APPLYING THE METHOD OF MEASURING AIRPORT PRODUCTIVITY IN THE BALTIC REGION

Transport ◽  
2012 ◽  
Vol 27 (2) ◽  
pp. 178-186 ◽  
Author(s):  
Ilona Jaržemskienė
Keyword(s):  
Data Envelopment Analysis ◽  
General Aviation ◽  
Data Envelopment ◽  
Baltic Region ◽  
Expert Survey ◽  
Theoretical Assumptions ◽  
Dea Method ◽  
Productivity Indicators ◽  
The Baltic ◽  
Decision Making Units

The author of the article describes the theoretical assumptions of the DEA method used for measuring the productivity of airports described in the article ‘Research into the methods of analysing the productivity indicators of transport terminals’ (Jaržemskienė 2009). The essential insights presented in the above mentioned paper reveal that Data Envelopment Analysis (DEA) is a relatively new ‘data oriented’ approach to evaluating the performance of the so-called Decision Making Units (DMU) that convert multiple inputs into multiple outputs. The article focuses on the findings of the study carried out by the author in accordance with those assumptions. Research represents the Data Envelopment Analysis (DEA) method testing 15 selected airports situated in the Baltic Region, including Vilnius, Kaunas, Palanga, Riga, Tallinn, St. Petersburg, Helsinki, Turku, Stockholm, Malme, Copenhagen, Hamburg, Gdansk, Warsaw and Minsk. Airport productivity indicators are ranked considering importance and using the method of Delphi expert survey made of two rounds. The author presented the following indicators (expressed as ‘ratio’) as the major ones estimated by PAX/LAND, AIR/LAND, PAX/AIR, PAX/RW, PAX/RWA, GA and INTER experts. The succeeding indicators were introduced by PAX/TERMAREA, PAX/GATES, AIR/RW, AIR/RWA, AIR/TERMAREA, AIR/GATES, FR/LAND and FR/RW. 10 indicators were accepted as the most important and selected from the current set in the following sequence: AIR/LAND, AIR/RW, PAX/RW, PAX/LAND, AIR/RWA, PAX/AIR, PAX/RWA, AIR/TERMAREA, PAX/GATES and PAX/TERMAREA. AIR/LAND and AIR/RW were submitted as two main indicators. The acronyms are explained as follows: LAND – airport area, RWA – runway length, PAX – the number of passengers, AIR – the number of aircraft take-offs and landings, RW – the number of runways, GATES – the number of gates, FR – the amount of freight served, TERMAREA – the area of passenger terminal, GA – a general aviation market share of airport served aircraft by percentage, INTER – the percentage of international passengers considering all passengers served by airports. After two key productivity indicators were chosen conducting the expert survey, airport productivity was compared applying the DEA method.

scholarly journals Cross-Efficiency Evaluation Method with Compete-Cooperate Matrix

2015 ◽  
Vol 2015 ◽  
pp. 1-7
Author(s):  
Qiang Hou ◽  
Xue Zhou
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Evaluation Method ◽  
Peer Assessment ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Self Assessment ◽  
Dea Method ◽  
Decision Making Units

Cross-efficiency evaluation method is an effective and widespread adopted data envelopment analysis (DEA) method with self-assessment and peer-assessment to evaluate and rank decision making units (DMUs). Extant aggressive, benevolent, and neutral cross-efficiency methods are used to evaluate DMUs with competitive, cooperative, and nontendentious relationships, respectively. In this paper, a symmetric (nonsymmetric) compete-cooperate matrix is introduced into aggressive and benevolent cross-efficiency methods and compete-cooperate cross-efficiency method is proposed to evaluate DMUs with diverse (relative) relationships. Deviation maximization method is applied to determine the final weights of cross-evaluation to enhance the differentiation ability of cross-efficiency evaluation method. Numerical demonstration is provided to illustrate the reasonability and practicability of the proposed method.

scholarly journals Identification and Prioritization of Hazardous Road Locations by Segmentation and Data Envelopment Analysis Approach

1970 ◽  
Vol 25 (2) ◽  
pp. 127-136 ◽  
Author(s):  
Aliasghar Sadeghi ◽  
Esmaeel Ayati ◽  
Mohammadali Pirayesh Neghab
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Regression Models ◽  
Data Envelopment ◽  
The Road ◽  
Black Spots ◽  
Main Factors ◽  
Dea Method ◽  
Decision Making Units

The aim of the present study is the representation of a method to identify and prioritize accident-prone sections (APSs) based upon efficiency concept to emphasize accidents with regard to traffic, geometric and environmental circumstances of road which can consider the interaction of accidents as well as their casual factors. This study incorporates the segmentation procedure into data envelopment analysis (DEA) technique which has no requirement of distribution function and special assumptions, unlike the regression models. A case study has been done on 144.4km length of Iran roads to describe the approach. Eleven accident-prone sections were identified among 154 sections obtained from the segmentation process and their prioritization was made based on the inefficiency values coming from DEA method. The comparisons demonstrated that the frequency and severity of accidents would not be only considered as the main factors for black-spots identification but proper rating can be possible by obtaining inefficiency values from this method for the road sections. This approach could applicably offer decision-making units for identifying accident-prone sections and their prioritizations. Also, it can be used to prioritize intersections, roundabouts or the total roads of the safety organization domain.

scholarly journals Evaluating Efficiency of Zakah Institutions: An Intermediation Approach Using Data Envelopment Analysis (DEA)

2021 ◽  
Vol 5 (1) ◽  
pp. 16
Author(s):  
Sepky Mardian ◽  
Rismayanti Rismayanti ◽  
Mustafa Kamal ◽  
Rianti Pratiwi
Keyword(s):  
Data Envelopment Analysis ◽  
Comprehensive Evaluation ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Inhibiting Factors ◽  
Input And Output ◽  
Long Duration ◽  
Dea Method ◽  
Using Data ◽  
Decision Making Units

Abstract   This paper analyzes the efficiency of Badan Aml Zakat Nasional (BAZNAS) and Dompet Dhuafa from 2002 to 2018. Based on selected input and output, the intermediary approach assumes that BAZNAS and Dompet Dhuafa act as a link between muzakki (giver) and beneficiaries. Furthermore, BAZNAS and Dompet Dhuafa were selected as decision-making units (DMU) from 2002 to 2018, and their efficiency was measured using Data Envelopment Analysis (DEA) method under output-orientation with Constant Return to Sclae (CRS) and Variable Return to Scale (VRS) assumptions. The results showed both BAZNAS and Dompet Dhuafa raise the optimum efficiency in the years before 2007. Meanwhile, their inefficiency was mostly due to lack of input such as higher personalia (amil/volunteers) expenses. Therefore, these findings suggests that both technical and scale efficiency should be improved by adjusting the input. This is to achieve the most efficient and productive level of performance in order to fulfill the institutions' objectives as an intermediary between muzakki and the beneficiaries. This paper is among the pioneers that analyzed the efficiency of zakat institutions from their initial establishment to present. Also, existing papers examined data spanning 5 years or less. Hence, long duration of data analysis provides a comprehensive evaluation of fluctuations in the zakat institutions efficiency and their supporting or inhibiting factors.  

scholarly journals Efficiency in the Worst Production Situation Using Data Envelopment Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Md. Kamrul Hossain ◽  
Anton Abdulbasah Kamil ◽  
Adli Mustafa ◽  
Md. Azizul Baten
Keyword(s):  
Data Envelopment Analysis ◽  
Shape Parameter ◽  
Pareto Distribution ◽  
Maximum Output ◽  
Data Envelopment ◽  
Dea Efficiency ◽  
Dea Method ◽  
Stochastic Data ◽  
Using Data ◽  
Decision Making Units

Data envelopment analysis (DEA) measures relative efficiency among the decision making units (DMU) without considering noise in data. The least efficient DMU indicates that it is in the worst situation. In this paper, we measure efficiency of individual DMU whenever it losses the maximum output, and the efficiency of other DMUs is measured in the observed situation. This efficiency is the minimum efficiency of a DMU. The concept of stochastic data envelopment analysis (SDEA) is a DEA method which considers the noise in data which is proposed in this study. Using bounded Pareto distribution, we estimate the DEA efficiency from efficiency interval. Small value of shape parameter can estimate the efficiency more accurately using the Pareto distribution. Rank correlations were estimated between observed efficiencies and minimum efficiency as well as between observed and estimated efficiency. The correlations are indicating the effectiveness of this SDEA model.

Relative Efficiency of Decision Making Units Producing Both Desirable and Undesirable Outputs: A Case of Textile Processing Units in Pakistan.

2011 ◽  
Vol 50 (4II) ◽  
pp. 685-698
Author(s):  
Samina Khalil
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Value Added ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Textile Processing ◽  
Decision Making Unit ◽  
Desirable And Undesirable Outputs ◽  
Decision Making Units

This paper aims at measuring the relative efficiency of the most polluting industry in terms of water pollution in Pakistan. The textile processing is country‘s leading sub sector in textile manufacturing with regard to value added production, export, employment, and foreign exchange earnings. The data envelopment analysis technique is employed to estimate the relative efficiency of decision making units that uses several inputs to produce desirable and undesirable outputs. The efficiency scores of all manufacturing units exhibit the environmental consciousness of few producers is which may be due to state regulations to control pollution but overall the situation is far from satisfactory. Effective measures and instruments are still needed to check the rising pollution levels in water resources discharged by textile processing industry of the country. JEL classification: L67, Q53 Keywords: Data Envelopment Analysis (DEA), Decision Making Unit (DMU), Relative Efficiency, Undesirable Output

scholarly journals Performance Evaluation of Fishery Enterprises Using Data Envelopment Analysis—A Malmquist Model

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 469
Author(s):  
Chia-Nan Wang ◽  
Thi-Ly Nguyen ◽  
Thanh-Tuan Dang ◽  
Thi-Hong Bui
Keyword(s):  
Performance Evaluation ◽  
Data Envelopment Analysis ◽  
Technological Progress ◽  
Data Envelopment ◽  
Domestic Economy ◽  
Factor Productivity ◽  
Sales Revenue ◽  
Business Efficiency ◽  
Using Data ◽  
Decision Making Units

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.

scholarly journals Selecting Suitable, Green Port Crane Equipment for International Commercial Ports

2021 ◽  
Vol 13 (12) ◽  
pp. 6801
Author(s):  
Guo-Ya Gan ◽  
Hsuan-Shih Lee ◽  
Yu-Jwo Tao ◽  
Chang-Shu Tu
Keyword(s):  
Data Envelopment Analysis ◽  
Environmental Protection ◽  
Green Energy ◽  
Programming Approach ◽  
Data Envelopment ◽  
Container Handling ◽  
Dea Method ◽  
Green Port ◽  
Large Container ◽  
Gantry Cranes

Responding to the increasing global need for environmental protection, a green port balances economic vibrancy with environmental protection. However, because exhaust emissions (e.g., CO2 or sulfide) are difficult to monitor around ports, data on such emissions are often incomplete, which hinders research on this topic. The present study aimed to fill this gap in this topic. To remedy this problem, this study formulated a new data envelopment analysis (DEA) method for collecting CO2 emissions data at their source. This method was applied to collect real-world operating data from a large container-handling company in Taiwan. Specifically, we provide a real example using a novel green energy index to account for undesirable outputs. Our main objective was to formulate two methods that combine: (1) data envelopment analysis based on a modified slack-based measure, and (2) a multi-choice goal programming approach. The contributions of this paper included the finding that rubber-tired gantry cranes are the greenest and should be used in ports. Finally, our findings aid port managers in selecting port equipment that provides the best balance between environmental protection and profitability.

scholarly journals Benchmarking—A Way of Finding Risk Factors in Business Performance

2021 ◽  
Vol 14 (5) ◽  
pp. 221
Author(s):  
Jarmila Horváthová ◽  
Martina Mokrišová ◽  
Mária Vrábliková
Keyword(s):  
Risk Factors ◽  
Data Envelopment Analysis ◽  
Heat Supply ◽  
Business Performance ◽  
Data Envelopment ◽  
Performance Factors ◽  
Best Value ◽  
Target Values ◽  
Dea Method ◽  
Comparison Of The Results

The purpose of this study was to emphasize that the Data Envelopment Analysis (DEA) method is an important benchmarking tool which provides necessary information for improving business performance. To fulfil the abovementioned goal, we used a sample of 48 Slovak companies involved in the field of heat supply. As their position in the economic and social environment of the country is essential, considerable attention should be paid to improving their performance. In addition to the DEA method, we applied the Best Value Method (BVM). We found that DEA is a highly important benchmarking tool, as it provides benchmarks for units that have problems with performance and helps us to reveal risk performance factors. The DEA method also allows us to determine target values of indicators. The originality of this paper is in its comparison of the results of the BVM and the DEA methods.

scholarly journals Measuring the Productivity of Energy Consumption of Major Industries in China: A DEA-Based Method

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Xishuang Han ◽  
Xiaolong Xue ◽  
Jiaoju Ge ◽  
Hengqin Wu ◽  
Chang Su
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Data Envelopment Analysis ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Policy Makers ◽  
Time Periods ◽  
Decision Making Units

Data envelopment analysis can be applied to measure the productivity of multiple input and output decision-making units. In addition, the data envelopment analysis-based Malmquist productivity index can be used as a tool for measuring the productivity change during different time periods. In this paper, we use an input-oriented model to measure the energy consumption productivity change from 1999 to 2008 of fourteen industry sectors in China as decision-making units. The results show that there are only four sectors that experienced effective energy consumption throughout the whole reference period. It also shows that these sectors always lie on the efficiency frontier of energy consumption as benchmarks. The other ten sectors experienced inefficiency in some two-year time periods and the productivity changes were not steady. The data envelopment analysis-based Malmquist productivity index provides a good way to measure the energy consumption and can give China's policy makers the information to promote their strategy of sustainable development.

Sign in / Sign up

Export Citation Format

Share Document