional methods under strong and weak disposability assumption, the proposed model shows great advantages in identifying the potential emission reduction and reflecting the real production process, which makes it more suitable for decomposing the changes of carbon emissions and other environmental pollutants.

Dynamic Data Envelopment Analysis Model Involving Undesirable Outputs in the Electricity Power Generation Sector: The Case of Latin America and the Caribbean Countries

Studying the evolution of the efficiency of the electricity generation sector is a relevant task for policy makers, and requires the undesirable outputs derived from the activity to be considered in the evaluation. In this work, we propose a dynamic slack-based Data Envelopment Analysis (DEA) model that incorporates the assumption of weak disposability between the generation of electricity from fossil sources and the CO2 emissions caused by the sector to measure the technical efficiency of 24 Latin American and Caribbean countries in the period 2000–2016. The results show that, of the total number of countries studied, four are efficient overall, and four groupings of countries in relation to the levels of efficiency achieved are also identified. These results are important given that less-efficient countries can, through learning, increase their efficiency in electricity generation or emulate the future strategies proposed by the most efficient countries.

Modeling carbon emission performance under a new joint production technology with energy input

Abstract The nonparametric data envelopment analysis (DEA) methodology has gained much popularity in assessing carbon emission performance within a joint production framework with energy inputs and CO2 emissions. The majority of existing studies, however, neglected the interlinkage between energy inputs and CO2 emissions in their analytical frameworks, which may distort the modeling results. To address this issue, we invoked the weak disposability assumption for both (fossil) energy inputs and CO2 emissions, and developed a new joint production technology that was found in line with the material balance principle and simultaneously allowed for the flexibility of emission abatement options. Built upon the production technology, we developed two indexes to measure carbon emission performance, and proposed a decomposition model to quantify the roles of different options in abating CO2 emissions. We also applied the proposed models to study the carbon emission performance of the world's top 25 CO2 emitters. It was found that carbon emission performance varied across different emitters and different abatement options. Energy efficiency improvement and energy structure adjustment were not of equal importance in pursuing the minimum CO2 emissions.

Performance and competition analysis with fixed-sum measures : A case on OPEC members

The problem of constructing a common equilibrium efficient frontier with fixed-sum inputs or outputs is studied in this paper. To do this, all decision making units are classified into different classes based on their size score and in each class, a common equilibrium efficient frontier is constructed. In the developed procedure, we consider undesirable products and weak disposability assumption is used to handle these products. The advantage of the classification is that DMUs with more similarity in size are in the same class and this makes the input/output tradeoff more rational. To clarify the applicability of the proposed approach, it has been applied to a real case on OPEC crude oil production in 2012.

A data envelopment analysis approach by partial impacts between inputs and desirable-undesirable outputs for sustainable supplier selection problem

PurposeThe objective of this paper is to propose a new data envelopment analysis (DEA) model for assessing sustainability of suppliers with partial impacts between inputs, desirable outputs and undesirable outputs.Design/methodology/approachThis paper examines partial impacts of inputs on desirable and undesirable outputs and applies weak disposability assumption to propose a novel DEA model to determine the sustainability of suppliers.FindingsThis paper shows the type of resource sharing in DEA models and takes into account sustainable development and sustainability assessment concepts for sustainable supplier selection problem and develops a DEA model for selecting the most sustainable suppliers with partial sharing of resources. To select the most sustainable suppliers, this model helps managers to consider aggregate efficiency, overall efficiency and bundle efficiency. The paper introduces the supplier which is efficient at all levels as the most sustainable supplier.Originality/valueFor the first time, this paper suggests a new DEA model by partial impact between inputs and good outputs/bad outputs for selecting sustainable supplier and deals with the situations in which each supplier has several subunits. The new model calculates aggregate efficiency, overall efficiency and subunit efficiency of supplier. paper introduces the supplier which is efficient in all levels including aggregate efficiency, overall efficiency and subunit efficiency as the best supplier.

Modelling undesirable products in non-parametric performance analysis

Purpose The purpose of this paper is introducing an alternative model to measure the relative efficiency of observations with undesirable products. Describing the reference set and benchmarking. Design/methodology/approach In this paper, an alternative definition of weak disposability assumption is introduced to handle undesirable outputs. Actually, two types of undesirable outputs are addressed and a substitute definition of weak disposability is presented. Findings Using this assumption a linear production technology set along with a performance analysis model is constructed to assess the relative efficiency of the decision-making units. To illustrate the radial application of the proposed approach, a real case on transportation system of USA during 1992-2009 is given. Originality/value To date, data envelopment analysis studies have investigated undesirable outputs by the assumption of weak disposability, defined as the proportional contraction of good and bad products, which leads to the null-joint assumption between good and bad outputs. Therefore, the only way to produce no undesirable outputs is producing zero desirable outputs. So the production process should be stopped while it is not economically cost-effective. However, in some processes there are some undesirable outputs, which are decreased with non-same percentages. So these undesirable outputs can be stopped while the good outputs have a strictly positive value. In this situation, the good outputs are not null-joint with this type of bad outputs. In the current paper, a new definition of the weak disposability of outputs was represented while two groups of undesirable outputs were considered. Hence, desirable outputs and the first kind of undesirable outputs were decreased proportionally. However, the reduction value was different for the second kind of undesirable outputs. Hence, the null-joint assumption is removed from the production technology. Then, a new technology was proposed based on five postulates as inclusion of observations, free disposability of desirable outputs and inputs, new weak disposability, convexity and minimum extrapolation.

Assessment of mixed network processes with shared inputs and undesirable factors

In the real world, there are processes whose structures are like a parallel-series mixed network. Network data envelopment analysis (NDEA) is one of the appropriate methods for assessing the performance of processes with these structures. In the paper, mixed processes with two parallel and series components are considered, in which the first component or parallel section consists of the shared in-puts, and the second component or series section consists of undesirable factors. By considering the weak disposability assumption for undesirable factors, a DEA approach as based on network slack-based measure (NSBM) is introduced to evaluate the performance of processes with mixed structures. The proposed model is illustrated with a real case study. Then, the model is developed to discriminate efficient units.

Sustainability assessment in the presence of undesirable factors over time: A case on gas companies

AbstractSustainability is an essential ingredient for long‐term success of firms, and its assessment has a significant impact on decision making and sustainability management. In the current paper, a data envelopment analysis‐based approach is proposed to assess the sustainability of systems over several periods when undesirable outputs are present in the process. Indeed, sustainability is assessed in each period and, as a whole, simultaneously. Furthermore, social, economic, and environmental efficiency scores of multiperiod systems are evaluated in each period. The weak disposability assumption is used to handle undesirable outputs. Also, the current study concerns socio‐economic, socioenvironmental, and eco‐environmental factors in addition to economic, social, and environmental aspects. A real‐world application on Iranian gas companies is used to illustrate the applicability of the proposed approach.

Supply chains performance with undesirable factors and reverse flows: A DEA-based approach

Supply chain performance evaluation is an essential aspect for decision-makers in order to make better and profitable decisions and survive in the competitive environment. Furthermore, considering desirable and undesirable outputs that are usually produced in supply chain processes simultaneously is significant and effective for obtaining rational results. This study proposes an approach based on data envelopment analysis (DEA) to evaluate the relative efficiency of supply chains with reverse flows in the presence of undesirable factors. The weak disposability assumption is used to handle undesirable factors. To illustrate, a radial DEA model is introduced to determine the efficiency of reverse supply chains while undesirable outputs are present as external factors and reverse flows. The proposed approach herein is illustrated using a data-set.

Efficiency evaluation in the presence of undesirable outputs: the most favorable shadow price approach

Undesirable outputs are generally by-products of producing desirable ones, and they can thus be reduced only with an accompanying reduction in the latter. To capture this notion, the shadow price of the undesirable output must be negative, as opposed to positive for the desirable output. Based on this condition, this paper proposes a data envelopment analysis model that allows the production units being evaluated to determine the shadow prices for both the desirable and undesirable outputs by themselves so that the measured efficiency score will achieve the highest possible level. The proposed model satisfies the assumption of weak disposability of outputs. It is also shown that it falls into one category of the directional distance function model that has been widely applied in modeling undesirable outputs. However, different from the conventional directional distance measures, the proposed model is able to provide efficiency measures in the range of zero and one for easy comparison among inefficient production units.

Relevance of Disposability Assumptions for Efficiency Measurement

A recent article of Dakpo, Jeanneaux and Latruffe critically reviews the developments, limits and future prospects of integrating environmental aspects into productive efficiency evaluation with Data Envelopment Analysis (DEA). In particular, it is concluded that multiple frontier technologies are more promising than the widely-used weak disposability assumption. This note comments on some of these conclusions thereby focusing the relevance of disposability assumptions. The suitability of generic disposability assumptions for pollution technologies is discussed. Furthermore, it is questioned whether the usual free disposability assumption in case of no bads is necessary, at all. It is argued that adequate explicit disposability assumptions should be well justified for the individual technology of the considered transformation process – if they are necessary at all and not already implicitly contained in the envelopment of the DMUs.

Potential carbon emission abatement cost recovery from carbon emission trading in China

Purpose This study aims to provide an estimation of carbon dioxide (CO2) emission abatement costs in China’s industry sector during the period of 2006-2010, and additionally provide an ex-post estimation of CO2 abatement cost savings that would be realized if carbon emission permits trading among different industry sectors of 30 provinces in China during the same period were allowed, to answer the question that whether the industrial carbon emission abatement cost can (partially) be recovered from carbon emission trading in China. Design/methodology/approach The joint production framework associated with the environmental technology is utilized for formulating the models for estimating abatement costs and simulating emission permits trading scheme. Several data envelopment analysis-based models that could deal with both the desirable and undesirable outputs within the above framework are utilized for abatement cost saving estimation. The weak disposability assumption and variable returns to scale assumption are applied in the modelling. Findings In China’s industry sector, during 2006-2010, the estimated CO2 emission abatement cost was 1,842 billion yuan, which accounts for 2.45 per cent of China’s total industrial output value; the emission abatement cost saving from emission permits trading would be 315 billion yuan, which accounts for 17.12 per cent of the emission opportunity abatement cost; and additional 1,065.95 million tonnes of CO2 emission reductions would be realized from emission permits trading, and this accounts for 4.75 per cent of the total industrial CO2 emissions. Research limitations/implications The estimation is implemented at the regional level, i.e. the emission permits trading subjects are the whole industry sectors in different Chinese provinces, because of the data limitation in this study. Further estimation could be implemented at the enterprise level to provide a deeper insight into the abatement cost recovery from emission permits trading. Practical implications The estimation models and calculation process introduced in this study could be applied for evaluating the efficiency and effectiveness of pollutant emission permits trading schemes from the perspective that whether these market-based abatement policy instruments help to realize the potential abatement cost savings. Originality/value To the best of the authors’ knowledge, no study has provided the estimation of CO2 emission abatement cost and the estimation of CO2 abatement cost saving effect from emission permits trading for China’s industry sector. This study provides the first attempt to fill this research gap.

China’s regional energy and carbon dioxide emissions efficiency evaluation with the presence of recovery energy: an interval slacks-based measure approach

Recovery energy has been one of important components of energy consumption structure in China. Recovery energy is a type of secondary energy, which is generated from various sources. Since the estimation of recovery energy from some sources such as coke oven gas and other coal gas contains some uncertainties, recovery energy can be represented as an interval variable. The extant studies in the literature ignore recovery energy in the evaluation of energy efficiency or carbon dioxide ( $$\text {CO}_{2}$$ ) emissions efficiency. As a part of energy supply in China, recovery energy may influence regional primary energy consumption and $$\text {CO}_{2}$$ emissions significantly. In this context, this paper proposes an interval slacks-based measure approach to evaluate energy efficiency and $$\text {CO}_{2}$$ emissions efficiency in the presence of recovery energy in China. In the described approach, the indicator of $$\text {CO}_{2}$$ emissions is incorporated based on the weak disposability assumption, and recovery energy is modeled as a dual factor. The optimal exact data on recovery energy of each region can be obtained. Based on the proposed approach, the measures of energy saving potential and $$\text {CO}_{2}$$ emissions reduction potential are derived. Findings resulting from the model application show that there are great disparities in regional efficiencies, and the inefficiency of Chinese regions is largely driven by those inefficient regions in the central and western areas. Notably, the development of recovery energy can help to improve regional energy efficiency and $$\text {CO}_{2}$$ emissions efficiency in China.

Water use efficiency and related pollutants' abatement costs of regional industrial systems in China: a slacks-based measure approach

Water saving and wastewater cleaning are two important ways to alleviate water shortage crisis in China. This paper aims to examine water use efficiency and abatement costs of two main pollutants in wastewater, i.e., chemical oxygen demand (COD) and ammonia nitrogen (NH4–N), of regional industrial systems in China. For this purpose, a slacks-based measure model based on the assumption of undesirable output weak disposability is developed. Based on the proposed model, the measures of water saving potential, COD reduction potential, NH4–N reduction potential, COD abatement cost and NH4–N abatement cost are presented. We apply the proposed approaches to investigate water use efficiency, water saving potential, the two pollutants' reduction potentials and their related abatement costs during 2009–2010. Results of the application show that there are great potentials to reduce water consumption and pollutants' discharges in China's regional industrial production process, and there exist evident geographic disparities in water saving potentials, pollutants' reduction potentials and their abatement costs. It is found that water use efficiency increases from 2009 to 2010, while pollutants abatement costs decrease. Some other findings and implications for efficiency improvement of China's regional industrial systems in water management and pollutants' abatement are achieved.

Evaluating economic and environmental efficiency of global airlines: A SBM-DEA approach

This study examined the economic and environmental efficiency of 27 global airlines in 2010. An extended environmental slacks-based measure data envelopment analysis model with the weak disposability assumption was developed to assess the efficiency of the airlines. Asia-based airlines are generally more efficient, followed by European and American airlines. The poor fuel consumption is a major cause of inefficient airlines both in economic and environmental aspects.