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The long tradition in the public sector of introducing decision-making tools that then fail to live up to expectations has fueled a debate over the proper role of government. This paper suggests that the debate over government productivity may be misplaced. Public productivity may be hindered as a result of inappropriate use of decisionmaking tools for the allocation of resources. Thus, this paper argues for an enlarged repertoire of decision-making techniques. In particular, data envelopment analysis (DEA) is presented as an alternative often more appropriate than such commonly used techniques as cost-benefit ratio and regression analyses.

The purpose of this paper is to present a case study showing how the selection of performance indices affects performance results and the evaluation of a firm's performance.

This paper employs a data envelopment analysis (DEA) framework using four kinds of performance indices selection, which include basic input/output items, balance scorecard (BSC) indices, balanced scorecard with risk management, and traditional financial indices, to evaluate banking operations.

Shows that a DEA‐based evaluation of performance produces a similar view of the firm's well‐being as does an analysis of financial indices; however, a BSC‐based evaluation produces a different assessment.

This study was based on the following assumptions: first, when organizational units achieve technical efficiency, they will improve their organizational performance. Secondly, the inputs and outputs selected for the data envelopment analysis provided an indicator of the changes of bank's technical efficiency over the six‐year period.

This research was based on the data envelopment analysis approach to find different performance efficiency to apply four performance indicator selections, which include basic inputs/outputs items, balanced scorecard indices, balanced scorecard with risk management, and traditional financial indices, to evaluate bank operation.

Combines the balanced scorecard concept with data envelopment analysis measurements (model information) to generate measures of technical efficiency for a Taiwanese bank. It shows how comparisons can be made within and across companies on the basis of balanced scorecard measures.

While market theorists have devoted a great deal of effort to the conceptualization of service quality, the practical guidance available to service providers continues to be very limited. Utilizing the emerging role of a new marketing entity, the retail electric service provider, as an illustration, the article discusses how data envelopment analysis might be used to analyze service quality at the retail service level. Specific dimensions thought to influence consumers’ perceptions of the quality of retail electric energy services are identified, and the potential use of data envelopment analysis as a diagnostic tool for effective management of service quality by retail electric service providers is demonstrated. Generalization to different types of service providers is suggested. Empirical studies to develop practical guidance along this line of analysis are encouraged.

The purpose of this study is to propose a model to evaluate the performance of organizational units considering intellectual capital (IC) and employee loyalty approach applying principal component analysis and data envelopment analysis (PCA-DEA) method.

Organization units are considered as decision-making units, IC components including human capital (HC), structural capital (SC) and customer capital are inputs and employee loyalty is output. The principal component analysis was used to converts inputs and outputs into the independent variables. As a return to scale is variable, a modified envelopment input-oriented BCC model applied to obtain the efficiency of organization units. Also, all units of organization are ranked. Eventually, sensitivity analysis performed to show how input variables influence on output variable.

Operation, design and construction, production planning, internal affairs, quality control and security were recognized as efficient units. Also, units of operation, internal affairs and quality control ranked first to third, and the human resource unit earned the last rank. In addition, results of sensitivity analysis on input variables showed that the order of impact intensity is: customer capital, HC and SC, respectively.

Existence a framework for the development of human resource strategies and prioritization in the allocation of organizational resources to improve the performance of the organization considering human resources is vital. Most of the previous studies, just have examined the impact of IC on different dimensions of organizational performance. Meanwhile, evaluating the performance of IC with employee loyalty approach, using PCA-DEA simultaneously can evaluate and measure the impact of IC on the performance of the organization and its units regarding employee loyalty, which has a significant impact on improving the organization’s level of IC and human resource management.

The chapter examines a comprehensive review of cross-disciplinary literature in the domain of supply chain forecasting during research period 1991–2017, with the primary aim of exploring the growth of literature from operational to demand centric forecasting and decision making in service supply chain systems. A noted list of 15,000 articles from journals and search results are used from academic databases (viz. Science Direct, Web of Sciences). Out of various content analysis techniques (Seuring & Gold, 2012), latent sementic analysis (LSA) is used as a content analysis tool (Wei, Yang, & Lin, 2008; Kundu et al., 2015). The reason for adoption of LSA over existing bibliometric techniques is to use the combination of text analysis and mining method to formulate latent factors. LSA creates the scientific grounding to understand the trends. Using LSA, Understanding future research trends will assist researchers in the area of service supply chain forecasting. The study will be beneficial for practitioners of the strategic and operational aspects of service supply chain decision making. The chapter incorporates four sections. The first section describes the introduction to service supply chain management and research development in this domain. The second section describes usage of LSA for current study. The third section describes the finding and results. The fourth and final sections conclude the chapter with a brief discussion on research findings, its limitations, and the implications for future research. The outcomes of analysis presented in this chapter also provide opportunities for researchers/professionals to position their future service supply chain research and/or implementation strategies.

This paper aims to evaluate commercial bank branches' performance in dynamic and competitive conditions where decision-making units (DMUs) seek a greater proportion of shared resources as it happens in the real world. By introducing the concepts of cross-shared and serial-shared resources, the authors have emphasized the role of evaluation results of past periods on branches' total efficiency.

In this study, a new mixed-integer data envelopment analysis (MI-DEA) model has been proposed to evaluate the performance of a dynamic network in the presence of cross-shared and serial-shared resources.

The proposed model helps bank managers to find the source of inefficiencies and establish a connection between the results of the periodic performance of the DMUs and the distribution of serial and cross-shared resources. The results show that the weighting coefficients of the periods do not significantly affect the overall efficiency of commercial bank branches, unlike desirable and undesirable intermediates.

This paper presents the following factors: (1) A new mixed-integer network data envelopment analysis model is developed under dynamic competitive conditions. (2) For the first time in DEA models, the concept of cross-shared resources is proposed to consider shared resources between DMUs. (3) All controllable, uncontrollable, desirable and undesirable outputs in the model are considered with the possibility to transfer to the next periods. (4) A case study is given for the performance evaluation of 38 branches of an Iranian commercial bank from 2016 to 2020.

The importance of health care is growing worldwide, and the health sector receives a good proportion of GDP. As health care costs are increasing, it is important to assess the performance of health care facilities across countries. Therefore, this paper aims to examine the effectiveness of data envelopment analysis, which is one of the most important techniques currently available to model and measure the efficiency of national health care systems across the world.

In this paper, the effectiveness of the operation of 180 countries is evaluated using data envelopment analysis (DEA). The countries selected are the members of the World Health Organization. Efficiency measures are calculated with respect to two groups of indicators, namely health status and health service coverage. In the health status group, four outputs representing mortality rates and one input representing the total expenditure on health is used in the analysis. In the health service coverage group, two outputs representing immunisation coverage and one input representing the total expenditure on health are used in the analysis.

Using data for the year 2008 from World Health Statistics (WHO), 45 countries are found to be efficient.

The value of the paper lies in the fact that it is one of the few studies to examine the robustness of data envelopment analysis to evaluate the performance of health care systems across countries.

Proper performance measurement is an important issue in library operational management. A data envelopment analysis (DEA) model is applied to evaluate the relative operational efficiency of 25 U.S. private research-university library members of the Association of Research Libraries (ARL). Operations of each library decision-making unit are considered as a production process using four resource input and four service output variables. The model results are analyzed and compared with the efficient group and a peer group by using a t-test. The model provides decision-makers with more accurate information to implement better library services with appropriate resource allocation.

Demands for accountability in education are not a new phenomenon, however, they have increased significantly in the recent past and have encompassed not only educational outcomes but also efficiency. In this study, ratio measures, similar to those recommended by the GASB, were compared to measures of relative efficiency determined through the use of data envelopment analysis (DEA). The consistency of the two approaches in distinguishing between relatively efficient and inefficient school districts was examined. It was found that compared to the DEA approach, the ratio measures, may be unable to provide reliable information for educational decision making.

This chapter provides a survey of alternative methodologies for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The survey shows the apparent shift from index procedures and traditional OLS estimation of production and cost functions to stochastic frontier methods and Data Envelopment Analysis (DEA) methods over the past three decades. Most of the airline productivity and efficiency studies over the last decade adopt some variant of DEA methods. Researchers in the 1980s and 1990s were mostly interested in the effects of deregulation and liberalization on airline productivity and efficiency as well as the effects of ownership and governance structure. Since the 2000s, however, studies tend to focus on how business models and management strategies affect the performance of airlines. Environmental efficiency now becomes an important area of airline productivity and efficiency studies, focusing on CO₂ emission as a negative or undesirable output. Despite the fact that quality of service is an important aspect of airline business, limited attempts have been made to incorporate quality of service in productivity and efficiency analysis.