1,558 research outputs found

    Carbon emission abatement quota allocation in Chinese manufacturing industries:An integrated cooperative game data envelopment analysis approach

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    The Chinese government announced to cut its carbon emissions intensity by 60%–65% from its 2005 level. To realize the national abatement commitment, a rational allocation into its subunits (i.e. industries, provinces) is eagerly needed. Centralized allocation models can maximize the overall interests, but might cause implementation difficulty and fierce resistance from individual subunits. Based on this observation, this article will address the carbon emission abatement quota allocation problem from decentralized perspective, taking the competitive and cooperative relationships simultaneously into account. To this end, this article develops an integrated cooperative game data envelopment analysis (DEA) approach. We first investigate the relative efficiency evaluation by taking flexible carbon emission abatement allocation plans into account, and then define a super-additive characteristic function for developing a cooperative game among units. To calculate the nucleolus-based allocation plan, a practical computation procedure is developed based on the constraint generation mechanism. Further, we present a two-layer way to allocate the CO2 abatement quota into different sub-industries and further different provinces in Chinese manufacturing industries. The empirical results show that five sub-industries (Processing of petroleum, coking and processing of nuclear fuel; Smelting and pressing of ferrous metals; Manufacture of non-metallic mineral products; Manufacture of raw chemical materials and chemical product; Smelting and pressing of non-ferrous metals) and two provinces (Guangdong and Shandong) will be allocated more than 10% of the total national carbon emission abatement quota

    A Review of DEA-based Resource and Cost Allocation models: Implications for services

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    Data envelopment analysis (DEA), by its design, was not intended for resource allocation but for measuring relative efficiency of decision-making units. Despite this, many researchers have successfully applied this modelling technique to a variety of resource and cost allocation decisions in order to improve operational efficiencies. This paper is a comprehensive review and classification of such articles. The papers were classified by industry and by DEA model-orientation. The findings of this paper show that existing models predominately apply DEA to mass service industries (e.g., banking), thus, revealing the opportunity for researchers to further develop DEA-based resource allocation modelling toward improving the operational efficiencies of other service industries (e.g., professional services). To guide researchers to this end, we offer a discussion of the use of DEA modelling when the service provider and the customer are both resources needing to be allocated, in other words, using DEA to model professional or co-created services

    Integration of Simulation and DEA to Determine the Most Efficient Patient Appointment Scheduling Model for a Specific Clinic Setting

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    This study develops a method to determine the most efficient scheduling model for a specific clinic setting. The appointment scheduling system assigns clinics' timeslots to incoming requests. There are three major scheduling models: centralized scheduling model (CSM), decentralized scheduling model (DSM) and hybrid scheduling model (HSM). In order to schedule multiple appointments, CSM involves one scheduler, DSM involves all the schedulers of individual clinics and HSM combines CSM and DSM. Clinic settings are different in terms of important factors such as randomness of appointment arrival and proportion of multiple appointments. Scheduling systems operate inefficiently if there is not an appropriate match between scheduling models and clinic settings to provide balance between indicators of efficiency. A procedure is developed to determine the most efficient scheduling model by the integrated contribution of simulation and Data Envelopment Analysis (DEA). A case study serves as a guide to use and as proof for the validity of the developed procedure

    Multi-Dimensional Assessment of Transit System Efficiency and Incentive-based Subsidy Allocation

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    Over the past several decades, contending with traffic congestion and air pollution has emerged as one of the imperative issues across the world. Development of a transit-oriented urban transport system has been realized by an increasing number of countries and administrations as one of the most effective strategies for mitigating congestion and pollution problems. Despite the rapid development of public transportation system, doubts regarding the efficiency of the system and financing sustainability have arisen. Significant amount of public resources have been invested into public transport; however complaints about low service quality and unreliable transit system performance have increasingly arisen from all walks of life. Evaluating transit operational efficiency from various levels and designing incentive-based mechanisms to allocate limited subsidies/resources have become one of the most imperative challenges faced by responsible authorities to sustain the public transport system development and improve its performance and levels of service. After a comprehensive review of existing literature, this dissertation aims to develop a multi-dimensional framework composed of a series of robust multi-criteria evaluation models to assess the operational and financial performance of transit systems at various levels of application (i.e. region/city level, operator level, and route level). It further contributes to bridging the gap between transit efficiency evaluation and the subsequent subsidy allocation by developing a set of incentive-based resource allocation models taking various levels of operational and financial efficiencies into consideration. Case studies using real-world transit data will be performed to validate the performance and applicability of the proposed models

    Centralised resource allocation using Lexicographic Goal Programming. Application to the Spanish public university system

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    Identificador de proyecto: FEDER-UPO UPO-1380624This paper deals with Data Envelopment Analysis (DEA) in centralised settings in which the operating units belong to the same organisation. In such a scenario, a global system-wide perspective may be adopted as regards resource allocation and target setting. In this paper, a new Lexicographic Goal Programming (lexGP) approach is proposed using three priority levels: the aggregated input consumption and output production goals; the input and output goals of the individual operating units; and the technical efficiency of the computed targets. It is assumed that the goals for the overall organisation are established by the Central Decision-Maker (CDM) and that they are consistent with those of the individual operating units. The proposed approach has been applied to the Spanish public university system, comprising 47 institutions. Given the CDM preferences in terms of input and output aggregate goals and relative importance weights, specific technical efficient targets have been computed for each university. The results show that the proposed approach is more suitable than the non-centralised DEA approach and produces targets that are more effective than other centralised resource allocation approaches in the sense that they are much closer to both the aggregate goals of the CDM and the specific goals of each university.Universidad de Sevill

    Ein DEA-basierter Ansatz zur Messung der Performance bei zentralisierten Managementstrukturen

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    Traditional performance measurement approaches are usually characterized by a number of different limitations. Among other things, these approaches require the subjective determination of weights to aggregate a set of indicators to an overall performance score. Furthermore, traditional approaches are usually not able to incorporate additional improvement potentials that can be received from a centralized management. A performance measurement framework which can overcome these limitations is called data envelopment analysis (DEA). Against this background, this thesis provides a thorough overview of how different degrees of centralization are modeled in the current DEA literature. The systematic literature review identified 135 different approaches that assume a centralized or partially centralized management structure. A concluding discussion of the respective DEA approaches showed two fundamental research gaps. In response to this, this thesis has two fundamental objectives: The first objective is to propose a DEA-based performance measurement approach for measuring performance changes over time. The second objective is to develop another DEA-based approach for comparing the performance of management groups. In contrast to so far developed DEA-models, the here proposed approaches explicitly incorporate the respective management structure. Both DEA approaches thus developed are based on the combination of the metafrontier concept and the Malmquist index. The first approach evaluates productivity changes of operating entities over time and, hence, may indicate potential sources for performance changes. Thereby, the proposed approach preserves the individual characteristics of each local group technology. The second DEA approach proposed here uses the Malmquist index for comparing the performance of management groups. This index accounts for the existence of a central decision maker who can, e.g., undertake resource reallocations to improve the overall performance of its managed group. The applicability and usefulness of both proposed approaches is empirically shown with real-world data from KONE Corporation.Traditionelle Performance Measurement Ansätze gehen mit einer Reihe von Herausforderungen einher. So erfordert die Aggregation unterschiedlicher Kennzahlen zu einem einzelnen Performancemaß die Verwendung von subjektiven Gewichtungen. Darüber hinaus lassen sich in traditionellen Ansätzen nur schwer etwaige Verbesserungspotentiale modellieren, die aus zentralisierten Managementstrukturen resultieren. Eine betriebswirtschaftliche Methode, welche die genannten Limitationen nicht aufweist, ist die Data Envelopment Analysis (DEA). Aufgrund dieser Vorteile wird in dieser Arbeit zunächst ein umfassender Literaturüberblick erarbeitet, wie unterschiedliche Managementstrukturen in einer DEA modelliert werden können. Mithilfe der Literaturrecherche wurden insgesamt 135 unterschiedliche Ansätze ermittelt, die entweder ein vollkommen zentralisiertes oder teilweise zentralisiertes Managementmodell unterstellen. Eine abschließende Diskussion der verschiedenen DEA-Ansätze zeigte allerdings eine Forschungslücke, woraus die beiden folgenden Forschungsziele für diese Arbeit abgeleitet wurden: Einerseits soll ein DEA-basierter Ansatz erarbeitet werden, der zur Messung von Effizienzveränderungen einzelner Produktiveinheiten über die Zeit geeignet ist. Andererseits soll eine DEA-basierte Methode entwickelt werden, welche bei Performancevergleichen zwischen Managementgruppen anwendbar ist. Im Gegensatz zu den bisher in der Literatur diskutierten Ansätzen sollten die entwickelten Methoden dabei die jeweils vorliegende Managementstruktur berücksichtigen. Die entwickelten DEA-Ansätze basieren auf der Kombination des Metafrontier-Konzepts mit dem Malmquist-Index. Der erste Ansatz erlaubt es, Performanceveränderungen von einzelnen Produktiveinheiten über mehrere Zeitperioden zu messen. Im Gegensatz zu konventionellen Metafrontier-basierten Malmquist-Indizes berücksichtigt der vorgeschlagene Ansatz die individuellen Eigenschaften der lokalen Produktionstechnologien. Der zweite vorgeschlagene DEA-Ansatz nutzt den Malmquist-Index für den Vergleich der Performance von Managementgruppen. Der Index berücksichtigt dabei explizit, dass eine zentrale Entscheidungsinstanz existiert, welche Ressourcenumverteilungen durchführen kann. Beide Ansätze werden anhand eines Datensatzes des Unternehmens KONE illustriert

    Efficiency decomposition for multi-level multi-components production technologies

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    This paper addresses the efficiency measurement of firms composed by multiple components, and assessed at different decision levels. In particular it develops models for three levels of decision/production: the subunit (production division/process), the DMU (firm) and the industry (system). For each level, inefficiency is measured using a directional distance function and the developed measures are contrasted with existing radial models. The paper also investigates how the efficiency scores computed at different levels are related to each other by proposing a decomposition into exhaustive and mutually exclusive components. The proposed method is illustrated using data on Portuguese hospitals. Since most of the topics addressed in this paper are related to more general network structures, avenues for future research are proposed and discussed.info:eu-repo/semantics/publishedVersio
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