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This chapter investigates whether signing more hospital contracts with Health Maintenance Organizations (HMOs) and Preferred Provider Organizations (PPOs), hospital affiliation in a system, having more system hospital members located in the same area, and increased competition from area hospitals, contributes to improvements in the cost efficiency of U.S. Midwestern hospitals. Hospitals may offer HMOs and PPOs discounts on contracts to provide health care services to firm employees enrolled in HMOs and PPOs (discounts would lead to smaller price mark-ups over costs for hospital services). Enacting policies to enhance cost efficiency may help hospitals maintain a specified level of profits.

The paper aims to enrich previous findings for an emerging banking industry such as Vietnam, reporting the difference between the parametric and nonparametric methods when measuring cost efficiency. The purpose of the study is to assess the consistency in issuing policies to improve the cost efficiency of Vietnamese commercial banks.

The cost efficiency of banks is assessed through the data envelopment analysis (DEA) and the stochastic frontier analysis (SFA). Next, five tests are conducted in succession to analyze the differences in cost efficiency measured by these two methods, including the distribution, the rankings, the identification of the best and worst banks, the time consistency and the determinants of efficiency frontier. The data are collected from the annual financial statements of Vietnamese banks during 2005–2017.

The results show that the cost efficiency obtained under the SFA models is more consistent than under the DEA models. However, the DEA-based efficiency scores are more similar in ranking order and stability over time. The inconsistency in efficiency characteristics under two different methods reminds policy makers and bank administrators to compare and select the appropriate efficiency frontier measure for each stage and specific economic conditions.

This paper shows the need to control for heterogeneity over banking groups and time as well as for random noise and outliers when measuring the cost efficiency.

The purpose of this paper is to assess product and service arrays of community banks within competitive markets that are impacted by varying sized financial institutions. A cost efficiency model is used to understand the relationship of product offerings and business cycle response upon bank performance.

A cost efficiency model is used to understand the relationship of product offerings and business cycle response upon bank performance. Markets comprised of alternate size and type of financial institutions are compared.

Greater values of X_EFF _i when institutions compete are observed in this analysis. Cost efficiency is lowest when community banks are the only institution in the market, and second lowest when credit unions are the only competing institutions. Call report data are analyzed from 1994 to 2013. The number of big banks increases community bank efficiency and efficiency of large banks. Also, the number of community banks does affect big bank cost efficiency. The magnitude of the effect pertaining to the number of community banks upon big bank efficiency is much smaller than that of the number of big banks on community bank efficiency.

This study considers cost efficiency and profitability as measures of institution on the performance of a competing institutional type. The modeling approach uses cost efficiency as a method of observing the performance of financial institutions and an explanation of how firms persist, grow, and respond to changes in technology or regulation. The effects of the presence of each type of financial institution on the performance of another type are compared. Situations in which any number of one or more institutional types is present in a market are considered for analysis purposes.

The purpose of this paper is to assess the efficiency of rice millers and determine factors influencing cost efficiency in Southwest Nigeria using the cost route approach.

The paper analyses cost efficiency of rice millers using primary data collected from 62 respondents through a structured questionnaire. A multi-stage sampling procedure was employed for this purpose. The profile of rice millers and mills were derived using the descriptive analysis. Cost efficiency of the millers was obtained using the quadratic cost function analysis, and Tobit regression was used to determine factors that influence cost efficiency.

The results showed that cost efficiency indexes range from 1 to 57 percent averaging at 20.2 percent. Large rice mills were found to be most efficient with the mean cost efficiency of 25 percent. Paddy, transport and energy costs contributed positively and significantly (p=0.05 and p=0.01) to cost efficiency. Milling capacity and machine age increase cost efficiency while the distance to purchase paddy and quantity of diesel used reduces cost efficiency.

The paper shows that there is enough potential for rice millers to improve their cost efficiency based on the available technology. This has a direct implication on the economy through the increased domestic production and processing of rice to meet the increasing demand for locally produced rice.

The paper attempts to bridge the gap in the literature of cost efficiency among rice millers in Nigeria, and specifically in the application of the normalized quadratic cost function in estimating cost efficiency in the rice milling sector in Nigeria.

This paper aims to develop and utilize a conceptual framework to examine the impact of liquidity and solvency on cost efficiency for a sample of Kansas farms.

A standard cost-efficiency model is modified to incorporate liquidity and solvency ratios. Tobit regressions are used to determine the impact of farm characteristics on improvements in efficiency.

Results confirm that liquidity and solvency measures have a significant impact on improving cost efficiency. Farms with larger expenditures on purchased inputs relative to capital were less likely to improve efficiency when liquidity and solvency were considered.

To the authors' knowledge, the paper is the first to add liquidity and solvency ratios to the cost-efficiency model developed by Färe et al. for the analysis of farms.

The purpose of this paper is to evaluate the importance of financial liquidity and solvency on US commercial and domestic banks’ cost efficiency while accounting for internal and external factors.

The Stochastic Frontier Analysis and Data Envelopment Analysis estimators are used to estimate the cost efficiency of 11,044  US commercial and domestic banks from 2005 to 2017. Using Tobit regression model, the importance of financial liquidity and solvency on cost efficiency is examined.

The results provide evidence that the financial liquidity and solvency negatively impact the cost efficiency of US commercial and domestic banks. Overall, US commercial and domestic banks were inefficient during the financial crisis in comparison to the tranquil period. The importance of financial solvency on the cost efficiency was not statistically significant, while the financial liquidity negatively collapsed because of contagion. Finally, the results provide evidence that the amount of total assets matters in the improvement of the cost efficiency.

This paper estimates and identifies the 2007-2009 financial crisis with liquidity, solvency or both financial factors.

The consistency of stochastic frontier analysis (SFA) and data envelopment analysis (DEA) cost efficiency measures using a sample of 650 commercial and domestic banks in the United States is investigated based on cluster analysis while accounting for the yearly variation in banks.

Due to the importance of efficiency measures for policy and managerial decision-making, the cost efficiency measures of SFA and DEA estimators are examined according to four criteria: levels, rankings, stability over time and stability over clustering groups. In this paper, we present two clustering methods, Gap Statistic and Dindex, that involve SFA and DEA cost efficiency measures. The clustering approach creates homogeneous groups of banks offering a similar mix of efficiency levels. Hence, each evaluated bank knows the cluster to which it belongs. Furthermore, this paper provides nonparametric statistical tests of SFA and DEA cost efficiency measures estimated with and without a clustering approach.

The results suggest that the clustering approach plays a considerable role in the rankings of US banks. Furthermore, the average SFA and DEA cost efficiency measures over time of the homogeneous US banks are substantially higher than those of the heterogeneous US banks.

This research is the first to provide comparative efficiency measures needed for desirable policy conclusions of heterogeneous and homogeneous US banks.

The study examines the relationship between the consequential social cost of market power (i.e. welfare performance of banks) and cost efficiency using data covering the period 2009 to 2017 from the Ghanaian banking industry.

The study adopts the ordinary least squares (OLS), fixed effect (FE) panel regression and the quantile regression (QR) approaches to control for heterogeneity and provide increased room for policy relevance. The two-stage least squares instrumental variables (2SLS-IV) regression is used to ensure the robustness of the findings against the problem of possible reverse causality.

The results indicate a positive relationship between banks' welfare performance and cost efficiency, which suggests that greater cost efficiency hedges welfare losses. In other words, welfare gains and cost-efficient banks are not mutually exclusive. Also, the results show evidence that the sensitivity of welfare gain to cost efficiency depends on the knowledge of local market dynamics. Further, the findings from the QR estimation suggest that, but for welfare loss at low (Q.25) to the median (Q.50) quantiles, cost efficiency is a necessary and sufficient condition to hedge the welfare losses.

The results demonstrate that financial consumer protection cannot be achieved without cost efficiency in the presence of both foreign banks and high market knowledge. Therefore, our paper suggests an integrated cost efficiency policy approach that has the complementary effect of a robust information sharing mechanism and incentives to hedge against welfare losses in the banking sector of emerging economies. Moreover, if welfare gain is synonymous with cost-efficient banks, then the presence of a quiet life is typical of financial consumer protection.

This study provides insight into the importance of cost efficiency to the public policy of financial consumer protection in an era of foreign banks' dominance. From the review of prior literature, this paper is the first to apply the QR estimation technique to examine the effect of cost efficiency throughout the conditional distribution of bank welfare performance rather than just the conditional mean effect of cost efficiency.

The processes of liberalisation, globalisation and integration have brought new dynamics into banking markets. In an increasingly competitive environment, banks have been forced to refocus their strategies and examine their performance, because their survival in the 21st century will depend on efficiency (Denizer & Tarimcilar, 2001). In recent years, therefore, bank efficiency has received wide attention, and researchers have developed an extensive array of sophisticated methods and tools to estimate efficiency.

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.