Data Envelopment Analysis Research Articles

Trajectories of persistence in exporting: a capability approach

Purpose The purpose of this paper is answering two research questions: What are the trajectories of persistence in exporting followed by different groups of firms? What factors relate to each trajectory of persistence in exporting? The authors propose and test a framework that links operational and marketing firms’ capabilities to different trajectories of persistence in exporting. Design/methodology/approach Using a dataset of 2,913 firms over 14 years from the annual manufacturing survey in Colombia (AMS), the authors explored the trajectories of persistence in exporting. The authors applied data envelopment analysis to measure operational and marketing capabilities and group-based trajectory modeling to discover and link such trajectories to firms’ capabilities. Findings The authors identified four trajectories of persistence in exporting. Also, the authors found that while the interplay between marketing and operational capabilities relates positively to the non-exporting trajectory and negatively to the persistent trajectory, operational capabilities relate positively to the erratic trajectory and negatively to the slow growth trajectory of persistence in exporting. Meanwhile, marketing capabilities do not relate to any trajectory. Research limitations/implications Policymakers should help firms develop marketing and operational capabilities to compete globally to motivate them to export and persist in exporting. Policymakers should avoid stimulating firms to reinforce learned and familiar capabilities that cannot leverage desirable trajectories of persistence in exporting. Originality/value The authors introduce the trajectories of persistence in exporting, providing a fresh perspective for analyzing exporting behavior over time. The authors have also proposed and tested a unique framework that links operational and marketing firms’ capabilities to these trajectories, thus contributing to the existing body of knowledge on exporting behavior by firms from emerging markets.

Evaluating circular economy performance in the global chemical sector: a dynamic network Data Envelopment Analysis model approach

Evaluating circular economy performance in the global chemical sector: a dynamic network Data Envelopment Analysis model approach

Network data envelopment analysis with interval intermediates under different types of link control

Network data envelopment analysis with interval intermediates under different types of link control

Efficiency Analysis of Turkish Container Ports: SFA or DEA?

Purpose: The study compares the efficiency of Turkish container ports using Stochastic Frontier Analysis and Data Envelopment Analysis. It aims to provide comparative insights for enhancing ports' operational performance. Capacity utilization and operational performance were analyzed in detail through ratio analysis. Methodology: Two efficiency measurement techniques were employed: SFA evaluates efficiency by accounting for random errors and external factors, while DEA assesses relative efficiency by comparing ports to the best performers. Ratio analysis was used to evaluate capacity utilization through current handling capacity and annual growth rates. Findings: Significant differences were observed between SFA and DEA results. Ports like MIP MERSİN and EVYAP demonstrated high efficiency in both methods, while discrepancies were detected in ports like MARDAŞ and ÇELEBİ BANDIRMA. SFA better captures external factors and operational challenges, whereas DEA emphasizes relative efficiency. For instance, MARDAŞ exhibited rapid growth in handling volume but low operational efficiency. Ratio analysis showed varying capacity utilization levels, with some ports operating near full capacity, while others, like AKÇANSA, operate at low capacity and need operational improvements. Originality: The study provides a holistic view of port efficiency by integrating SFA, DEA, and ratio analysis. It not only measures comparative efficiency but also examines ports’ capacity utilization. Differences in efficiency measures were discussed, with SFA offering valuable insights into strategic improvements by effectively reflecting operational challenges and external factors.

A proposed integrated methodology for evaluation and adjustment of Balance of Performance (BoP) schemes in Grand Touring (GT) racecar championships

The concept of Balance of Performance (BoP) has been extensively applied to various forms of motorsports, and especially championships involving Grand Touring (GT) racecars. The organizing bodies of these championships have devised schemes restricting various technical features of the participating racecars, in order to achieve competition parity and subsequently avoid dominance of certain racecars. BoP schemes mainly focus on adjusting engine horsepower and racecar weight, additionally including provisions for restrictions pertinent to aerodynamics, suspension, fuel tank capacity, etc. However, the methodology used by the organizing bodies of motorsports championships in order to evaluate and adjust the BoP schemes is not so transparent to competitors and other interested parts (e.g., racecar manufacturers). In fact, no motorsports organizing body applying the BoP concept to GT racecars, has disclosed details associated with imposing, evaluating, and adjusting the BoP scheme for each championship season. In the current paper, an integrated methodology deploying statistical analysis and Data Envelopment Analysis (DEA) is proposed, for the purpose of evaluating and adjusting BoP schemes in any motorsports championship, primarily focused on GT racecars. The scientifically justified framework along with the simulated application resulting in a performance differentiation range of around 0.40 to 0.45%, comprise strong arguments for the validity and effectiveness of the proposed methodology. In this context, implementation of the proposed methodology by motorsports organizing bodies could potentially render the process of evaluating and adjusting BoP schemes more objective and consequently transparent.

CO2 Emission Efficiency Measurement: Green Logistics Perspective

Purpose: This study aims to measure the carbon emission activities of Turkey, Azerbaijan, Kazakhstan, Kyrgyzstan and Uzbekistan and evaluate them from a green logistics perspective. Method: Within the scope of the research, efficiency analyses were conducted using the output-oriented Data Envelopment Analysis (DEA) constant returns to scale (CRS) model and the super efficiency CRS DEA model. The input and output variables used in the research were obtained from the World Bank website. Findings: In the research, the efficiency scores of the relevant countries were determined. It was determined that the efficiency scores of the countries were generally above 50%. The ranking of the efficient decision-making units among themselves was carried out with the super efficiency CRS DEA model. Some potential improvement suggestions were presented for the decision-making units that were not efficient. Originality: In order to leave a livable world to future generations, green energy production should be supported and Carbon Dioxide (CO2) emissions should be kept under control. Therefore, the efficiency assessment of countries' CO2 emissions is of vital importance. This study has an original feature because the CO2 emission activities of the Turkish Republics were carried out using the super efficiency CRS DEA model. This study can provide guidance to those who will conduct research on this subject and to country leaders.

The Impact of Bank Regulation on Commercial Bank Performance: Evidence From South Africa

ABSTRACTUsing data on South Africa's commercial banks in the period 2005–2018, this paper investigates the impact of bank regulation on bank performance. The study uses a fixed effects model to run the regression model as well as the data envelopment analysis approach to estimate efficiency scores. We find a number of interesting results. First, we find a negative relationship between capital stringency and bank performance, suggesting that increased capital requirements force banks to increase their reserves, adversely affecting their performance. Second, we find a positive relationship between activity restrictions and bank performance, indicating that this kind of regulation, which may well be good for the public as argued by the public interest view of regulation, is also good for the regulated banks. Third, we find a negative and significant relationship between supervisory power and bank performance. Fourth, we find a positive and significant relationship between the market discipline index and bank performance, suggesting that by creating environments characterised by high market discipline, the regulatory regime enhances the ability and incentives of private investors to efficiently monitor banks. This ensures better management of banks, ultimately increasing profitability. Overall, the study finds that regulation matters for bank performance.

Assessing banks efficiency: DEA implementation

By examining intermediate, operating, and profitability aspects, this paper aims to construct a performance model for evaluating the relative efficiency and potential for improvement of 20 banks operating in Serbia for the 2022-2023 period. Data Envelopment Analysis (DEA), which belongs to relatively new data-oriented techniques, was used in the research to measure efficiency. To achieve its goals, the paper makes use of the CCR and BCC, two fundamental DEA models, and three approaches: intermediary, operating and profitability. The results of the analysis showed that the highest efficiency can be attributed o the use of the intermediate approach, while the lowest efficiency of banks can be attributed to the profitability approach. Additionally, the BCC model has higher efficiency compared to the CCR model. According to the analysis results, efficiency has generally grown and is comparatively stable.

Determining the congestion with undesirable outputs of sustainable suppliers using data envelopment analysis

Determining the congestion with undesirable outputs of sustainable suppliers using data envelopment analysis

Research on energy efficiency and carbon efficiency evaluation for copper metallurgy based on data envelopment analysis

Research on energy efficiency and carbon efficiency evaluation for copper metallurgy based on data envelopment analysis

The effect of subsidies and reform options on profit efficiency of trout farms: Focus on energy subsidies

Energy and imported trout egg subsidies hold a pivotal role for Iranian trout farms. They aim to decrease production costs, yet their impact on the profit efficiency of farms remains dubious. The first objective of this paper is to assess how the current subsidy scheme affects the profit efficiency of hatchery and propagation trout farms in Mazandaran, Iran. We examine several subsidy reform scenarios to enhance profit efficiency as a second objective. Standard profit efficiency (SPE) is used to acquire the efficiency of the trout farms using data envelopment analysis. Results show that the majority of farms are inefficient and highly dependent on subsidies. Comparing farms with high efficiency against those with low efficiency as a third aim of research highlights the importance of farms holding a propagation license, engaging in vertical integration, achieving adult trout production surpassing 81 t, and maintaining a fish total feed consumption to trout production ratio below 0.74. Findings from reformation scenarios reveal 1) redirecting the current subsidy towards purchasing the extruder machines for fish feed production, 2) transferring funds to subsidize electricity based on the farm's electricity consumption, and 3) opting for the production of genetically modified eggs gives higher SPE. Reformation can also reduce the burden on public funds and dependency on importation.

Product tracing or component tracing? Blockchain adoption in a two-echelon supply chain management

Consumer awareness of product authenticity and carbon footprint tracing are among the most remarkable reasons for adopting blockchain in the supply chain in today’s world. However, the research literature has not yet examined specific ways to adopt blockchain in the supply chain. This study aims to develop a decision support tool to deal with the adoption of blockchain technology to design a two-echelon supply chain. In this regard, four specific cases for integrating supply chain and blockchain are developed based on types of tracing and block generation authority. In product tracing, green products are investigated throughout the supply chain, while in component tracing, green products are examined between the components of the supply chain. As it is necessary to record and verify the supply chain information by authorities in the blockchain network, in this work, such authorities are taken into account for both links and members of the supply chain. As far as we know, this is the first attempt to classify the various methods of adopting blockchain in Green Supply Chain Management (GSCM) and propose mathematical optimization models related to them. In this line, four Mixed-Integer Linear Programming (MILP) models with the aim of minimizing the costs related to the physical supply chain and blockchain deployment are developed for the integration of the supply chain with blockchain technology. They are treated by the Branch and Efficiency (B&E) algorithm and Simultaneous Data Envelopment Analysis (SDEA) model considering common (cost and service) and innovative (blockchain) criteria. The results showed that link-based and component tracing models are cost-effective. In addition, the cost objective function of green product tracing is more sensitive to the number of blocks than that of component tracing. Eventually, the study provides great opportunities for decision-makers and managers to understand how to adopt blockchain in terms of supply chain network characteristics, cost, transparency, and service.

Risk assessment of musculoskeletal disorder symptoms for touch screen mobile devices users by failure mode and effect analysis method: a data envelopment analysis approach

Touch-screen mobile devices (TSMDs) are digitally enhanced means of communication and information. This study aims to assess and identify the risks of musculoskeletal disorders. Cornell Musculoskeletal Disorder Questionnaire (CMDQ) was used with 340 university students (70% males and 30% females). Failure Mode and Effects Analysis (FMEA), which uses Data Envelopment Analysis (DEA), was applied to determine the potential musculoskeletal discomfort and its effects. The highest frequency of musculoskeletal discomfort symptoms was reported in the neck (73.53%) and lower back (67.94%), followed by the upper back (56.47%) and the right shoulder (46.18%). There was a positive correlation between the neck and musculoskeletal discomfort in; the right shoulder, upper back, right hand of base of thumb, and part of the wrist. It is essential to raise awareness among university students about the signs and risks of musculoskeletal disorder symptoms to help them prevent potential health issues in using TSMDs.

The nexus between digital economy and tourism eco-efficiency under the environmental regulation: evidence from 277 cities in China

PurposeThis study is of great significance in revealing the interactive and coordinated relationship between tourism development and the ecological environment, improving the level of environmental governance in the process of tourism economic development and realising the dual-carbon goal and sustainable development of the tourism industry.Design/methodology/approachThis paper performs slack-based measure (SBM)-data envelopment analysis (DEA) analysis, benchmark regression and threshold effect measurement on a sample of 277 cities in China from 2011 to 2019, to estimate the impact of the digital economy on tourism eco-efficiency and to identify the moderating role of environmental regulation.FindingsChina’s tourism eco-efficiency shows a spatio-temporal characteristic of steady growth amid fluctuations. The digital economy has a positive facilitating effect on tourism eco-efficiency, which is non-linear with a single threshold effect (0.631), and when the level of the digital economy exceeds the threshold value, its facilitating effect increases from 0.696 to 0.927. Environmental regulation does not play the role of “the icing on the cake” during the digital economy’s impact on tourism eco-efficiency.Originality/valueThis study for the first time includes the digital economy, eco-efficiency and environmental regulation in the research perspective, and analysed the mechanism of action between the three, expanding the depth of research on the digital economy and environmental regulation in the field of tourism. Meanwhile, based on the development needs of policy specialisation and industrial refinement, this study has strong practical significance when conducted at the city level.

WHAT PREDICTS THE TECHNICAL EFFICIENCY IN MALAYSIA’S FOOD PROCESSING INDUSTRY?

The present study focuses on the technical efficiency of Small and Medium Enterprises (SMEs) and Large-scale enterprises (LSEs) in Malaysia's food processing industry by adopting Data Envelopment Analysis (DEA) and Tobit regression. The empirical results provide that the SMEs technical efficiency score in constant return to scale (CRS) and variable return to scale (VRS) are 0.940 and 0.986 respectively which indicates the SMEs can enhance the level of output by 6 per cent for CRS and 1.4 per cent for VRS by using the given level of inputs. Moreover, the technical efficiency level of LSE is 0.673 and 0.942 from CRS and VRS respectively. The finding also suggests that the training cost, research and development, and foreign direct investment positively affect technical efficiency while information and technology, public infrastructure, and trade openness negatively affect the technical efficiency in SMEs. On the other hand, government infrastructure and trade openness have a positive connection with the technical efficiency of LSEs in Malaysia's food processing industry. Contradiction, research and development, and world oil price are negatively affecting the technical efficiency in LSEs which means the higher of these variables, the higher the efficiency in LSEs.

Revisit the First 60 Days of COVID-19: Assessment of the Global Healthcare Systems using Data Envelopment Analysis

Revisit the First 60 Days of COVID-19: Assessment of the Global Healthcare Systems using Data Envelopment Analysis

Research efficiency in Chilean universities: A look from data envelopment analysis

Objective. The objective is to analyze Chilean universities' efficiency in using some research-related inputs to determine their impact on the results of their scientific production. Design/Methodology/Approach. To achieve the outlined objective, some strategic resources are used as inputs, such as financial income, full-time equivalent academic staffing, and the number of enrolled students, and, as output, the number of publications in journals indexed in the Scopus database between 2020 and 2022. This is a descriptive and quantitative research using the data envelopment analysis technique. Results/Discussion. Valuable information for university management and governance was identified, including that three universities reached 100 % efficiency and seven others exceeded 90 %. The Mann-Whitney U and Student's t-tests, which show significant and favorable results for public entities, evidence the differences between public and private universities. Conclusion. The analysis suggests that multiple factors should be considered when evaluating the efficiency of academic institutions, especially their context and mission, especially regarding scientific production.

Sequential data envelopment analysis: decentralization and solutions for panel data

Sequential data envelopment analysis: decentralization and solutions for panel data

What Kind of Relationship Between Government and Business Can Stimulate Regional Green Innovation Development?—Analysis Based on Mixed Methods

China’s economic development has had adverse effects on the environment. Nevertheless, the Chinese government is optimistic about its ability to achieve a harmonious balance between economic growth and environmental sustainability. To this end, the government promotes, guides, and supports green innovation through the provision of policies and the creation of a conducive environment. Enterprises play a vital role in implementing and advancing green innovation, making them essential to realizing green development through their innovative capabilities. The relationship between government and business acts as a bridge between these two entities, fostering a synergistic effect that is crucial for achieving this objective. This paper conducts a comprehensive analysis of the existing literature on government–business relationships and green innovation, both domestically and internationally. Utilizing data envelopment analysis, it accurately measures the green innovation efficiency of 292 prefectural-level cities in China. The paper then employs a combination of a qualitative comparative analysis and a requisite condition analysis to establish the causal link between government–business relationships and green innovation development. Our detailed analysis of the data has identified three modes of driving green innovation: ‘government service-oriented’, ‘policy support-oriented’, and ‘pro- and clean-oriented’. These modes correspond to the developmental trajectories of China’s first, second, and third–fourth–fifth-tier cities, respectively. This paper offers policy recommendations for the systematic reform and optimization of government–business relationships in China. These recommendations are grounded in the three dimensions of the government–business relationship and consider the current conditions of cities at various stages of economic development. The findings and recommendations presented in this paper can serve as valuable insights for policymakers and businesses alike, providing guidance for future initiatives aimed at fostering a more sustainable economy.

Based on the New Dynamic Network DEA and Malmquist Index of High-Quality Innovation in the New Energy Vehicle Economy Development Research of the Internet of Things

This paper takes the enterprise economic data of new energy vehicles (NEVs) in 2018–2023 as the research background, combined with the performance evaluation theory of the NEV industry, and systematically discusses how to make the high-quality innovative development of NEVs as the research purpose. We use the new dynamic network data envelope analysis (DEA) model, Marmquist Index and other and the Internet of Things internationally recognized, scientific and effective data models as research methods to make an in-depth analysis of the business performance of five representative enterprises on multi-quantitative input-output issues. The research results show that the NEV industry has a good development prospect and economic foundation on the whole, but it still faces challenges such as limited space for core technology progress, insufficient carbon emission reduction and environmental protection planning. At the end, this paper puts forward innovation suggestions such as accelerating technological innovation, optimizing production process and responding to preferential policies and exploring international market.