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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 paper analyses the cost efficiency of Italian football clubs using a stochastic frontier model. The frontier estimation confirmed that the model fits the data well with all coefficients correctly signed and in line with the theoretical requirements. Marketing and Sponsorship is taken into account as an explanatory variable and the factors which contributed to these findings, as well as other policy implications, are provided.

The aim of the paper is to estimate the cost efficiency of supermarket chains in the Spanish retailing industry.

The methodology applied is based on a random stochastic frontier model that enables separation of the covariates in the cost function into homogeneous and heterogeneous variables. The methodology is applied to panel data on a sample of 78 supermarket chains between 2001 and 2004.

The results reveal high levels of cost inefficiency in the Spanish retail sector. The results also reveal that the random frontier models better describe Spanish retailers than homogeneous frontier models.

The generalisation of the conclusions of the study to the whole sector should be made with caution, given the fact that only one of the players in the distribution channel has been analysed.

Managers should be aware of the importance that cost efficiency has for their own firms. Further, a common government retailing policy will be unable to reach all retailing companies, since heterogeneity exists.

For the first time, the cost efficiency of the intermediaries in the Spanish retailing sector is studied.

The purpose of this paper is to consider a new application of stochastic frontier analysis, in which the method is applied to demand data for a food product category, in an attempt to benchmark category consumption and segment food consumers.

In a unified, two‐stage approach, a stochastic frontier model is first estimated and subsequently deviations from the demand frontier are regressed on customer characteristics. The method is illustrated in scanner panel data.

A frontier demand function estimated in scanner data of a frequently‐bought food category has significant and consistent parameters. Specific descriptor variables can explain excessive category demand and profile customers with considerable sales potential.

More work is needed to generalise the usefulness of the proposed model in different food categories. Future research may employ alternative functional specifications and explanatory variables.

The empirical identification of salient characteristics improves consumer understanding and can assist in the design of data‐driven marketing action. Applied researchers can use marketing and demographic variables that are found in standard consumer panels to estimate frontier models.

The paper introduces stochastic frontier analysis as a means to determine consumer differences in food demand. This is an important area for retailers, producers and researchers.

Given some similarities in the banking industry and economic condition across Vietnam, China and India, the purpose of this paper is to estimate and compare the cost and revenue efficiency of banks across these three countries over the period 1995–2011.

This study employs the meta-frontier of Battese et al. (2004) and O’Donnell et al. (2008) which envelops the three country-frontiers to measure the cost and revenue efficiency of banks in these three countries.

This study finds that Chinese banks adopt the most advanced cost-reducing and revenue-increasing technology when providing banking products to their customers, followed by Indian banks. Indian banks are as cost-efficient as Chinese banks, but more cost-efficient than Vietnamese banks. Indian banks are as revenue-efficient as Vietnamese banks, but less revenue-efficient than Chinese banks. Over the analysis period, banks in the three countries have employed the more advanced technology in reducing costs, and they have become more cost-efficient. Nonetheless, for revenue side, the improvement in revenue efficiency and adopted technology are observed only in Chinese banks. The main source of meta-cost and meta-revenue inefficiency of these banking systems stems from undertaking inferior technology rather than managerial ability. Results from comparison across bank types show that state-owned banks (SOBs) are more cost and revenue-efficient than privately owned banks, with Indian and Chinese SOBs being the most cost- and revenue-efficient, respectively.

To improve meta-cost efficiency, Chinese and Indian banks would constitute a relevant benchmark for Vietnamese banks, while to improve meta-revenue efficiency, Chinese banks would be considered as a relevant benchmark for Vietnamese and Indian banks.

This is the first study which utilizes meta-frontier to compare cost and revenue efficiency and technology across banks in Vietnam, China and India.

A firm is technically efficient when it produces the maximum level of output for a given level of input on the assumption that technology is fixed. Although the above definition of technical efficiency has been around for decades, economists have, for the most part, been estimating average production functions (i.e. production functions that assume that all firms are technically efficient except for random noise), and then proceeding to make inferences regarding the potential of firms from this average production function.

Examines 88 academic member libraries of the Association of Research Libraries (ARL) to determine their relative cost efficiency, using stochastic frontier regression and data envelopment analysis (DEA) methods. Both methods give average ARL cost efficiencies of around 80 percent. This places academic ARL libraries in the same range of efficiency as other institutions, including for‐profit and non‐profit institutions. Many libraries are above 80 percent efficiency. For those below, some speculation is given for the lower efficiency. The lack of an output measure for the use of electronic sources may contribute to lower efficiency for a few libraries. Large staff size and a large number of serial subscriptions do predict lower efficiency, but this is not a necessary consequence. The DEA model allows us to determine increasing, constant, or declining returns to scale for research libraries. From this, it appears research libraries with expenditures between $10,000,000 and $20,000,000 are operating at the most efficient scale. Since the methods used are outside the repertoire of most LIS research, a conceptual explanation is provided.

This chapter examines the main methodological issues involved in the comprehension of the cost structure of the airport industry and suggests considerations for future airport cost analyses. Such understanding has become a crucial concern for policy makers, regional planners, and managers in order to deal with optimal market design (e.g., regulation and market configuration) and airport strategies (e.g., pricing, investments, and alliances). An in-depth analysis of the economics of cost functions is presented, together with a description of the relevant multi-output cost economies measures (average incremental costs, scale and scope economies, and cost complementarities). We also discuss the assumptions underlying estimates of total versus variable cost functions and the importance of estimating a sufficiently flexible functional form. Moreover, we provide a critical survey of the international empirical literature on the cost structure of the airport industry, which highlights how econometric estimates strongly depend on the sample choice and the empirical model considered. Indeed, while econometric studies on international samples based on long-run cost function estimates show that long-run scale economies are never exhausted, single country studies mostly estimate variable cost functions and find lower values for scale economies at median sample points that tend to decrease with size. We discuss why we believe that studies based on the estimation of short-run variable cost functions offer more reliable results, given the reasonable assumption of airport overcapitalization in the short run. We conclude our work by noting that underlying policy issues related to planning and regulation, as well as to the optimal market structure of the airport sector, need to take into account the role played by vertical relationships between airports and airlines.

Using a panel of 1,122 UK firms listed on the London Stock Exchange over the period of 1981-2009, corporate efficiencies are predicted in this paper as inverse proxies of agency cost and the agency cost hypotheses are tested. The paper aims to discuss this issue.

Stochastic frontier analysis is used to estimate corporate efficiency of firms, but from two different perspectives. The long-run and short-run corporate efficiencies are predicted focussing on modern approach of value maximization and traditional approach of profit maximization, respectively.

The estimation results reveal that, an average firm in the sample achieves 74.5 percent of its best performing peer's market value and 86.6 percent of its best performing peer's profit and both of them are highly significant in the analysis. The long-run market value efficiency supports the agency cost of outside equity and the short-run profit efficiency supports the agency cost of outside debt hypothesis. Also there is a positive rank correlation between these two efficiencies which confirms that an average firm in the UK suffers from inefficiency or agency conflicts to a certain extent, no matter whether the firm is driven by short-run or long-run growth perspectives.

The predicted broad measures of agency costs in the paper have wider implications in enhancing the understanding of the UK firms’ corporate performance especially when they operate under a relatively free and market based governance and financial system.

The work is distinguished by the large panel of UK firms and a long period of time that is considered. Emphasizing on the empirical implications of the distinctions between short-run and long-run efficiency is also novel.

The purpose of this paper is to analyze the relationship between farm size and agricultural production efficiency from the aspects of output and profit in order to find an optimal farm size that achieves both output and profit efficiency in agricultural production in China.

This study uses the 2012 China Family Panel Studies survey data and employs the stochastic frontier analysis (SFA) models to investigate empirically the relationship between farm size and agricultural production efficiency.

The study finds that there is an inverted-U curve relationship between farm size and output efficiency and a U-shaped curve relationship between farm size and profit efficiency in agricultural production in China. Based on the empirical results, the study estimates that the appropriate farm size is around 10–40 mu and the optimal farm size is around 20–40 mu both in terms of output efficiency and profit efficiency in Chinese agricultural production under the current agricultural technology and land management system.

The findings of this study suggest that appropriate land consolidation will bring more benefits to farmer households and agricultural production efficiency. There are some policy implications. First, governments should give long term and more stable land using rights to farmers through extending the period of land contract and verifying land using rights. Second, governments should encourage transfers of land using rights and promote land consolidation. But the implementation of this policy should consider regional differences and not be used for blindly pursuing increasing land size. Third, land consolidation should be accompanied with the development of specialized agricultural services.

The paper makes two major contributions to the literature. First, the authors use the SFA model to investigate the relationship between land size and agricultural production efficiency. Second, the authors establish two SFA models – the stochastic frontier output analysis model and the stochastic frontier profit analysis model – to estimate the optimal land size to achieve both output and profit efficiency of agricultural production in China.