海上通道关键节点安全保障效率及应急效率评价研究

为了能够全面系统地评价海上通道关键节点的安全保障效率及应急效率,在两阶段DEA模型的基础上,考虑负投入产出变量、决策者对于2种不同效率的偏好差异及效率分解,构建了海上通道关键节点安全保障效率与应急效率评价模型,并将其应用到16个海上通道关键节点的安全保障效率及应急效率评价中.研究结果显示,龙目海峡和霍尔木兹海峡的效率始终是非有效的,且随着α值的增加,曼德海峡、苏伊士运河和望加锡海峡也会转变成非有效单元.除此之外,朝鲜海峡,霍尔木兹海峡和英吉利海峡3个关键节点的子系统效率值波动不明显,安全保障系统占据主体,而马六甲海峡和龙目海峡2个单元的子系统效率值存在部分不规律的变化.     

基于DEA的高速公路服务区服务效率评价研究

为了更有针对性地提升高速公路服务区的整体服务效率,根据服务区的特性,从基础输入和服务输出两个方面建立了服务区服务效率评价指标体系,以衡量服务区的投入和产出效率。输入指标包含地理选址、交通流量和基础设施3 个子项,输出指标包含用户体验1 个子项,各子项中分别有可量化的指标用于具体测算。基于所提指标测算方法,利用DEA评价方法中的C2R模型与C2GS2 模型,对山东省9 对样本服务区进行了问卷调研和MATLAB实例测算,并对评价结 果进行了分析。根据评价结果,对服务区的服务效率进行排序,发现部分服务区存在投入产出效益较低的情况,需要对存在投入冗余的指标进行相应改进,以提高服务效率。     

城市交通与土地利用协调关系的数据包络分析模型

为评价高密度开发特征下城市交通与土地利用之间的关系,提出了评价指标体系,建立了评价二者协调关系的数据包络分析(DEA)模型。利用模型计算了1990~2005年北京市八区交通与土地利用的协调程度,识别了影响二者协调发展的关键因素。分析结果表明:1994年以前以及2003年之后的各年交通与土地利用双向协调发展指数均达到或接近1,协调性相对较好,而1995~2003年的协调性相对较差;就业居住比的投入贡献值为2.743 9,位居土地利用系统指标贡献值之首,公交承担率的投入贡献值为2.733 1,位居城市交通系统指标贡献值之首,说明公交承担率过低,就业岗位与人口分布失衡是影响北京市交通与土地利用协调发展的主要制约因素。     

Sustainability assessment of inland transportation in China: A triple bottom line-based network DEA approach

The transport sector accounts for nearly one third of the world’s total energy use, while inland transport alone is responsible for half of the global petroleum consumption. The expansion of motorization in newly industrialized economies necessitates setting realistic targets. To support decision-makers in better assessment of transport sustainability performance, we introduce a systematic triple bottom line-based approach to evaluate inland transport, considering social, economic, and environmental dimensions of sustainability. The proposed network data envelopment analysis (DEA) measure organizes the three components of the system into a parallel structure, allocates shared input across subsystems, and incorporates undesirable output. The empirical application determines the efficiency of regional inland transportation systems in China from 2006 to 2015. The results indicate a rise in overall transport efficiency between China’s 11th and 12th five-year development plan periods and link the economic growth with a decrease in environmental transport efficiency in the Central and Western zones and with a decline in social efficiency in the Eastern zone. Since 2012, the social sustainability remains the weakest component of inland transport, which requires special attention by policy-makers to support vulnerable groups of transport users. This study provides further insight into the investigated measures and proposes recommendations for the improvement of inland transport in China.     

基于DEA模型的我国邮轮母港的综合评价

针对现阶段我国邮轮母港建设过盛的情况,运用DEA模型对我国相对有可能发展成邮轮母港的港口城市进行评价。通过分析影响邮轮母港建设的因素和条件,构建邮轮母港指标体系进行评价,并对得出的结果进行分析,解决邮轮港口功能定位的问题,即发展国际邮轮母港和发展国际邮轮靠泊港孰优的问题。     

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 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.     

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.     

The impact of competition on container port (in)efficiency

There are many studies on container port efficiency and that seek to understand what factors, such as technical and scale efficiency, private versus public terminal management or macro-economic factors, play on the efficiency score of a given port. There are fewer studies that focus on the role played by the inter-port competitive environment. This role remains difficult to assess. In fact, on the one hand, a port subject to high inter-port competition may record higher efficiency scores due to the pressure from the competitive environment. On the other hand, a port subject to high competition may be forced to over-invest and could therefore records a lower efficiency score. This article investigates this issue and examines how the degree of competition measured at different levels (local, regional and global level) impacts the efficiency score of a given container port. To do so, we implement a truncated regression with a parametric bootstrapping model. The model applied to information gathered for 200 container ports in 2007 and 2010 leads to the following conclusions: port efficiency decreases with competition intensity when measured in a range of 400–800 km (regional level); and the effect from competition is not significant when competition is measured at a local (less than 300 km) or at a global (more than 800 km) level. Estimates also show a tendency for ports who invested from 2007 to 2010 to experience a general decrease in efficiency scores, an element which could be explained by the time lag between the investment and the subsequent potential increase in container throughput.