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Purpose – The accounting literature has demonstrated increased concern over issues of sustainability. One of the most critical issues that corporations face at the moment is climate change. This especially concerns companies that are substantial consumers of materials and energy. Corporations have increasingly acknowledged that to address this issue the existing ways of managing business must be changed.

This study examines the challenges posed by measurement of energy efficiency performance in an energy-intensive industry. It covers the challenges encountered with respect to the energy efficiency indicator and its use as a management tool.

Methodology – The case study method was used to conduct the research, which took place in a single firm in an energy-intensive process industry.

Findings – The results indicate that the current energy efficiency indicator, specific energy consumption (SEC), does not meet the criteria for good performance measurement. In particular, the controllability of energy efficiency seems problematic. Another major challenge is target setting. Measurable targets are needed to identify and prioritise areas where consumption and emission can be reduced.

Practical implications – The study provides practical knowledge on what is happening in organisations that pursue sustainable development and in particular, environmental efficiency.

Originality/value – Although the conceptual challenges in energy efficiency measurement are well known in the technical literature, discussions dealing with its management have been few in number. This study is a cross-disciplinary work and combines technical energy efficiency literature and management accounting research on performance management.

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.

Universities are expected to operate with high efficiency, with ever-growing expectations from a rising number of stakeholders in society. From a theoretical perspective economic science does provide frameworks and methods in order to tackle this, with the cornerstone of defining efficiency as a simple relation of a quantity of inputs toward a quantity of outputs. For the practice of university management and policy this does not answer the crucial questions of which inputs and which outputs to measure, and how to ensure the quality aspect of such management approaches. Higher education research can contribute to answering these questions. This chapter outlines a sector-specific framework for efficiency analysis and management, including suggestions regarding how to implement efficiency-improving measures in university settings.

In this chapter, the concepts of technical efficiency, efficiency, effectiveness, and productivity are illustrated. It is discussed that when firms are not homogeneous, the situation is the same as when each factor has a different unit of measurement from one firm to another, and therefore, no meaningful discrimination can be expressed, unless a set of known weights are introduced to standardize data. A linear programming data envelopment analysis model is used when a set of known weights are given to calculate the technical efficiency and efficiency of a set of homogeneous DMUs with multiple input factors and output factors. A numerical example is also provided.

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.

This paper aims to develop and test a new way of modeling airline operations and apply it to measure and compare the efficiency of international airlines, with a special focus on deregulation effects. The paper elaborates on the choice of variables, following the early work of Schefczyk (1993) and Scheraga (2004). The value chain of the airlines determines the variables included in three different models. Using data envelopment analysis, the efficiency scores show that North American airlines are more efficient in producing services offered to customers. Few differences are found between regions in allocating service output to match demand. One plausible explanation for this difference is that airlines operate within competitive environments. In a highly competitive market, management decisions focus on productive actions and cost reduction. In a less competitive environment, there is a higher degree of adjustments of the services produced. Using the Malmquist productivity index, measurements reveal that there is a catch-up effect for the European and Asian/South American airlines service production during the studied time period, which was from 1990 to 2003.

Introduction: Performance evaluations are a critical tool in evaluating tourism development of countries where the tourism industry provides a significant share of the GDP. One of the measures used in performance evaluation of the financial decision-making units is economic efficiency. Aim: This study aims at measuring tourism-related technical efficiency performance of six European countries: Spain, Greece, Turkey, France, Italy, and Portugal. Method: Tourism revenue and visitor numbers are referenced as output variables. Within the model, the natural and sociocultural index and substructure index were formed. Data envelopment analysis was applied for these datasets. Results: Considering tourism revenues, Spain, Italy and Greece managed to use their natural and cultural resources efficiently. In contrast to these countries, inefficiency level scores were measured for Turkey, Portugal and France. In the model based upon the number of visitors, all other countries apart from Turkey and Portugal achieved the most efficient score. As for substructure index, the score of decreasing returns to scale for the countries of Italy and Spain in terms of tourist numbers is noteworthy. Conclusion: The implementation of efficient tourism policies and strategies hold great importance in terms of tourism efficiency. Implications: Even though Portugal and Turkey are rich in both natural and cultural assets, low scores seem to stem from failure to realize their potentials. Strategies should be developed to diversify tourist products. Originality of the Paper: This study differs from other studies in the literature with regard to the composition of the wide input components.

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.