Evaluating sustainability of supply chains by two-stage range directional measure in the presence of negative data

Assessing sustainability of supply chains is a critical and increasingly complex problem. In recent years sustainability has received more attention in supply chain management (SCM) literature with triple bottom lines including social, environmental, and economic factors. Conventional data envelopment analysis (DEA) models consider decision making units (DMUs) as black boxes that consume a set of inputs to produce a set of outputs and do not take into consideration internal interactions of DMUs. Two-stage DEA models deal with such DMUs. However, existing two-stage DEA models are applicable only in technologies characterized by positive inputs/outputs. This paper aims to build and present a new two-stage DEA model considering negative input-intermediate-output data. Some numerical examples along with some theorems and properties are given to show capability of proposed method. The proposed ideas are used in a case study where 29 Iranian supply chains producing equipment of expendable medical devices are evaluated in terms of sustainability.     

A slacks-based network DEA efficiency analysis of European airlines

Conventional data envelopment analysis (DEA) models consider a system as a single-process ‘black box’. There are, however, DEA approaches that consider a system as composed of distinct processes or stages, each one with its own inputs and outputs and with intermediate flows among the stages. In this paper, a network DEA approach to airline efficiency assessment is presented. One conclusion of the study is that the network DEA approach has more discriminative power than the single-process DEA approach and that the computed targets, efficiency scores and rankings are more valid. This is because network DEA allows for a more fine-grained analysis that leads to a more realistic estimation of the overall system production possibility set than the one assumed by conventional DEA. In other words, compared with network DEA the conventional, single-process DEA represents an aggregated analysis that merges all system processes with their inputs and outputs and ignores their internal flows. The main drawbacks are the need for more detailed data (i.e. at the process level) and the greater complexity of the resulting models, especially if there are inputs or outputs that are shared among the processes.     

Have Emission Control Areas (ECAs) harmed port efficiency in Europe?

Ports in the European Union and North America have enforced environmental regulations on controlling SO_x and NOx emissions from ships in their coastal areas known as Emission Control Areas (ECAs). This study uses two-stage approaches to examine whether ECA regulations impact the efficiency of ports operating in such areas. First, port efficiencies are estimated using non-radial slacks-based measure (SBM) Data Envelopment Analysis (DEA) models. The efficiency scores estimated by the SBM DEA models are then regressed on explanatory variables, including the ECA factor, and macroeconomic indicators using bootstrapped truncated regression (BTR) models. Panel data is collected on countries in EU ECAs and non-ECAs regarding such input variables as capital and labor, with cargo as an output variable. The results indicate that ECA regulations can harm port efficiency, reflecting concerns of policy-makers and industrial managers: the average efficiency loss from an ECA designation amounts to 0.058–0.066 on a scale of 0–1, accounting for a 15–18% loss from ECA ports’ average efficiency scores.     

A data envelopment analysis model for evaluating the performance of taxi operators: a case study in Harbin,China

ABSTRACT

This paper measures the performance of taxi operators using data envelopment analysis (DEA) and the improvement of performance based on benchmarks. This includes basic DEA models and a cross efficiency model. In the present work, a sample set of 20 taxi operators are considered, and an evaluation indicator framework is constructed, which mainly involves the identification of decision-making units (DMUs) and the determination of input-output variables. The combined results of multiple DEA models are used to evaluate the performance of taxi operators in a case study of Harbin. The results highlight the significance of the combined application of multiple DEA models, especially a cross-efficiency model that can obtain more objective efficiency values. Finally, the benchmarking method is used to capture the achievements of best-performing operators and provide valuable improvement recommendations for inefficient operators. Conclusions provide a suitable basis for the operation and management of the taxi market.     

Efficiency in Asian railways: a comparison between data envelopment analysis approaches

Performance analysis has become a vital part of the management practices in the logistics infrastructure. Although there are numerous applications using Data Envelopment Analysis (DEA) models to estimate efficiency in ports and airports, research on railway efficiency remains scarce. Most of the efficiency studies of railways assume that inputs and outputs are known with absolute precision. Here, we compare Stochastic-DEA and Fuzzy-DEA models to assess, respectively, how the underlying randomness and fuzziness impact efficiency levels in railway operations in six different Asian countries: Japan, Thailand, Vietnam, Malaysia, Myanmar, and Indonesia. Findings reveal that conclusions with respect to the ranking of these railways may vary substantially depending upon the type of model chosen, although efficiency scores are similar to some extent when compared within the ambits of Stochastic-DEA and Fuzzy-DEA models. Additionally, modeling choices on fuzziness, rather than randomness, appear to be the most critical source for variations in efficiency rankings.     

Additive models for network data envelopment analysis in the presence of shared resources

This paper studies the problem of evaluating the relative efficiency of a set of specialized and interdependent decision-making subunits that make up a large decision-making unit (DMU). The paper develops a data envelopment analysis (DEA) approach for measuring the efficiency of decision processes which can be divided into two stages. In these processes the first stage uses its own inputs to generate outputs which a part of these outputs become the inputs to the second stage. Moreover, DMUs use shared input sources in both operation stages. This paper provides a set of additive models which measure the performance of two-stage network DEA processes with shared inputs. Numerical examples show the applicability of the approach.     

A bus route evaluation model based on GIS and super-efficient data envelopment analysis

When compared to large cities in developed countries, the shares of public transportation in most Chinese cities are low. Increasing the competitiveness of urban public transportation remains an urgent problem. A capable evaluation method for public transportation is required to assist the development of urban transit systems. This paper focuses on the bus system. Being devoid of standard criteria, it is difficult to determine the efficiency of a transit system or any bus line using a single evaluation index. This paper proposes a comparative analysis to evaluate bus lines so as to filter out candidates for further optimization. From the viewpoints of transit planning, operation and quality of service, this paper establishes 10 subordinate evaluation indices and then uses geographical information system tools, global positioning system data and smart card data to assist the index definition and calculation. Super-efficient data envelopment analysis (DEA) method is adopted for the proposed single factor and comprehensive evaluation models. Finally, the bus system in Shenzhen, China is used as a case study. The comparable significant results validate the capability of the proposed model.     

Eco-design of transportation in sustainable supply chain management: A DEA-like method

This study addresses the issue of eco-design for transportation in sustainable supply chain management (SSCM). Data envelopment analysis (DEA) is adopted and extended to construct a model for this application. This proposed model, together with the tractable algorithm developed in this research, can provide stakeholders with a Pareto Optimal transportation strategy. This derived transportation strategy can help stakeholders realize certain transportation goals with less resource consumption and pollution emission. The discussion presented leads to a heuristic Joint Transportation Policy and concludes with two useful suggestions for putting the strategy into practice. The proposed model was used in an empirical study of design sustainable transportation mechanism for one air-condition manufacturer in China to transport its products as well, the analysis further demonstrating the theoretical and practical value of this research.     

Assessing the technical efficiency, service effectiveness, and technical effectiveness of the world’s railways through NDEA analysis

This paper presents an approach to include both the unstorable feature of transportation service and the technological differences within railway companies in efficiency and effectiveness measurements. We explore efficiency and effectiveness for a group of 40 global railways in the year 2002, using traditional data development analysis (TDEA) and network data development analysis (NDEA). Comparing the results obtained from the NDEA model with those from the TDEA indicate that performance measures are quite different in terms of the magnitude, and even using different DEA type models to evaluate railway system performance does not distort the ranking of their performance. We also analyze the inter-related effects among three performance measures, finding that transportation service characteristics have positive effects on the evaluation of performance. Generally speaking, the NDEA model provides deeper insight regarding the sources of inefficiency and process-specific guidance to railway managers so as to help them improve their railway’s performance.     

Future planning for benchmarking and ranking sustainable suppliers using goal programming and robust double frontiers DEA

Decision-making for selecting sustainable suppliers has become an intricate duty. To rank sustainable suppliers and select benchmarks this paper proposes an efficiency improvement plan. Two levels of improvement plans including goals and benchmarks are presented for the suppliers. To this end, the first-level goals are obtained using goal programming (GP) and data envelopment analysis (DEA). Since inputs and outputs of the first-level goals might be imprecise, robust Charnes-Cooper-Rhodes (CCR) model is run. As a result, the benchmarks of the second-level are obtained. Then, a robust CCR inefficiency model is applied for ranking the suppliers. In fact, such a ranking capability is made by creating double-frontiers including CCR efficiency and inefficiency frontiers. Accordingly, the suppliers are ranked using the first-level goals. In the new ranking, uncertainty of the goals is considered by running robust optimization technique. The proposed approach provides technical and planning capabilities which are demonstrated by a case study.     

Efficiency evaluation and PM emission reallocation of China ports based on improved DEA models

The emission of particulate matter (PM) and other atmospheric pollutants in port operations and shipping have caused a huge negative impact on the environment. Consequently, how to evaluate the environmental efficiency of ports and put forward corresponding countermeasures on this basis is becoming a more important issue than ever before from the perspectives of the government, academia, and society. We construct three data envelopment analysis (DEA) models to evaluate the environmental efficiency of ports under the circumstances of environmental control, non-environmental control and PM emission through inter-ports cooperation. The innovation of the DEA models constructed in this paper lies in: (1) Setting environmental control parameters to uniformly manipulate the situations of environmental control and non-environmental control, etc.; (2) Allowing non-equal proportional change of input index, expected output and non-expected output index; (3) Setting preference coefficients for ports to admit favorable decisions; (4) Providing a distance formula of expected output for PM emission reallocation. Further, data from 11 major ports in China are collected to compare the expected output under different PM emission standards assuming the situation of environmental control and non-environmental control, port cooperation, and non-cooperative sewage discharge. The empirical results show that: (1) Ports in the eastern China (Shanghai, Ningbo, and Nanjing) have higher port efficiency; (2) Port cooperation can improve the overall expected output but it will lose its edge with the improvement of PM emission standards. (3) Ports follow the same trend of output loss regardless of favorable decisions. In the end, the author makes a summary, puts forward relevant policy suggestions and makes the recommendation for future research.     

The evaluation of transportation energy efficiency: An application of three-stage virtual frontier DEA

In this paper, transportation energy efficiency is newly defined and its inputs and outputs are obtained through literature review. Labor input, capital input and energy input are selected as the inputs, passenger turnover volume and freight turnover volume are defined as the outputs. A new model—three-stage virtual frontier DEA (three-stage virtual frontier Data Envelopment Analysis) is proposed to evaluate transportation energy efficiencies. The case of thirty Chinese PARs (provincial administrative regions) from 2003 to 2012 is applied to verify its rationality. In the three-stage virtual frontier DEA, the reference DMU (decision-making unit) set and the evaluated DMU set are two different sets so that it can distinguish the DEA efficient DMUs. And in the evaluating process, the reference DMU set remains unchanged to assure its results more reasonable than Super DEA model. The results show that transport structure and management measures have important impacts on transportation energy efficiency.     

Towards a common measure of greenhouse gas related logistics activity using data envelopment analysis

Monitoring company emissions from freight transport is essential if future greenhouse gas (GHG) reductions are to be realised. Modern economies are characterised increasingly by lower density freight movements. However, weight-based measures of freight transport activity (tonne-kilometre, tonnes lifted) are not good at describing volume-limited freight. After introducing the need for performance measurement, the problem of benchmarking is outlined in more detail. A context-dependent undesirable output data envelopment analysis (DEA) model, designed to be sensitive to business context, is then tested on a simulated set of fleet profiles. DEA can produce more consistent measures of good-practice, compared to ratio-based key performance indicators (KPI), providing emission reduction targets for companies and an aggregate reporting tool.     

An analytical model to conduct a person-based evaluation of transit preferential treatments on signalized arterials

The complexities of urban transportation networks where multiple modes with different characteristics and needs travel in combination with constraints on space and funding make the sustainable management of these systems a challenge. In order to improve transit service, space (e.g., dedicated bus lanes) and time (e.g., transit signal priority strategies) Transit Preferential Treatments (TPT) are deployed to improve transit operations. The objective of this paper is to develop an analytical model that allows for a person-based evaluation of alternative TPTs when considered individually and in combination. In particular, the analytical model is developed to assess person delay and person discharge flow at any intersection that is part of a signalized arterial, where auto arrivals are in platoons. The performance of TPTs is evaluated using both the analytical model and through microsimulation tests on two intersections of San Pablo Avenue in Berkeley, CA. Space TPTs such as dedicated bus lanes and queue jumper lanes are beneficial in reducing bus person delay when provided in addition to the existing lanes; however, the effectiveness of time TPTs such as green extension depends on the level of auto demand in combination with signal settings. Changes in person discharge flow are not significant for any of the treatments tested with the exception of the bus lane substitution with and without green extension, which led to a significant decrease in person discharge flow. Increased bus frequency increases the effectiveness of transit signal priority in reducing total and bus person delay. The analytical model results produce ranking outcomes that are comparable with the microsimulation ones and therefore, the model may be used for a quantitative evaluation of TPTs without the need for data intensive and time consuming calibration efforts required for microsimulation models. The developed model can be used to guide infrastructure and investment decisions on where such TPTs should be implemented and under what conditions space TPTs should be combined with time TPTs to improve person mobility.     

Boundedly rational route choice behavior: A review of models and methodologies

Perfect rationality (PR) has been widely used in modeling travel behavior. As opposed to PR, bounded rationality (BR) has recently regained researchers’ attention since it was first introduced into transportation science in the 1980s due to its power in more realistic travel behavior modeling and prediction. This paper provides a comprehensive survey on the models of BR route choice behavior, aiming to identify current research gaps and provide directions for future research. Despite a small but growing body of studies on employing bounded rationality principle, BR route choice behavior remains understudied due to the following reasons: (a) The existence of BR thresholds leads to mathematically intractable properties of equilibria; (b) BR parameters are usually latent and difficult to identify and estimate; and (c) BR is associated with human being’s cognitive process and is challenging to model. Accordingly, we will review how existing literature addresses the aforementioned challenges in substantive and procedural bounded rationality models. Substantive bounded rationality models focus on choice outcomes while procedural bounded rationality models focus on the empirical studies of choice processes. Bounded rationality models in each category can be further divided based on whether time dimension is included. Accordingly, static and dynamic traffic assignment are introduced in substantive bounded rationality while two-stage cognitive models and day-to-day learning models in procedural bounded rationality are discussed. The methodologies employed in substantive bounded rationality include game theory and interactive congestion game, while those in procedural bounded rationality mainly adopt random utility and non- or semi-compensatory models. A comparison of all existing methodologies are given and bounded rationality models’ scope and boundaries in terms of predictability, transferability, tractability, and scalability are discussed. Finally existing research gaps are presented and several promising future research directions are given.     

Using DEA models to jointly estimate service quality perception and profitability – Evidence from international airports

With increasing competition between airports and a growing share of non-aeronautical revenues, particularly at large international hubs, perceived quality and consumer satisfaction have not only become a key focus of management but potentially the most important tool to achieve or maintain a competitive advantage. However, in the long run stakeholders aim for profit maximisation and it has been shown for other parts of the aviation supply chain that quality does significantly impact on profitability. In this paper we aim to investigate whether perceived airport quality has an impact on airport profit margins. We further apply two-stage Data Envelopment Analysis (DEA) models to estimate a single efficiency measure that combines the potentially conflicting indicators of perceived service quality and profitability for the airport context. We also identify determinants of the jointly estimated single quality/profitability measure.     

Closed-loop Inventory Routing Problem for returnable transport items

Increasing concerns on supply chain sustainability have given birth to the concept of closed-loop supply chain. Closed-loop supply chains include the return processes besides forward flows to recover the value from the customers or end-users. Vendor Managed Inventory (VMI) systems ensure collaborative relationships between a vendor and a set of customers. In such systems, the vendor takes on the responsibility of product deliveries and inventory management at customers. Product deliveries also include reverse flows of returnable transport items. The execution of the VMI policy requires vendor to deal with a Closed-loop Inventory Routing Problem (CIRP) consisting of its own forward and backward routing decisions, and inventory decisions of customers. In CIRP literature, traditional assumptions of disregarding reverse logistic operations, knowing beforehand distribution costs between nodes and customers demand, and managing single product restrict the usage of the proposed models in current food logistics systems. From this point of view, the aim of this research is to enhance the traditional models for the CIRP to make them more useful for the decision makers in closed-loop supply chains. Therefore, we propose a probabilistic mixed-integer linear programming model for the CIRP that accounts for forward and reverse logistics operations, explicit fuel consumption, demand uncertainty and multiple products. A case study on the distribution operations of a soft drink company shows the applicability of the model to a real-life problem. The results suggest that the proposed model can achieve significant savings in total cost and thus offers better support to decision makers.     

How to assess sustainability of suppliers in volume discount context? A new data envelopment analysis approach

In this paper, we reformulate conventional data envelopment analysis (DEA) models and propose a novel method for evaluating sustainability of suppliers in the presence of interval volume discount offers, fuzzy data, and ordinal data. To this end, we convert all data into interval data. To convert fuzzy data into interval data, we use nearest weighted interval approximation by applying weighting function and we convert each ordinal data into interval one. Then, using enhanced Russell model, interval efficiencies are obtained. After that, using preference degree approach, we rank suppliers. Finally, a case study is presented to illustrate our proposed approach.     

高铁枢纽建设与城市功能空间协同发展效率评价

随着我国高铁迅速发展,高铁建设如何与城市功能空间协同发展的问题引起广泛关注。为了评价高铁与城市协同发展的效率,本文从城市协同性、高铁枢纽建设、站城距离等角度,构建高铁枢纽建设与城市功能空间协同发展效率评价指标体系。并引入DEA模型进行分析计算其效率匹配度,为城市既有高铁站与城市协同发展程度提供依据。最后以京沪高铁为案例分析了24个车站与所在城市的协同关系效率值,结果表明,北京南站、上海虹桥站等高铁枢纽发展较好,常州北站、苏州北站、天津南站等较差,尤其是天津南站的通过能力、客流量等产出指标还需要进一步加强。     

Measuring foregone output under industry emission reduction target in the transportation sector

Numerous countries have implemented or are considering a range of policies to lower emissions from transportation. An analysis of the impacts of environmental regulation is a crucial issue, which has not been properly highlighted in the transportation literature, particularly in terms of the foregone output by such regulation. This study develops a novel DEA model that measures the foregone output when the industry emissions target is imposed. This model reflects the real regulatory process more appropriately than other models in that the authority in charge sets the emission reduction target first, and the transport operators respond to it. In addition, the model can test the industrywide impacts over a wide range of emission target values, which can help policy makers determine the optimal emission target. Finally, the proposed model was applied to the port industry in Korea. The results suggest that Korean ports can reduce their emissions by a maximum of 239,850 tons of CO₂, which accounts for 13% of the total emissions in 2010. The 13% reduction in emission, however, would result in $ 91,109,000 of foregone cargo traffic to the Korean economy. In addition, the foregone cargo traffic increases at much faster rate than the emission reduction rate. For example, the shadow price of emission differs by 2.25 times between the most moderate and strictest emission targets. This suggests that the government needs to impose moderate emission targets at the initial stages if it decides to minimize the regulatory impacts on the industry.