Analyzing the solutions of DEA through information visualization and data mining techniques: SmartDEA framework

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations, which is of vital practical importance in managerial decision making. DEA provides a significant amount of information from which analysts and managers derive insights and guidelines to promote their existing performances. Regarding to this fact, effective and methodologic analysis and interpretation of DEA solutions are very critical. The main objective of this study is then to develop a general decision support system (DSS) framework to analyze the solutions of basic DEA models. The paper formally shows how the solutions of DEA models should be structured so that these solutions can be examined and interpreted by analysts through information visualization and data mining techniques effectively. An innovative and convenient DEA solver, SmartDEA, is designed and developed in accordance with the proposed analysis framework. The developed software provides a DEA solution which is consistent with the framework and is ready-to-analyze with data mining tools, through a table-based structure. The developed framework is tested and applied in a real world project for benchmarking the vendors of a leading Turkish automotive company. The results show the effectiveness and the efficacy of the proposed framework

An agent-based dynamic information network for supply chain management

One of the main research issues in supply chain management is to improve the global efficiency of supply chains. However, the improvement efforts often fail because supply chains are complex, are subject to frequent changes, and collaboration and information sharing in the supply chains are often infeasible. This paper presents a practical collaboration framework for supply chain management wherein multi-agent systems form dynamic information networks and coordinate their production and order planning according to synchronized estimation of market demands. In the framework, agents employ an iterative relaxation contract net protocol to find the most desirable suppliers by using data envelopment analysis. Furthermore, the chain of buyers and suppliers, from the end markets to raw material suppliers, form dynamic information networks for synchronized planning. This paper presents an agent-based dynamic information network for supply chain management and discusses the associated pros and cons

Grabbing the Air Force by the Tail: Applying Strategic Cost Analytics to Understand and Manage Indirect Cost Behavior

Recent and projected reductions in defense spending are forcing the military services to develop systematic approaches to identify cost reduction opportunities and better manage financial resources. In response, the Air Force along with her sister services are developing strategic approaches to reduce front-line mission resources, commonly referred to as the Tooth . However, an underemphasized contributing source of costs are mission support activities, commonly referred to as the Tail . With the tail historically representing a sizable portion of the annual Air Force budget, strategically managing cost behavior of these indirect activities has the opportunity to generate significant cost reductions. However, very little applied or academic research have focused on advancing the knowledge behind the economics of, or the analytic techniques applied to, these activities for cost management purposes. To address this concern, this dissertation investigates i) how organizations use analytic methodologies and data sources to understand and manage cost behavior, ii) how to identify underlying cost curves of concern across tail activities, iii) how to distinguish historical relationships between the tooth and tail, iv) how to improve the performance assessment of tail activities for improved resource allocation, and v) how to provide a decision support tool for tooth-to-tail policy impact analysis

An integrated approach for lean production using simulation and data envelopment analysis

According to the extant literature, improving the leanness of a production system boosts a company’s productivity and competitiveness. However, such an endeavor usually involves managing multiple, potentially conflicting objectives. This study proposes a framework that analyzes lean production methods using simulation and data envelopment analysis (DEA) to accommodate the underlying multi-objective decision-making problem. The proposed framework can help identify the most efficient solution alternative by (i) considering the most common lean production methods for assembly line balancing, such as single minute exchange of dies (SMED) and multi-machine set-up reduction (MMSUR), (ii) creating and simulating various alternative assembly line configuration options via discrete-event simulation modeling, and (iii) formulating and applying DEA to identify the best alternative assembly system configuration for the multi-objective decision making. In this study, we demonstrate the viability and superiority of the proposed framework with an application case on an automotive spare parts production system. The results show that the suggested framework substantially improves the existing system by increasing efficiency while concurrently decreasing work-in-process (WIP).Q10006980682000012-s2.0-8511520297

A review of application of multi-criteria decision making methods in construction

Construction is an area of study wherein making decisions adequately can mean the difference between success and failure. Moreover, most of the activities belonging to this sector involve taking into account a large number of conflicting aspects, which hinders their management as a whole. Multi-criteria decision making analysis arose to model complex problems like these. This paper reviews the application of 22 different methods belonging to this discipline in various areas of the construction industry clustered in 11 categories. The most significant methods are briefly discussed, pointing out their principal strengths and limitations. Furthermore, the data gathered while performing the paper are statistically analysed to identify different trends concerning the use of these techniques. The review shows their usefulness in characterizing very different decision making environments, highlighting the reliability acquired by the most pragmatic and widespread methods and the emergent tendency to use some of them in combination

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

Ananlysis of productivity and efficiency in MSRTC

Maharashtra State Road Transport Corporation (MSRTC) has been instrumental in providing access and connectivity across the entire state of Maharashtra. Over the last few years, due to a variety of factors, particularly competition from the private sector, MSRTC’s financial performance has shown a marked deterioration. After the financial turnaround of Karnataka State Road Corporation when it was split in to four smaller organizations, the same solution was suggested by many for large corporations like MSRTC. In this paper, we examine the issue of splitting MSRTC into smaller regions to find out whether it would actually help in its financial recovery. Also, we examine the possibility of improvement in financial profitability by means of enhanced input productivity.State Road Transport Corporations, Scale Economies, Technical Efficiency, Total Factor Productivity

Seaport Management Aspects and Perspectives: an Overview

Ireland occupies the northern part of the western European coast which has a 70,000 Kilometres coasting along two oceans and four seas. These coasts are Europe’s lifeblood and represent the trade routes, climate regulator and source of food, energy and resources. Seaports and shipping are key maritime activities which allow European coast countries to benefit from the rapid growth of international trade. Therefore, port management became the centre of governments’ interest and the focal point of research to improve the efficiency. This research aims to summaries past publications of seaport systems to highlight challenges and reveal relevant research gaps. Having the objective to classify the literature, a comprehensive review of journal articles and the best practices in the field was conducted. A wide variety of management issues and opportunities to improve service delivery of port systems was discussed in a three main categories based on port authority objectives; strategic, economic and operational

An Integrated Framework to Assess ‘Leanness’ Performance in Distribution Centres

The theory behind lean philosophy is to create more value with less. Effective lean management enables organisations to exceed customer expectations while reducing costs. Despite the fact that numerous practices and approaches are used in the process of implementing lean philosophy and reducing waste within supply chain systems, little effort has been directed into assessing the leanness level of distribution and its impact on overall performance. Given the vital role of distribution units within supply chains, this research aims to develop a comprehensive lean assessment framework that integrates a selected set of statistical, analytical, and mathematical techniques in order to assess the ‘leanness’ level in the distribution business. Due to the limited number of published articles in the area of lean distribution, there are no clear definitions of the underlying factors and practices. Therefore, the primary phase of the proposed framework addresses the identification of lean distribution dimensional structure and practices. The other two phases of the framework discuss the development of a structured model for lean distribution and address the process to find a quantitative lean index for benchmarking lean implementation in distribution centres. Integrating the three phases provides the decision makers with an indicator of performance, subject to applying various lean practices. Incorporating the findings of a survey that sent to 700 distribution businesses in Ireland along with value stream mapping, modelling, simulation, and data envelopment analysis, has given the framework strength in the assessment of leanness. Research outcomes show that lean distribution consists of five key dimensions; workforce management, item replenishment, customers, transportation, and process quality. Lean practices associated with these dimensions are mainly focused on enhancing the communication channels with customers, simplifying the distribution networks structure, people participating in problem solving and a continuous improvement process, and increasing the reliability and efficiency of the distribution operations. The final output of the framework is two key leanness indices; one is set to measure the tactical leanness level, while the second index represents the leanness at the operational level. Both indices can effectively be used in evaluating the lean implementation process and conducting a benchmarking process based on the leanness level

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

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