Eco-innovation analysis of OECD countries with common weight analysis in data envelopment analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Reza Kiani Mavi ◽  
Neda Kiani Mavi ◽  
Reza Farzipoor Saen ◽  
Mark Goh

PurposeDespite unanimity in the literature that eco-innovation (EI) leads to sustainable development, evidence remains limited on measuring EI efficiency with the Malmquist productivity index (MPI). In conventional data envelopment analysis (DEA) models, decision-making units (DMUs) are inclined to assign more favorable weights, even zero, to the inputs and outputs to maximize their own efficiency. This paper aims to overcome this shortcoming by developing a common set of weights (CSW). Design/methodology/approachUsing goal programming, this study develops a CSW model to evaluate the EI efficiency of the organization for economic co-operation and development (OECD) countries and track their changes with MPI during 2010–2018. FindingsAchieving a complete ranking of DMUs, findings show the higher discrimination power of the proposed CSW compared with the original DEA models. Furthermore, results reveal that Iceland, Latvia and Luxembourg are the only OECD countries that have incessantly improved their EI productivity (MPI > 1) from 2010 to 2018. On the other hand, Japan is the OECD country that has experienced the highest yearly EI efficiency during 2010–2018. This paper also found that Iceland has the highest MPI over 2010–2018. Practical implicationsMore investment in environmental research and development (R&D) projects instead of generic R&D enables OECD members to realize more opportunities for sustainable development through minimizing energy use and environmental pollution in any form of waste and greenhouse gas emissions. Originality/valueIn addition to developing a novel common weights model for DEA-MPI to measure and evaluate the EI of OECD countries, this paper develops a CSW model by including the undesirable outputs for EI analysis.

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Slađana Savović ◽  
Predrag Mimović

PurposeThe purpose of this paper is to explore the effects of cross-border acquisitions on the efficiency and productivity of acquired companies in the cement industry in the context of a transitional economy.Design/methodology/approachThe Data Envelopment Analysis (DEA) and Malmquist Productivity Index were used to assess the efficiency and productivity of the acquired companies over the period 2000–2018. DEA and Malmquist index are combined with bootstrapping to perform succinct statistical inferences for determining the accuracy of results. The study assesses partial efficiency and productivity of three inputs: material, capital and labour, as well as the total factor efficiency and productivity of the acquired companies in the short and long term after the acquisitions.FindingsThe research results suggest that efficiency of material, efficiency of labour and the total factor efficiency of the acquired companies are higher after the acquisitions than before, while efficiency of capital is lower. In addition, the results show that the acquisitions had a positive impact on total factor productivity of the acquired companies.Practical implicationsThe results of this study have practical implications for managers, especially for policy-makers and industry analysts in deciding whether to encourage or discourage cross-border acquisitions in transitional economies.Originality/valueThe study contributes to a better understanding of the impact of cross-border acquisitions on efficiency and productivity of acquired companies in the manufacturing industry. Research in transitional economies related to subject matter is limited, and this study is the first empirical investigation of the effect of cross-border acquisitions on the efficiency and productivity in the cement industry in Serbia by applying the Data Envelopment Analysis.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahmoud Abdelrahman Kamel ◽  
Mohamed El-Sayed Mousa ◽  
Randa Mohamed Hamdy

PurposeThis study used data envelopment analysis (DEA) models to measure financial efficiency of twelve commercial banks listed in the Egyptian stock exchange (CBLSE), along with evaluating changes to the financial efficiency during the period 2017–2019.Design/methodology/approachThe study used BCC-I, cross-efficiency, super-efficiency models, and Malmquist productivity index (MPI) to assess financial efficiency of the examined banks. The available data from both inputs and outputs were analyzed using R. studio V.I.3. 1056 software.FindingsOut of twelve banks examined, only four banks were efficient under BCC-I model over different years of the study period; however, only one bank (CIB) appeared to be the most efficient compared to other peers in the study sample. Moreover, MPI results revealed decreased financial efficiency during the study period, due to the decreased technological innovation, except for HDB. Tobit regression results confirmed that total assets and total equity are significant factors impacted financial efficiency of CBLSE.Practical implicationsThis study sheds light on the importance of evaluating financial efficiency of CBLSE to all stakeholders, to pinpoint weaknesses in banks' performance, and for evaluating financial policies and investment decisions.Originality/valueSeveral studies sought to implement different models of DEA to assess banking performance in different regions of the world, but very few studies examined financial efficiency of banks. To the best of authors’ knowledge, this study is one of those few that addressed financial efficiency of banks in Egypt.


2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Farhad Hosseinzadeh Lotfi ◽  
Golamreza Jahanshahloo ◽  
Mohsen Vaez-Ghasemi ◽  
Zohreh Moghaddas

Data envelopment analysis (DEA) models can calculate the Malmquist Productivity Index (MPI). Classic Malmquist Productivity Index shows regress and progress of a DMU in different periods with efficiency and technology variations without considering the present value of money. This issue is of major importance since while a currency of in previous year is not equal to that of now this would yield bias results which can affect the correct interpretation. The index developed here is defined in terms of Modified Malmquist Productivity Index model, which can calculate progress and regress by using the factor of present time value of money. The incorporation of present time value of money is also calculated within the framework of data envelopment analysis. This factor is fundamental and should be considered in DEA Malmquist Productivity Index. Moreover, here, differences between presented models are compared to those of previous ones indeed, biased results will be shown in the case study in banks, and problem and solution have been investigated in the literature.


2017 ◽  
Vol 59 (6) ◽  
pp. 826-838 ◽  
Author(s):  
Aminath Amany Ahmed ◽  
Azhar Mohamad

Purpose In this study, the authors use data envelopment analysis to assess the technical efficiency and performance of real estate investment trusts (REITs) in Singapore, for the years 2009 through 2013. Design/methodology/approach The authors apply the Malmquist Productivity Index to express the productivity change of the REITs over time. Findings The authors find that while most REITs have experienced efficiency improvements, there has been little productivity growth at the frontier during the study period. Originality/value The finding indicates that it is possible to improve the performance of the REITs by further improving technological efficiency because technological regress has been the main reason for the poor productivity growth of the REITs in Singapore.


2018 ◽  
Vol 25 (9) ◽  
pp. 3570-3591 ◽  
Author(s):  
Aradhana Vikas Gandhi ◽  
Dipasha Sharma

Purpose The purpose of this paper is to ascertain the performance of Indian hospitals in recent past and derive meaningful insights for policy makers and practicing managers in this area. Design/methodology/approach This paper analyses the technical efficiency of select Indian private hospitals using three related methodologies: data envelopment analysis (DEA), Malmquist Productivity Index (MPI) and Tobit regression. Two output variables (i.e. total income and profit after tax) and four input variables (i.e. cost of labour, net fixed assets, current assets and other operating expenses) were selected for the purpose of the study. Findings DEA analysis has shown that 14 out of 37 hospitals are found to be efficient under the Cooper and Rhodes model of DEA and 20 out of 37 hospitals are efficient under the Banker, Charles and Cooper model of DEA. The empirical results pertaining to MPI indicate an overall productivity progress in the private Indian hospital industry during the study period, which is largely due to technological advancement in the industry. Tobit regression demonstrates that chain affiliated, specialized and multi-city located hospitals exhibit a higher technical efficiency. Research limitations/implications This study has a limitation with reference to the unavailability of data on the input and output parameters of the model. The data related to the number of beds, number of doctors, number of nurses, etc., were not available for the period under consideration. Originality/value This study seems to be one of the few studies applying productivity and performance analysis using DEA, MPI and Tobit regression for the Indian private hospital industry.


2020 ◽  
Vol 5 (2) ◽  
pp. 193-210
Author(s):  
Shih-Liang Chao ◽  
Yi-Hung Yeh

Purpose This study aims to measure the productivity of 21 major shipyards in China, South Korea and Japan. Design/methodology/approach Data envelopment analysis was applied to measure the productivity of shipyards. The contemporaneous and intertemporal productivity scores of each shipyard were measured. Additionally, the technical gaps among shipyards in China, South Korea and Japan were measured and compared. Findings The results indicate that Japan led the global shipbuilding industry in 2014 and South Korea dominated in 2015. Additionally, from 2014 to 2015, shipyards in South Korea and Japan maintained their levels of productivity. Comparatively, major shipyards in China made substantial progress from 2014 to 2015, revealing their strong ambition to improve productivity. Originality/value This study first used a metafrontier framework to measure the technical gap of shipyards among major shipbuilding countries. The model and approach objectively analyze the productivity of major shipyards and considers their nationalities. Additionally, this study is the first to measure changes in the productivity of shipyards. By decomposing the metafrontier Malmquist productivity index, major shipyards were categorized into eight sets. The results of this study can provide a clear direction for shipyards to improve their productivity.


2018 ◽  
Vol 29 (5) ◽  
pp. 664-684 ◽  
Author(s):  
Qingyou Yan ◽  
Xu Wang ◽  
Tomas Baležentis ◽  
Dalia Streimikiene

This paper presents a modified environmental production technology which imposes the proper disposability on the undesirable outputs depending on the underlying technical properties. Then, aggregate and disaggregate (Russell-type) data envelopment analysis (DEA) models are proposed to evaluate the energy–economy–environment (3E) efficiency based on the modified technology (hereafter referred to as the 3E-DEA models). The non-radial Malmquist productivity index is adapted to model the changes in the 3E productivity over time. A case study of 3E efficiency analysis for the 30 Chinese administrative regions during 2011–2013 is presented. In general, Chinese regions did not perform well in terms of 3E goals as only three of them exhibited full efficiency. It was also found out that the eastern area showed the best 3E performance, whereas the central area followed suit, thus putting the western area at end of ranking. Still, some regions in the eastern area showed 3E efficiencies lower than those of some cities in the central and eastern areas. Anyway, most of the regions showed improving 3E productivity during 2011–2013.


Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3915 ◽  
Author(s):  
Nelson Amowine ◽  
Zhiqiang Ma ◽  
Mingxing Li ◽  
Zhixiang Zhou ◽  
Benjamin Azembila Asunka ◽  
...  

In Africa, energy plays an important role in the processes of economic and sustainable development. However, inefficiency such as mismanagement of resources constrains productivity. Prior energy efficiency studies in Africa have failed to provide the paths through which energy efficiency improvement can be achieved. The current study aims to assess energy efficiency improvement among 25 selected countries in Africa. First, the dynamic slack-based measure (DSBM) data envelopment analysis (DEA) model is applied to gauge the efficiency measurement. Further, the Malmquist productivity index (MPI) is employed to investigate the energy efficiency improvement during 2006–2014. Empirically, the results from the dynamic slack-based measure (DSBM) model show that energy efficiency in Africa is generally low. Also, the findings from the MPI suggest there is no significant improvement in energy efficiency in Africa. Based on the estimated results, some energy efficiency improvement strategies are further proposed for sample countries in Africa.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mustafa İsa Doğan ◽  
Volkan Soner Özsoy ◽  
H. Hasan Örkcü

Purpose The Covid-19 pandemic spread rapidly around the world and required strict restriction plans and policies. In most countries around the world, the outbreak of the disease has been serious and has greatly affected the health system and the economy. The factors such as the number of patients with chronic diseases, the number of people over 65 years old, hospital facilities, the number of confirmed Covid-19 cases, the recovering Covid-19 cases and the number of deaths affect the rate of spread of Covid-19. This study aims to evaluate the performances of 21 Organisation for Economic Co-operation and Development (OECD) countries against the Covid-19 outbreak using three data envelopment analysis (DEA) models. Design/methodology/approach In this study, the performance of 21 OECD countries to manage the Covid-19 process has been analysed weekly via DEA which is widely used in various practical problems and provides a general framework for efficiency evaluation problems using the inputs and outputs of decision-making units. Findings The analysis showed that 11 countries out of 21 countries were efficient for selected weeks. According to the DEA results from the 20-week review (09 April 2020–20 August 2020), information about the course of the epidemic prevention and the normalization process for any country can be obtained. Originality/value In this study, due to the problem of the discrimination power of DEA, the cross-efficiency model and the super-efficiency model also used. In addition, the output-oriented model was preferred in this study for Covid-19 management efficiency.


2014 ◽  
Vol 42 (6) ◽  
pp. 500-520 ◽  
Author(s):  
Aradhana Gandhi ◽  
Ravi Shankar

Purpose – The purpose of this paper is to analyze the performance of Indian retailers in recent past and derive meaningful insight for practicing managers in this area. Design/methodology/approach – This paper analyses the economic efficiencies of select Indian retailers using three related methodologies: Data Envelopment Analysis (DEA), Malmquist Productivity Index (MPI) and Bootstrapped Tobit Regression. Findings – DEA analysis has shown that five retail firms out of selected 18 are found as efficient under the CCR model of DEA and seven out of 18 retail firms are efficient under the BCC model of DEA. MPI results indicate that 61 percent of the firms have progressed in terms of the MPI during the period under consideration. The Bootstrapped Tobit Regression shows that number of retail outlets and mergers and acquisitions can be considered as the driving forces influencing efficiency of retailers in India. Research limitations/implications – The paper has a limitation with reference to the availability of data for a few retail outlets, especially in the modeling through the Bootstrapped Tobit Regression. Originality/value – This study seems to be the first in applying productivity analysis using DEA, MPI and Bootstrapped Tobit Regression for the Indian retail sector.


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