Envelopment Analysis Model Research Articles

Nonprofit Public Libraries and Organizational Performance

This study applied a two-stage data envelopment analysis (DEA) model with variable return to scale (VRS) to assess the impact of intermediate outputs on the technical efficiency of nonprofit public libraries (NPLs) in the United States (US) with respect to attaining service and program outcomes. The findings revealed that 46% of the NPLs were technically efficiency with respect to attaining the intermediate outputs at stage one. At stage two, 7% of the libraries were efficient with respect to attaining their service and program outcomes. The findings also revealed that the libraries which were efficient at stage one had an average reciprocal inefficiency score of 0.396 at stage two. By contrast, libraries which are inefficient at stage one had higher efficiency scores at stage two. The DEA analysis also produced estimates in regard to the optimal level of performance the NPLs should attain for each intermediate output to increase the level of technical efficiency at stage two.

Evaluation of the operating performance of Taiwanese machine tool industry with the dynamic network DEA model

ABSTRACT This study aims to evaluate the performance of the machine tool industry in Taiwan between 2010 and 2014 by using a dynamic network data envelopment analysis (DN-DEA) model. Taiwanese machine tool industry had an improvement in productivity from 2010 to 2014. Under the two-stage DEA model, we find that productivity in the production and market stage represent a rapid growth, and the productivity growth of the market stage is greater than that of the production stage. The overall productivity growth is mainly attributable to the market stage productivity growth and partially to the production stage productivity growth.

An Entropy-Based Cross-Efficiency under Variable Returns to Scale

Cross-efficiency evaluation is an effective methodology for discriminating among a set of decision-making units (DMUs) through both self- and peer-evaluation methods. This evaluation technique is usually used for data envelopment analysis (DEA) models with constant returns to scale due to the fact that negative efficiencies never happen in this case. For cases of variable returns to scale (VRSs), the evaluation may generate negative cross-efficiencies. However, when the production technology is known to be VRS, a VRS model must be used. In this case, negative efficiencies may occur. Negative efficiencies are unreasonable and cause difficulties in calculating the final cross-efficiency. In this paper, we propose a cross-efficiency evaluation method, with the technology of VRS. The cross-efficiency intervals of DMUs were derived from the associated aggressive and benevolent formulations. More importantly, the proposed approach does not produce negative efficiencies. For comparison of DMUs with their cross-efficiency intervals, a numerical index is required. Since the concept of entropy is an effective tool to measure the uncertainty, this concept was employed to build an index for ranking DMUs with cross efficiency intervals. A real-case example was used to illustrate the approach proposed in this paper.

Efficient and Sustainable Bioenergy Production in Swedish Forests – A Network DEA Approach

Forest fuel defined as branches and tops (GROT) of harvested trees represents a large share of forest biomass and is increasingly viewed as a potential energy source. This study assesses the economic potentials of forest bioenergy production in Swedish forests, using a network data envelopment analysis (DEA) model to estimate the technology for biofuel and other forest products. We consider that forests are managed to use multiple inputs to produce multiple outputs. Outputs include sawtimber, pulpwood, fuelwood, and bioenergy in terms of GROT. Our model also considers environmental concerns over biodiversity and CO2 emissions from burning biomass. We apply the network DEA model to measure the revenue efficiency of forest production of Swedish forests using a panel consisting of 20 counties and covering the years from 2008 to 2014. Our results show that there exist persistent economic inefficiencies of forest production in some counties, reducing the overall efficiency of Sweden’s forest and wood products industry. In addition, we also estimate the potential increase in bioenergy, deadwood and CO2 emissions reduction from combustion of bioenergy and by-products from sawtimber and pulpwood.

Industrial Efficiency Evaluation in China: A Nonparametric Production-Frontier Approach

An industrial system has positive and negative strategies to adapt to environmental regulations, which can be defined as natural disposability and managerial disposability. Meanwhile, the operational process of an industrial system can be divided into regular production activities and pollutant control activities. Within this, industrial system’s technical efficiency (TE) can be decomposed into economic efficiency (ECE) and environmental efficiency (ENE). On the basis of natural disposability and managerial disposability, this paper proposes static and dynamic data envelopment analysis (DEA) models to evaluate the efficiencies of industrial systems. Based on the proposed approach, TE, ECE, ENE, and Malmqusit productivity index (MPI) values were obtained simultaneously. The MPI values were further separated into the effects of static efficiency change and technical change. The proposed method was applied to assess the technical efficiencies of Chinese regional industrial systems between 2011 and 2015. Key findings are that (1) the low ENE is the main source of technical inefficiency; (2) the average static TE and ENE under natural disposability are both lower than those under managerial disposability; (3) the static efficiency change and technical change of TE are similar to those of ENE; and (4) the technical change has a significant impact on the changes in TE.

Performance Evaluation of Groundwater Overdraft Recovery Units in North and Coastal China Based on DEA Models

Pan, Z.-H.; Jiao, X.-Y.; Conradt, T.; Ding, X.-M., and Wang, H.-Y., 2019. Performance evaluation of groundwater overdraft recovery units in north and coastal China based on DEA models. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 1–5. Coconut Creek (Florida), ISSN 0749-0208.Groundwater overdraft has affected sustainable development, especially in North and Coastal China, since the 1960s. The Chinese government instituted the Pilot Project of Groundwater Overexploitation Control (PPGOC) in Hebei Province during 2014 to 2016. This project introduced a set of hydrological, agricultural and administrative activities to recover the aquifer in the pilot area. In order to evaluate the effects of these activities on the groundwater status, a series of Data Envelopment Analysis (DEA) models are assembled as a model group and applied to calculate the relative performance of groundwater recovery units, i.e. the recovery efficiency in 49 counties or Decision-Making Units (DMUs). It is shown that the DEA model group can be used to evaluate the recovery efficiency, improve the performance of units not on the DEA frontier via radial and slack movement, and study the possibility of cost reduction. The result shows that 20 DMUs formed the frontier, which is the collective of the efficient DMUs, and that another 29 DMUs require efficiency improvement. The high efficiency of certain DMUs is related to the location and farmers' responses, which indicates that groundwater overdraft recovery is a technical problem that also has something to do with social and economic development and comprehensive governance. The model group can be used as a reference in the forthcoming implementation of aquifer recovery in groundwater overdraft zones in North and Coastal China.

Evaluating the technical efficiency of care among long-term care facilities in Xiamen, China: based on data envelopment analysis and Tobit model

BackgroundThe technical efficiency (TE) of care among the elderly in long-term care facilities (LTCF) have become increasingly crucial policy concerns faced by developing countries and Asia, especially China. The purpose of this study was to evaluate the TE and the quality of care and identify its influencing factors among LTCF.MethodsA total of 32 registered LTCF in Xiamen of China were surveyed in 2016. The Banker-Charnes-Cooper (BCC) model and Slacks-Based Measure (SBM) model of Data Envelopment Analysis (DEA) were used to evaluate the TE of LTCF. The TE has been decomposed into pure technical efficiency and scale efficiency. Utilization of DEA with human, financial, and material resources as inputs and quantity, quality of nursing care as outputs allowed estimation of the relative TE of care in LTCF. In addition, this study applied SBM to measuring the efficiencies and slacks. Furthermore, Tobit model was performed to explore factors associated with TE.ResultsThere were 7 public and 25 private LTCF respectively, with a total of 6729 beds and 3154 elderly people. 17 LTCF were technically efficient (53.1%). In the BCC model, the average TE was 0.963. The average pure technical efficiency and scale efficiency of LTCF were 0.979, 0.984, respectively. There were 5 LTCF with increasing returns to scale, 8 LTCF with decreasing returns to scale. In the SBM model, the average TE was 0.813, and it had the same effective decision-making unit with SBM model. Depending on TE score from high to low, the top eight are private LTCF, and the last four were public LTCF. The slack analysis showed that they can be reduced in 8 LTCF with decreasing returns to scale such as 53.31% administrative staffs, 67.73% medical staffs, 33.1% caregivers, 51.66% paramedical staffs and 4.1% beds on average. The TE of private LTCF was higher than that of public LTCF. The LTCF in urban were more effective than rural. The TE of LTCF raised by increasing of working hours, training frequency and institutional occupancy.ConclusionsThe overall TE of LTCF in Xiamen of China was relatively high, especially in private institutions. However, LTCF still needs to further improve the utilization of physical resources and the management and training of human resources. The TE of LTCF was associated to their location, institutional nature, allocation of human resources and occupancy rate. It was needed to focus on promoting the efficiency and quality of LTCF in order to achieve sustainability.

Envelopment Analysis, Preference Fusion, and Membership Improvement of Intuitionistic Fuzzy Numbers

In this article, we propose a novel intuitionistic fuzzy decision making approach from the perspective of envelopment analysis. This method helps make a decision by calculating the intuitionistic fuzzy efficiencies of all the alternatives. The calculated efficiency values are relative indexes instead of stock indexes such as the aggregated and measured values. A prominent advantage is that this method can distinguish the efficient and inefficient alternatives and further improve the inefficient ones by modifying their membership and nonmembership degrees. Consequently, we can optimize the inefficient alternatives in the future, which cannot be achieved by other similar methods. To do this, we construct two intuitionistic fuzzy envelopment analysis (IFEA) models based on the membership and nonmembership degrees, respectively, which are different from the data envelopment analysis (DEA) and the fuzzy DEA. Their dual forms are derived so that these models can be transformed into the linear programming forms. With respect to the attributes’ differences, two preference IFEA models are developed by integrating subjective preference relations. Moreover, we provide the membership improvement formulas and summarize the specific decision making and membership improvement processes for practical applications. Finally, an example of ranking and improving the six listed companies is presented to demonstrate these approaches.

Benchmarking on Water Resource Utilization Efficiency of Prefecture-Level Cities in Jiangxi, China: A Bootstrap-DEA Approach with Three-Stage DEA Models

China has long been adopted traditional data envelopment analysis (DEA) models to measure water resources utilization efficiency of different provinces and cities without bias correction of efficiency scores. In this study, the Bootstrap-DEA approach embedded 3-stage DEA models was introduced to analyze the comprehensive efficiency of water resources utilization in the different prefecture-level cities Jiangxi and tried to improve the application of this method for benchmarking and inter-regional research. It is found that the bias corrected efficiency scores of Bootstrap-DEA differ significantly from those of the traditional DEA model, which implies that Chinese researchers need to update their DEA models for more scientific calculation of water resources utilization efficiency scores. This research has helped narrow the inter-regional gap in the comprehensive efficiency measurement and improvement of water resources utilization. It is suggested that Bootstrap-DEA embedded 3-stage DEA models be widely applied into afterward research to measure comprehensive efficiency of water resources utilization in regional inter-city so as to better serve for efficiency improvement and related decision making.

DEA models for two decision makers with conflicts: the principal-agent problem

This paper studies the impact of two decision makers’ interaction with conflicts on the efficiencies of the system. We start with a general principal-agent framework where the principal and the agent make decisions independently and the principal has a contradictive objective to that of the agent. We develop data envelopment analysis (DEA) models in the principal’s and the agent’s perspectives respectively. Non-cooperation between the principal and the agent is discussed to illustrate how one decision maker affects the other and the corresponding efficiency and incentive contract of the system. In addition, cooperation of the two parties is also analyzed to better derive how the performance of the system is influenced by the parties and their interactions as well. Then, this study illustrates the proposed models and effective incentive contracts by applying them to the efficiency evaluations of 22 China listed electric power companies.

Technical efficiency analysis of the conversion of cropland to forestland program in Jiangxi, Shaanxi, and Sichuan

ABSTRACTConversion of Cropland to Forestland Program (CCFP) has greatly impacted China’s agricultural sector, and more specifically rural farmers. While changes in living standards as a result of the implementation of the CCFP have been analyzed, little research has been conducted regarding the impacts of such policies on farming operations. As agriculture contributes nearly 10% of national GDP, it is important to analyze the implications of policies on a national industry. An input-oriented data envelopment analysis (DEA) model was used to examine the technical efficiency of farming operations following implementation of the CCFP, using survey data from farmers in Jiangxi, Shaanxi, and Sichuan provinces. Additionally, the impact of factors such as urbanization, age and education, and land fragmentation was examined with respect to farming operational efficiency. Scale inefficiency was found to have the greatest effect on overall inefficiency in farming operations in comparison to pure technical inefficiency, which was largely influenced by the presence and degree of land fragmentation of land holdings. Findings can be used to inform national land-use policies facilitating land fragmentation in China and address gaps in existing broader level studies that utilize non-parametric approaches to examine the technical efficiency of Chinese farmers affected by the CCFP.

Evaluating Winter Barley Cultivar Using Data Envelopment Analysis Models

Unlike feed barley, malting barley must meet a specific set of quality standards for acceptability by maltsters. Multiple quality criteria in addition to the grain yield makes ranking of genotypes challenging. The objective of this study was to apply data envelopment analysis (DEA) models to rank the efficiencies of 27 winter barley entries based on grain yield and quality indices. Four methods of DEA including Charnes, Cooper and Rhodes (CCR), Färe and Grosskopf (FG), Banker, Charnes and Cooper (BCC), and Seiford and Thrall (ST) used for the ranking. Testing trial included 14 two-rows and 13 six-rows winter barley. All entries except two, demonstrated high winter survival ratings. Overall, the six-row cultivars out-yielded the two-row cultivars by 18%. However, in terms of brewing quality, the two-row entries performed better than six-row entries and had 40% lower thinness, 12% higher plump, and lower grain protein content. The six-row entries had 32% higher germinative energy than two-row entries. The ranking by four models were not similar, however, SU-Mateo and Calypso had the highest efficiency (1.0) by all four models followed by Wintmalt and Vincenta.

Efficiency assessment of state-owned financial institutions using data envelopment analysis: the case of Vietnam

ABSTRACT Measurement of public sector enterprises' performance, especially efficiency measurement by way of a DEA model, has gained prominence in recent years among academics and practitioners. However, the different sources of input and output chosen to be used in the DEA model would produce different results for the assessor. The current research uses a closed-ended questionnaire aiming to explore suitable sources of input and output for use in a data envelopment analysis (DEA) model to assess the efficiency of public sector commercial banks (PSCBs) in Vietnam. The data is subsequently analysed quantitatively using confirmatory factor analysis (CFA) with the AMOS program. The results show five sources of input and five sources of output suitable for inclusion in the DEA model. This paper provides a reliable basis for policy analysts and performance assessors to use DEA to analyse efficiency and effectiveness in PSCBs and might trigger future research on efficiency evaluation of PSCBs using DEA in the context of Vietnam.

Measuring the innovation efficiency of the Chinese pharmaceutical industry based on a dynamic network DEA model

ABSTRACTA dynamic network data envelopment analysis (DEA) model is employed for measuring the innovation efficiency of the Chinese pharmaceutical industry. The results show that the reason for innovation inefficiency in the Chinese pharmaceutical manufacturing industry is the inefficiency of pure technology and scale, but pure technical inefficiency plays the main role. The contribution of knowledge innovation to innovation efficiency in the pharmaceutical industry is greater than that of commercialization.

Efficiency bounds and efficiency classifications in imprecise DEA: An extension

Park proposed a pair of mathematical data envelopment analysis (DEA) models to estimate the lower and upper bound of efficiency scores in the presence of imprecise data. This article illustrates that his approach suffers from some drawbacks: (i) it may convert weak ordinal data into an incorrect set of precise data; (ii) it utilizes various production frontiers to obtain an interval efficiency score for each decision making unit (DMU); (iii) in the absence of exact output data (pure ordinal output data), the approach leads to a meaningless model; (iv) the built model is infeasible with pure ordinal input data; (v) it may include free or unlimited production output which results in unreliable and suspicious results. Moreover, the utilized models by Park involve a positive lower bound (non-Archimedean epsilon) for the weights to deter them from being zero. However, the author ignored the requirement of determining a suitable value for the epsilon. This study constructs two new DEA models with a fixed and unified production frontier (the same constraint set) to compute the upper and lower bounds of efficiency. It is demonstrated that the suggested models can successfully capture the aforementioned shortcomings. Although these models are also epsilon-based, a new model is developed to obtain a suitable epsilon value for the proposed models. It is proved that the suggested approach effectively eliminates all the weaknesses. Additionally, a case study of Iranian Space Agency (ISA) industry is taken as an example to illustrate the superiority of the new approach over the previous ones.

Carbon Emission Allocation in a Chinese Province-Level Region Based on Two-Stage Network Structures

With the increasingly severe global environment and climate change, the growing social attention toward the environmental problems has prompted local governments to make policy adjustments. The formulation of the carbon emission right allocation scheme is important for policy-makers. Many researchers have studied the problem of carbon emission right allocation by using data envelopment analysis (DEA) models. However, the existing literature using traditional models consider each Decision-Making Unit (DMU) as a “black box” without taking the internal structure into account, but in fact, it is more accurate for formulating the scheme when considering the inner operation of DMUs. This paper investigates the allocation plan of carbon emission right among each province in China from 2007–2016 based on a two-stage DEA model. The results indicate that, first, there is no space for carbon emission in the north, northeast, and northwest from 2007–2016, while in the southern regions, it always exists. In addition, the carbon emission permits of the southern and eastern regions are increasing, but in the southwestern regions, the carbon emission space barely fluctuated during this decade. Second, the potential of carbon emission reduction of each region tends to be stable after 2014, and in the north and northwest, it fluctuated greatly from 2007–2016. Besides, the northwest region has had the potential of emission reduction since 2010, while it also exists in the northern region after 2014.

DEA를 활용한 대학의 창업지원 효율성 분석 : 인적자원, 연구개발 역량 및 인프라를 중심으로

DEA를 활용한 대학의 창업지원 효율성 분석 : 인적자원, 연구개발 역량 및 인프라를 중심으로

Drivers of Farm Efficiency and Their Potential for Development in a Changing Agricultural Setting in Kerala, India

The agricultural sector is a main source of income for many smallholder farmers in developing countries. In Kerala, the sector faces various challenges linked to land, labour and capital scarcity. This paper explores efficiency levels of farms and identifies measures that increase farm efficiency in a rural region in Kerala. By means of data envelopment analysis (DEA) and subsequent Tobit regression models based on primary data from 333 farms, we show the specific distribution of farm efficiency and explain efficiency differences by various factors relating to socio-economic conditions and farm management. Our analysis finds that average farm efficiency is low. Female farmers, remittances and farm machinery tend to increase farm efficiency, whereas coconut and rice crops as well as fertiliser use tend to decrease efficiency. Our analysis informs the decision-making of farmers and policy-makers, and helps farmers generate marketable surplus that ensures the livelihood of rural communities and drives development.

Measuring the Efficiency of Community Colleges Using Super Efficiency Approach for the Case of Non-discretionary Factors in Data Envelopment Analysis with Sensitivity Analysis

Malaysian community colleges play a significant role in achieving Malaysia's vision to be a developed country in 2020. For this reason, their efficiency should appropriately be measured. However, their efficiency measurement using a conventional data envelopment analysis (DEA) model is not appropriate since some of their inputs; e.g., entrant and enrolment students are non-discretionary while a part of output of their graduate employability is discretionary. This paper thus proposes an alternative approach of super efficiency slack-based measure for the case of non-discretionary factors in DEA. The proposed approach was used to evaluate the efficiency of 25 main campuses of Malaysian community colleges from 2012 to 2013. The results support the decision maker of Malaysian community colleges to discriminate and rank efficient and inefficient community colleges in the presence of both super efficiency and non-discretionary factors. The significance of inputs-outputs on efficiency status was tested by sensitivity analysis.

Evaluating the Efficiency and Determinants of Efficiency of Rural Health Centers Situated in Punjab, Pakistan

This study calculates the efficiency of Rural Health Centers (RHCs) and investigates the impact of other variables affecting the efficiency of RHCs. The study considers 29 RHCs, 13 of District Faisalabad, 9 of Toba and 7 of Jhang; a survey was conducted to collect data from each RHC for the year 2016. Data Envelopment Analysis (DEA) model was utilized to get the scores for efficiency. Thereafter, after getting the results from DEA Tobit regression was used in the second stage. Out of the 29 Rural Health Centers, only 11 (38%) are working efficiently as compare to others. Distance from the tehsil headquarter, Distance from the road with “0” probability, Distance from private hospital with “0” probability, Behavior of the staff with “0.0064” probability and laboratory equipment’s with “0” probability, have an impact on the efficiency scores. Distance from other health facilitators, Staff’s behavior, list of medicine and equipment’s used at RHCs should be improved to increase the efficiency of RHC’s.