In search of contextual variables in a stochastic DEA framework: effect of regulation on efficiency of Indian cement industry

The paper assesses the difference in the nature of relationship between efficiency and its determinants of Indian cement producing firms in the presence and absence of environmental regulation. It provides an intuitive construct to identify the determinants of efficiency, which is followed by an empirical verification using a two-stage stochastic data envelopment analysis. Important quantitative determinants of efficiency include factor intensities of outputs, levels of pollution abatements, gross value added, whereas size, age, ownership type, development indicators of the place of location of a firm are among the qualitative determinants. An initial phase and a matured phase of regulation are considered in the paper. The main results suggest that capital intensity of output plays a positive role in increasing efficiency under regulation in the initial phase, material intensity in both phases and labour intensity, a negative role, in the subsequent phase. Higher levels of pollution abatements cause higher efficiency under regulation, while in the initial phase private firms report higher efficiencies under regulation; it is just the reverse in the subsequent phase. Size, age and development indicator of the state in which a firm is located can play a positive role to achieve higher efficiencies in the matured phase of regulation.     

Industry structural inefficiency and potential gains from mergers and break-ups: A comprehensive approach

An efficiency indicator of industry configuration (allowing for entry/exit of firms) is presented which accounts for four sources components: (1) size inefficiencies arising from firms which can be conveniently split into smaller units; (2) efficiency gains realized through merger of firms; (3) re-allocation of inputs and outputs among firms; (4) technical inefficiencies. The indicator and its components are computed using linear and mixed-integer programming (data envelopment analysis models). A method to monitor the evolution of these components in time is introduced. Data on hospitals in Australia show that technical inefficiency of hospitals accounts for less than 15% of total industry inefficiency, with 40% attributable to size inefficiencies and the rest to potential mergers and re-allocation effects.     

Measuring inefficiency for specific inputs using data envelopment analysis: evidence from construction industry in Spain and Portugal

This article contributes to the efficiency literature by defining, in the context of the data envelopment analysis framework, the directional distance function approach for measuring both technical and scale inefficiencies with regard to the use of individual inputs. The input-specific technical and scale inefficiencies are then aggregated in order to calculate the overall inefficiency measures. Empirical application focuses on a large dataset of Spanish and Portuguese construction companies between 2002 and 2010 and accounts for three inputs: materials, labor and fixed assets. The results show, first, that for both Spanish and Portuguese construction companies, fixed assets are the most technically inefficient input. Second, the most inefficient scale concerns the utilization of material input in both samples; the reason for this inefficiency is that firms tend to operate in the increasing returns to scale portion of technology set. Third, in both samples, large firms have the lowest input-specific technical inefficiencies, but the highest input-specific scale inefficiencies, compared to their small and medium-sized counterparts, and tend to suffer from decreasing returns to scale. Finally, in both samples, input-specific technical inefficiency under constant returns to scale increased during the period of the recent financial crisis, mainly due to the augmentation in scale inefficiency.

     

Measurement and sources of overall and input inefficiencies: Evidences and implications in hospital services

Traditional data envelopment analysis (DEA) focuses exclusively on measuring the overall efficiency of a decision making unit (DMU). Yet, variables that have explanatory power for the overall operational inefficiency of a DMU may not necessarily be the same as those that affect its individual input inefficiencies. On many occasions, variables that explain the overall inefficiency of a DMU can be inconsistent or incongruent with those that cause its individual input inefficiencies. Therefore, we conjecture that an overall inefficiency score alone may have limited value for decision making since such a process requires fine-tuning and adjustments of specific input factors of the DMU in order to maximize its overall efficiency. In this paper, the utilization and financial data of a set of hospitals in California is used to empirically test the above conjecture.Our study has several important contributions and practical implications. First, we fine-tune previous efficiency measures on hospitals by refining input and output measures. Second, with variables on organization, management, demographics, and market competition, we identify specific factors associated with a hospital's overall operational inefficiency. More importantly, by decomposing the overall DEA operational inefficiency score into different individual input inefficiencies (including slacks), we further identify specific variables that cause individual input inefficiency. Third, significant differences are observed among factors of the overall inefficiency and individual input inefficiencies. These findings have important implications for identifying congruent factors for performance standard setting and evaluation; it also provides invaluable information for guiding effective resource allocation and better decision making for improving hospital operational efficiency.     

Efficient firm groups: Allocative efficiency in cooperative games

The concept of efficiency in groups postulates that a coalition of firms has to record a smaller distance toward the aggregate technology frontier compared with the sum of individual distances. Efficiency analysis (either allocative or technical) is defined with respect to cooperative firm game in order to provide operational distance functions, the so-called pseudo-distance functions. These pseudo-distances belong to the core interior of the allocative firm game, in other terms, any given firm coalition may always improve its allocative efficiency. We prove that such a result is impossible for technical efficiency, i.e., the technical efficiency cannot increase for all possible coalitions.     

Investigating technical and ecological efficiencies in the electricity generation industry: are there win-win opportunities?

Using data from the EPA's EGRID and Clean Air Markets databases, we investigate the energy (technical) and emissions (ecological) efficiencies of 437 of the largest US electricity generators. We focus on fossil-fuel-based electricity generating plants because of their significant impact on industry environmental performance, especially with respect to air media emissions. Data envelopment analysis is used to determine the relative technical and environmental performance of these plants and whether win-win opportunities and end-of-pipe versus in-process (reactive versus proactive) practices relate to these efficiencies. The results show that win-win opportunities in terms of simultaneous technical (operational) efficiency and ecological efficiency do not appear to exist.     

Effect of regulation on efficiency: evidence from Indian cement industry

The main objective of the paper is to analyze the impact of environmental regulation on technical efficiencies of Indian cement producing firms. It derives the technical efficiency (TE) scores of firms in the presence and absence of regulation and brings out the differences in their magnitudes in two scenarios: one in which the firms take initiatives to comply with the set standards by investing additional resources for pollution abatement and the other in which the firms do not take the necessary initiatives. The paper uses establishment level data from Annual Survey of Industries on cement for two years, the most recent data published for 2003–2004 and a previous year for 1999–2000 when the environmental regulations in India were in the initial phases of implementation. A non-parametric deterministic method of data envelopment analysis (DEA) is used to derive the TE scores of firms. The traditional DEA framework is modified by introducing weak disposability of bad outputs to characterize ‘effective environmental regulation’, which ensures that reducing pollution is not costless. For both years it has been found that the TE scores of firms under ‘effective regulation’ scenario are either higher than or equal to those derived under ‘ineffective regulation’ scenario resulting in a higher average TE at the industry level in the ‘effective regulation’ scenario.     

Measurement of a linkage among environmental,operational, and financial performance in Japanese manufacturing firms: A use of Data Envelopment Analysis with strong complementary slackness condition

This study investigates a linkage among environmental, operational and financial performance in Japanese manufacturing industry. All manufacturing firms examined in this study are listed in Tokyo stock exchange market. We use DEA (Data Envelopment Analysis) as an evaluation methodology. This study finds that large firms have managerial capabilities to improve their operational and environmental performance. The improvement leads to the enhancement of their financial performance. However, we cannot find such a business linkage in small and medium-sized firms. They improve their operational performance and then direct themselves toward the improvement of their environmental performance. Their environmental performance is, not the first priority, the second priority for the small and medium-sized firms even though Japanese government is currently making a policy pressure on all manufacturing firms to pay attention to various environmental issues related to the global warming and climate change. The environmental protection policy is effective on only large Japanese manufacturing firms that have technological and financial capabilities for environmental protection.     

Returns to scale pattern and efficient firm size in the public accounting industry: an empirical investigation

This paper employs Data Envelopment Analysis to investigate returns to scale patterns and efficient firm size in the public accounting industry in the USA post-Sarbanes–Oxley Act. Using contemporary survey data from Accounting Today's top-100 accounting firms for the years 2003 and 2004, our results indicate that the very largest accounting (first tier) firms display constant returns to scale, whereas approximately half of the smaller (second tier) firms exhibit increasing returns to scale. These findings suggest that while very large firms are optimally scaled, there still are economic efficiencies to be gained through expanding the size of nearly half of the second-tier accounting firms. Results for the remaining second-tier firms show either constant or decreasing returns to scale, indicating that they are either already optimally sized or that they should consider contraction. The results for the second-tier firms remain qualitatively unchanged when the first-tier firms are excluded from the estimation.     

Alternative measures of environmental technology structure in DEA: An application

The nonparametric data envelopment analysis (DEA) literature on environmental efficiency (EE) considers handling undesirable outputs in two alternative ways: either in their original forms with the assumption that these are weakly disposable or in various translated forms with the assumption that these are strongly disposable. Choosing a particular approach implies adoption of a particular, distinct treatment of undesirable outputs, and hence yields a distinct set of EE estimates. To explore the effects of the interplay between choice of EE measure and specific treatment of undesirable outputs, this paper attempts to generate all possible output-oriented EE measures based on these two alternative approaches. Furthermore, guided by the argument that slacks are important in identifying properly the efficiency behavior of firms, it proposes two new alternative, slacks-based formulations of EE: one based on the range directional model, and the other on the generalized proportional distance function model. Using a confected data set of ten firms and a real-life data set of 22 OECD countries, our empirical analysis reveals that: first, EE scores are influenced not only by the choice of disposability assumption for undesirable outputs but also by the way these are treated in various translated forms; second, the choice of any particular treatment of undesirable outputs plays no role in influencing the rankings of firms; and third, our two new alternative EE formulations are, at the least, viable alternatives to existing EE measures in ranking firms according to their eco-efficiency behavior.