Research activities relating to data envelopment analysis (DEA) have grown at a fast rate recently. Exactly what activities have been carrying the research momentum forward is a question of ...particular interest to the research community. The purpose of this study is to find these research activities, or research fronts, in DEA. A research front refers to a coherent topic or issue addressed by a group of research articles in recent years. The large amount of DEA literature makes it difficult to use any traditional qualitative methodology to sort out the matter. Thus, this study applies a network clustering method to group the literature through a citation network established from the DEA literature over the period 2000 to 2014. The keywords of the articles in each discovered group help pinpoint its research focus. The four research fronts identified are “bootstrapping and two-stage analysis”, “undesirable factors”, “cross-efficiency and ranking”, and “network DEA, dynamic DEA, and SBM”. Each research front is then examined with key-route main path analysis to uncover the elements in its core. In addition to presenting the research fronts, this study also updates the main paths and author statistics of DEA development since its inception and compares them with those reported in a previous study.
•This study presents research fronts in DEA in the period 2000-2014.•These research fronts include two-stage analysis, undesirable factors, cross-efficiency, and network DEA.•The growth of the network DEA subarea shows a surge in the period 2008-2012.•This study also updates the main paths and author statistics of DEA development since its inception.
•Comprehensive comparison of CCDEA, StoNED, and bootstrap methods.•Insights into efficiency scores in cultural regeneration.•Reveals regional disparities in management efficiency and value ...creation.•Provides guidance for choosing efficiency methods in cultural regeneration.•Enriches knowledge in efficiency analysis and policy development.
This study comprehensively compares three efficiency measurement methods—chance-constrained data envelopment analysis (CCDEA), stochastic nonparametric envelopment of data (StoNED), and the bootstrap method—in the context of the cultural regeneration performance of cities. The research examines these methods’ methodological differences, advantages, and disadvantages with a focus on uncertainty handling, production function assumptions, and computational requirements. The analysis reveals that CCDEA and the bootstrap method yield similar efficiency scores, while StoNED tends to produce lower efficiency scores. Furthermore, regions exhibit higher value-creation efficiency of cultural and creative industry than operational management efficiency, thus highlighting the untapped potential for improving value creation in cultural regeneration projects. This comprehensive comparison enables researchers and practitioners to further understand the nuances among these methods and select the most suitable method for their specific needs and objectives when evaluating the performance of cultural regeneration projects or other applications.
In an era where sustainability is paramount, this study presents a novel analytical framework that uses inverse data envelopment analysis (IDEA) and machine learning to optimize supplier performance ...in Apple's supply chain. We introduce the application of IDEA to recalibrate operational benchmarks, focusing on substantial CO2 reduction, and couple this with advanced predictive algorithms to proactively steer supplier practices toward Apple's sustainability targets. The study systematically simulates scenarios to achieve 30%–50% CO2 cuts, setting a precedent for environmental strategy integration. Beyond environmental metrics, our approach rigorously evaluates economic indicators such as earnings persistence and market recognition, providing a holistic view of supplier viability. The research employs machine learning, notably random forest and k-Nearest neighbors, to distill unbiased insights from historical data, ensuring precise, objective supplier assessments. Our findings offer a strategic blueprint for corporations and supply chain stakeholders aiming to embed sustainability into their operational ethos, supported by data-centric decision-making. These methodologies and insights contribute valuable perspectives to sustainable supply chain management and predictive analytics discourse. Finally, the study offers guidance on implementing CO2 reduction strategies and evaluating suppliers' economic performance, aligning with Sustainable Development Goals (SDGs) objectives.
•Conflict of Interest: The authors declare that they have no conflicts of interest.•This article does not contain any studies involving animals performed by any of the authors.•This article does not contain any studies involving human participants performed by any of the authors.
•Shared input dynamic network data envelopment analysis empirically estimates performance efficiency of 34 investment trust corporations (ITC).•Research indicates significant externalities from ...ownership structures on ITC efficiency, suggesting strategic considerations for the public service pension fund management board (PSPFMB).•K-means clustering helps differentiate ITC operational traits.•ITCs show better performance in bond than equity funds.•Diversification and professional management enhance PSPFMB.
Investment trust corporations (ITCs) constitute one of the financial industry's subsectors, and their evaluations of fund management performance play a crucial role. With the recent increase in the number of ITCs and their assets, how the Public Service Pension Fund management board (PSPFMB) of Taiwan makes investment decisions regarding multiple companies has become a critical issue. Using the shared input dynamic network data envelopment analysis approach (SDNDEA), we empirically estimate the performance efficiency scores of the funds of 34 ITCs and analyze the performance of the manufacturing structures of their internal networks. Our results indicate that the PSPFMB should consider the effects of being entrusted with decisions on efficiency. Employing K-means clustering techniques, we investigate the operational characteristics of each group and identify the differences among them. Moreover, this research identifies significant externalities related to ownership structures, indicating that the PSPFMB should consider the effects of such structures on efficiency in the context of entrusting decisions. Thus, the PSPFMB can make optimal investment decisions based on our ITC evaluation and selection model and help pension funds achieve stable long-term investment benefits.
The contribution from the creative industry to the regional economic growth has made the creative industry a new driver in economic development. But as a relatively young economic sector, the ...creative industry has its unique way of profiting through generating intellectual property with human creativity, talents, and skills. This profiting mechanism draws attention from both academia and industry to explore the factors that influence the performance of creative industry. This study explores the relationship between corporate social responsibility and financial performance of the creative industry. Using the dynamic DEA approach, we evaluated the longitudinal efficiency performance of 53 creative firms during the period of 2010–2013. Regression analysis was employed to determine if corporate social responsibility influences financial performance. The empirical results indicated that content media related businesses, which include motion pictures, publishing, and broadcasting, are the performance growth leaders, and the regression result showed that corporate social responsibility has a significant positive influence on the financial performance of the creative industry. In addition, the results also revealed that risk taking and capital oriented characteristics exist within the creative industry.
To achieve the goal of limiting global warming to 1.5 °C above preindustrial levels, net-zero emissions targets were proposed to assist countries in planning their long-term reduction. Inverse Data ...Envelopment Analysis (DEA) can be used to determine optimal input and output levels without sacrificing the set environmental efficiency target. However, treating countries as having the same capability to mitigate carbon emissions without considering their different developmental stages is not only unrealistic but also inappropriate. Therefore, this study incorporates a meta-concept into inverse DEA. This study adopts a three-stage approach. In the first stage, a meta-frontier DEA method is adopted to assess and compare the eco-efficiency of developed and developing countries. In the second stage, the specific super-efficiency method is adopted to rank the efficient countries specifically focused on carbon performance. In the third stage, carbon dioxide emissions reduction targets are proposed for the developed and developing countries separately. Then, a new meta-inverse DEA method is used to allocate the emissions reduction target to the inefficient countries in each of the specific groups. In this way, we can find the optimal CO
reduction amount for the inefficient countries with unchanged eco-efficiency levels. The implications of the new meta-inverse DEA method proposed in this study are twofold. The method can identify how a DMU can reduce undesirable outputs without sacrificing the set eco-efficiency target, which is especially useful in achieving net-zero emissions since this method provides a roadmap for decision-makers to understand how to allocate the emissions reduction targets to different units. In addition, this method can be applied to heterogeneous groups where they are assigned to different emissions reduction targets.
Serious environmental problems have accompanied remarkable global economic growth for decades. To assist managers in the semiconductor industry with economic and environmental management, this study ...executes DuPont analysis to examine economic impacts from the effective implementation of sustainability initiatives. We propose a two-stage process including economic development efficiency and environmental protection efficiency through the dynamic data envelopment analysis (DDEA) to reflect the characteristics of eco-efficiency. Through DuPont analysis, the main finding shows the potential improvement in firms’ return on equity (ROE) by efficiently utilizing assets to generate sales quickly.
Relative to economic development efficiency, the firms show lower scores and higher standard deviations in the environmental protection ability, thus denoting a large gap in the level of environmental protection production technology. The findings in this study reveal that the financial foundations and sustainable development of industries should be improved simultaneously even though specific levels of semiconductor industrial eco-efficiency improvement vary among companies in Taiwan.
A survey of DEA applications Liu, John S.; Lu, Louis Y.Y.; Lu, Wen-Min ...
Omega (Oxford),
10/2013, Volume:
41, Issue:
5
Journal Article
Peer reviewed
The literature of data envelopment analysis (DEA) encompasses many surveys, yet all either emphasize methodologies or do not make a distinction between methodological and application papers. This ...study is the first literature survey that focuses on DEA applications, covering DEA papers published in journals indexed by the Web of Science database from 1978 through August 2010. The results show that on the whole around two-thirds (63.6%) of DEA papers embed empirical data, while the remaining one-third are purely-methodological. Purely-methodological articles dominated the first 20 years of DEA development, but the accumulated number of application-embedded papers caught up to purely-methodological papers in 1999. Among the multifaceted applications, the top-five industries addressed are: banking, health care, agriculture and farm, transportation, and education. The applications that have the highest growth momentum recently are energy and environment as well as finance. In addition to the basic statistics, we uncover the development trajectory in each application area through the main path analysis. An observation from these works suggests that the two-step contextual analysis and network DEA are the recent trends across applications and that the two-step contextual analysis is the prevailing approach.
► We survey systematically DEA applications from 1978 through August 2010. ► Two-thirds of DEA papers embed application data and one-third is purely-methodological. ► Top-5 applications: banking, health care, agriculture and farm, transportation, education. ► Find no obvious methodological preferences for each of the five major applications. ► Two-step contextual analysis and network DEA are the recent trends across applications.
To develop a better way of assessing the sustainability efficiency (SE) and profitability efficiency (PE) of mining multinational enterprises (MNEs), the two‐stage data envelopment analysis (DEA) ...network model is proposed. The study shows that slack‐based models (SBM) can strengthen the previous and present measurements of the mining industry. When we assess the SE and PE of 53 mining MNEs from 2016 to 2019, the overall efficiencies of both the sustainability and profitability of mining MNEs are not higher than 70%. Such results are shown to be helpful for suggesting that global mining companies need to improve their efficiencies. This study addresses filling the research gap in the literature review about SE positively and significantly influencing PE with the moderating effect of corporate social responsibility (CSR) in mining MNEs. The result reveals that higher sustainability yields higher returns to the companies. In other words, MNEs have improved their SE to achieve a higher PE. Furthermore, the value of SE significantly influences PE regardless of whether the moderating effect, CSR, is higher or lower. The results show that a higher governance pillar score (GPS) and social pillar score (SPS) lead them to have greater profitability. However, a higher Environmental Pillar Score (EPS) tends to create a weaker relationship between SE and PE. We addressed a few interpretations of why higher EPS negatively influences profitability. Nevertheless, our study strongly recommends companies to increase their CSR score. Last, this study proves that all hypotheses are supported.
•We propose a dynamic network data envelopment analysis model with carry-overs.•Carry-overs are important to the performance evaluation of insurers.•We study investment assets as the carry-over ...variable in investment efficiency.•Modeling investment assets increases the discriminatory power of performance.•Some insights are derived from regression and multidimensional scaling approaches.
This study proposes a dynamic two-stage network data envelopment analysis (DEA) model with and without carry-over variables to evaluate corporate performance. Carry-over variables are those continuously held from one term to another, reflecting dynamic components. Apart from considering dynamic aspects, the DEA model called dynamic slacks-based measure with network structure can address various inputs and outputs at both stages and multiple intermediates that link the two stages. We demonstrate the applicability of the proposed model under the assumption of variable returns to scale to the performance evaluation of 30 insurance companies in Malaysia from 2008 to 2016. Specifically, we gauge resource management and investment efficiencies as the two production stages of insurance companies. While investment asset is considered the carry-over variable, investment income is treated as one of the ultimate outputs. Results indicate that the discriminatory power of the overall performance is high when we consider investments, particularly investment assets, as a carry-over variable. Moreover, we employ a multi-criteria decision analysis to compare all insurance companies in a common setting, including each ratio of liquidity, profitability, and leverage. The decision to include these ratios is made after performing regression analyses. This study entails practical implications for insurers and policy makers in terms of resource management and investment after considering investments and relevant performance ratios.
