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Open research questions in Efficiency Analysis Using DEA

394 gap statements mined from Efficiency Analysis Using DEA papers in our 7.9M-paper local library, which holds 2,979 papers on the topic — drawn mostly from each paper's own stated research gap, future-work, challenge and limitation notes, and its abstract. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one.

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What the literature leaves open

  • In addition to uncertainty modeling, future research could investigate alternative production technologies beyond the VRS assumption adopted in this study.

    Splitting decision-making units: A comprehensive DEA approach based on value and traditional efficiency · 2026 · DOI

  • Most studies focused on the analysis of productivity changes over a period do not account for the influence of contextual or environmental variables. The existing methods for incorporating contextual variables in efficiency measures have limitations, such as not allowing for formal inference about the marginal effect of these variables.

    The measurement and decomposition of productivity change with environmental variables: a conditional nonparametric frontier analysis approach · 2026 · DOI

  • The cold start problem, where data are sparse or when new users and products have little interaction history. The inability to capture shifting user preferences and market disruptions. The need to evaluate the performance of NFTs and construct relation-specific graphs in a complex and dynamic market.

    Enhancing deep learning with data envelopment analysis: market-oriented recommendation system for non-fungible tokens · 2026 · DOI

  • The research must consider the complexities of modern financial ecosystems and the varying environmental conditions. The study needs to provide a more comprehensive and realistic understanding of efficiency in diverse banking environments.

    Market structure, financial distress, and input prices in the Chinese banking industry: a novel 2-stage total partial productivity approach · 2026 · DOI

  • There is a need for DEA models that can handle nonhomogeneous DMUs. The existing literature lacks DEA models for business partnerships between nonhomogeneous DMUs, particularly in the context of banking partnerships.

    New DEA models for business partnerships: evidence from nonhomogeneous banking · 2026 · DOI

  • Data uncertainties, such as fluctuating costs and volatile demand, must be accommodated. The need to reconcile conflicting objectives across economic, productivity, and environmental efficiencies.

    A range-adjusted robust DEA model for evaluating multi-efficiencies in retail chain stores · 2026 · DOI

  • Most RDEA approaches do not assume a specific probability distribution or rely on interval-based worst-case assumptions, which may be overly conservative or inapplicable when distributional information is lacking.

    Data envelopment analysis under hybrid uncertainty: a distributionally robust optimization and intuitionistic fuzzy modeling approach · 2026 · DOI

  • The lack of a definitive accepted approach for handling negative data in DEA models. The limitations of traditional DEA models in dealing with negative data. The need for a more effective method to handle negative data in DEA models.

    Two-Stage semi-oriented radial measure network DEA model for decision-making units with negative data · 2026 · DOI

  • Conventional distance-based clustering may fail to capture internal production relationships. There is a need for a clustering framework that considers both internal and external characteristics of DMUs.

    Integrating internal and external attributes in clustering: a goal programming-data envelopment analysis model · 2026 · DOI

  • The paper identifies a gap in existing Data Envelopment Analysis methods, which do not provide a robust approach to efficiency ranking when different directions can yield different efficiency assessments. It highlights the challenge of direction selection in directional distance function.

    Multi-directional DEA with Win-Rate aggregation: a robust approach to efficiency ranking · 2026 · DOI

  • The 'curse of dimensionality' is a major challenge facing DEA. DEA suffers from sensitivity to outliers. Prior work has not effectively addressed these challenges.

    Enhancing data envelopment analysis: a comprehensive calibration with random forests · 2026 · DOI

  • While this study provides a comprehensive analysis, certain limitations remain to be addressed in future research: Refinement of the Indicator System. Despite efforts to ensure data quality, this research is limited by the lack of more granular, quality-adjusted metrics such as patent citation values at the provincial scale.

    Measurement and Spatiotemporal Evolution of Science and Technology Innovation Efficiency Based on Sustainable Development: Evidence from China · 2026 · DOI

  • Given the “core–periphery” differentiation and negative assortativity of CTFPN, a tailored governance system is necessary. Core urban clusters, such as the Yangtze River Delta and Pearl River Delta, should be strengthened as hubs, with the establishment of a national carbon reduction center to facilitate cross-regional carbon quota trading and open patent sharing.

    Networked urban responses to climate change: carbon efficiency and collaborative adaptation in Chinese cities · 2026 · DOI

  • Several areas remain underexplored and offer potential avenues for future research. While this study focuses on China’s urban CTFP, future research could extend the framework to a global context, comparing urban carbon productivity across different countries and regions.

    Networked urban responses to climate change: carbon efficiency and collaborative adaptation in Chinese cities · 2026 · DOI

  • Future research could focus on the following two aspects: (1) Optimization of indicators and data accuracy. Although one-period achieve rigorous causal lagged explanatory variables are employed to alleviate reverse causality and omitted-variable bias, treatments are insufficient to fully resolve endogeneity.

    Analysis of the spatiotemporal evolution, convergence trends, and influencing factors of ecological efficiency in Chinese cities · 2026 · DOI

  • The approach provides deeper insights into both overall SDG performance and stage-specific SDG performance. The study highlights the importance of institutional quality in achieving SDGs.

    The global frontier of sustainable development goals: examination of multiple objective programming using network data envelopment analysis · 2026 · DOI

  • Extending the methodology to address the limitation of not allowing for formal inference about the marginal effect of contextual variables, - Applying the proposed approach to other datasets…

    The measurement and decomposition of productivity change with environmental variables: a conditional nonparametric frontier analysis approach · 2026 · DOI

  • Overcoming known shortcomings of hybrid systems, - Improving the effectiveness of CF and CBF in NFT…

    Enhancing deep learning with data envelopment analysis: market-oriented recommendation system for non-fungible tokens · 2026 · DOI

  • Extending the proposed DEA models to other types of business partnerships - Applying the proposed DEA models to other industries - Investigating the effectiveness of business partnerships in different…

    New DEA models for business partnerships: evidence from nonhomogeneous banking · 2026 · DOI

  • Further research can be conducted to apply the proposed approach to other types of decision-making units, - The approach can be compared with other methods in the literature, - The study can be extended to include more insurance companies or other…

    Two-Stage semi-oriented radial measure network DEA model for decision-making units with negative data · 2026 · DOI

  • Further evaluation of the proposed GP-DEA clustering framework from both internal and external validity perspectives. Comparison of the proposed method with other benchmark approaches. Investigation of the performance of the proposed method for large-scale examples.

    Integrating internal and external attributes in clustering: a goal programming-data envelopment analysis model · 2026 · DOI

  • Investigating the application of the methodology to other fields, - Examining the impact of different direction sets on efficiency rankings, - Developing methods to handle outliers and non-efficient…

    Multi-directional DEA with Win-Rate aggregation: a robust approach to efficiency ranking · 2026 · DOI

  • The study uses a simulated dataset - The sample size is limited to {50, 100, 200, 400} - The number of inputs and outputs is limited to {2, 3} and {1, 2}…

    Enhancing data envelopment analysis: a comprehensive calibration with random forests · 2026 · DOI

  • From a combined input and output perspective (Figures 2, 3), the eastern region exhibited markedly higher efficiency. It utilized only 22.03% of K, 13.18% of L, and 14.59% of FL, yet generated 49.02% of Y and achieved the fastest growth in FCS. In contrast, the western region relied on 55.18% of FL and nearly half of total K, but contributed just 20.05% of Y while showing relatively high emission intensity.

    China’s forestry green total factor productivity (2000–2020): a multidimensional analysis from static efficiency to dynamic growth · 2026 · DOI

  • Spatial-temporal characteristics of cultivated land use eco-efficiency under carbon constraints and its relationship with landscape pattern dynamics. Ecol. Indic. 141, 109140.

    Analysis of the spatiotemporal evolution, convergence trends, and influencing factors of ecological efficiency in Chinese cities · 2026 · DOI

Most-cited papers in Efficiency Analysis Using DEA

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Open questions raised by papers listed on this page include: (1) There is a need for DEA models that can handle nonhomogeneous DMUs (“New DEA models for business partnerships: evidence from nonhomogeneous banking”, 2026); (2) Most RDEA approaches do not assume a specific probability distribution or rely on interval-based worst-case assumptions, which may be overly conservative or inapplicable when distributional information is lacking (“Data envelopment analysis under hybrid uncertainty: a distributionally robust…”, 2026); (3) The lack of a definitive accepted approach for handling negative data in DEA models (“Two-Stage semi-oriented radial measure network DEA model for decision-making…”, 2026); (4) There is a need for a clustering framework that considers both internal and external characteristics of DMUs (“Integrating internal and external attributes in clustering: a goal…”, 2026); (5) Several areas remain underexplored and offer potential avenues for future research (“Networked urban responses to climate change: carbon efficiency and…”, 2026). 394 gap statements have been mined from Efficiency Analysis Using DEA papers in our 7.9M-paper local library, which holds 2,979 papers on the topic; the gaps come from whichever of those papers state one. They are mostly the research gaps the authors state and the papers' abstracts, plus future-work, limitations and challenges passages. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one, so you can read the original claim in context.

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