Efficiency of winemaking in developing countries

2017 ◽  
Vol 29 (1) ◽  
pp. 98-118 ◽  
Author(s):  
Anatoliy G. Goncharuk ◽  
Aleksandra Figurek
Keyword(s):  
Developing Countries ◽  
Returns To Scale ◽  
Wine Industry ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Potential Growth ◽  
Policy Makers ◽  
Content Type ◽  
Current State ◽  
Wine Market

Purpose This paper aims to the evaluation and comparison of the efficiency of winemaking in two developing countries (Ukraine and Bosnia and Herzegovina (B&H)) from the perspective of their development. Design/methodology/approach In this research study, four models of data envelopment analysis (DEA), correlation and other tools of the data analysis are used to analyze the efficiency of wineries in two developing countries. Returns to scale, scale efficiency, super-efficiency and some other indicators are examined. The research is based on the sample, including 33 wineries of Ukraine and B&H. Findings Characterized by the same average efficiency and number of leaders, in Ukraine, medium and large wineries are developing more efficiently than small ones, whereas the opposite is true for B&H. The authors found the high potential growth of efficiency on Ukrainian (up to 28.9 per cent) and Bosnian wineries (up to 28.3 per cent). The ways for its realization were suggested. Cross-country efficiency analysis enabled us to find inter-country leaders of wine industry. The authors grouped inefficient wineries, calculated the potential for inputs reduction and found the main directions for the improvement of efficiency for each group. Research limitations/implications The research is limited to a single industry in only two developing countries. Future studies can be devoted to the comparison of the efficiency of wineries in developed and developing countries. The results can determine which countries can be leaders in the global wine market in the future. Practical implications This study provides useful information for: researchers of wine market in developing countries enabling them to understand the current state, basic problems and efficiency levels of wineries in Ukraine and B&H; domestic policy-makers- to improve regulation of wine industry as to make it more competitive and efficient; wine producers in these countries- to find the benchmarks using the best practices to adapt them in own business and to increase an efficiency. Originality/value On the example of Ukraine and B&H, this study has shown that each respective country has its own conditions of doing wine business. This is the first paper that compares the efficiency of wine industry in Ukraine and B&H.

International performance benchmarking in winemaking

2017 ◽  
Vol 24 (1) ◽  
pp. 24-33 ◽  
Author(s):  
Anatoliy G. Goncharuk ◽  
Natalia Lazareva
Keyword(s):  
Wine Industry ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Content Type ◽  
International Performance ◽  
Performance Benchmarking ◽  
Capital Productivity ◽  
Product Service ◽  
Study Results ◽  
Dea Models

Purpose The purpose of this paper is to study winemaking efficiency with the help of international performance benchmarking and to finding ways for its improvement. Design/methodology/approach In this research, three models of data envelopment analysis (DEA) and other tools of international performance benchmarking are used to analyse the efficiency of wine companies. Return to scale (RTS) and scale efficiency, labour and capital productivity and some other indicators are examined. The research is based on a sample of 36 wine companies from 15 countries. Findings International benchmarking expands performance improvement for domestic companies. The most efficient wine companies are originated from Germany, USA and New Zeeland. Scale inefficiency and increasing RTS for most of the wine companies was identified. Only three wine companies have decreasing RTS (those from UK, Australia and France). To increase relative efficiency, these companies need to reduce the output and sales as their costs are growing faster than the revenues. A huge potential for cost reduction and efficiency growth within Ukrainian wine companies was revealed. Research limitations/implications The research is limited to a single industry. This is explained by the requirement of technology (product, service) homogeneity while using DEA tools. Practical implications Study results include the data and recommendations to develop winemaking. These results can be used by wine companies’ management, present and potential investors and proprietors, regulative public authority, e.g. to improve efficiency in winemaking. Originality/value This is the first paper that adapts various DEA models to measure efficiency in the wine industry of Ukraine and the tools of international performance benchmarking for wine companies around the world.

scholarly journals DATA ENVELOPMENT ANALYSIS (DEA) APPROACH FOR ASSESSING TECHNICAL, ECONOMIC AND SCALE EFFICIENCY OF BROILER FARMS

2021 ◽  
Vol 52 (2) ◽  
pp. 291-300
Author(s):  
Fardos A.M. Hassan
Keyword(s):  
Returns To Scale ◽  
Sampling Technique ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Policy Makers ◽  
Education Experience ◽  
Level Of Training ◽  
Constant Returns To Scale ◽  
Variable Returns To Scale

This study was surveyed and evaluated technical, economic and scale efficiency of broiler farms in Egypt using DEA technique. So as to accomplish the specified aim, stratified random sampling technique was utilized to gather information from 150 broiler farms. The results showed that mean technical efficiencies of broiler farms were 0.915 and 0.985 under constant returns to scale (CRS) and variable returns to scale (VRS) respectively, implying that on average the farms could reduce input utilization by 8.5% and 1.5% for production level of output to be technically efficient. Notably, 48.7% of the farms were estimated fully technical efficient under VRS-model. The mean allocative and economic efficiency of the farms were assessed as 0.941 and 0.918 respectively, with only 2% of the farms were fully allocative and economic efficient. Furthermore, the average scale efficiency was 0.929 with the majority of broiler farms (82%) were operating with increasing returns to scale. The estimated Tobit regression showed that farmer's age, education, experience, access to extension services, and level of training were the most significant variables contributing to the disparities in efficiency of broiler farms. Such results are useful for extension workers and policy makers so as to guide policies towards expanding efficiency. 

Data envelopment analysis for estimating efficiency of intensive care units: a case study in Iran

2018 ◽  
Vol 31 (4) ◽  
pp. 276-282 ◽  
Author(s):  
Mohammad Amin Bahrami ◽  
Sima Rafiei ◽  
Mahdieh Abedi ◽  
Roohollah Askari
Keyword(s):  
Intensive Care ◽  
Data Envelopment Analysis ◽  
Intensive Care Units ◽  
Service Providers ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Comparative Performance ◽  
Content Type ◽  
Low Efficiency

Purpose As hospitals are the most costly service providers in every healthcare systems, special attention should be given to their performance in terms of resource allocation and consumption. The purpose of this paper is to evaluate technical, allocative and economic efficiency in intensive care units (ICUs) of hospitals affiliated by Yazd University of Medical Sciences (YUMS) in 2015. Design/methodology/approach This was a descriptive, analytical study conducted in ICUs of seven training hospitals affiliated by YUMS using data envelopment analysis (DEA) in 2015. The number of physicians, nurses, active beds and equipment were regarded as input variables and bed occupancy rate, the number of discharged patients, economic information such as bed price and physicians’ fees were mentioned as output variables of the study. Available data from study variables were retrospectively gathered and analyzed through the Deap 2.1 software using the variable returns to scale methodology. Findings The study findings revealed the average scores of allocative, economic, technical, managerial and scale efficiency to be relatively 0.956, 0.866, 0.883, 0.89 and 0.913. Regarding to latter three types of efficiency, five hospitals had desirable performance. Practical implications Given that additional costs due to an extra number of manpower or unnecessary capital resources impose economic pressure on hospitals also the fact that reduction of surplus production plays a major role in reducing such expenditures in hospitals, it is suggested that departments with low efficiency reduce their input surpluses to achieve the optimal level of performance. Originality/value The authors applied a DEA approach to measure allocative, economic, technical, managerial and scale efficiency of under-study hospitals. This is a helpful linear programming method which acts as a powerful and understandable approach for comparative performance assessment in healthcare settings and a guidance for healthcare managers to improve their departments’ performance.

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.

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.

GREEN OPEN ACCESS IN KENYA: A REVIEW OF THE CONTENT, POLICIES AND USAGE OF INSTITUTIONAL REPOSITORIES

Mousaion ◽  
2016 ◽  
Vol 33 (3) ◽  
pp. 25-54
Author(s):  
Wanyenda Leonard Chilimo
Keyword(s):  
Developing Countries ◽  
Open Access ◽  
Descriptive Study ◽  
Google Scholar ◽  
Research Institutions ◽  
Journal Articles ◽  
Content Type ◽  
Institutional Repositories ◽  
Current State ◽  
Theses And Dissertations

 There is scant research-based evidence on the development and adoption of open access (OA) and institutional repositories (IRs) in Africa, and in Kenya in particular. This article reports on a study that attempted to fill that gap and provide feedback on the various OA projects and advocacy work currently underway in universities and research institutions in Kenya and in other developing countries. The article presents the findings of a descriptive study that set out to evaluate the current state of IRs in Kenya. Webometric approaches and interviews with IR managers were used to collect the data for the study. The findings showed that Kenya has made some progress in adopting OA with a total of 12 IRs currently listed in the Directory of Open Access Repositories (OpenDOAR) and five mandatory self-archiving policies listed in the Registry of Open Access Repositories Mandatory Archiving Policies (ROARMAP). Most of the IRs are owned by universities where theses and dissertations constitute the majority of the content type followed by journal articles. The results on the usage and impact of materials deposited in Kenyan IRs indicated that the most viewed publications in the repositories also received citations in Google Scholar, thereby signifying their impact and importance. The results also showed that there was a considerable interest in Swahili language publications among users of the repositories in Kenya.

scholarly journals Does Farm Size and Specialization Matter for Productive Efficiency? Results from Kansas

2011 ◽  
Vol 43 (4) ◽  
pp. 515-528 ◽  
Author(s):  
Amin W. Mugera ◽  
Michael R. Langemeier
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Production Technology ◽  
Returns To Scale ◽  
Productive Efficiency ◽  
Farm Size ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Sample Period ◽  
Analysis Techniques

In this article, we used bootstrap data envelopment analysis techniques to examine technical and scale efficiency scores for a balanced panel of 564 farms in Kansas for the period 1993–2007. The production technology is estimated under three different assumptions of returns to scale and the results are compared. Technical and scale efficiency is disaggregated by farm size and specialization. Our results suggest that farms are both scale and technically inefficient. On average, technical efficiency has deteriorated over the sample period. Technical efficiency varies directly by farm size and the differences are significant. Differences across farm specializations are not significant.

Efficiency evaluation of Indian oil and gas sector: data envelopment analysis

2019 ◽  
Vol 14 (2) ◽  
pp. 362-378 ◽  
Author(s):  
Vikas Vikas ◽  
Rohit Bansal
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Capital Investment ◽  
Oil And Gas ◽  
Stock Exchange ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Content Type ◽  
Indian Economy ◽  
Oil And Gas Sector

Purpose Data envelopment analysis (DEA), a non-parametric technique is used to assess the efficiency of decision-making units which are producing identical set of outputs using identical set of inputs. The purpose of this paper is to find the technical efficiency (TE), pure technical efficiency and scale efficiency (SE) levels of Indian oil and gas sector companies and to provide benchmark targets to the inefficient companies in order to achieve efficiency level. Design/methodology/approach In the present study, a group of 22 oil and gas companies which are listed on the National Stock Exchange for which the data were available for the period 2013–2017 has been considered. DEA has been performed to compare the efficiency levels of all companies. To measure efficiency, three input variables, namely, combined materials consumed and manufacturing expenses, employee benefit expenses and capital investment and two output variables – operating revenues and profit after tax (PAT) have been considered. On the basis of performance for the financial year ending 2017, benchmark targets based on DEA–CCR (Charnes, Cooper and Rhodes) model have been provided to the inefficient companies that should be focused upon by them to attain the efficiency level. The performance of the companies for the past five years has been examined to check the fluctuations in the various efficiency scores of the companies considered in the study over the years. Findings From the results obtained, it is observed that 59 percent, i.e. 13 out of 22 companies are technically efficient. By considering DEA BCC (Banker, Charnes and Cooper) model, 16 companies are observed to be pure technically efficient. In terms of SE, there are 14 such companies. The inefficient units need to improve in terms of input and output variables and for this motive, specified targets are assigned to them. Some of these companies need to upgrade significantly and the managers must take the concern earnestly. The study has also thrown light on the performance of the companies over last five years which shows Oil India Ltd, Gujarat State Petronet Ltd, Petronet LNG Ltd, IGL Ltd, Mahanagar Gas, Chennai Petroleum Corporation Ltd and BPCL Ltd as consistently efficient companies. Research limitations/implications The present study has made an attempt to evaluate the efficiency of Indian oil and gas sector. The results of the study have significant inferences for the policy makers and managers of the companies operating in the sector. The results of the study provide benchmark target level to the companies of Oil and Gas sector which can help the managers of the relatively less efficient companies to focus on the ways to improve efficiency. The improvement in efficiency of a company would not only benefit the shareholders, but also the investors and other stakeholders of the company. Originality/value In the context of Indian economy, very limited number of studies have focused to measure the efficiency of oil and gas sector in the context of Indian economy. The present study aims to provide the latest insight to the efficiency of the companies especially operating in the Indian oil and gas sector. Further, as per our knowledge, this study is distinctive in terms of analyzing the efficiency of Indian oil and gas sector for a period of five years. The longitudinal study of the sector efficiency provides a bird eye view of the average efficiency level and changes in the efficiency levels of the companies over the years.

Macroeconomics of money laundering: effects and measurements

2017 ◽  
Vol 24 (1) ◽  
pp. 65-81 ◽  
Author(s):  
Nella Hendriyetty ◽  
Bhajan S. Grewal
Keyword(s):  
Developing Countries ◽  
Money Laundering ◽  
Tax Evasion ◽  
Developed Countries ◽  
Tax Revenue ◽  
Negative Effects ◽  
Policy Makers ◽  
Content Type ◽  
Macroeconomic Conditions ◽  
Illicit Flows

Purpose The purpose of this paper is to review studies focusing on the magnitude of money laundering and their effects on a country’s economy. The relevant concepts are identified on the basis of discussions in the literature by prominent scholars and policy makers. There are three main objectives in this review: first, to discuss the effects of money laundering on a country’s macro-economy; second, to seek measurements from other scholars; and finally, to seek previous findings about the magnitude and the flows of money laundering. Design/methodology/approach In the first part, this paper outlines the effects of money laundering on macroeconomic conditions of a country, and then the second part reviews the literature that measures the magnitude of money laundering from an economic perspective. Findings Money laundering affects a country’s economy by increasing shadow economy and criminal activities, illicit flows and impeding tax collection. To minimise these negative effects, it is necessary to quantify the magnitude of money laundering relative to economic conditions to identify the most vulnerable aspects of money laundering in a country. Two approaches are used in this study: the first is the capital flight approach, as money laundering will cause flows of money between countries; the second is the economic approach for measuring money laundering through economic variables (e.g. tax revenue, underground economy and income generated by criminals) separately from tax evasion. Originality/value The paper offers new insights for the measurement of money laundering, especially for developing countries. Most methods in quantifying money laundering have focused on developed countries, which are less applicable to developing countries.

scholarly journals Efficiency of Estonian grain farms in 2000 2004

2008 ◽  
Vol 17 (1) ◽  
pp. 31 ◽  
Author(s):  
N. VASILIEV ◽  
A. ASTOVER ◽  
M. MÕTTE
Keyword(s):  
Parametric Method ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Small Scale ◽  
Data Envelopment ◽  
The European Union ◽  
New Member States ◽  
Farm Scale ◽  
Grain Farms ◽  
The Eu

The aim of this study is to analyse the efficiency of Estonian grain farms after Estonia’s transition to a market economy and during the accession period to the European Union (EU). The non-parametric method Data Envelopment Analysis (DEA) was used to estimate the total technical, pure technical and scale efficiency of Estonian grain farms in 2000–2004. Mean total technical efficiency varied from 0.70 to 0.78. Of the grain farms 62% are operating under increasing returns to scale. Solely based on the DEA model it is not possible to determine optimum farm scale and the range of Estonian farm sizes operating efficiently is extensive. The most pure technically efficient farms were the smallest and the largest but the productivity of small farms is low compared to larger farms because of their small scale. Therefore, they are the least competitive. Since pre-accession period to the EU, large input slacks of capital have replaced the former excessive use of labour and land. This raises the question about the effects on efficiency of the EU’s investment support schemes in new member states.;

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