Development and Urban Sustainability: An Analysis of Efficiency Using Data Envelopment Analysis

Abstract

Abstract:In recent decades, the majority of cities in developing countries have grown rapidly and have experienced increasing environmental problems. These changes have generated a broad discussion on urban sustainability and development. In this discussion, it is fundamental to establish methods for measuring urban sustainability using a quantitative approach. This research seeks to estimate and evaluate the environmental, social, and economic efficiency of cities in a developing country, Colombia, using data envelopment analysis to determine the changes that occurred between 2005 and 2013. In this study, indicators related to economic, environmental, and social performance are used with the objective of analyzing efficiency from urban sustainability. The results indicate differences among cities, where the efficient cities show adequate resource use, lower environmental impacts, improved social conditions, and guaranteed economic growth and development. Moreover, as the city scale increases, urban sustainability declines. All these findings are important in the formulation and design of adequate urban policies to improve and strengthen sustainability and social welfare over the long term, particularly in cities in developing countries.

Research on Population Spatiotemporal Aggregation Characteristics of a Small City: A Case Study on Shehong County Based on Baidu Heat Maps

“…However, most of these studies have been conducted in large cities, and small cities are rarely examined [1]. Small cities are an important part of the urbanization process and they have begun to face "urban diseases" in China, such as traffic congestion (Figure 1) [2,3], environment pollution [4], lack of infrastructure [5,6], and so forth. Therefore, it is necessary to examine the distribution law of small urban populations.…”

Modeling Regulation of Economic Sustainability in Energy Systems with Diversified Resources

“…The verification methodology should show that the basic theoretical representation of the four stages and methods of the cycle in Figure 3, modeled by functional analysis tools and shown in Figures 4 and 5, is reliably verified using criteria-based indicators according to Formulas (7)- (11) in mathematical modeling of organizational and technological processes. Verification is an analysis of the results of a real project, corresponding to the experience and directions of development of energy and resource conservation [31][32][33][34][35][36][37] for use of products in the formed energy technology complex combining objects and polygeneration (ETC) of solid, household and other waste (SHW-based products, in general, liquid for plasma-fire neutralization or biogas production). The result of the project may be the reduction of losses from the insufficient quality of energy-saving control processes, expressed in the under-utilization of the results: replacement of traditional energy resources; more types of energy products in terms of cogeneration, trigeneration and, in general, their polygeneration; diversification of energy production methods, increasing the reliability of energy supply in remote areas; increased processing of SHW to solve environmental problems; sale of waste to other countries.…”

A Spatial DEA-Based Framework for Analyzing the Effectiveness of Disaster Risk Reduction Policy Implementation: A Case Study of Earthquake-Oriented Urban Renewal Policy in Yongkang, Taiwan

“…(4) The distinctly inefficient unit (E < 0.9) is the most inefficient DMU. Half of the DMUs belonged to this type of unit, including DMUs 2,3,5,9,10,12,13,14,16,17,18,19,20,22,23,24,27,28,29,35,36,and 37. This type of DMU is difficult to move on the efficiency frontier in a short period of time.…”

“…Additionally, DEA provides various extended models that use information to resolve research issues. In using a combined analysis stemming from various models, DEA is particularly appropriate for comparing diversified recourse profiles [12,20,21] and providing suggestions for adopting policy. Moreover, it can have the capacity to handle several input and output variables simultaneously without methodological restrictions in a multiple-dimension decision-making process.…”