scholarly journals Evaluation of Car Performances Using Data Envelopment Analysis

2018 ◽  
Vol 22 ◽  
pp. 01051
Author(s):  
Yunus GÜRAL ◽  
Ayşe Turan BUĞATEKİN

Data Envelopment Analysis (DEA) is a nonparametric method used to examine the relative efficiencies of Decision Making Units (DMUs) on conditions where there are multiple inputs and multiple outputs. As in all sectors, it is very important for the automotive sector to operate effectively. Therefore, it is also important to measure the efficiency and find the source of the inefficiency. In this study, the performances of the DMU of the automobiles will examine using Data Envelopment Analysis. In this direction, it is aimed to assist consumers in purchasing by calculating the relative efficiencies of automobile models, determining effective and ineffective DMUs according to the wishes of the consumers. Sales price and fuel consumption are determined as input variables; maximum speed, cylinder volume, horsepower, maximum torque, luggage volume, acceleration time from 0 to 100 km are determined as output variables.

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 469
Author(s):  
Chia-Nan Wang ◽  
Thi-Ly Nguyen ◽  
Thanh-Tuan Dang ◽  
Thi-Hong Bui

In Vietnam, fishing is a crucial source of nutrition and employment, which not only affects the development of the domestic economy but is also closely related to exports, heavily influencing the economy and foreign exchange. However, the Vietnamese fishery sector has been facing many challenges in innovating production technology, improving product quality, and expanding markets. Hence, the fishery enterprises need to find solutions to increase labor productivity and enhance competitiveness while minimizing difficulties. This study implemented a performance evaluation from 2015 to 2018 of 17 fishery businesses, in decision making units (DMUs), in Vietnam by applying data envelopment analysis, namely the Malmquist model. The objective of the paper is to provide a general overview of the fishery sector in Vietnam through technical efficiency, technological progress, and the total factor productivity in the four-year period. The variables used in the model include total assets, equity, total liabilities, cost of sales, revenue, and profit. The results of the paper show that Investment Commerce Fisheries Corporation (DMU10) and Hoang Long Group (DMU8) exhibited the best performances. This paper offers a valuable reference to improve the business efficiency of Vietnamese fishery enterprises and could be a useful reference for related industries.


2019 ◽  
Vol 2 (2) ◽  
pp. 82-89
Author(s):  
Nor Tasik Misbahrudin

Waqf is a voluntary charity that cannot be disposed of and the ownership cannot be transferred once it is declared as waqf assets. Waqf institutions play an important role in helping the development of Muslims ummah through wealth distribution. State Islamic Religious Councils (SIRCs) in Malaysia are the sole trustee that manage and develop waqf assets. Based on selected input and output, the intermediary approach assumes that cash waqf received as output while total expenditure of SIRCs as input. Under this approach SIRCs act as intermediary between waqif (giver) and beneficiaries. Thus, this paper attempts to analyze the efficiency of waqf institutions in Malaysia by using Data Envelopment Analysis (DEA) method under output-orientation using Variable Return to Scale (VRS) assumptions. Four SIRCs were selected as decision making units (DMU) for the period of 2011 to 2015. The result indicates that changes in average technical efficiency for every year is contributed by both pure technical and scale. However, inefficiency of Malaysian waqf institutions is mostly contributed by pure technical efficiency aspects rather than scale. 2012 showed the highest average technical efficiency with 73.9% as most of the institutions operated in optimum level of input to produce output. Thus, the result suggests that both technical and scale efficiency should be improved to achieve the most efficient and productive level of performance in order to fulfill objectives of the institutions as an intermediary between waqif and beneficiaries.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Chao Lu ◽  
Haifang Cheng

Data envelopment analysis (DEA) is a nonparametric method for evaluating the relative efficiency of a set of decision-making units (DMUs) with multiple inputs and outputs. As an extension of the DEA, a multiplicative two-stage DEA model has been widely used to measure the efficiencies of two-stage systems, where the first stage uses inputs to produce the outputs, and the second stage then uses the first-stage outputs as inputs to generate its own outputs. The main deficiency of the multiplicative two-stage DEA model is that the decomposition of the overall efficiency may not be unique because of the presence of alternate optima. To remove the problem of the flexible decomposition, in this paper, we maximize the sum of the two-stage efficiencies and simultaneously maximize the two-stage efficiencies as secondary goals in the multiplicative two-stage DEA model to select the decomposition of the overall efficiency from the flexible decompositions, respectively. The proposed models are applied to evaluate the performance of 10 branches of China Construction Bank, and the results are compared with the results of the existing models.


Complexity ◽  
2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Marzieh Ghasemi ◽  
Mohammad Reza Mozaffari ◽  
Farhad Hosseinzadeh Lotfi ◽  
Mohsen Rostamy malkhalifeh ◽  
Mohammad Hasan Behzadi

One of the mathematical programming techniques is data envelopment analysis (DEA), which is used for evaluating the efficiency of a set of similar decision-making units (DMUs). Fixed resource allocation and target setting with the help of DEA is a subject that has gained much attention from researchers. A new model was proposed by determining a common set of weights (CSW). All DMUs were involved with the aim of achieving higher efficiency in every DMU after the procedure. The minimum resources and targets allocated to each DMU were commensurate to the efficiency of that DMU and the share of DMU in the input resources and the output productions. To examine the proposed method, other methods in the DEA literature were examined as well, and then, the efficiency of the method was demonstrated through a numerical example.


2020 ◽  
Vol 54 (2) ◽  
pp. 325-339
Author(s):  
Changyong Liang ◽  
Binyou Wang ◽  
Tao Ding ◽  
Yinchao Ma

Many researchers have concentrated on production planning issues by using data envelopment analysis (DEA). However, the assumption made by existing approaches that all decision making units (DMUs) are equipped with the same level of production technology is not realistic. Additionally, with the development in the society, environmental factors have come to play important roles in the production process as well. Thus, undesirable outputs should be considered in production planning problems. Therefore, this paper considers the technology heterogeneity factors and undesirable outputs using the data envelopment analysis-based production planning approach. Two examples containing a numerical example that compare with other method and a real sample that concerns the industrial development of 30 provinces in China are used to validate the applicability of our approach.


2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Hongjun Zhang ◽  
Youliang Zhang ◽  
Rui Zhang

Data envelopment analysis (DEA) is a powerful tool for evaluating and improving the performance of a set of decision-making units (DMUs). Empirically, there are usually many DMUs exhibiting “efficient” status in multi-input multioutput situations. However, it is not appropriate to assert that all efficient DMUs have equivalent performances. Actually, a DMU can be evaluated to be efficient as long as it performs best in a single dimension. This paper argues that an efficient DMU of a particular input-output proportion has its own specialty and may also perform poorly in some dimensions. Two DEA-based approaches are proposed to measure the dimension-specific efficiency of DMUs. One is measuring efficiency in multiplier-form by further processing the original multiplier DEA model. The other is calculating efficiency in envelopment-form by comparing with an ideal DMU. The proposed approaches are applied to 26 supermarkets in the city of Nanjing, China, which have provided new insights on efficiency for the managers.


2017 ◽  
Vol 13 (10) ◽  
pp. 31 ◽  
Author(s):  
Halenur Soysal-Kurt

This study aims to measure relative efficiency of 29 European countries with the data of the year 2013 using input-oriented and constant returns to scale Data Envelopment Analysis and to offer improvement suggestions for the countries found inefficient based on their measured relative efficiency scores. Three input and three output variables are used to assess relative performances of the countries. In this study, tourism expenses, number of employees and number of beds are used as input variables; tourism receipts, tourist arrivals and number of nights spent are used as output variables. As the result of the analysis, 16 countries are found relatively efficient and 13 countries are found relatively inefficient. This study is one of the few publications within the scope of European countries based on data envelopment analysis. Unlike most researches evaluating the efficiency of tourism establishments at the micro level, this paper is thought to contribute to the related literature as it evaluates relative efficiency of the countries at the macro level for tourism industry. Considering the variables used in the analysis, it is expected to give ideas to relatively inefficient European countries on efficiency improvement.


2021 ◽  
Vol 39 (5) ◽  
pp. 9-24
Author(s):  
Javad Vakili ◽  
Hanieh Amirmoshiri ◽  
Mir Kamal Mirnia

Data Envelopment Analysis (DEA) is a nonparametric method for measuring the relative efficiency and performance of Decision Making Units (DMUs). Traditionally, there are two issues regarding the DEA simultaneously i.e., the identification of a reference point on the efficient boundary of the production possibility set (PPS) and the use of some measures of distance from the unit under assessment to the efficient frontier. Due to its importance, in this paper, two alternative target setting models were developed to allow for lowefficient DMUs find the easiest way to improve its efficiency and reach to the efficient boundary. One seeks the closest weak efficient projection and the other suggests the most appropriate direction towards the strong efficient frontier surface. Both of these models provides the closest projection in one stage. Finally, a proposed problem is empirically checked by using a recent data related to 30 European airports.


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