scholarly journals Study on Urban Efficiency Measurement and Spatiotemporal Evolution of Cities in Northwest China Based on the DEA–Malmquist Model

2019 ◽  
Vol 11 (2) ◽  
pp. 434 ◽  
Author(s):  
Jun Yin ◽  
Qingmei Tan
Keyword(s):  
Technical Efficiency ◽  
Economies Of Scale ◽  
High Efficiency ◽  
Returns To Scale ◽  
Northwest China ◽  
Scale Efficiency ◽  
Spatiotemporal Evolution ◽  
Capital Cities ◽  
Low Efficiency ◽  
Constant Returns To Scale

Urban efficiency can effectively measure the management and allocation level of urban factor inputs. Based on the data of 30 prefecture-level cities in Northwest China from 2006 to 2015, urban efficiency is measured by data envelopment analysis (DEA). Then the spatiotemporal evolution rule is identified by Malmquist model. The results illustrate that the overall average urban efficiency of cities in Northwest China each year from 2006 to 2015 was at the low level. Only Jiayuguan, Yulin, Yan’an, and Karamay reached the high average urban efficiency, while Dingxi, Pingliang, Guyuan, Shangluo, Tianshui, Longnan, and Baiyin were at the inefficient level. Most cities in Northwest China were still in the “growing” stage of increasing returns to scale. The scale of urban investment was relatively insufficient, and economies of scale had not yet formed. Cities with decreasing returns to scale were mainly distributed in the capital cities and the central and sub-central cities of Guanzhong-Tianshui Economic Zone with relatively abundant urban resources and capital. Cities with constant returns to scale were mainly distributed in four cities including Yan’an, Yulin, Jiayuguan, and Karamay with high efficiency. The overall comprehensive efficiency, technical efficiency, and scale efficiency of cities in Northwest China were not only low, but also showing a downward trend. The overall progress of urban technology had failed to make up for the shortfall caused by low efficiency, resulting in total factor productivity (TFP) decreasing by 0.5%. Therefore, the cities in Northwest China should continuously improve their technical efficiency and scale efficiency, and ultimately enhance the comprehensive efficiency.

Technical efficiency drivers for the Italian water industry

2010 ◽  
pp. 87-103
Author(s):  
Tiziana Caliman ◽  
Paolo Nardi
Keyword(s):  
Technical Efficiency ◽  
Business Strategy ◽  
Economies Of Scale ◽  
Negative Impact ◽  
Returns To Scale ◽  
Geographical Location ◽  
Parametric Models ◽  
Water Industry ◽  
Component Distribution ◽  
Constant Returns To Scale

The aim of this work is to introduce a first analysis concerning the relevance that ownership and financial structure, but also market dimension and business portfolios, have on the technical efficiency of Italian water utilities. Even though scholars have provided information on the influence of some dimensional or geographical variables, mono-utility character or ownership on efficiency, no paper, to the best of our knowledge, has ever considered the presence of all these hedonic variables as efficiency shifters or drivers. Antonioli and Filippini (2001) have not included ownership; Benvenuti and Gennari (2008) have included ownership and multi-utility strategy, but excluded the geographical dimension; Fabbri and Fraquelli (2000) have not included geographical location, business strategy or ownership; furthermore, most analyses of the Italian water sector have focused on the ATO level (investments, labour costs) and not on utility performances. We have estimated four heteroskedastic stochastic production frontiers: two different parametric models, where the hedonic dummy mono is either in the model as an additional variable or it is used to parameterize the variance of the inefficiency term; two competitive statistical formulations have also been introduced to specify the inefficiency component distribution, that is, the half normal and the exponential distributions. The most important findings of this paper can be summarized as follows. The labour, capital and other input elasticities are always highly significant, positive and quite stable in all the performed models, as expected for a well-behaved production function. The main results show that the mono-business strategy is not efficient; at the same time, operating water and sewerage together implies higher efficiency than water- only management. Theoretically, the population density can have an ambiguous effect on efficiency: on one hand, it could be more expensive to serve dispersed customers, but, on the other, it could generate congestion problems. It could be argued that the second effect prevails, therefore a higher density is accompanied by a higher inef- ficiency. The analysis points out that the variance of the idiosyncratic term is a function of the size of the firm, which is measured as the number of connected properties; the null hypothesis, that the firms use a constant returns-to-scale technology, has also been rejected. Considering the 1994 reform, it is possible to state that the integration of water and sewerage has substantially been positive; at the same time, the economies of scale and the ambiguity of density justify the division into provincial basins. The role of the private sector in the water industry, in agreement with previous literature, has neither a positive nor a negative impact on efficiency and ownership is simply not influent [obviously the quality of service should be considered, although the same indifference seems to emerge (Dore et al., 2001)]. Southern Italy suffers from a higher degree of inefficiency (also recently confirmed by Svimez, 2009), and this is probably the most important issue that has to be dealt with, because of the risks of drought and watering bans in those Regions during summer.

scholarly journals A comparative study of efficiency and its determinants in Islamic, conventional, and socially responsible banks

2016 ◽  
Vol 13 (4) ◽  
pp. 470-482 ◽  
Author(s):  
Majed Alharthi
Keyword(s):  
Financial Crisis ◽  
Technical Efficiency ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Islamic Banks ◽  
Socially Responsible ◽  
Market Capitalization ◽  
Efficiency Measures ◽  
Conventional Banks ◽  
Constant Returns To Scale

This study empirically estimates efficiency and its determinants in 190 Islamic (IBs), conventional (CBs), and socially responsible banks (SRBs) in 22 countries during the period 2005-2012. The study first uses non-parametric approaches to estimate the efficiency measures (scale efficiency (SE), technical efficiency-constant returns to scale (CRS), and technical efficiency-variable returns to scale (VRS)) and second employs ordinary least squares, fixed effects, random effects, and TOBIT models to get the efficiency determinants. The findings indicate that the average efficiency is 0.966, 0.952, and 0.983 for the SE, CRS, and VRS, respectively. However, efficiency measures show that the SRBs are most efficient banks whereas, the least efficiency scores archived by Islamic banks. Islamic bank efficiency is positively correlated with size, loan intensity, ROA, inflation rates, market capitalization and financial crisis. However, conventional banks’ TE and CRS efficiency are positively and significantly correlated with size, ROA, and market capitalization, while their VRS efficiency is negatively and significantly related to capital ratio, age and GDP. In addition, SRBs’ efficiency is increased by size, capital ratio, loan intensity, ROA, foreign ownership, domestic ownership, inflation and financial crisis. Furthermore, the financial crisis affects the SE and CRS efficiency measures in Islamic banks while socially responsible banks SE efficiency measure is positively affected by the financial crisis, which means that socially responsible banks were stabled and resisted during the crisis period. Finally, there is no significant correlation between financial crisis and efficiency indictors in conventional banks during the period

scholarly journals Efficiency of Micro and Small Enterprises in Ethiopia: Evidence from Data Envelope Analysis Model

2021 ◽  
Author(s):  
Abebe Birhanu Ayele
Keyword(s):  
Technical Efficiency ◽  
Service Sector ◽  
Returns To Scale ◽  
Least Square ◽  
Scale Efficiency ◽  
Small Enterprises ◽  
Analysis Model ◽  
Micro And Small Enterprises ◽  
The Government ◽  
Constant Returns To Scale

This study measures the technical and scale efficiency of Micro and Small Enterprises (MSEs) and input slacks using Data Envelop Analysis (DEA) model and identifies the determinants of efficiencies of MSEs by employing ordinary least square (OLS) econometrics model. A sample of 375 randomly selected MESs are included in the study. The study found that the average technical and scale efficiency of MSEs are relatively low; technical efficiency averaged at 30 percent and 38.4 percent under constant returns to scale (CRS) and variable returns to scale (VRS) assumptions, respectively. Besides, the overall average scale efficiency score of MSEs was estimated at 77.8 percent. The highest mean technical and scale efficiencies were registered in the construction (71.8 percent) and manufacturing (85.7 percent) sectors, respectively. Whereas, the lowest technical and scale efficiency goes to urban agriculture sector and service sector, with 38.9 percent and 67.2 percent, respectively. The level of inputs, enterprise age and sector, human capital, labor productivity variables significantly affect relative technical efficiency level of MSEs with different directions while variables such as start-up capital, gender of the enterprise manager and availability of support from the government identified statistically not significant in determining the MSEs’ technical efficiency.

scholarly journals Applying DEA in Analysing the Efficiency of Top Manufacturing Companies in Pakistan

2011 ◽  
Vol 1 (2) ◽  
pp. 225
Author(s):  
Izah Mohd Tahir ◽  
Mehran Ali Memon
Keyword(s):  
Technical Efficiency ◽  
Returns To Scale ◽  
International Markets ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Manufacturing Companies ◽  
Critical Elements ◽  
Input Variables ◽  
Constant Returns To Scale ◽  
Variable Returns To Scale

The efficiency of manufacturing companies is one of the critical elements for its competitiveness in the domestic as well as international markets. Previous research on efficiency measurement usually adopts Data Envelopment Analysis (DEA) approach. Therefore this paper is aimed to analyse the efficiency of 14 top manufacturing companies in Pakistan for a five year period from 2006 to 2010. Data of top 14 manufacturing companies are gathered from OSIRIS database. DEA method is applied using both the Constant Returns to Scale (CCR) and Variable Returns to Scale (BCC) models to find the overall efficiency, technical efficiency and scale efficiency. In this paper we use two input variables (total expenses and total assets) and two output variables (sales and profit before tax). The results under CCR method show that only one company is considered technically efficient while the average overall technical efficiency varies from 0.64 to 0.99. Company number 5 (NRL) demonstrates the best performance for all years under study.

scholarly journals The Extent, Dynamics, and Potential Predictors of Technical Efficiency and Capacity Utilisation in Small-Scale Fisheries in Oman

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
MOHAMMED AL-SIYABI ◽  
SHEKAR BOSE ◽  
HUSSEIN AL-MASROORI
Keyword(s):  
Technical Efficiency ◽  
Returns To Scale ◽  
Policy Implications ◽  
Scale Efficiency ◽  
Small Scale ◽  
Two Stage ◽  
Capacity Utilisation ◽  
Explanatory Variables ◽  
Small Scale Fisheries ◽  
Constant Returns To Scale

This paper investigates the extent, dynamics, and factors influencing technical efficiency (TE) and capacity utilisation (CU) in small-scale fisheries (SSF) using a two-stage data envelopment analysis (DEA) approach covering the period 2010–2012. A considerable extent of boat-level technical inefficiency, capacity underutilisation and scale inefficiency were evident. On average, TE and CU levels under the constant returns to scale (CRS) and variable returns to scale (VRS) models declined over time. The TE and CU scores of 2010 remained unaltered with the addition of ‘fishing time’ as an input to the model. The proportion of boats with unitary scale efficiency (SE) decreased from 26 % in 2010 to 12 % in 2012. The underutilisation rates of the inputs ‘crew’ and ‘fishing time’ ranged from 15.5 % to 31.6 % and 15.8 % to 28.6 %, respectively. Among the species category, the extent of excess capacity was 70 % to 156 % and 47 % to 119 % under the CRS and VRS models, respectively. The second-stage DEA results indicated that the explanatory variables ‘fishing location’, ‘catch per unit of effort’ (CPUE), ‘fuel costs’ and ‘crew share’ significantly influenced CU under the CRS model. In contrast, the significant influence of subsidies and other operating costs were noted under the VRS model. For the TE case, ‘age’, ‘education’, ‘subsidy’ and ‘CPUE’ were found to be significant under the CRS and VRS models. Other significant variables were found in the study under CRS and VRS models. Finally, the results from the descriptive and empirical analysis under the two-stage DEA model are discussed together with policy implications.

scholarly journals Efficiency and scale effect of county public hospitals in Shandong Province, China: a cross-sectional study

BMJ Open ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. e035703
Author(s):  
Qian Li ◽  
Liqi Tian ◽  
Xiaolin Jing ◽  
Xianghua Chen ◽  
Jiangfeng Li ◽  
...  
Keyword(s):  
Technical Efficiency ◽  
Scale Effect ◽  
Returns To Scale ◽  
Cross Sectional Study ◽  
Shandong Province ◽  
Public Hospitals ◽  
Scale Efficiency ◽  
Sectional Study ◽  
Cross Sectional ◽  
Constant Returns To Scale

ObjectiveTo evaluate the efficiency of county public hospitals in Shandong Province following China’s new medical reform and compare the efficiency of hospitals with different bed sizes for improving efficiency.Design and settingThis was a cross-sectional study on the efficiency and size of 68 county public hospitals in China in 2017.Outcome measuresData envelopment analysis was used to calculate the efficiency scores of hospitals and to analyse the slack values of inefficient hospitals. The actual number of open beds, doctors, nurses and total expenditure were selected as inputs, and the total number of annual visits, discharges and total income were selected as outputs. The Kruskal-Wallis H test was employed to compare the efficiency of hospitals with different bed sizes. The χ2 test was used to compare the returns to scale (RTS) of hospitals with different bed sizes.ResultsTwenty (29.41%) hospitals were efficient. There were 27 hospitals with increasing returns to scale, 23 hospitals with constant returns to scale and 18 hospitals with decreasing returns to scale (DRS). The differences in technical efficiency (p=0.248, p>0.05) and pure technical efficiency (p=0.073, p>0.05) were not statistically significant. However, the differences in scale efficiency (p=0.047, p<0.05) and RTS (p<0.001) were statistically significant. Hospitals with DRS began to appear at 885 beds. All sample hospitals with more than 1100 beds were already saturated and some hospitals even had a negative scale effect.ConclusionsThe government and hospital managers should strictly control the bed size in hospitals and make hospitals resume operating in the interests of public welfare. Interventions that rationally allocate health resources and improve the efficiency of medical workers are conducive to solving redundant inputs and insufficient outputs.

Data envelopment analysis of technical efficiency and productivity growth in the US Pacific Northwest sawmill industry

2008 ◽  
Vol 38 (10) ◽  
pp. 2553-2565 ◽  
Author(s):  
Ted L. Helvoigt ◽  
Darius M. Adams
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Pacific Northwest ◽  
Productivity Growth ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Efficiency Change ◽  
Constant Returns To Scale ◽  
Sawmilling Industry

This paper uses data envelopment analysis (DEA) to characterize the changing production frontier (technical efficiency, productivity growth, technical and efficiency change, and returns to scale) of the sawmilling industry in the Pacific Northwest (PNW) US using geographical panel data for the period 1968–2002. Unlike past DEA studies, we develop confidence intervals for all estimates using an improved bootstrapping method. The results indicate that the gap between the least and most efficient regions in PNW has grown and the least efficient regions are falling further behind the most efficient regions. For the Oregon regions, the null hypothesis of constant returns to scale (CRS) could not be rejected for any year. For the Washington regions, returns to scale varied year by year, although only two of the five regions showed strong tendencies away from CRS. For PNW as a whole, mean productivity growth was 0.5% per year between 1968 and 1992. Between 1992 and 2002, the regional mean was 1.3%, although with wide variation across regions. DEA results indicate that the vast majority of productivity growth in the PNW sawmilling industry between 1968 and 2002 was due to technical change. Improvements in scale efficiency played a very small role, and efficiency change was zero or negative.

Efficiency of Gulf Cooperation Council Banks

2016 ◽  
Vol 26 (1) ◽  
pp. 118-136 ◽  
Author(s):  
Peter A Aghimien ◽  
Fakarudin Kamarudin ◽  
Mohamad Hamid ◽  
Bany Noordin
Keyword(s):  
Technical Efficiency ◽  
Parametric Method ◽  
Returns To Scale ◽  
Gulf Cooperation Council ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Content Type ◽  
Use Of Resources ◽  
Potential Factors ◽  
Constant Returns To Scale

Purpose – This paper aims to investigate the efficiency level of Gulf Cooperation Council (GCC) banks on technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE). Both PTE and SE represent the potential factors that influence the efficiency of the GCC banks. In total, 43 GCC banks were observed in this study over the period from 2007 until 2011. Design/methodology/approach – The Data Envelopment Analysis, a non-parametric method using variable returns to scale under Banker, Charnes and Cooper model, was used with assets and deposit (as input) and loan and income (as output). Findings – On average, the results show that many GCC banks are operating within an optimal scale of efficiency. Nevertheless, the results also show managerial inefficiency in the use of resources. Furthermore, the results indicate that, while the larger banks (the 22 largest) tend to operate at constant returns to scale (CRS) or decreasing returns to scale, the smaller banks (the 21 smallest) are susceptible to operate at either CRS or increasing returns to scale. Research limitations/implications – Because of the chosen research method, the results may lack generalisation. Therefore, researchers are encouraged to test the propositions further. An additional implication of the results is that it was able to identify some banks that may become potential targets for outside acquisition. Practical implications – The findings should be useful to banks in the GCC in increasing their efficiencies and recognizing those with a potential for outside acquisition. Originality/value – The findings are valuable because they will facilitate the maintenance of efficient banks in the GCC. This is necessary to enable the countries to maintain a healthy and sustainable economy.

scholarly journals Analyzing the Efficiency Differences among Basic Health Units in Sargodha District

2011 ◽  
Vol 3 (1) ◽  
pp. 42-50 ◽  
Author(s):  
Touqeer Abbas ◽  
Muhammad Amir Aslam . ◽  
Muhammad Waqas .
Keyword(s):  
Health Services ◽  
Technical Efficiency ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Basic Health ◽  
Health Services Delivery ◽  
Services Delivery ◽  
The Mean ◽  
Constant Returns To Scale ◽  
Basic Health Units

Pakistan has adequate infrastructure for health services delivery at primary level. The study aims to calculate the technical efficiency of Basic Health Units (BHUs) in Sargodha by using the Data Envelopment Analysis (DEA) with the choice of inputs and outputs being specific to BHUs operation. DEA model results reveals that the mean technical efficiency under, Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) was 0.719 and 0.807 while the mean scale efficiency was 0.88. Study exposed that 77 % BHUs were technically inefficient under CRS while 66 % BHUs were technically inefficient under VRS modal. Overall 76% BHUs were inefficient and destructing the infrastructure. Moreover, findings evidently point to adverse inefficiency of BHUs in health services delivery. Study concluded that existing high level of inefficiency in BHUs needs institutional fascination for scaling up BHUs to meet both regional as well international targets such as Millennium Development Goals (MDGs) and recommended such measures that may curb the waste.

Efficiency in the Indian iron and steel industry – an application of data envelopment analysis

2014 ◽  
Vol 11 (1) ◽  
pp. 4-19 ◽  
Author(s):  
Roma Mitra Debnath ◽  
V.J. Sebastian
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Steel Industry ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Annual Income ◽  
Content Type ◽  
Steel Manufacturing ◽  
Constant Returns To Scale

Purpose – The purpose of this paper applies to Indian steel manufacturing industries to evaluate the technical and scale efficiency (SE). Design/methodology/approach – Data envelopment analysis (DEA) has been employed to calculate the relative efficiency of the steel manufacturing units. The selection criteria for the inclusion of a steel manufacturing unit in the analysis has been annual income of more than 50 crores and units manufacturing pig iron, steel and sponge iron. Within the DEA framework, the output-oriented model with constant returns to scale and variable returns to scale were studied. Four input variables, namely, gross fixed assets, total energy cost, total number of employees and currents assets were considered. Among the output variables, the four variables considered are income, sales, PBIT and PAT. Findings – The result of the efficiency scores have been categorized into three parts. The pure technical efficiency represents local efficiency and the reason of inefficiency is due to inefficient operations. Technical efficiency indicates that the respective decision-making units are globally efficient in case the efficiency is 100 per cent. The SE explains that the inefficiency is caused by disadvantageous conditions. As the result shows, that public sector undertaking (PSUs) are operating under disadvantageous conditions as compared to private manufacturing units. One of the possible reasons of location disadvantage condition is manufacturing units for PSUs are scattered throughout India. Some of the units are located in such places where, the raw material, supply chain could be difficult. It has been found that 45 per cent of the private manufacturing units are technically as well as scale inefficient units. Practical implications – The result of the study would benefit the steel industry to develop a performance benchmarking as steel companies must be profitable in the long term to ensure sustainable achievements. Originality/value – This is an original study to apply DEA to get insights on productivity efficiency of the steel manufacturing units in India. Though the manufacturing units were selected on the basis of annual income, the analysis of productivity does not reflect any impact of income on the efficiency of the manufacturing firms.

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