Ecological Efficiency Based Ranking of Cities: A Combined DEA Cross-Efficiency and Shannon’s Entropy Method

Abstract

Abstract:In this paper, a method is proposed to calculate a comprehensive index that calculates the ecological efficiency of a city by combining together the measurements provided by some Data Envelopment Analysis (DEA) cross-efficiency models using the Shannon's entropy index. The DEA models include non-discretionary uncontrollable inputs, desirable and undesirable outputs. The method is implemented to compute the ecological efficiency of a sample of 116 Italian provincial capital cities in 2011 as a case study. Results emerging from the case study show that the proposed index has a good discrimination power and performs better than the ranking provided by the Sole24Ore, which is generally used in Italy to conduct benchmarking studies. While the sustainability index proposed by the Sole24Ore utilizes a set of subjective weights to aggregate individual indicators, the adoption of the DEA based method limits the subjectivity to the selection of the models. The ecological efficiency measurements generated by the implementation of the method for the Italian cities indicate that they perform very differently, and generally largest cities in terms of population size achieve a higher efficiency score.Keywords: cross-efficiency; data envelopment analysis; Shannon's entropy; ecological efficiency; cities; ranking; Italy BackgroundIn the last decade, cities have gained a greater centrality in the economic and social growth of nations. The recent report delivered by the Brookings Institution indicates that in 2014 the economies of the 300 largest metropolitan areas accounted for 47% of global gross domestic product (GDP) and 38% of GDP growth [1]. According to recent estimates provided by Seto et al.[2], more than 80% of the national gross domestic product (GDP) is generated in urban areas. A recent worldwide research conducted by the McKinsey Global Institute on a sample of 600 cities estimates that between 2010 and 2050, the GDP of these cities is expected to double, while 23 megacities-cities having more than 10 million inhabitants-in 2007 generated 14% of global GDP [3].People move to and live in cities to have access to better jobs, education, health care, goods and services. More than half of the human population over the world is living in cities and towns, and, in the next decades, the number of people expected to live in cities will grow to 75%, while population growth over the next 25 years will be concentrated in cities and towns [4,5]. The most urbanized areas are located in the American and Europe continents, respectively having about 80% and 70% of all inhabitants residing in cities and towns. However, while cities are the primary source of economic development and social prosperity, and house more than half of the world population, they are large users of resources, responsible for about 2/3 of energy demand and greenhouse gas emissions [5]. The recent rapid and intense urbanization has often resulted in an over consumption of water, energy, raw

Efficiency vs Effectiveness: a Benchmarking Study on European Healthcare Systems

“…While outputs O2, O3, and O4 effectively provide measurements of benefits enjoyed by people, O1 measures an "undesirable" or "bad output" of the health care system. Therefore, the bad output was treated as an input in performing DEA (lo Storto, 2016;Scheel, 2001). Total country population was included in the analysis as a proxy of total demand for national healthcare service.…”

Efficiency, Conflicting Goals and Trade-Offs: A Nonparametric Analysis of the Water and Wastewater Service Industry in Italy

“…Since its introduction, DEA has been extensively employed in economic analysis to calculate measures of efficiencies in various situations and industries, such as transportation [29,31,32], government and public sector [33][34][35], public utilities [21,22,[36][37][38], healthcare [39][40][41], education [42,43], banking and finance [44,45], energy and environmental studies [46][47][48][49][50][51][52], manufacturing and information technology [53][54][55][56].…”

A Comprehensive Evaluation of Sustainable Development Ability and Pathway for Major Cities in China

“…The reason for the low frequency of usage of the DEA method, as noted by Li et al [18], is the limited availability of statistical data at the city level in China. In reality, the DEA method is perfectly suitable for comprehensive evaluation of a city's efficiency, and several case studies that have already been performed abroad using this method [19,20]. Studies that are related to the topic of this work are somewhat more common at the provincial level, due to the availability of data, but they still favor the engineering discipline.…”