Data Envelopment Analysis (DEA) applications frequently involve nonsubstitutable inputs and nonsubstitutable outputs (that is, fixed proportion technologies). However, DEA theory requires substitutability. In this paper, we illustrate the consequences of nonsubstitutability on DEA efficiency...

We describe a statistical method for estimating DEA score confidence intervals, and illustrate it with panel data of large US transit agencies from the years 2002-2006. The method applies statistical panel data analysis (PDA), which provides proven and powerful methodologies for diagnostic...

In Data Envelopment Analyses (DEA) of fossil-fuel electricity generating plants, the most common input measures are installed generator capacity (as a proxy for capital), number of employees (as a proxy for labor), and BTUs of fuel (as a proxy for energy). However, these three inputs cannot be...

This paper examines transport modes that have employed Data Envelopment Analysis (DEA). It ascertains whether key DEA specifications necessary for estimating valid efficiency scores are present, the impact on the scores when they are not, and methods for correcting the errors. One critical...

This paper provides transit policy makers and managements with a protocol for analyzing the efficiency of an urban area's non-rail transit when multiple types of service are operated. Procedures are described for estimating (a) the individual technical efficiency of each non-rail transit type,...

The aim of this study is to investigate how moral hazard arises during financing R&D and technological innovation activities of firms through their corporate governance attributes and firm-specific characteristics. We study 106 firms that received a specially designed loan by a Turkish...

Fossil-fuel based electricity generation produces the largest proportion of human-related carbon pollution in the United States. Hence, fuel choices by steam plants are key determinants of the industry's impact on national and global greenhouse gas emissions, and key foci for climate change...