A Decomposed Data Analysis Approach to Assessing City Sustainable Development Performance: A Network DEA Model with a Slack-Based Measure

Food security is a global challenge. With rising world population and demand for food being compounded by resource and arable land constraints, raising the efficiency of food production and use has become increasingly important. While much of the research on food security is focused on farm efficiency and productivity, most neglect post-harvest (PH) handling which is critical in determining the availability of food. In this study, we employ the network Data Envelopment Analysis (DEA) model to evaluate the PH efficiency of milling, using data from Kenya’s rice processing industry. The results show lower efficiency scores when using a network DEA model, which reflects its greater discriminatory power when compared to the standard DEA approach. The study also quantified sources of productive efficiency using a fractional regression model and identified storage space and distance to market as having an impact on drying efficiency; while experience, age of mill, servicing and energy type influenced milling efficiency. The results suggest that policy makers should focus on investing in drying technologies and storage facilities to improve drying efficiency. To improve milling efficiency, policy recommendations include enhancing millers’ access to better technologies, investing in reliable sources of energy and providing PH handling workshops to reduce PH losses.

Assessing the performance of tourism supply chains by using the hybrid network data envelopment analysis model

When the number of Decision-Making Units (DMUs) is not large enough compared to the total number of input parameters and outputs, traditional Data Envelopment Analysis (DEA) and Network Data Envelopment Analysis (NDEA) models often produce solutions that identify many DMUs as efficient, in addition to obtaining unrealistic weight distributions. In fact, this poor discrimination power and unrealistic weight distribution presented by DEA and NDEA models remain a major challenge, leading to the development of models to improve this performance. Thus, this paper proposes a Multiple Criteria Network Data Envelopment Analysis (MCNDEA), based on relational NDEA models. The idea of this model is to be used in network structures. To test the MCNDEA model, one a real instance linked to an evaluation problem of academic departments of a public university was used. Other instances were also used to validate the proposed MCNDEA, and these tests are included in the supplementary files. Finally, it should be noted that, in summary, the model proposed in this article had greater discrimination power of the analyzed DMUs, being able to identify the most efficient departments in each of the considered stages, besides pointing out to the University Management points of improvement regarding the best use of its resources for each department.

Nested dynamic network data envelopment analysis models with infinitely many decision making units for portfolio evaluation

Comprehensive performance evaluation of banking branches: A three-stage slacks-based measure (SBM) data envelopment analysis

Accurate measurement of regional efficiency is a prerequisite for effective management. Prior studies have expanded on the overall "black box" evaluation with two stages of research and development (R&D) and commercialization, opening up the internal structure of the regional innovation process, but ignoring the independent innovation activities of universities, research institutes, and firms in the R&D stage. We construct a mixed structure with two stages, three actors, and four subsystems, and conduct an empirical analysis of China's provincial samples from 2017 to 2019 by using the network data envelopment analysis (DEA) model. Results show that the efficiency of the R&D stage at the provincial level is generally higher than that of the commercialization stage. However, the three subsystems of the R&D stage perform poorly. Spearman’s rank correlation coefficient suggests that there is a significantly positive correlation between total regional efficiency and commercialization. In addition, we use the k-means method to divide 27 provinces into three clusters, setting a more appropriate improvement benchmark for inefficient provinces. Based on enlightenment of regional tobacco industry, we put forward some proposals for specific stage and specific subsystem.

An efficiency measurement model of a university faculty is proposed with additional new sub-functions that produce new output variables, based on the network Data Envelopment Analysis (DEA) model for systems with a hierarchical structure.For production systems composed of hierarchical processes, the system efficiency is well represented as the aggregated performance of the components involved in the system. It is identified that the conventional DEA model ignores internal process activities in a university. Therefore, an improved DEA model based on a network structure that accounts for more activities in a university is proposed to measure its overall efficiency. The impact of major functions of a university are taken into account to represent the output variables in assessing the efficiency. Currently, collaboration activities have been given more attention, so, this variable is suggested as a new output for the hierarchical production system. In order to show the practicality of the model, a hypothetical set of data of 14 faculties has been used as a numerical example. The results show that none of the faculties is relatively efficient since its functions were found to be inefficient. The proposed model enables to help the management of university faculties to identify weaknesses of each function and thus to plan for suitable actions on improving the overall performance of the university.

Energy efficiency of China's industry sector: An adjusted network DEA (data envelopment analysis)-based decomposition analysis

Data Envelopment Analysis (DEA) is a popular non-parametric technique for the assessment of efficiency of a set of homogeneous decision making units (DMUs) with the same set of inputs and outputs. In the conventional DEA models, it is assumed that all variables are fully controllable. However, in the real-world applications of DEA, some of the variables are completely uncontrollable or partially controllable. In this paper, we are concerned about partially controllable variables which are called semi-discretionary variables. In DEA models, in the presence of semi-discretionary variables, decision makers have partial control on these variables and the proportional changes are possible to some extent. Previous DEA models with semi-discretionary variables consider a certain level of control on the variables which is fixed and it is given by decision makers or a higher authority. Since this level is usually given by experts, it is possible that in some cases all experts may not come up with an agreement, so in this paper we consider variable instead of fixed level of control on each semi-discretionary variable. In the presence of semi-discretionary variables, the proportional changes in inputs and out-puts may not be feasible and as a result the obtained target value by conventional DEA models is not achievable for an inefficient DMU. Thus, we propose a bi-objective model to evaluate DMUs when modifying a variable to its target value should be managed by decision makers in a voting system. One of the advantages of the proposed model is including decision making conditions directly into a DEA model.

Urban development is facing increasingly complex disturbances. Assessing large cities’ urban resilience is important for improving their ability to withstand disturbances and promoting sustainable development. Therefore, this paper establishes an improved assessment model for urban resilience based on the driving force–pressure–state–impact–response (DPSIR) and data envelopment analysis (DEA) model. The Malmquist index, Dagum Gini coefficient, and Markov chain were sequentially used for spatiotemporal evolution and differential resilience analysis. Then, 105 large Chinese cities were selected as case studies. The results indicate their overall resilience is relatively high; each year’s average resilience efficiency can achieve DEA effectiveness. The distribution pattern of resilience level presents a healthy olive-shaped structure. However, there is also a significant difference between the two poles. During the research period, the combined effect of technological efficiency improvement and technological progress resulted in the overall resilience slowly improving, and this process was more driven by technological innovation. At the same time, the overall regional difference in resilience also shows a narrowing trend, and the current spatial differences mainly come from the difference within subregions and super-density. In future transfer predictions, the resilience of large cities will show good stability with a higher probability of maintaining stability; if the resilience undergoes a transition, the probability of an increase will be higher than a decrease. Based on the life cycle process of resilience, this study selects indicators that can characterize the level of resilience according to the DPSIR model, which comprehensively reflects the characteristics of urban resilience. This study’s results can provide particular reference values for urban disaster response emergency planning and sustainable development construction, and it also provides new ideas for the assessment research of urban resilience.

The present study aims to systematize research that uses networks and dynamic models of Data Envelopment Analysis (DEA) for the energy segment. This study examines how these new models are being applied and what are their contributions in solving the sector problems. Therefore, in order to obtain an in-depth bibliographic review, the analysis period covers the years of 2003 to 2016, as well as represent the trend of recent development in the literature. Different criteria were adopted to select articles that were classified by year, nationality, application area, inputs, outputs, intermediate products and carry-overs, as well as by the network structure adopted in the research. The results indicate the applicability of DEA to adequately portray a diversity of problems related to the energy sector. Also, these models allow to accomplish different planning levels, including the area of regulation. It was also confirmed the capacity of the new models to provide a greater range of information, helping in a better decision-making process.

Data envelopment analysis (DEA) is a non-parametric technique for measuring the efficiency of decision making units (DMU) with exact input and output terms. So far, a number of DEA models with interval data have been developed. The radial DEA model such as CCR or BCC model with interval data are well known as basic DEA models with interval data. However, these radial DEA models have some defects. In this study, we develop a new approach based upon the slacks-based measurement (SBM) of super-efficiency model for dealing with interval data in DEA. The SBM super-efficiency DEA model can not only discriminate the performance of efficient DMUs from inefficient ones, but can distinguish between the efficient DMUs. In addition, this model can overcome the drawback that the super-efficiency model can be infeasible under variable returns to scale (VRS) assumption. An illustrative example is provided to verify the idea of this paper and show its potential application and validity.

Objectives: This paper aims to assess the agricultural ecological and economic efficiency of the Yangtze River Economic Belt by using the data envelopment analysis (DEA) model to evaluate the regional agricultural level. Methods: Relevant data from 11 provinces and cities in the Yangtze River Economic Belt from 2010 to 2020 was collected from statistical yearbooks. Then, the agricultural eco-efficiency and economic efficiency were evaluated using the slack-based measure (SBM) model in the DEA model. Findings: The evaluation result of agricultural eco-efficiency was consistently higher than that of ecological efficiency. From a regional perspective, the eco-efficiency of the downstream area was higher than that of the middle and upper reaches. From the perspective of group division, only Guizhou and Chongqing had a high eco-efficiency. Improvement: The findings suggest that the overall agricultural eco-efficiency in the Yangtze River Economic Belt is low, and there is still a large space for development. It is necessary to further reduce agricultural carbon emissions and non-point source pollution and improve agriculture through technological innovation and other means.

Forgotten spaces, often referred to as lost spaces or non-places, represent a crucial challenge in contemporary urbanism and sustainable urban development. They are underdeveloped and undesirable urban areas that are in urgent need of rethinking, replanning, and redesign. They are mostly undefined, lacking measurable boundaries and communication routes. These natural areas are usually neglected and underutilized, which leads to their insufficient exploration from an urban-ecology perspective. Due to the impacts of climate change, it is necessary to reintegrate these lost places into urban planning. In organized non-spaces, it is crucial to rediscover their function and make these areas accessible or released for use. Wetlands, rich in biodiversity in urban areas and subject to seasonal changes, are threatened by human activity, and their protection is essential for the sustainable development of cities and urbanism today. Cities are interwoven with such non-places, which exhibit various characteristics within the urbans system. In conclusion, unrecognized urban spaces and lost wetlands represent an untapped potential for sustainable urban ecosystem development. This shifts the perception of urban voids from traditional urbanization towards their new potential as spaces for green development within the framework of sustainable contemporary cities.

1. Introduction, Curtis Andressen Part 1: Sustainability of Chinese Society 2. Sustaining the Dragon: International Relations Theory and the Rise of China, Martin Griffiths 3. Unsustainable Economic Interdependence: Two Asia-Pacific Examples, Richard Leaver 4. China's Cities: Reflecting on the Last 25 years, Dean Forbes 5. Social Security for an Aging Society: The Experience of Australia and China, Andrew Watson 6. Education and Change in China Today, Zhou Guan Qi and Curtis Andressen 7. Sustainable Development and Health Care Reform in China, Shen Yajun and Arthur Van Deth 8. Malpractice of Chinese News Media: Grassroots Professionals Trapped in Three Paradoxes, Xie Baohui and Mobo Gao 9. Building the Micro-Foundation of China's Sustainable Economic Development: Share-holder Oriented Corporate Governance Reform & the Performance of Chinese Publicly Traded Companies, Yang Dian Part 2: Sustainability of the Environment in China 10. Sustainable Development - A Way Forward or an Illusion? Don Clifton 11. Developing Sustainable Societies: Challenges and Perspectives, Simon Marsden 12. Addressing Climate Change in China: Challenges and Opportunities, Wang Mou, Jiahua Pan and Ruiying Zhang 13. How Climage Change Affected the Herders' Livelihood in a Semi-arid Pastoral Community, Wang Xiaoyi and Zhang Qian 14. English for Environmental Protection in China, Jeffrey Gil and Han Lin 15. Conclusion, Wang Xiaoyi