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This volume describes how frontier efficiency methodologies such as Data Envelopment Analysis (DEA) and other techniques such as multi-criteria decision making can help service industries to improve their performance by providing a ranking of best-practice efficient service units and by identifying sources of inefficiency for each service unit. It explains how they can be used to determine potential improvement targets for each of the inefficient service units, to identify peers for each service organization and to provide a basis for continuous performance improvement. Presenting applications in a variety of industries, this book will be useful for the service management to improve service productivity, profitability, sustainability and quality and effectiveness of service deliveries. A free trial version of the World’s leading Data Envelopment Analysis Software (PIM-DEA) is available for readers of this book.



Managing Service Productivity Using Data Envelopment Analysis

This chapter provides the theoretical foundation and background on data envelopment analysis (DEA) method. We first introduce the basic DEA models. The balance of this chapter focuses on evidences showing DEA has been extensively applied for measuring efficiency and productivity of services including financial services (banking, insurance, securities, and fund management), professional services, health services, education services, environmental and public services, energy services, logistics, tourism, information technology, telecommunications, transport, distribution, audio-visual, media, entertainment, cultural and other business services. Finally, we provide information on the use of Performance Improvement Management Software (PIM-DEA). A free limited version of this software and downloading procedure is also included in this chapter.
Ali Emrouznejad, Emilyn Cabanda

Development of Assessment Model for Research Efficiency of Universities

Research in university is an essential part for national competitiveness and the foundation of knowledge and information of a society. This study assumed that the effective operation of limited resources by size of universities would be the plan for maximizing their effectiveness, and suggested grouping of similar universities by establishing a new classifying system. Based on new classifying system the current status of universities is assessed to help concentration on research activities for their target.
In this study, four models such as high efficiency expanding model (HEEM), high efficiency stable model (HESM), low efficiency stable model (LESM) and low efficiency expanding model (LEEM) were suggested through a practical analysis.
This chapter is based on the Ph.D. thesis of Dr. Jong-Woun Youn.
Jong-Woun Youn, Kwangtae Park

Incorporating Intra- and Inter-Input/Output Weight Restrictions in Piecewise Linear DEA: An Application to the Assessment of the Research Activity in Higher Education

Standard Data Envelopment Analysis models view all input/output factors as linear value functions. Piecewise Linear Data Envelopment Analysis (PL-DEA) is a generalization of the DEA methodology which incorporates piecewise linear functions of factors to handle situations that do not have a linear impact on efficiency, as they may exhibit either diminishing or increasing marginal values. In this chapter we extend PL-DEA to Value-based PL-DEA that incorporates value judgments and allows common treatment for intra- and inter-input/output weight restrictions. Value-based PL-DEA further enables a better expression of individual preferences, enhances the model with the fully units invariance property and also resolves the discontinuity issue that exist in the original PL-DEA model. Value based PL-DEA is illustrated by an application to assess the quality and extent of research work in higher education.
Dimitris Sotiros, Yannis G. Smirlis, Dimitris K. Despotis

Estimating the Efficiency of Healthcare Facilities Providing HIV/AIDS Treatment in Zambia: A Data Envelopment Approach

Zambia and many other countries in Sub-Saharan Africa face a key challenge of sustaining high levels of coverage of AIDS treatment under prospects of dwindling global resources for HIV/AIDS treatment. Policy debate in HIV/AIDS is increasingly paying more focus to efficiency in the use of available resources. In this chapter, we apply Data Envelopment Analysis (DEA) to estimate short term technical efficiency of 34 HIV/AIDS treatment facilities in Zambia. The data consists of input variables such as human resources, medical equipment, building space, drugs, medical supplies, and other materials used in providing HIV/AIDS treatment. Two main outputs namely, numbers of ART-years (Anti-Retroviral Therapy-years) and pre-ART-years are included in the model. Results show the mean technical efficiency score to be 83 %, with great variability in efficiency scores across the facilities. Scale inefficiency is also shown to be significant. About half of the facilities were on the efficiency frontier. We also construct bootstrap confidence intervals around the efficiency scores.
Felix Masiye, Chrispin Mphuka, Ali Emrouznejad

Benchmarking in Healthcare: An Approach Based on Closest Targets

This chapter examines the process of benchmarking in healthcare. In particular, we focus on hospital performance. We are especially interested in showing that the determination of closest targets as a benchmarking technique has significant advantages over traditional Data Envelopment Analysis (DEA) methods for signaling keys for the inefficient hospitals to improve their performance. In doing so, we use a sample of hospital located in the eastern region of Spain. We show the computational problems related to the estimation of this type of targets and the ways that exist to solve such problems. Finally, we suggest in the application some guidance in relation to determining potential improvement targets for each of the inefficient units.
Juan Aparicio, Fernando Borras, Lidia Ortiz, Jesus T. Pastor

Service Enterprise Productivity in Action (SEPIA)

Services [Service sectors include financial services (banking, insurance, securities, fund management), professional services (accounting, legal, engineering, architecture), health services, education services, environmental services, energy services, logistics, tourism, information technology, telecommunications, transport, distribution, standards and conformance, audio-visual, media, entertainment, cultural and other business services (Australian Services Round Table Memorandum of Understanding with Australia 2009)] are becoming increasingly important to the Australian economy and that of other developed and developing economies. Yet, evidence shows that as production moves from agriculture and manufacturing to service- and knowledge-based economies, productivity growth rates have declined. To date there are no clear indicators for quantifying productivity for service and network based firms. This raises the question: How can productivity be measured for service and network based firms? This chapter presents a systems view of productivity and is organized into five sections: Overview of productivity; Current measures of productivity using KLEMS; Existing Service Productivity Models; Service Enterprise Productivity in Action (SEPIA) model, and New Measures for Service Enterprise Productivity. The key contribution of this chapter involves the operationalisation of the SEPIA model and an illustration of the model through the use of an industry example.
Moira Scerri, Renu Agarwal

Using Data Envelopment Analysis to Measure Good Governance

Sustainable development takes place in an environment of good governance. This chapter provides an estimate of good governance index using the Data Envelopment Analysis (DEA) method using data from Philippine provinces. We illustrate how DEA can be used to provide insights on how provinces can improve on various indicators of governance. Aside from identifying peers, DEA is also able to estimate targets, which can serve as a guide for central governments in holding provinces accountable. This chapter shows that DEA is not used only for efficiency measurement but also applied to other applications in benchmarking and index generation, including non-profit sectors such as public agencies.
Rouselle Lavado, Emilyn Cabanda, Jessamyn Encarnacion, Severa de Costo, Jose Ramon Albert

Measuring the Performance of Service Organizations and the Effects of Downsizing on Performance: Evidence from the Greek Citizen Service Centers

A Data Envelopment Analysis-based methodology is developed to measure the performance of not-for-profit and for-profit service organizations. The proposed methodology can incorporate endogenous and exogenous variables in the production process, which are directly or inversely related. This methodology always identifies reference units that are qualified in all of the dimensions of performance. In addition, it defines appropriate changes to the resources that are used by the low-performing units to enable them to become qualified in all facets of performance at the optimal condition. The methodology that is developed in this study is applied to public organizations, which are in charge of the provision of administrative services to citizens, in two instances: before and after the implementation of downsizing as part of the public management reform agenda. The results obtained from the assessment methodology are the basis for the analysis of the impact of structural reform, and particularly of downsizing, on the performance of public service organizations.
Panagiotis D. Zervopoulos

Measuring Efficiency of Courts: An Assessment of Brazilian Courts Productivity

This chapter uses Data Envelopment Analysis (DEA) to measure efficiency in the Brazilian Judiciary, specifically in State Courts. As in many other countries, inefficiency of Brazilian courts is usually credited to the shortage of material and human resources (e.g., Rebelo 2003). But is it the only, or the main, reason for the current critical situation of the Brazilian Judiciary? A second frequently blamed reason for inefficiency is the poor quality of the procedural law. Yet, given that all the courts in the country follow the same law, why is it that some are able to perform better than others? We will apply DEA to answer these questions. By analyzing data of the 27 Brazilian State Courts, from years 2006 to 2010, we create a ranking of judicial efficiency and, with that, be able to identify the best-practice efficient units. For years 2006 to 2010, results show that efficiency varies substantially across the units. The biggest problem, yet, seems to be with a group of State Courts presenting very unstable results, which might indicate a deficient data collection and/or measurement. Both inefficient and unstable units could use DEA results to improve their management and to achieve better results in their efficiency, productivity and effectiveness in the delivery of judicial services.
Luciana Yeung

Cost Efficiency and Market Power: A Test of Quiet Life and Related Hypotheses in Indonesian Banking Industry

This chapter investigates the relation between market power and cost efficiency (the quiet life hypothesis), and the two competing hypotheses of the relationship between market power and efficiency as well as market concentration on profitability (Structure Conduct Performance and Efficient Structure) in the Indonesian banking industry from 2002 to 2011. The estimation of efficiency is obtained by using a non-parametric Data Envelopment Analysis (DEA). To capture the equilibrium dynamic of the Indonesian banking industry, the Lerner index method is used to measure the level of competition. Results of this study failed to reject both Structure Conduct Performance hypothesis and Efficient Structure hypothesis, but disapprove the existence of the quiet life hypothesis in the Indonesian banking market.

Internal Structure of Service Organization: From Multi-activity Financial Institutions to Network Structure Hotels

Data Envelopment Analysis (DEA) has been frequently used to measure the performance in the financial services and hotel industries. In recent years, based on characteristics that operational processes of financial institutions and hotels may jointly engage in multiple activities and multiple processes, DEA has been further developed to consider internal structures of financial institutions and hotels. This chapter is dedicated to describing internal structures of financial institutions and hotels as well as providing relative DEA models and applications. The chapter illustrates that in order to conform to real operational situations, the construction of DEA model should consider and match the internal operational characteristics of decision making units.
Ming-Miin Yu, Li-Hsueh Chen

Application of DEA in the Electricity Sector: The Case of Meralco Distribution Sectors

Manila Electric Company (MERALCO) is a utility company operating in Manila, Philippines supplying 90 % of the power requirement in the Metro Manila, Philippines. This chapter measures the relative efficiency performance of Meralco Distribution Sectors for the period 2006–2009. The study seeks to (1) evaluate and compare the technical efficiency performance of Meralco Distribution Sectors using selected PBR indicators and other inputs; (2) determine which Meralco Distribution Sector achieved the highest technical efficiency performance, and (3) identify areas for improvement of each Meralco Distribution Sector. The study employed input-oriented Data Envelopment Analysis (DEA), using Banker, Charnes and Cooper (BCC) Variable Returns to Scale (VRS) model to evaluate the panel data sets. A linear monotone transformation was adapted to make use of undesirable output in the DEA BCC model. Empirical results of the study revealed that the mean efficiency score of all DMUs was 89.90 %, which means that on the average, Meralco is below best practices by 10.10 %. This is a clear indication that there are Meralco Distribution Sectors, which drive down the overall performance of the company. These findings imply that the management of Meralco or the distribution sectors need to formulate strategies and policies that would further improve their performances.
Michael L. Antonio, Ma. Socorro P. Calara

Improving Energy Efficiency Using Data Envelopment Analysis: A Case of Walnut Production

Walnut is one of the most nutritive crops and modern production methods require large quantities of energy. Efficient use of these energies is a necessary step toward agricultural sustainability. This study therefore focuses on optimizing energy consumption in walnut production by identifying and reducing excessive use of energy. A non-parametric input-oriented Data Envelopment Analysis (DEA) was applied to analyze energy efficiency of different walnut producers in Iran. DEA was used to model efficiency as an explicit function of human labor, machinery, fertilizers-chemicals and irrigation energies. The result of DEA analysisshows substantial inefficiency between the walnut producers in the studied area, withthe main difference between efficient and inefficient producers being in the use of chemicals, potash, machinery and irrigation water. The use of chemicals such as insecticides and herbicides for efficient producers was considerably less than inefficient ones by 90.21 % and 77.5 %.
Alireza Khoshroo, Richard Mulwa

Service Productivity in IT: A Network Efficiency Measure with Application to Communication Systems

This chapter introduces a network efficiency measure, which is a new kind of thinking for many evaluators in information technology and engineering. Efficiency measure involves going beyond knowledge (true efficiency or estimated efficiency) of program (nodes, algorithms, networks etc.) impact and attempting to compare with other programs. In most cases, this knowledge leads to a decision as whether to replace the program with another more effective program. Efficiency analysis is the approach to program evaluation that looks beyond program effectiveness. The key assumption in efficiency measure is that we live in a world of limited resources and we must make decisions about how to use and allocate the limited resources. In this chapter, Data Envelopment Analysis (DEA), which are appropriate and adequate for the relative efficiency measure and resource control utilization is considered. The technique is applied to extend the existing engineering method in computer networks and to evaluate the efficiency of communication networks. Further, the input-oriented and slacks models are implemented to show how routing loads with overheads are reduced in order to put the IEEE802.11 and packet level network coding based (COPE) protocols in their efficiency frontier.
Adeyemi Abel Ajibesin, Neco Ventura, H. Anthony Chan, Alexandru Murgu

Efficiency of Software Development Projects: A Case Study on an Information Technology Company in India

In this chapter, Data Envelopment Analysis (DEA) is applied to evaluate the relative efficiency of software development projects of a leading software company in India. Further, the projects are categorized as per their efficiency scores into highly efficient, moderately efficient and less efficient companies through a process called Tier Analysis. The chapter also includes an Improvement Path for the projects with low efficiencies. Furthermore, through the application of Kruskal Wallis test, the software development project efficiency is compared with team size to determine whether efficiency vary across various team size categories i.e. small, medium, large and extra large.
Geeta Sharma, Anshu Kataria

Protocol for Comprehensive Efficiency Analysis of Multi-Service Metropolitan Transit Agency Operators

This chapter presents a Data Envelopment Analysis (DEA) protocol for analyzing the efficiency of metropolitan transit agencies that oversee multiple types of transportation services. The protocol is illustrated by applying it to United States transit agencies that can serve their cities with four types of subunits: self-operated motorbus, outsourced motorbus, self-operated demand-responsive, and outsourced demand-responsive. Using DEA models adapted for non-substitutable inputs and outputs, scores estimated for a focus agency include: (1) technical efficiency of the focus agency as a whole, (2) technical efficiency of each of the focus agency’s subunit types when each subunit is compared only to others of the same type, (3) allocation efficiency of the focus agency in apportioning resources among its subunits, and (4) the effect of each subunit’s technical efficiency on its parent agency’s technical efficiency. Finally, a mathematical programming algorithm is illustrated that allocates the focus agency’s resources to its subunits with the objective of decreasing the cost of transit in an urban area while holding total ridership constant. The protocol thereby is a comprehensive analysis and synthesis of a focus transit agency’s efficiency in providing services to its metropolitan area.
Darold T Barnum, John M Gleason, Matthew G Karlaftis

Measuring the Sustainability of Air Navigation Services

Service productivity is synonymous with organizational sustainability. It has applications that are broader than conserving the environment via agroindustrial innovation. The domain of Air Navigation Services is a classic example of a service industry, in which sustainability can be determined using its organizational efficiency and effectiveness. It is a challenge to measure these organizational factors in this profession, because of insufficient data and the effect of random events such as inclement weather that cannot be quantified. A data envelopment analysis (DEA) caters for these restrictions, and is thus, an appropriate tool for determining the sustainability of Air Navigation Service Providers. The DEA method reveals that from among 34 Air Navigation Service Providers in Europe and the Middle East, 33 % shows potentials for sustainability. Eleven ANSPs are relatively efficient and effective by at least 60 %, which was the average organizational efficiency and effectiveness score. The maximum and minimum scores were 146 % and 15 %, respectively. These results highlight the need for urgent attention to the organizational structure of Air Navigation Services and the reallocation of resources that will improve sustainability.
Vladimir Grigorov, Paula Rachel Mark

Measuring and Managing the Productivity of U.S. Public Transit Systems: An Unoriented Network DEA

Governments at all levels face budget shortfalls, and consequently public transit systems in the U.S. must compete with other public services for financial support. In order to depend less on public funding, it is critical that public transit systems focus on their operational performance and identify any sources of inefficiency. In this chapter, we present an unoriented network DEA methodology that measures a public transit system’s performance relative to its peer systems, compares its performance to an appropriate efficient benchmark system, and identifies the sources of its inefficiency.
Sreekanth Mallikarjun, Herbert F. Lewis, Thomas R. Sexton

Using DEA to Improve the Efficiency of Pupil Transportation

Washington State, like many other states, spends hundreds of millions of dollars annually to support the transportation of pupils to and from school. As with other state-funded activities, inefficiency increases costs and saps resources away from other critical state functions such as public and higher education, health care, transportation, and many others. In 2006, the state undertook a project to revise its pupil transportation funding formula and encourage its school districts to operate more efficiently. Together with Management Partnership Services, Inc., the state developed a DEA-based efficiency measurement system that it now uses to identify inefficient pupil transportation systems for management intervention. The system has identified potential first-year savings of roughly $33 million with recurrent annual savings of at least $13 million. The efficiency improvements could remove 312 school buses from the highways of Washington State.
Thomas R. Sexton, Allan J. Jones, Andy Forsyth, Herbert F. Lewis
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