Russell G. Thompson

The role of multiplier bounds in efficiency analysis with application to Kansas farming

Abstract As long recognized, the problem of efficiency involves both technical and economic facets. Determination of the technically efficient firms provides the base for economic analysis. Values in terms of prices or costs must be introduced into the problem to work towards finding firms which might be regarded as overall efficient. That problem came to the forefront in a 1984 study to find the best site for location of a Superconducting Super Collider (SSC) in the state of Texas. Application of a modern value-free frontier method called Data Envelopment Analysis (DEA) to the data, which was primarily engineering and geological in character, showed five of the six feasible sites were technically efficient. However, additional socioeconomic/environmental data provided ‘price-cost’ inequality bounds for the mathematical multipliers in the DEA problem. Including those bounds in the analysis, which was called an Assurance Region (AR), reduced the number of efficient sites from five to one. In 1988, the U.S. Department of Energy in national competitionactually selected the site identified by the bounding method for location of the SSC. In this paper, the AR concept is defined for efficiency analysis of the linear production possibility set. As applied here to 83 farms, we use only the special case of AR consisting of separate linear homogeneous restrictions on the input and output multipliers. When applied to the technically efficient farms, the AR principles reduced the number of candidates for overall efficiency from 23 to 8 in one case (Ratio Model) and from 44 to 13 in another case (Convex Model).

CITY LOGISTICS. NETWORK MODELLING AND INTELLIGENT TRANSPORT SYSTEMS

This book presents fundamental concepts and general approaches to City Logistics. City Logistics is the process of totally optimising urban logistics activities by considering the social, environmental, economic, financial and energy impacts of urban freight movement. City Logistics initiatives are required to solve urban freight transport problems including high levels of traffic congestion, negative environmental impacts, high energy consumption and a shortage of labour. The focus of this work is on modelling City Logistics. Modelling is of crucial importance, since estimates of the impacts generated by City Logistics measures are required for evaluating them. It highlights the formulation of mathematical models of vehicle routing and scheduling with Intelligent Transport Systems (ITS), optimal terminal locations and impact estimation by City Logistics measures. Heuristics techniques such as genetic algorithms, simulated annealing and tabu search are also given to identify approximate optimal solution of these combinatorial optimisation problems. ITS provides powerful tools for efficiently managing and operating vehicle fleets. Sophisticated logistics systems can now be developed by integrating Global Positioning Systems (GPS) and Geographical Information Systems (GIS) in conjunction with application software. In this context, the book presents a theoretical and practical treatment of modelling City Logistics based on ITS.

Chapter 1 Introduction: Extensions and new developments in DEA

The extensions, new developments and new interpretations for DEA covered in this paper include: (1) new measures of efficiency, (2) new models and (3) new ways of implementing established models with new results and interpretations presented that include treatments of “congestion”, “returns-to-scale” and “mix” and “technical” inefficiencies and measures of efficiency that can be used to reflect all pertinent properties. Previously used models, such as those used to identify “allocative inefficiencies”, are extended by means of “assurance region” approaches which are less demanding in their information requirements and underlying assumptions. New opportunities for research are identified in each section of this chapter. Sources of further developments and possible sources for further help are also suggested with references supplied to other papers that appear in this volume and which are summarily described in this introductory chapter.

MODELING CITY LOGISTICS

Urban freight systems are experiencing many problems due to higher levels of service and lower costs being demanded by shippers, with carriers having to operate in increasingly congested road conditions. Trucks operating in urban areas produce many negative impacts for society in terms of emissions, crashes, noise, and vibration. City logistics aims to globally optimize urban freight systems by considering the costs and benefits of schemes to the public as well as the private sector. The concepts of city logistics are introduced, and an outline is presented of some models that have recently been developed to predict the consequences of intelligent transportation systems. In particular, a stochastic vehicle routing and scheduling procedure that incorporates the variation of travel times is described. Results indicate that this approach can lead to significant reduction in operating costs by carriers as well as shorter routes with fewer trucks and increased reliability for customers. This procedure also reduces emissions and fuel consumption.

DEA/AR efficiency and profitability of Mexican banks a total income model

Abstract Data envelopment analysis (DEA) and linked-cone assurance region (LC-AR) models are used in this paper to investigate the efficiency and profitability potential of Mexican banks as they engage in activities that incur interest and non-interest expenses and produce income. DEA provides a measure of each banks relation to the best-practice frontier for its competitors. This can provide a better quality-benchmark than using industry averages or a particular peer bank as the benchmark. The banks are classified into efficient and inefficient sets. Multiplier values for AR-inefficient banks with unique slacks indicate the potential for management to improve the banks performance relative to its peers. LC-ARs that provide economically reasonable bounds for the multipliers lead to profitability potential, as distinct from efficiency, results.

A REVIEW OF URBAN CAR PARKING MODELS

Car parking is an issue of significance both at the local and at the strategic level of planning. Parking policy and supply play a major role in the management of transportation systems in dense urban areas. Although the policies that govern the provision and operation of parking facilities are recognized to have an important bearing on the operation of urban transport systems, decisions have often been made on an ad hoc basis, without proper integration with other elements of transport systems analysis. In order for parking policy decisions to be well founded, the analysis of parking behaviour and the effects of parking policies should be fully integrated with the other elements of the transport planning and modelling process. To assist this interaction this paper presents a state‐of‐the‐art review of models of parking as an integral component of urban transport systems. The paper develops model groupings by relating their main objectives: choice, allocation and interaction models. It then discusses the ...

Importance for DEA of Zeros in Data, Multipliers, and Solutions*

Some prominent literature in the DEA field has displayed the following three problems involving zeros: (1) The structural role of zeros in data has not necessarily been recognized; in fact, without explanation, arbitrary, small positive numbers have been substituted for such zeros. (2) It is not well recognized that the artificial, non-Archimedean construct is not necessarily needed to exclude zero multipliers and to identify positive slacks. (3) Because of degeneracy, optimal solutions are not necessarily unique; this lack of uniqueness is especially important in interpretation of the multipliers and slacks.

DEA/AR-efficiency of U.S. independent oil/gas producers over time

The productive efficiencies of 45 randomly sampled oil/gas independent firms were analyzed year-by-year by application of data envelopment analysis (DEA) methods for the 7 years 1980–1986. This approach differs fundamentally from a “window” analysis, where structural differences in the efficiency distributions over time may not be easily discerned. Both DEA Ratio and Convex models were applied; also, bounds were placed on the modeled prices (multipliers) by the use of assurance region (AR) principles. The distributions of DEA-efficiency measures were found to have significantly different characteristics in the 1980–1982 period than in the 1983–1986 period. Constant returns-to-scale prevailed in each of the 7 years. The AR-efficiencies, in the presence of multiplier bounds, refined appreciably the candidate set of firms for overall efficiency. The AR-efficiency distributions exhibited significantly different levels and spreads in the 1980–1982 period than in the 1983–1986 period. Very few (5 at most) of the candidates for overall efficiency were viable economic firms in 1985 and 1986. Strikingly different energy policy conjectures follow from this micro analysis than from the U.S. Department of Energys macro analysis in its Energy Security study.

Linked-cone DEA profit ratios and technical efficiency with application to Illinois coal mines

Data Envelopment Analysis (DEA) profit ratios and technical efficiency measures require separate treatment as proved in newly developed theory of Thompson and Thrall. This point is illustrated here by analysis of an example problem; it shows that DEA technical efficiency does not necessarily imply a DEA maximum profit ratio; and, vice versa, a DEA maximum profit ratio does not necessarily imply DEA technical efficiency. The essence of the mathematical framework underlying this argument is provided. Application of the concepts to Illinois coal mining data (previously reported) lends support to the need for separate treatment of DEA technical efficiency and DEA profit ratios.

Sensitivity Analysis of Efficiency Measures with Applications to Kansas Farming and Illinois Coal Mining

Data envelopment analysis (DEA), as its name indicates, is data based. In view of the possibility of erroneous or misleading data, some critics of DEA have questioned the validity and stability of measures of DEA efficiency.