The non-parametric approach is a common method for measuring the relative efficiency in the area of performance benchmarking and operations research. This approach does not require the a priori specification of a function. The estimation of the frontier of the production set only requires that the production set satisfies some properties, such as input and output factors. The Data Envelopment Analysis (DEA) method is a non-parametric approach that uses mathematical programming to esti-mate production frontiers and calculus efficiency scores.
The above technical explanation is necessary, as the present seminar paper deals with the application of the DEA approach in the field of the public transport. The objective of this paper is to review the state of the art in performance benchmarking in terms of different DEA-based framework and criteria to measure efficiency in the environments of public transport. To contribute to this goal, the ambition is to provide a systematic analysis of the performance criteria of the DEA models. Consequently, the main focus of this paper is to examine and classify the performance criteria.
Table of Contents
1 Introduction
1.1 Motivation
1.2 Objectives and Outline
2 Performance Benchmarking
2.1 Overview
2.2 Basic DEA Models
3 Performance Benchmarking in Public Transport
3.1 Structure of the Public Transportation Sector
3.2 Different Views
3.3 Classification of the Performance Criteria
3.3.1 Input Variables
3.3.2 Output Variables
3.3.3 External Variables
3.4 Features of DEA Models
4 Conclusion and Outlook
5 Bibliography
Objectives and Scope
This seminar paper aims to provide a systematic review of Data Envelopment Analysis (DEA)-based frameworks and performance criteria used to evaluate efficiency within the public transport sector. The core research objective is to examine and classify input, output, and external variables, helping to understand how different stakeholder perspectives influence the measurement of efficiency in highly regulated transport environments.
- Theoretical foundations of performance measurement and basic DEA models.
- Analysis of the public transportation sector's structural characteristics.
- Classification of performance indicators into supply-oriented, demand-oriented, and financial categories.
- Examination of external/environmental factors and their impact on efficiency benchmarking.
- Review of DEA-based frameworks used in existing academic literature.
Excerpt from the Book
3.1 Structure of the Public Transportation Sector
Mobility is seen as a key element for the prosperity of our society. The demand for mobility is satisfied by both individual transport and public transport. Through technological progress and tariff enhancements, public transport has a unique role in increasing mobility. Public transport even has positive side-effects on individual transport through avoiding congestion on roads and parking spaces. Public transport can be classified into long-distance passenger transport (served by aircrafts, buses, ferries, and railways) and local public transport (served by buses, ferries, railways, taxis, and all types of aerial cableways, light railways, subway, and tramways).
Policy makers play a major role in public transport. Public service obligations, regulatory approval, and the peculiarities associated with certain types of infrastructure are all subject to public debate. The provision of public transport services serves as a social right for the sector’s existence. However, transport services are often not as cost-efficient as possible. In the last three decades, industrialized countries have developed unique, complex, and capacious local public transport systems. Consequently, there are some characteristic differences among countries. These differences, at times, result from regulation, ownership, or market structure. For example, the United Kingdom is a popular subject for liberalization and deregulation studies, while Sweden has long been at the forefront of competitive tendering. Moreover, Italy similar to many other countries faces financial pressure on losses occurring in local public transport. From a welfare economic viewpoint, the public sector attends to four main goals: efficiency, equity, financial balance, and macroeconomic stabilisation.
Summary of Chapters
1 Introduction: Provides the motivation for the paper, highlighting the importance of efficiency in public transport, and outlines the objectives and structure of the work.
2 Performance Benchmarking: Describes the theoretical background of efficiency measurement and introduces basic Data Envelopment Analysis (DEA) models such as CCR and BCC.
3 Performance Benchmarking in Public Transport: Analyzes the structure of the transport sector, explores different stakeholder viewpoints, and provides a detailed classification of input, output, and external performance criteria.
4 Conclusion and Outlook: Summarizes the key findings regarding the classification of performance criteria and suggests future research directions concerning the interrelationship between these variables.
5 Bibliography: Lists the academic sources and literature used to support the research presented in the paper.
Keywords
Public Transport, Performance Benchmarking, Data Envelopment Analysis, DEA, Efficiency, Productivity, Input Variables, Output Variables, External Factors, Regulatory Environment, Transportation Sector, Management Control, Technical Efficiency, Scale Efficiency, Resource Optimization.
Frequently Asked Questions
What is the primary focus of this seminar paper?
The paper primarily focuses on reviewing and classifying the performance criteria—specifically input, output, and external variables—used in Data Envelopment Analysis (DEA) models within the public transportation sector.
What are the central themes discussed in the work?
Key themes include the structural characteristics of the public transport industry, the theoretical basis of performance benchmarking, the influence of stakeholder viewpoints (providers, travelers, and community), and the application of non-parametric efficiency models.
What is the main research objective?
The core objective is to provide a systematic analysis of performance criteria to help understand how efficiency is measured in the diverse and complex environment of public transport, thereby aiding decision-makers.
Which scientific method is utilized in this study?
The paper focuses on the Data Envelopment Analysis (DEA) method, a non-parametric approach to measuring relative efficiency that does not require the a priori specification of a production function.
What aspects are covered in the main section of the paper?
The main section covers the theoretical foundations of benchmarking, the specific structure of the public transport sector, and a comprehensive breakdown of inputs (capital, labor, energy), outputs (supply/demand-oriented, financial), and external/environmental factors.
How can this work be characterized by its keywords?
The work is characterized by terms such as Public Transport, Performance Benchmarking, Data Envelopment Analysis (DEA), Efficiency, and performance classification metrics.
Why is the distinction between supply-oriented and demand-oriented variables important?
This distinction is crucial because different stakeholders have conflicting objectives; while regulators may focus on efficiency in resource use, transport operators often focus on passenger volume and service availability.
What role do "External Variables" play in the DEA models described?
External variables represent environmental factors—such as population density, network length, or socio-economic characteristics—that impact performance but are not traditional inputs or outputs, thus requiring specific adjustment to ensure fair benchmarking.
- Arbeit zitieren
- Andreas Davidek (Autor:in), 2015, Performance Benchmarking in Public Transport Sector. The Data Envelopment Analysis (DEA) method, München, GRIN Verlag, https://www.grin.com/document/380812
