Using Data Envelopment Analysis to Evaluate the Performance of Third Party Distribution Centers

There has been considerable interest worldwide in last few years in the growth of third party logistics (3PL) providers. 3PL distribution center (DC) enables firms to achieve reduced operating costs, increased revenues, and to focus on their core competence. This research aims to find the key performance indicators through a survey of a set of DCs and then evaluate their efficiency over the period 2005-2007 using data envelopment analysis (DEA) models based on selected performance indicators as inputs and outputs. Three inputs and two outputs for all DCs from the surveyed performance indicators were selected in this study. DEA is a non-parametric linear programming technique used to evaluate the efficiency of decision making units (DMUs) where multiple inputs and outputs are involved. We adopted both the input-oriented CCR model and the BCC model that were designed to derive weights instead of being fixed in advance and handle positive inputs/outputs. A Malmquist productivity index (MPI) analysis further evaluates efficiency change and productivity growth between two time points. Our empirical results show that scale inefficiency is the major reason for the inefficient DMUs. For the future research, more DC data should be collected and different DEA models could be applied for other benchmark studies

MEASURING EFFICIENCY CHANGE IN TIME APPLYING MALMQUIST PRODUCTIVITY INDEX: A CASE OF DISTRIBUTION CENTRES IN SERBIA

In the last decade, more and more attention has been paid to the efficiency of logistics systems not only in the literature but also in practice. The reason is the huge savings that can be achieved. In a very dynamic market with environmental changes distribution centers have to realize their activities and processes in an efficient way. Distribution centers connect producers with other participants in the supply chain, including end-users. The main objective of this paper is to develop a DEA model for measuring distribution centers’ efficiency change in time. The paper investigates the impact of input and output variables selection on the resulting efficiency in the context of measuring the change in efficiency over time. The selection of variables on the one hand is a basic step in applying the DEA method. On the other hand, the number of basic and derived indicators that are monitored in real systems is increasing, while the percentage of those used in the decision-making process is decreasing (less than 20%). The developed model was tested on the example of a retail chain operating in Serbia. The main factors changing the efficiency have been identified, as well as the corresponding corrective actions. For measuring efficiency change in time Malmquist productivity index is used. The developed approach could help managers in the decision-making process and also represents a good basis for further research

Hybrid Data Envelopment Analysis and simulation methodology for measuring capacity utilisation and throughput efficiency of container terminals

As growth in international trade slowed down in the recent years, inter-modal traffic volume declined and subsequently led to reduction in demand for container services. The reduced demand in container services and the ongoing glut of container port facilities throughout the world have sparked fierce competition among international container terminals. In an effort to help the port authorities to develop a winning strategy in the increasingly competitive container market, this paper develops a meaningful set of benchmarks that will set the standard for best practices. In particular, we propose a hybrid Data Envelopment Analysis (DEA)/simulation model that is designed to evaluate the relative efficiency of container terminal operations. To illustrate the usefulness of the proposed hybrid DEA/simulation model, we used the real examples of major container terminals in South Korea

Efficiency of the Portuguese metros. is it different from other European metros?

This research analyses the performance of Portuguese metros in the European context. By means of two non-parametric benchmarking techniques, respectively performance indicators and data envelopment analysis, we compute the efficiency of 37 European metros. In order to provide statistical inference and robustness to our results we apply the recent technique of bootstrap. We also use the partial frontiers (order-m) to identify outliers and the double bootstrap procedure in a second stage methodology to take into account the influence of the operational environment. The results show important levels of inefficiency both in the Portuguese metros and in other European metros.Metro; Efficiency; Portugal; Performance Indicator; Data Envelopment Analysis

Productivity Drivers in Japanese Seaports

This paper analyses efficiency drivers of a representative sample of Japanese seaports by means of the two-stage procedure proposed by Simar and Wilson (2007). In the first stage, the technical efficiency of seaports is estimated using several models of data envelopment analysis (DEA) that might be employed in order to establish which of them are most efficient. In the second stage, the Simar and Wilson (2007) procedure is used to bootstrap the DEA scores with a truncated bootstrapped regression to identify efficiency drivers. The policy implications of our findings are considered.Seaports; Japan; Data Envelopment Analysis; Truncated Bootstrapped Regression.

Key characteristics for designing a supply chain performance measurement system

Purpose The purpose of this paper is to conduct a review of the literature that gives insight into design elements for constructing a supply chain performance measurement (SCPM) system. Design/methodology/approach A systematic review of published research on SCPM systems and frameworks over the last two decades was conducted with the purpose of categorising key functions of SCPM systems by providing an insight into the design, functionality, implementation and practical implications of SCPM systems. Findings The review revealed a set of functions governing the SCPM system that have not been fully explored in previous research: the process focus, prioritisation, integration and causality functions of a SCPM system. A relationship between two or more functions can be created to include more functionality based on the needs of the company to create a comprehensive performance measurement system. Research limitations/implications The paper concludes with a conceptual framework to guide future research in the area of designing a SCPM system and define the main aspects that should be considered when developing a SCPM system. Practical implications The paper brings a new dimension to the SCPM research by identifying the main functions of SCPM systems that could benefit practitioners to set up a SCPM system relevant to its intended function. The paper presents multiple potential stages of merging different functions in one SCPM system. Based on the company’s needs and context, the functionality of the SCPM system can be designed at four levels creating ten possible scenarios when designing a company’s SCPM system. Originality/value The paper integrated the literature and findings of 269 research papers of the last two decades, upon which a conceptual framework was developed as a guide for constructing an effective SCPM system

Insights and Challenges about the use of VNA on Airport/Hinterland Linkages

Airport operators, planners and regulatory agencies to measure the economic contribution of an airport to its local and regional surroundings, frequently use economic impact studies. The most common methods to measure airport economic impacts have been the Input-Output method, the Collection of Benefits method and most recently the Catalytic method. The most used measured variables include employment, wages, local and regional spending and air traffic levels. This paper is a new approach to these impact studies in which is used a new tool to identify the added values generated within airports and surrounding community interactions to better catch real socio-economic impacts. The VNA – Value Network Analysis, is used as an integrated methodology to identify these interactions and added values generated (tangibles and intangibles) in the business system of landside airports. To define the system it is used the matrix key airport performance benchmarking areas of ACI (Airport Council International) that are in the range of landside of the airport. Key words: Social Networks, Airport Landside, Value Network Analysis, Key Performance Indicators, Business System.

Technical Efficiency, Regulation, and Heterogeneity in Japanese Airports

In this paper, the random stochastic frontier model is used to estimate the technical efficiency of Japanese airports taking into regulation and heterogeneity in the variables. The airports are ranked according to their productivity for the period 1987 to 2005 and homogenous and heterogeneous variables in the cost function are disentangled. Policy implication is derived.Japan; airports; efficiency; random frontier models; policy implications

Logistic Efficiency Through Horizontal Cooperation: The Case of Flemish Road Transportation Companies

This paper describes a practical application of Data Envelopment Analysis (DEA) to the Flemish road transportation sector.The efficiency of 82 road transportation companies responding to a large-scale survey focused on horizontal cooperation is evaluated, based on two inputs and two outputs.Various DEA models are used to identify differences between subgroups of respondents.The results demonstrate that, in general, Flemish road transportation companies operate at unacceptably low efficiency levels.Given the findings that the median company is operating on too small a scale one apparent remedy would be a dramatic increase in market concentration through mergers and acquisitionshorizontal cooperation;road transportaion companies;data envelopment analysis

Benchmarking Environmental Efficiency of Ports Using Data Mining and RDEA: The Case of a U.S. Container Ports

This study provides step-wise benchmarking practices of each port to enhance the environmental performance using a joint application of the data-mining technique referred to as Kohonen’s self-organizing map (KSOM) and recursive data envelopment analysis (RDEA) to address the limitation of the conventional data envelopment analysis. A sample of 20 container ports in the U.S.A. were selected, and data on input variables (number of quay crane, acres, berth and depth) and output variables (number of calls, throughput and deadweight tonnage, and CO2 emissions) are used for data analysis. Among the selected samples, eight container ports are found to be environmentally inefficient. However, there appears to be a high potential to become environmentally efficient ports. In conclusion, it can be inferred that the step-wise benchmarking process using two combined methodologies substantiates that a more applicable benchmarking target set of decision-making units is be projected, which consider the similarity of the physical and operational characteristics of homogenous ports for improving environmental efficiency