Benchmarking Environmental Efficiency of Ports Using Data Mining and RDEA: The Case of a U.S. Container Ports

This study provides step-wise benchmarking practices of each port to enhance the environmental performance using a joint application of the data-mining technique referred to as Kohonen’s self-organizing map (KSOM) and recursive data envelopment analysis (RDEA) to address the limitation of the conventional data envelopment analysis. A sample of 20 container ports in the U.S.A. were selected, and data on input variables (number of quay crane, acres, berth and depth) and output variables (number of calls, throughput and deadweight tonnage, and CO2 emissions) are used for data analysis. Among the selected samples, eight container ports are found to be environmentally inefficient. However, there appears to be a high potential to become environmentally efficient ports. In conclusion, it can be inferred that the step-wise benchmarking process using two combined methodologies substantiates that a more applicable benchmarking target set of decision-making units is be projected, which consider the similarity of the physical and operational characteristics of homogenous ports for improving environmental efficiency

Police Organizational Performance In The State Of Florida:confirmatory Analysis Of The Relationship Of The Environment And Design Structure to Performance

To date, police organizations have not been rigorously analyzed by organizational scholars and most analysis of these organizations has been captured through a single construct. The purpose of this study is to develop confirmatory police organizational analysis by validating a multi-dimensional conceptual framework that explains the relationships among three constructs: environmental constraints, the design structures of police organizations, and organizational performance indicators. The modeling is deeply rooted in contingency theory, and the influence of isomorphism and institutional theory on the covariance structure model are investigated. One hundred and thirteen local police organizations from the State of Florida are included in this non-experimental, cross-sectional study to determine the direct effect of the environmental constraints on the performance of police organizations, the indirect effect of environmental constraints on the performance of police organizations via the organizational design structure of police organizations, and the direct affect of organizational design structure on performance of police organizations. For the first time, structural equation modeling and data envelopment analysis are used together to confirm the effects of the environment on police organization structure and performance. The results indicate that environmental social economic disparity indicators have a large positive effect on police resources and a medium effect on police efficiency. Propensity of crime indicators has a large negative effect on police resources, and population density has a small to medium negative effect on crime clearance. Structure has a much smaller effect on performance than the environment. The results of the efficiency analysis revealed unexpected findings. Three of the top five largest police organizations in the study scored maximum efficiency. The cause of this unexpected result is explained and confirmed in the covariance model. The study methodology and results enhances the understanding of the relationship among the constructs while subjecting environmental and police organizational data to two comprehensive analytical techniques. The policy implications and practical contributions of the study provide new knowledge and information to organizational management of police organizations. Furthermore, the study establishes a new approach to police organizational analysis and police services management research called Police Services Management Research (PSMR) that encompasses a variety of disciplines with a primary responsibility of theory building and the selection of theoretical framework

Infrastructure performance and reform in developing and transition economies: evidence from a survey of productivity measures

The authors review about 80 studies on electricity and gas, water and sanitation, and rail and ports (with a footnote on telecommunications) in developing countries. The main policy lesson is that there is a difference in the relevance of ownership for efficiency between utilities and transport in developing countries. In transport, private operators have tended to perform better than public operators. For utilities, ownership often does not matter as much as sometimes argued. Most cross-country studies find no statistically significant difference in efficiency scores between public and private providers. As for the country-specific studies, some do find differences in performance over time but these differences tend to matter much less than a large number of other variables. Across sectors, private operators functioning in a competitive environment or regulated under price caps or hybrid regulatory regimes tend to catch up best practice faster than public operators. There is a very strong case to push regulators in developing and transition economies toward a more systematic reliance on yardstick competition in a sector in which residual monopoly powers tend to be common.Enterprise Development&Reform,Labor Policies,Banks&Banking Reform,Environmental Economics&Policies,Economic Theory&Research,Environmental Economics&Policies,Economic Theory&Research,Banks&Banking Reform,Health Monitoring&Evaluation,Health Economics&Finance

Performance Measurement in the Australian Water Supply Industry

Various government-owned businesses provide water supply services to Australian residents. With the advent of recent competition and regulatory reforms in infrastructure industries in Australia, more and more of these businesses are now facing new types of incentive-based regulatory regimes. This has led to a desire for more information on the performance of these businesses, both relative to each other and over time. In this study we use panel data on the 18 largest Australian water services businesses, observed over an eight-year period from 1995/6 to 2002/3, to measure the relative efficiency and productivity growth of these businesses. Data envelopment analysis (DEA) methods are used to obtain estimates of the multi-input, multi-output production technology. The potential use of these performance measures in price-cap regulation is discussed, where the effects of variable selection and data quality upon empirical results is emphasised.

Regulation and Efficiency & Productivity Considerations in Water & Wastewater Industry: Case of Iran

AbstractSince the beginning of 1980s, many countries decided to reform and regulate some public utilities such as water, electricity, gas etc. Since, the public utilities specially water are managed as regional or local entities, the benchmarking approaches are therefore applied to compare the performance of local firms active in an industry on the basis of their relative efficiency along with ways that are used to determine the yardstick model for evaluating the performance of such enterprises. Thus, this study aims at measuring the efficiency of water & wastewater companies (WWCs) as incentive regulation tools for stimulating efficiency of production and supply through cost reduction and improving the quality of services provide by water distributors. In this study, the performances of 34 WWCs were assessed using non-parametric methods as “Data Envelopment Analysis” (DEA) in 2011. Furthermore, we reviewed the DEA-based Malmquist approach for total factor productivity (TFP) and technology change in WWCs over the period of 2008 to 2011. An input variable includes operating costs, number of employees (staff) and number of water connections and output variables are the volumes of water billed and the number of customers. The results of analysis indicate that the average efficiency of WWCs under constant return to scale (CRS) is equal to 77% (technical efficiency) and under variable return to scale (VRS) is equal to 88% (scale efficiency). In other words, given the existing resources and facilities, the potential to improve water production equals to 23% and 12% respectively. Whereas in terms of constant return to scale (CRS), the cost saving potential amounts to 1874 billion Rials or 16% of the operating costs (price=2011). Also, the Malmquist index for total factor productivity (TFP) and technology change are calculated as 0.951 and 0.940 respectively, indicating a decrease of productivity in the Iranian water & wastewater industry during 2008 to 2011

Supplier Evaluation and Rationalization via Data Envelopment Analysis: An Empirical Examination

Strategic evaluation of supplier performance assists firms in improving their operations across a variety of dimensions. Specifically, it aids in supplier process improvement, which in turn enhances firm performance, allows for optimal allocation of resources for supplier development programs, and assists managers in restructuring their supplier network based on performance. In order to address these issues, this article proposes a methodology for effective supplier performance evaluation based on data envelopment analysis (DEA), a multi-factor productivity analysis technique. The efficiencies derived from the DEA model are utilized in conjunction with managerial performance ratings in identifying supplier clusters, which are categorized into high performers and efficient (HE), high performers and inefficient (HI), low performers and efficient (LE), and low performers and inefficient (LI). Effective benchmarks from the HE cluster are identified for improving the operations of suppliers in the HI, LE, and LI clusters. Finally, managerial insights and implications from the study are discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72517/1/j.1745-493X.2001.tb00103.x.pd

Profits and Productivity

In this study we consider the linkage between productivity change and profit change. We develop an analytical framework in which profit change between one period and the next is decomposed into three sources: (i) a productivity change effect (which includes a technical change effect and an operating efficiency effect), (ii) an activity effect (which includes a product mix effect, a resource mix effect and a scale effect), and (iii) a price effect. We then show how to quantify the contribution of each effect, using only observed prices and quantities of products and resources in the two periods. We illustrate our analytical decomposition of profit change with an empirical application to Spanish banking during the period 1987 - 1994.Profits, Productivity