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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.

This chapter provides an empirical assessment of the effects of infrastructure provision on structural change and aggregate productivity using industrylevel data for a set of developed and developing countries over 1995–2010. A distinctive feature of the empirical strategy followed is that it allows the measurement of the resource reallocation directly attributable to infrastructure provision. To achieve this, a two-level top-down decomposition of aggregate productivity that combines and extends several strands of the literature is proposed. The empirical application reveals significant production losses attributable to misallocation of inputs across firms, especially among African countries. Also, the results show that infrastructure provision has stimulated aggregate total factor productivity growth through both within and between industry productivity gains.

This study aims to present the cost and revenue efficiency evaluation models in data envelopment analysis in the presence of fuzzy inputs, outputs and their prices that the prices are also fuzzy. This study applies the proposed approach in the energy sector of the oil industry.

This study proposes a value-based technology according to fuzzy input-cost and revenue-output data, and based on this technology, the authors propose an approach to calculate fuzzy cost and revenue efficiency based on a directional distance function approach. These papers incorporated a decision-maker’s (DM) a priori knowledge into the fuzzy cost (revenue) efficiency analysis.

This study shows that the proposed approach obtains the components of fuzzy numbers corresponding to fuzzy cost efficiency scores in the interval [0, 1] corresponding to each of the decision-making units (DMUs). The models presented in this paper satisfies the most important properties: translation invariance, translation invariance, handle with negative data. The proposed approach obtains the fuzzy efficient targets corresponding to each DMU.

In the proposed approach, by selecting the appropriate direction vector in the model, we can incorporate preference information of the DM in the process of evaluating fuzzy cost or revenue efficiency and this shows the efficiency of the method and the advantages of the proposed model in a fully fuzzy environment.

The purpose of this study is to estimate inputs (outputs) and flexible measures when outputs (inputs) are changed provided that the relative efficiency values remain without change.

A novel inverse data envelopment analysis (DEA) approach with flexible measures is proposed in this research to assess inputs (outputs) and flexible measures when outputs (inputs) are perturbed on condition that the relative efficiency scores remain unchanged. Furthermore, flexible inverse DEA approaches proposed in this study are used for a numerical example from the literature and an application of Iranian banking industry to clarify and validate them.

The findings show that including flexible measures into the investigation effects on the changes of performance measures estimated and leads to more reasonable achievements.

The traditional inverse DEA models usually investigate the changes of some determinate input-output factors for the changes of other given input-output indicators assuming that the efficiency values are preserved. However, there are situations that the changes of performance measures should be tackled while some measures, called flexible measures, can play either input or output roles. Accordingly, inverse DEA optimization models with flexible measures are rendered in this paper to address these issues.

To investigate the relationship between performance frontier and operations strategy. A two-level conceptual framework is proposed based on performance elements that act as output/input variables and delimit the scope of the frontier analysis.

The framework proposition is based on the fourth round of high-performance manufacturing survey data. A representative set of variables for assessing performance based on operations strategy constructs is defined through multivariate data analysis techniques. The main method used is the principal component analysis.

The proposed first-level conceptual framework formalizes the relationships between performance frontier analysis techniques and operations strategy, delimiting the scope and the structural definitions. The second-level conceptual framework defines the constructs of the input and output dimensions for frontier analysis studies.

The paper contribution is developed in the gap of market-led orientation to study operations strategy performance frontier since most related literature focuses on capabilities development with a main focus on the resource-based view (RBV) approach. A conceptual framework based on the competitive priorities is therefore proposed to represent the operations strategy in the view of the frontier techniques. The value lies in defining performance measures which are not a straightforward task as the growth of organization competitiveness and complexity require multiple performance measures. A deeper understanding of frontier estimation on the operations strategy context is also provided, contributing to positively influence firms to succeed in the current dynamic competitive environments.

Both the improvement of productivity and the effectiveness of performance measures have been topics of extreme interest to managers and researchers in recent years. Looks at the potential advantages and disadvantages of using the traditional productivity measure, output/input, as a measure of performance at the firm, work‐unit, individual, product, or product‐line level. Considers the ability of productivity measures to adjust for price changes and to detect factor substitutions. The distortion of productivity measures by fixed expenses and the inability of productivity measures to consider quality changes are among the disadvantage cited. Also, criticisms that have been levelled at traditional cost accounting measures are found to apply to productivity measures. Proposes three criteria that can aid in determining when productivity measures are appropriate as performance measures. Makes recommendations for ways of using productivity measures effectively also.

The purpose of this paper is to provide an input‐output analysis of electronic resources in academic libraries by verifying evaluation indicators and applying them to the digital library environment.

This study measures the performance of electronic resources in academic libraries in Korea. To measure the efficiency of the input‐output ratio, evaluation indicators were divided into inputs and outputs. Inputs refer to the e‐resource use environment as well as the acquisition of e‐resources such as web DB, e‐books, e‐journals, and so on. Outputs quantify the use of each resource.

First, the results of this study show that a large share of academic library budgets is spent on e‐resource purchases and e‐resource environment improvement for better use. Second, the measurement shows that web DB subscription, annual e‐resource development, and education for e‐resource exhibit higher efficiency, while e‐resource use, web DB and e‐journal download exhibited relatively high efficiency. Third, when the input‐output ratio is calculated in percentage terms, the efficiency of e‐resources of Korean academic libraries reaches 88.20 per cent.

First, to measure performance accurately, results/effectiveness must be included. However, this study focused on quantifiable input and output factors. It is recommended that future research include user satisfaction and learning effects. Second, this study was conducted in a particular country (Korea). So it is advisable to conduct research to compare the results of this study to results in other countries.

This study is the first research to consider the performance of electronic resources in depth. This paper contributes to improving the reliability of library evaluation.

The growth in importance of performance assessment in education over recent years has been linked with a concern to ensure that the service represents “value for money”. Increasing concern over funding of schools by government and the limitation on the resources available to the education sector has given rise to demands for greater efficiency and public accountability. These concerns reflect the need for comprehensive techniques to assess the degree to which school management practices and the education industry structure promote efficiency in education. An additional problem has been that, whilst there are many different desirable outcomes which are appropriate for education authorities to pursue, conventional models handle these one at a time.