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"data envelopment analysis"
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Applications of management science
'Applications of Management Science' focuses on the application of management science to multiple criteria decision making, data envelopment analysis, and managerial applications.
Book
A novel approach to assess sustainability of supply chains
PurposeThis paper discusses how learning-by-doing (LBD) criterion can be used to evaluate the sustainability of supply chains. This paper assesses the impacts of teamwork on the LBD criterion. Besides, the effect of the internship of new labors on the LBD criterion is discussed.Design/methodology/approachThe repeat of a task leads to a gradual improvement in the efficiency of production systems. LBD occurs by accumulating knowledge and skills in multiple periods. LBD can be used to study changes in the efficiency. Efficiency can be improved by accumulating knowledge and skills. In this paper, the LBD criterion is projected on learning curve (LC) models. Furthermore, the LC models are fitted to the supply chains. Each supply chain may have a unique LC model. A minimum difference is set between the current performance of decision making unit (DMU) and the estimated performance of DMU based on DMU's LC. Hence, a point in which the LBD occurs is determined.FindingsThis paper develops an inverse network dynamic data envelopment analysis (DEA) model to assess the sustainability of supply chains DMUs. Findings imply that the LBD criterion plays an important role in assessing the sustainability of supply chains. Furthermore, managers should increase the internships and teamwork to get more benefit from the LBD criterion.Originality/valueFor the first time, this paper uses the LBD criterion to assess the sustainability of supply chains given the LC equations.
Journal Article
Ranking sustainable suppliers by context-dependent data envelopment analysis
Sustainable supplier selection is one of the most critical activities for establishing an effective sustainable supply chain and is typically a multi-criteria decision-making problem. One of the important ways for evaluating sustainable suppliers is to use data envelopment analysis (DEA) models. There are many DEA models for ranking decision making units (DMUs) that are applicable for selecting the best sustainable suppliers. This paper presents a new DEA model for ranking DMUs (suppliers) based on a modification of context-dependent DEA models. Using the concept of attractiveness and progress for each supplier, this paper suggests a new DEA ranking approach. The proposed method is able to rank all efficient and inefficient suppliers. A case study demonstrates the efficiency of the proposed method. Our proposed method is used to determine the most sustainable suppliers of Sazeh Gostare Saipa Company. There are fourteen active suppliers for Sazeh Gostare Saipa Co., and results show that Hydraulic Structures Engineering Services is the most sustainable supplier.
Journal Article
The COVID-19 pandemic and the performance of healthcare supply chains
Recent pandemic outbreaks, including the COVID-19 and SARS, have revealed that supply chains (SCs) are unable to respond to such disasters. To mitigate the destructive impacts and improve the performance of SCs, Operations Research (OR) techniques have been applied to address the issues over the last two decades. The objective of this paper is to develop a network data envelopment analysis (NDEA) model to measure the resilience and sustainability of healthcare SCs in response to the COVID-19 pandemic outbreak. In the proposed NDEA model, for the first time, outputs’ weak disposability, chance-constrained programming (CCP), the convexity assumption, and the semi-oriented radial approach are aggregated. Moreover, a modified directional distance function (DDF) measure is developed to measure the overall and divisional efficiency scores. Furthermore, the proposed model can deal with different types of data such as integer-valued data, negative data, stochastic data, ratio data, and undesirable outputs. Also, several useful and interesting properties of the novel efficiency measure are presented. Finally, we measure the performance of 28 healthcare SCs to demonstrate the applicability and capability of our proposed approach.
Journal Article
Data Envelopment Analysis
Using the neo-classical theory of production economics as the analytical framework, this book, first published in 2004, provides a unified and easily comprehensible, yet fairly rigorous, exposition of the core literature on data envelopment analysis (DEA) for readers based in different disciplines. The various DEA models are developed as nonparametric alternatives to the econometric models. Apart from the standard fare consisting of the basic input- and output-oriented DEA models formulated by Charnes, Cooper, and Rhodes, and Banker, Charnes, and Cooper, the book covers developments such as the directional distance function, free disposal hull (FDH) analysis, non-radial measures of efficiency, multiplier bounds, mergers and break-up of firms, and measurement of productivity change through the Malmquist total factor productivity index. The chapter on efficiency measurement using market prices provides the critical link between DEA and the neo-classical theory of a competitive firm. The book also covers several forms of stochastic DEA in detail.
eBook
A network data envelopment analysis based paradigm to benchmark fiscal performance – an analysis of fiscal outlay efficiency among Indian states
PurposeThe fiscal outlay efficiency matters when the performance-based allocation of funds is made to state governments by the central government in a federal structure of an economy like India. Also the efficiency cannon of public expenditure is a key aspect in the field of public economics. Thus, a study to evaluate the efficiency in fiscal outlay of Indian states has been conducted.Design/methodology/approachThe paper offers a three divisions–based paradigm under Network Data Envelopment Analysis framework to compare the performance of fiscal entities (say Indian state governments) in converting available fiscal resources into desired short-run and long-run growth and development objectives. The network efficiency score has been taken as a measure of the quality of fiscal outlay management that is trifurcated into divisional efficiencies representing budgeting process, fiscal outlay efficiency process and fiscal outlay effectiveness process.FindingsIt has been noticed that the states are under performing in achieving short-run growth targets and so the efficiency process division has been identified a major source of fiscal under performance. Suboptimum allocation of fiscal expenditure under various heads within the fiscal resources, as explained under budgeting process, is another major cause of fiscal under performance.Practical implicationsThe study purposes a three divisions–based paradigm that takes into account efficiency of a state in (1) planning budget, (2) achieving short-run growth targets and (3) achieving long-run development targets. These three stages are named as budgeting process efficiency, fiscal outlay efficiency and fiscal outlay effectiveness, respectively. Therefore, a new paradigm called BEE paradigm is proposed to evaluate performance of fiscal entities in terms of fiscal outlay efficiency.Originality/valueIn existing literature on measuring efficiency of public expenditure, the public sector outputs have been made as function of fiscal expenditure as input treating the said outlay as an exogenous variable. In present context, the fiscal expenditure has been treated endogenous to the budgeting process. A high inefficiency on account of budgeting process supports this treatment too.
Journal Article
Finding closest target for bank branches in the presence of weight restrictions using data envelopment analysis
Data envelopment analysis technique, not only evaluates Decision making units (DMUs), but also introduces a benchmark for inefficient DMUs. By having the data related to the benchmark and using it appropriately, the DMU under the assessment determines how to eliminate its inefficiency and become efficient. The closer the evaluated DMU is to the presented target, the faster and easier it reaches the efficiency frontier. Furthermore, target setting in the presence of weight restrictions is an important issue. In this paper, a model for finding the closest target, in the presence of weight restrictions is presented. Thus, taking into account trade-offs, as well as weight restrictions, the closest target for each DMU is introduced. The proposed model is also compared with the previous models. Finally, administrating the proposed model for evaluating one of Iranian Banks, the least changes to inefficient branches is represented.
Journal Article
Impacts on efficiency of merging the Swedish district courts
Judicial courts form a stringent example of public services using partially sticky inputs and outputs with heterogeneous quality. Notwithstanding, governments internationally are striving to improve the efficiency of and diminish the budget spent on court systems. Frontier methods such as data envelopment analysis are sometimes used in investigations of structural changes in the form of mergers. This essay reviews the methods used to evaluate the ex post efficiency of horizontal mergers. Identification of impacts is difficult. Therefore, three analytical frameworks are applied: (1) a technical efficiency comparison over time, (2) a metafrontier approach among mergers and non-mergers, and (3) a conditional difference-in-differences approach where non-merged twins of the actual mergers are identified by matching. In addition, both time heterogeneity and sources of efficiency change are examined ex post. The method is applied to evaluate the impact on efficiency of merging the Swedish district courts from 95 to 48 between 2000 and 2009. Whereas the stated ambition for the mergers was to improve efficiency, no structured ex post analysis has been done. Swedish courts are shown to improve efficiency from merging. In addition to the particular application, this work may inform a more general discussion on public service efficiency measurement under structural changes, and their limits and potential.
Journal Article
Exploring the Performance of International Airports in the Pre- and Post-COVID-19 Era: Evidence from Incheon International Airport
Considering the socio-economic importance of Incheon International Airport, this study explored the changes in its aeronautical and non-aeronautical efficiency between 2001 and 2021. The study was conducted to measure and observe the changes in efficiency during the pre- and post-pandemic era of COVID-19. We employed a two-stage analytical approach to obtain the results using a set of desirable and undesirable variables. For the first stage, we employed a novel network data envelopment analysis–window analysis model to find the efficiency measures; for the second stage, we applied the Tobit regression analysis to observe the impact of some control variables on efficiency levels. The empirical results from the efficiency analysis stage revealed that, although the pandemic negatively affected the efficiency of this airport, the gain from appropriate strategies mitigated the excessive efficiency decline. Moreover, aeronautical activities showed better efficiency than non-aeronautical activities during the study period. In addition, further investigation of the second-stage analysis implied that an outbreak of pandemic diseases such as COVID-19 would dramatically impact international hubs such as Incheon International Airport; however, focusing on the import and export activities, in addition to increasing the connectivity with other airports, would improve the efficiency.
Journal Article
Sustainability assessment of supply chains by inverse network dynamic data envelopment analysis
This paper focuses on assessing sustainability of supply chains. This paper, at first, proposes network dynamic Range Adjusted Measure (RAM) model. Then, an inverse version of network dynamic RAM model is proposed. The proposed inverse network dynamic Data Envelopment Analysis (DEA) model changes both inputs and outputs of Decision-Making Units (DMUs) so that existing efficiency scores of DMUs remain unchanged. We change inputs and outputs without any modification in efficiency score of DMU under evaluation, while inputs and outputs may have a large range. A case study shows the efficacy of the proposed model.
Journal Article