ASSESSING TECHNICAL EFFICIENCY OF INNOVATIONS IN CANADA: THE GLOBAL SNAPSHOT

2019 ◽  
Vol 23 (03) ◽  
pp. 1950025 ◽  
Author(s):  
WOJCIECH NASIEROWSKI
Keyword(s):  
Technical Efficiency ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Simulation Experiments ◽  
Canadian Perspective ◽  
Country Characteristics ◽  
Policy Measures ◽  
The Subject ◽  
Definition Of ◽  
Innovation Approach

This paper presents the results of a comparison of the technical efficiency of innovation approach in Canada to approaches in 41 other countries. Data Envelopment Analysis was used to investigate this subject. Results of simulation experiments were used to anticipate possible general suggestions regarding policy measures that may be considered when exploring means to improve Canadian performance. Data from the World Competitiveness Yearbook and European Innovation Scoreboard were used. Oslo Manual definition of innovations was used. Enablers (context) — difficult to change country characteristics that may impact upon technical efficiency — were entered into the examination. A qualitative overview of the Canadian perspective to innovations supplements the quantitative portion of the presentation. It is observed that return to scale and congestion issues dominate considerations on technical efficiency of innovations. Wealthier countries seem to be less technically efficient in innovations than not so rich ones. Canada operates under Decreasing Returns to Scale. Congestions seem to be the main contributor to inefficiencies. Suggestions regarding the betterment of technical efficiency of innovations in Canada are presented here. Attention was drawn to several questions for further studies on the subject and their importance clarified.

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.

scholarly journals Levels, Trends and Determinants of Technical Efficiency of General Hospitals in Uganda: Data Envelopment Analysis and Tobit Regression Analysis

2020 ◽  
Author(s):  
Rogers Ayiko ◽  
Paschal N. Mujasi ◽  
Joyce Abaliwano ◽  
Dickson Turyareeba ◽  
Rogers Enyaku ◽  
...  
Keyword(s):  
Technical Efficiency ◽  
Average Length ◽  
Returns To Scale ◽  
Geographical Location ◽  
Data Envelopment ◽  
Tobit Regression ◽  
General Hospitals ◽  
Hospital Size ◽  
Average Length Of Stay ◽  
Variable Returns To Scale

Abstract Background: General hospitals provide a wide range of primary and secondary healthcare services. They accounted for 38% of government funding to health facilities, 8.8% of outpatient department visits and 28% of admissions in Uganda in the financial year 2016/17. We assessed the levels, trends and determinants of technical efficiency of general hospitals in Uganda from 2012/13 to 2016/17. Methods: We undertook input-oriented Data Envelopment Analysis to estimate technical efficiency of 78 general hospitals using data abstracted from the Annual Health Sector Performance Reports for 2012/13, 2014/15 and 2016/17. Trends in technical efficiency was analysed using Excel while determinants of technical efficiency were analysed using Tobit Regression Model in STATA 15.1. Results: The Average Constant Returns to Scale, Variable Returns to Scale and Scale Efficiency of general hospitals for 2016/17 were 49% (95% CI, 44% - 54%), 69% (95% CI, 65% - 74%) and 70% (95% CI, 65% - 75%) respectively. There was no statistically significant difference in the efficiency scores of public and private hospitals. Technical efficiency generally increased from 2012/13 to 2014/15, and dropped by 2016/17. Some hospitals were persistently efficient while others were inefficient over this period. Hospital size, geographical location, training status and average length of stay were statistically significant determinants of efficiency at 5% level of significance. Conclusion: The 69% average variable returns to scale technical efficiency indicates that the hospitals could generate the same volume of outputs using 31% (3,439) less staff and 31% (3,539) less beds. Benchmarking performance of the efficient hospitals would help to guide performance improvement in the inefficient ones. There is need to incorporate hospital size, geographical location, training status and average length of stay in the resource allocation formula and adopt annual hospital efficiency assessments.

Technical Efficiency of State Road Transport Undertakings in India - Data Envelopment Analysis

2012 ◽  
Vol 1 (2) ◽  
pp. 31-42 ◽  
Author(s):  
V. Prakash ◽  
J. Rajesh ◽  
M. Thilagam
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Relative Efficiency ◽  
Fuel Efficiency ◽  
Returns To Scale ◽  
Road Transport ◽  
Data Envelopment ◽  
Variable Returns To Scale ◽  
Decision Making Units

Data envelopment analysis (DEA) is a method of analyzing the relative efficiency of similar types of organizations known as decision making units (DMU’s). In this paper, DEA model is applied to evaluate the relative technical efficiency of state road transport undertakings (SRTU’s) in India during the period 2011-2012. The authors have considered thirty-four SRTU’s functioning in India. The variables chosen to characteristic production units are the number of fleet held, staff strength and fuel efficiency as inputs and Passengers carried as output. The BCC model is input- oriented allowing for variable returns to scale (VRS), units are ranked and the projection analyses are given.

Efficiency of glass firms in India: an application of data envelopment analysis

2016 ◽  
Vol 13 (1) ◽  
Author(s):  
Mini Kundi ◽  
Seema Sharma
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Design Methodology ◽  
Large Scale ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Efficiency Measures ◽  
Target Values ◽  
Practical Implications

Purpose The purpose of the present study is to evaluate the efficiency of glass firms in India. Design/methodology/approach Data envelopment analysis (DEA) has been employed to study the technical, scale and super efficiency measures of glass firms in India. Findings Major findings of DEA analysis show that 65 percent firms are found to be technically efficient. Returns to scale analysis indicate that five firms are operating at decreasing returns to scale and two firms are exhibiting increasing returns to scale. Further, results show that small– and medium–scale firms are more efficient than large–scale firms. Old firms are more efficient compared to the young firms and foreign-owned firms are technically more efficient compared to the domestic firms. Practical implications The results of this study would help the managers to assess their relative efficiency and take corrective measures to efficiently use their resources. Originality/value This seems to be the first study to apply DEA to analyze the efficiency of glass firms in India. No previous study on glass industry seems to have decomposed the measure of overall technical efficiency into its components, namely pure technical efficiency and scale efficiency and no study seems to have examined whether ownership, age and size of a firm are significant for its efficiency. In addition, no earlier study seems to have ranked the glass firms based on their efficiency values. Further, target values of inputs and outputs are demonstrated in this study. Stability of efficiency scores is also checked.

scholarly journals Levels, Trends and Determinants of Technical Efficiency of General Hospitals in Uganda: Data Envelopment Analysis and Tobit Regression Analysis

2020 ◽  
Author(s):  
Rogers Ayiko ◽  
Paschal N. Mujasi ◽  
Joyce Abaliwano ◽  
Dickson Turyareeba ◽  
Rogers Enyaku ◽  
...  
Keyword(s):  
Technical Efficiency ◽  
Average Length ◽  
Returns To Scale ◽  
Geographical Location ◽  
Data Envelopment ◽  
Tobit Regression ◽  
General Hospitals ◽  
Hospital Size ◽  
Average Length Of Stay ◽  
Variable Returns To Scale

Abstract Background: General hospitals provide a wide range of primary and secondary healthcare services. They accounted for 38% of government funding to health facilities, 8.8% of outpatient department visits and 28% of admissions in Uganda in the financial year 2016/17. We assessed the levels, trends and determinants of technical efficiency of general hospitals in Uganda from 2012/13 to 2016/17. Methods: We undertook input-oriented Data Envelopment Analysis to estimate technical efficiency of 78 general hospitals using data abstracted from the Annual Health Sector Performance Reports for 2012/13, 2014/15 and 2016/17. Trends in technical efficiency was analysed using Excel while determinants of technical efficiency were analysed using Tobit Regression Model in STATA 15.1. Results: The Average Constant Returns to Scale, Variable Returns to Scale and Scale Efficiency of general hospitals for 2016/17 were 49% (95% CI, 44% - 54%), 69% (95% CI, 65% - 74%) and 70% (95% CI, 65% - 75%) respectively. There was no statistically significant difference in the efficiency scores of public and private hospitals. Technical efficiency generally increased from 2012/13 to 2014/15, and dropped by 2016/17. Some hospitals were persistently efficient while others were inefficient over this period. Hospital size, geographical location, training status and average length of stay were statistically significant determinants of efficiency at 5% level of significance. Conclusion: The 69% average variable returns to scale technical efficiency indicates that the hospitals could generate the same volume of outputs using 31% (3,439) less staff and 31% (3,539) less beds. Benchmarking performance of the efficient hospitals would help to guide performance improvement in the inefficient ones. There is need to incorporate hospital size, geographical location, training status and average length of stay in the resource allocation formula and adopt annual hospital efficiency assessments.

scholarly journals Estimation of technical efficiency of cattle feedlot system in Adamawa State, Nigeria: Comparison among estimators

2020 ◽  
Vol 12 (1) ◽  
pp. 24-30
Author(s):  
B.H. Gabdo ◽  
M.R. Ja’afar-Furo ◽  
M.Y. Hamid ◽  
Y.A. Thlaffa
Keyword(s):  
Technical Efficiency ◽  
Animal Feed ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Free Disposal Hull ◽  
Total Cost ◽  
Free Disposal ◽  
Feed Cost ◽  
Salt Lick ◽  
Cattle Feedlot

Abstract. This study adopts an output oriented Shephard Distance Function (SDF) to estimate Technical Efficiency (TE) in cattle feedlot under five distinct estimators (Data Envelopment Analysis /DEA/, Free Disposal Hull /FDH/, Order-m, Order-α and Bootstrap). The aim is to rank the efficiency estimates based on descending order of the TE estimates from the five estimators and test the hypotheses of mean difference across the estimators. In addition, the independent variables used in the feedlot system were also ranked based on magnitude to total cost. Results show initial cost of animal, feed cost, water cost, labour cost, depreciation, medicaments and cost of salt lick are ranked 1st, 2nd, 3rd, 4th, 5th, 6th and 7th, respectively, in terms of proportion to total cost. The study found a combination of inappropriate scale of production and managerial problems as the causes of inefficiency in the cattle feedlot. The study advocates for proper pricing of inputs, commensurate and timely utilization of inputs to avert input waste. Similarly, the study recommends up-scaling (178 cattle feedlot) and down-scaling (92 cattle feedlot) the cattle feedlot production owing to their operation at increasing and decreasing returns to scale, respectively, to attain enhanced efficiency.

scholarly journals Technical Efficiency Of Social Foundations In A Multidimensional Context

2010 ◽  
Vol 9 (11) ◽  
Author(s):  
Imelda S. Dorado ◽  
Emilyn Cabanda
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Returns To Scale ◽  
The Philippines ◽  
Data Envelopment ◽  
Non Profit ◽  
Dea Model ◽  
Social Foundations ◽  
Efficiency Assessment ◽  
Constant Returns To Scale

The paper is the first attempt at examining the technical efficiency and benchmarking the performance of 15 social foundations in the Philippines for the period 2000-2005 using the data envelopment analysis (DEA) model. The 65.55% of social foundations are operating at increased returns to scale, 4.45% at decreased returns to scale and 30% at constant returns to scale. Forty percent of firms are efficiently utilizing their expenses and the majority shows resource excesses (capital and labor). All firms show output deterioration for donations and total awards to beneficiaries. With the aid of the DEA tool, measurement of the efficiency of social foundations has been verified and proven as manageable and quantifiable from a multidimensional assessment. Results reveal the importance of technical efficiency assessment for the non-profit sector.

Technical efficiency: the pathway to credit union cost efficiency in Ghana

2018 ◽  
Vol 44 (11) ◽  
pp. 1292-1310
Author(s):  
Benjamin Amoah ◽  
Kwaku Ohene-Asare ◽  
Godfred Alufar Bokpin ◽  
Anthony Q.Q. Aboagye
Keyword(s):  
Technical Efficiency ◽  
Cost Efficiency ◽  
Banking Sector ◽  
Returns To Scale ◽  
Credit Unions ◽  
Credit Union ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Content Type ◽  
Macroeconomic Conditions

Purpose The purpose of this paper is to investigate the factors that tend to influence credit union efficiency, specifically examining cost efficiency (CE) and technical efficiency. Design/methodology/approach Using a two-stage method, the authors first estimate CE using Tones’ SBM data envelopment analysis method and technical efficiency in a variable returns to scale setting during the period 2008–2014. The authors estimate a mixed-effects and two-limit Tobit regression to examine the effect of credit union specific characteristics, banking industry and macroeconomic conditions, on efficiency. Findings Credit unions’ CE averaged 38.9 percent compared to 54.4 percent for technical efficiency. The authors find that technical efficiency does not translate into CE and vice versa. Practical implications The authors suggest that when targeting CE, credit union managers would have to make technical efficiency a priority. A monopolized and inefficient banking sector does not challenge efficiency improvement in the credit unions industry. Originality/value This study employs data from a frontier market.

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 Access to Credit and Farm Efficiency in Cameroon: A Data Envelopment Analysis Approach

2021 ◽  
pp. 48-62
Author(s):  
Orelien Tresor Feumba Tchamba
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Returns To Scale ◽  
Farm Households ◽  
Farm Size ◽  
Data Envelopment ◽  
Agricultural Field ◽  
Access To Credit ◽  
Farm Efficiency ◽  
Constant Returns To Scale

The aims of this paper is to analyze the effect of access to credit on the technical efficiency of farms in Cameroon’s rural area. Using a sample of 545 farm households, we first estimate a Data Envelopment Analysis (DEA) model with constant returns to scale; then a censored TOBIT model enabling us to identify factors of efficiency, especially the effect of access to credit on efficiency. Two main results emerge from our analysis. First, we find that on average, the level of technical efficiency of farms is 56.78%; showing therefore the possibility of substantial efficiency gains. Second, farm size, association membership, and fertilizer expenditure negatively affect technical efficiency, while access to credit, age and education increase it. Based on these results, we believe that it’s interesting for farm householders to organize themselves in associations to benefit from available credits and financial facilities and to share their experiences in the agricultural field in order to improve their efficiency.

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