An efficiency analysis of food distribution system through data envelopment analysis

2019 ◽  
Vol 36 (4) ◽  
pp. 538
Author(s):  
Leonardo Postacchini ◽  
Giovanni Mazzuto ◽  
Maurizio Bevilacqua ◽  
Filippo Emanuele Ciarapica ◽  
Claudia Paciarotti
2019 ◽  
Vol 36 (4) ◽  
pp. 538
Author(s):  
Claudia Paciarotti ◽  
Maurizio Bevilacqua ◽  
Filippo Emanuele Ciarapica ◽  
Giovanni Mazzuto ◽  
Leonardo Postacchini

Author(s):  
Matthias Klumpp ◽  
Dominic Loske

Although resources are scarce and outputs incorporate the potential to save human lives, efficiency measurement endeavors with data envelopment analysis (DEA) methods are not yet commonplace in the research and practice of non-government organizations (NGO) and states involved in humanitarian logistics. We present a boot-strapped DEA window analysis and Malmquist index application as a methodological state of the art for a multi-input and multi-output efficiency analysis and discuss specific adaptions to typical core challenges in humanitarian logistics. A characteristic feature of humanitarian operations is the fact that a multitude of organizations are involved on at least two levels, national and supra-national, as well as in two sectors, private NGO and government agencies. This is modeled and implemented in an international empirical analysis: First, a comprehensive dataset from the 34 least developed countries in Africa from 2002 to 2015 is applied for the first time in such a DEA Malmquist index efficiency analysis setting regarding the national state actor level. Second, an analysis of different sections in a Rohingya refugee camp in Bangladesh is analyzed based on a bootstrapped DEA with window analysis application for 2017, 2018, and 2019 quarter data regarding the private NGO level of operations in humanitarian logistics.


2017 ◽  
Vol 13 (1) ◽  
pp. 1
Author(s):  
Natelda R Timisela ◽  
Ester D Leatemia ◽  
Febby J Polnaya ◽  
Rachel Breemer

The current research aimed to analyze the relative efficiency level of enbal (sago starch) agro-industries. The relative efficiency analysis on 32 DMUs of enbal agro-industries showed that 40,63% of the industries were efficient and 59.38% were inefficient. Every efficient DMU became the reference for the inefficient DMUs based on the suggested quality. Each DMU of the enbal agro-industries has not reached a good efficiency level, which was indicated by the average relative efficiency scale of 0.886. This was a relatively low value, and improvements on the use of production input were needed. The analysis result on the DMUs of the enbal agro-industries which were on constant return to scale position were 40,62%. This showed that enbal agro-industries actors have applied production input efficiently, for the production increase was equal to the use of input. In other words, the use of input was more proportional. The DMUs of enbal agro-industries which were on decreasing return to scale position were 15,63%. This showed that the use of production input had been unsuitable so that the output decreases and the production cost increased. Meanwhile, the DMUs that were on increasing return to scale position were 43,75%. This showed that the industry actors who used certain production input would create efficient DMUs. On the other hand, the input excess would possibly decrease the output. As a result, the industry actors should be concerned about the use of production input in order to establish business efficiency.


2017 ◽  
Vol 23 (6) ◽  
pp. 787-795 ◽  
Author(s):  
Joanicjusz NAZARKO ◽  
Ewa CHODAKOWSKA

The primary problems pertaining to productivity or – more precisely – efficiency are: how to define it and how to measure it. This article studies technical efficiency in Stochastic Frontier Analysis (SFA) – the input-oriented frontier model – in the construction industry and compares it with Data Envelopment Analysis (DEA) results. The models ex­plored in this paper were constructed on the basis of two outputs and personnel cost as an input. The research sample consisted of European countries. The aim was to determine whether there are substantial differences in estimation of ef­ficiency derived from those two alternative frontier approaches. The comparison of results according to the models may translate into higher reliability of the undertaken labour efficiency analysis in construction and its conclusions. Although the results are not characterized by high compatibility, the conducted analysis indicated the most attractive countries taking into account labour cost to profit and turnover ratios of enterprises. One of the determinants which should not be ignored when analysing the labour efficiency is the level of development of a country; however, it is not the sole factor affecting the efficiency of the sector.


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