scholarly journals A TRIPLE BOTTOM LINE APPROACH FOR MEASURING SUPPLY CHAINS SUSTAINABILITY USING DATA ENVELOPMENT ANALYSIS

Author(s):  
Alessandro Cortes
2014 ◽  
Vol 2014 (1) ◽  
pp. 12595 ◽  
Author(s):  
Abagail McWilliams ◽  
Annaleena Parhankangas ◽  
Jason Coupet Coupet ◽  
Darold Barnum

2017 ◽  
Vol 10 (6) ◽  
pp. 1948
Author(s):  
Raul Assef Castelao ◽  
Celso Correia de Souza ◽  
Daniel Massem Frainer ◽  
José Francisco Dos Reis Neto ◽  
Michelle Da Rosa

O uso de indicadores para avaliar determinado fenômeno tem sido empregado nas mais diversas áreas do conhecimento. Mais recentemente, indicadores têm sido utilizados com o intuito de vencer o desafio quando se discute a questão ambiental, e se busca a harmonia entre o crescimento econômico e a preservação do meio ambiente. Desse modo, o uso de indicadores pode ser o instrumento mais adequado para melhorar a comunicação entre os decisores políticos e a sociedade na discussão de temas complexos sobre os quais há necessidade de um consenso. O objetivo geral deste artigo foi determinar o índice de desenvolvimento sustentável (IDS) de 78 municípios do estado do Mato Grosso do Sul (MS), com a utilização de análise envoltória de dados (DEA), que permite a análise conjunta de diversas variáveis como os indicadores de natureza econômica, social e ambiental. Estes indicadores são os parâmetros do Triple Bottom Line (TBL), que permite avaliar o nível de sustentabilidade de cada município de modo multicriterial. Na determinação dos IDS foram utilizados dados secundários de diversos órgãos públicos no MS.  Como resultado geral, pode-se identificar e hierarquizar as cidades com melhores desempenhos em cada dimensão e também quando em conjunto. Foi possível identificar que os municípios com melhores índices de desenvolvimento econômico apresentaram menor qualidade ambiental e social, e os menos desenvolvidos encontram-se mais preservados. De modo semelhante, também foi analisado o desenvolvimento sustentável nas mesorregiões no estado do MS, com a mesorregião leste apresentando o melhor índice de desenvolvimento sustentável.  The use of indicators to evaluate a given phenomenon has been used in several areas of knowledge. More recently, indicators have been used to overcome the challenge when discussing the environmental issue, and seek harmony between economic growth and preservation of the environment. In this way, indicators can be the most appropriate instrument for improving communication between policy makers and society in discussing complex issues on which consensus is needed. The general objective of this article was to determine the sustainable development index (IDS) of 78 municipalities in the state of Mato Grosso do Sul (MS), using data envelopment analysis (DEA), which allows the joint analysis of several variables as Indicators of economic, social and environmental nature. These indicators are the parameters of the Triple Bottom Line (TBL), which allows assessing the level of sustainability of each municipality in a multi-criteria way. In the determination of IDS, secondary data from several public agencies in the MS were used. As a general result, one can identify and rank cities with better performance in each dimension and also when together. It was possible to identify that the municipalities with the best economic development indices presented lower environmental and social quality, and the less developed ones are more preserved. Similarly, sustainable development was also analyzed in mesoregions in the MS state, with the eastern mesoregion presenting the best index of sustainable development. Keywords: environment, sustainable development, local indicators, Mato Grosso do Sul.  


2019 ◽  
Author(s):  
Jeffrey A. Shero ◽  
Sara Ann Hart

Using methods like linear regression or latent variable models, researchers are often interested in maximizing explained variance and identifying the importance of specific variables within their models. These models are useful for understanding general ideas and trends, but often give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method with roots in organizational management that make such insights possible. Unlike models mentioned above, DEA does not explain variance. Instead, it explains how efficiently an individual utilizes their inputs to produce outputs, and identifies which input is not being utilized optimally. This paper provides readers with a brief history and past usages of DEA from organizational management, public health, and educational administration fields, while also describing the underlying math and processes behind said model. This paper then extends the usage of this method into the psychology field using two separate studies. First, using data from the Project KIDS dataset, DEA is demonstrated using a simple view of reading framework identifying individual efficiency levels in using reading-based skills to achieve reading comprehension, determining which skills are being underutilized, and classifying and comparing new subsets of readers. Three new subsets of readers were identified using this method, with direct implications leading to more targeted interventions. Second, DEA was used to measure individuals’ efficiency in regulating aggressive behavior given specific personality traits or related skills. This study found that despite comparable levels of component skills and personality traits, significant differences were found in efficiency to regulate aggressive behavior on the basis of gender and feelings of provocation.


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