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This chapter develops a productivity analysis of the US pharmaceutical industry via Data Envelopment Analysis (DEA). This study concerns itself with 16 US pharmaceutical companies. The output variables are profit margin, operating margin, return on assets, and return on equity. The input variables are corporate workers and market capital. Since negative data appear in DEA, a directional distance approach was applied.

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.

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this chapter, we examine how efficiently banks manage their credit risk via a powerful tool used widely in the decision/management science area called data envelopment analysis (DEA). Among various existing versions, our DEA is a two-stage, dynamic model that captures how each bank performs relative to its peer banks in terms of value creation and credit risk control. Using data from the largest 22 banks in the United States over the period of 1996 till 2013, we have identified leading banks such as First Bank systems and Bank of New York Mellon before and after mergers and acquisitions, respectively. With the goal of preventing financial crises such as the one that occurred in 2008, a conceptual model of credit risk reduction and management (CRR&M) is proposed in the final section of this study. Discussions on strategy formulations at both the individual bank level and the national level are provided. With the help of our two-stage DEA-based decision support systems and CRR&M-driven strategies, policy/decision-makers in a banking sector can identify improvement opportunities regarding value creation and risk mitigation. The effective tool and procedures presented in this work will help banks worldwide manage the unknown and become more resilient to potential credit crises in the 21st century.

Purpose: The present study investigates how the performance of Greek bank branching varies when the external environment causes dramatic changes that are reflected in recession and capital control effects.

Design/Methodology: A unique dataset of accounting Profit and Loss statements of retail branches of a systemic Greek commercial bank, closely supervised by the European Central Bank (ECB), is utilized. A profit bootstrap Data Envelopment Analysis (DEA) model is selected to measure the bank branch efficiency. The derived efficiency estimates are analyzed through a second-stage panel data regression analysis against a set of efficiency drivers related to branch profitability, diversification of income, branch size, and branch activity.

Findings: The results indicate that recession negatively affects branch efficiency in the short and long run. The occurrence of recession significantly intensifies the efficiency premium of branch profitability, reduces the efficiency premium of diversification of income (i.e., a negative efficiency effect is recorded during the early recession period), while mitigating the generally negative efficiency effect of branch size. The analysis of efficiency effects from the deep recession period that encompasses capital controls reveals the importance of diversification of income for the improvement of profit efficiency at bank branch level.

Originality/Value: This is the first branch banking study that explores branch efficiency alteration and the dynamic of branch efficiency drivers when the economy suddenly enters recession and afterwards when conditions are becoming extremely difficult and consequently capital controls are imposed on the economy.

This chapter investigates the financial performance and technical efficiency of the 26 listed firms in the services sector of the Philippine Stock Exchange over the period 1998–2007, using the DuPont system and the super-efficiency data envelopment analysis (SE-DEA). Empirical findings revealed a negative return on equity for the sector and the presence of outliers in the sample. We also verified a robust significant association between the financial and technical performances of the sector.

The chapter offers new significant contributions to knowledge in terms of the multidimensional performance evaluation and the efficiency of the stock market, especially in developing economies, which has not been a well-researched area. Managerial implications are also identified for the improvement of the firms’ management and the usefulness of the SE-DEA model in performance management.

This chapter analyses the efficiency of African airlines using a two-stage network DEA (Data Envelopment Analysis) model. Network DEA models usually take into account the production process with intermediate inputs derived from the first stage and a second stage that departs from it. This fundamental feature enables one to view the airline production process as a carry-over activity. The analysis covers the 2010–2013 period. The relative efficiency ranks are presented and policy implications are derived.

This chapter presents a data envelopment analysis (DEA) based relative financial strength (RFS) indicator using accounting data that is predictive of stock market performance of public firms. Such an indicator is indispensable in the fundamental analysis of firms for stock portfolio selections. This methodology requires optimally configuring inputs and outputs for the DEA model such that the strength indicator is maximally correlated with observed stock returns. This optimized RFS indicator providing the maximum predictive strength of stock returns is determined by factors such as asset utilization, leverage, profitability, and growth rates, in addition to the well-known factor, book-to-market ratio. Computational evidence is provided using more than 800 firms covering all major sectors of the U.S. stock market. Using quarterly financial data, we employ the RFS indicator to devise portfolios that yield superior financial performance relative to using portfolios of sector-based funds.

The study estimates total factor productivity growth (TFPG) and its components of the 4-digit manufacturing industries of chemical and chemical products in India from 1998–1999 to 2017–2018, pre-economic crises period (from 1998–1999 to 2007–2008) and post-economic crises period (from 2008–2009 to 2017–2018) using frontier approaches, that is, data envelope analysis DEA and stochastic frontier approach (SFA). The components of TFPG are technological progress (TP), technical efficiency change (TEC) and economic scale change (SC). It is found that the growth rates of total factor productivity (TFP) in most of the 4-digit industries of chemical and chemical products in India increased during the post-economic crises period (from 2008–2009 to 2017–2018) and the increase in TFPG of them during that period is mainly accounted for by the increase in TP of the same during that period. The TEC of almost all the industries remains the same, however, declined during the post-economic crises (from 2008–2009 to 2017–2018) and SC of them remains very low or even negative during the aforementioned study periods.

The economic crisis of 2007–2009 had a major negative impact on financial institutions in general. Health and life insurance industry continues to face growth challenges even six years after the economic crisis. Due to the challenges faced by health and life insurance industry, several companies in this industry have merged and some decided to get out of this business altogether. This study benchmarks 10 life and health insurance companies on the basis of return on equity, investment yield, and loss ratio for the year 2009 and 2014.

This chapter examines the influence of outsourcing on airlines’ performance from countries of the Asia Pacific region. Performance in the context of this study is drawn from productivity growth and technical efficiency scores that are calculated using the standard data envelopment analysis (DEA) approach. We utilize data from airlines over the period 2003–2011 and estimate the impact of outsourcing on productivity and technical efficiency using generalized method of moments (GMM) estimators. The findings from DEA reveal an improvement in the technical efficiency score of airlines from Asia Pacific. Nonetheless, productivity estimates indicate fluctuations in the productivity growth trend of airlines, attributable to global economic recession in 2007/2008. GMM estimation results, however, suggest negative impacts of outsourcing on technical efficiency and productivity of the airlines from Asia Pacific countries. We offer several explanations for these outsourcing findings. Heavy outsourcing of airlines activities particularly maintenance of aircraft may negatively affect aircraft utilization and ultimately erode the service level of airlines. The erosion of the service level of airlines would affect the demand for air travel in a downward manner, thereby lowering the technical efficiency and productivity of airlines. Also, relatively low labor costs enjoyed by airlines in the Asia Pacific region would suggest that having many airline activities in-house would save operating expenses attributable to labor costs.