As environment constraints on economic growth are strengthening, Carbon Emissions Abatement (CEA) allocation becomes a significant issue that draws academia׳s attention. In the literature, the Data Envelopment Analysis (DEA) technique has been applied to obtain CEA allocation with centralized models. Nevertheless, a centralized allocation plan suffers from an implementation difficulty in persuading decision-making units (DMUs) into an agreement. In this paper, we propose a new two-step method to mitigate this side effect. In the first step, we provide improved DEA-based centralized allocation models under the assumptions of constant returns-to-scale (CRS) and variable returns-to-scale (VRS) respectively and in the second step, two compensation schemes are developed for centralized allocation plans. An empirical application to the countries in Organization for Economic Co-operation and Development (OECD) is presented to elaborate the main idea.

Carbon Emissions Abatement (CEA) allocation and compensation schemes based on DEA

China's regional natural resource allocation and utilization: a DEA-based approach in a big data environment

In the big data context, decision makers usually face the problem of evaluating environmental efficiencies of a massive number of decision making units (DMUs) using the data envelopment analysis (DEA) method. However, standard implementations of the traditional DEA calculation process will consume much time when the data set is very large. To eliminate this limitation of DEA applied to big data, firstly, the slacks-based measure (SBM) model is extended considering undesirable outputs and the variable returns to scale (VRS) assumption for environmental efficiency evaluation of the DMUs. Then, an approach comprised of two algorithms is proposed for environmental efficiency evaluation when the number of DMUs is massive. The set of DMUs is partitioned into subsets, a technique which facilitates the application of a parallel computing mechanism. Algorithm 1 can be used for identifying the environment efficient DMUs in any DMU set. Further, Algorithm 2 (a parallel computing algorithm) shows how to use the proposed model and Algorithm 1 in parallel to find the environmental efficiencies of all DMUs. A simulation shows that the parallel computing design helps to significantly reduce calculation time when completing environmental efficiency evaluation tasks with large data sets, compared with using the traditional calculation processes. Finally, the proposed approach is applied to do environmental efficiency analysis of transportation systems.

An SBM-DEA model with parallel computing design for environmental efficiency evaluation in the big data context: a transportation system application

Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach

This paper proposes new fixed cost allocation approaches for allocating a fixed cost among decision-making units (DMUs) with two-stage structures under the framework of data envelopment analysis (DEA). Firstly, we give the set of possible fixed cost allocations, prove that all DMUs can be overall efficient when evaluated by a common set of weights after fixed cost allocation. Secondly, from a centralized point of view, we consider the competition between the DMUs’ two stages in fixed cost allocation and regard these two kinds of stages as two unions. Then, we incorporate leader-follower models to propose a fixed cost allocation approach to handle the situation in which the two unions make decisions sequentially. Based on the result of these models, a concept of satisfaction degree of each union on a fixed cost allocation is presented. A satisfaction degree bargaining game model is then proposed to obtain a fixed cost allocation which is a bargaining equilibrium of the two unions. We show that the proposed approaches always obtain a fixed cost allocation that is proportionally invariant. Additionally, the satisfaction degree bargaining game approach automatically guarantees the uniqueness of the fixed cost allocation. These properties make the fixed cost allocation generated by our approaches more stable and more acceptable. Finally, a numerical example and an application of fixed cost allocation among bank branches are given to illustrate the proposed approach and to compare it with a benchmark approach among the current studies, respectively.

DEA-based fixed cost allocation in two-stage systems: Leader-follower and satisfaction degree bargaining game approaches

The existing centralized resource allocation models often assume that all of the DMUs are efficient after resource allocation. For the DMU with a very low efficiency score, it means the dramatic reduction of the resources, which can cause the organizational resistance. In addition, in reality, it is particularly difficult for the DMUs to achieve their target efficiencies in a single step, especially when they are far from the efficient frontier. Thus, gradual progress towards benchmarking targets is gaining importance. In this paper, we present a new approach for resource allocation based on efficiency analysis under a centralized decision-making environment. Through our approach, the central decision-maker can obtain a sequence of intermediate benchmark targets based on efficiency analysis, which provide a level-wise improvement path to direct the DMUs to reach their ultimate targets on the efficient frontier in an implementable and realistic manner. Numerical examples are presented to illustrate the application procedure of the proposed approach.

Centralized resource allocation based on efficiency analysis for step-by-step improvement paths ☆

Energy performance contracting is a turnkey service for an enterprise to achieve the goal of energy-saving or emission abatement. This study investigates the value of energy performance contracting in a two-echelon supply chain consisting of one supplier and two financially asymmetric manufacturers under carbon tax regulation for climate change mitigation. The supplier provides a trade credit for a financially weak manufacturer who engages in Cournot competition with a financially strong manufacturer. Furthermore, the supplier can act as an energy service company to offer energy performance contracting for the two manufacturers to achieve carbon tax savings. The impact of sharing ratio of energy performance contracting and coefficient of variable cost are analyzed to explore whether and which manufacturer should be chosen by the supplier to implement energy performance contracting. The results suggest that when the coefficient of variable cost is within a high range, the supplier will not provide energy performance contracting for any manufacturer. However, when the coefficient of variable cost and sharing ratio are not very high, the supplier prefers to provide energy performance contracting for the financially weak manufacturer. With the increasing of sharing ratio, the supplier changes the decision to select the financially strong one. Moreover, the model is extended to consider the impact of demand uncertainty and coefficient of investment cost. Furthermore, the result of numerical studies indicates that there exists a Pareto zone for the three supply chain members to achieve a multi-win situation, if the supplier provides the energy performance contracting for both the manufacturers.

Energy performance contracting in a supply chain with financially asymmetric manufacturers under carbon tax regulation for climate change mitigation

Conventional DEA models treat the entire production system as a black box and ignore its internal structures. To address this issue, many studies have examined the DEA efficiencies of two-stage systems in which all outputs of the first stage are the only inputs to the second stage. Based on game theory, the non-cooperative model and centralized model were developed for such a two-stage network structure. However, for the centralized model with multiple optimal solutions and the non-cooperative model, an assumption is required as to whether the first or second stage should be assigned the absolute priority for optimization. In many cases, certain circumstances might exist in which one stage does not completely dominate the other stage. In this paper, we develop a methodology for assessing the overall and stage efficiencies by considering the different and DMU-specific degree of priority given to the stages. Particularly, the non-cooperative model and the centralized model can be deemed as special cases. Moreover, we compare the proposed approaches with the existing approaches, which indicates that our approaches can greatly reduce the computational burden. Two empirical examples are used to demonstrate the proposed approach.

Lei Fang

Papers

Centralized resource allocation based on efficiency analysis for step-by-step improvement paths ☆

Energy performance contracting in a supply chain with financially asymmetric manufacturers under carbon tax regulation for climate change mitigation

Stage efficiency evaluation in a two-stage network data envelopment analysis model with weight priority