Output Shortfalls Research Articles

Using super-efficiency slack-based measure data envelopment analysis with enhanced neural network frontier to evaluate the operating efficiency of Chinese-listed real estate companies

China's real estate industry has faced significant changes and challenges in the aftermath of the COVID-19 pandemic and recent years, and has been unable to maintain its former prosperity. Facing a rapidly changing market environment and new loan restriction policies, real estate companies are encountering unprecedented challenges. Efficiency evaluation and analysis of real estate companies are essential to guide them in improving operational efficiency and adapting to new development models. This paper examines 87 real estate development companies listed on the Shenzhen and Shanghai markets, first evaluating and analyzing their operational efficiency in 2023 using the output-oriented super-efficiency slack-based measure data envelopment analysis (SBM-DEA) method. To address the issue of overestimated operational efficiency in the original model, this paper integrates it with the backpropagation neural network (BPNN) algorithm to obtain more robust re-evaluated efficiency scores. The results align with expectations, showing an overall decline in efficiency scores, and more significant decreases for companies with smaller output shortfalls in the original evaluation. The re-evaluated efficiency scores do not excessively underestimate efficiency and can serve as a reliable proxy for the original scores. The enhanced model combining BPNN with super-efficiency SBM DEA provides reliable and robust efficiency evaluations for these 87 listed real estate companies.

Synchronizing short-, mid-, and long-term operations of hydro-wind-photovoltaic complementary systems

Hydro-wind-photovoltaic (PV) complementary power systems (HWPCSs) offer a promising solution for integrating intermittent wind and PV power, leveraging the long-term energy storage capacity of reservoirs and the short-term flexible adjustability of hydro units. However, existing studies often neglect the reciprocal influences among short-, mid-, and long-term operations of HWPCSs, resulting in suboptimal operating strategies. To tackle this issue, the study proposes a generic framework for synchronizing operations of HWPCSs across multiple time scales. The framework simultaneously optimizes long-term operating rule curves, mid-term water consumption allocation, day-ahead power generation plan scheduling, and intraday economic operation of HWPCSs. A HWPCS located in the Yalong River Basin is selected as the case study. The results indicate that: (1) synchronized operation effectively reduces the output shortage risk (from 4.86 % to 0 %) and average absolute water consumption deviation (from 2.07 % to 0.09 %) compared to the conventional method; (2) synchronized operation provides more reasonable boundaries for short-term operations, reducing the average online time percentage (from 65.08 % to 63.57 %) and start-up/shut-down times (from 3185 to 2981) of hydro units, leading to an increase in the average hydropower efficiency (from 9.05 to 9.12). This study highlights the impracticality of the conventional method, underscoring the necessity of synchronized operation for HWPCSs. The proposed method provides a practical framework for the efficient operation of HWPCSs.

Measuring the Efficiency of Water Supply Service: Application of Charnes, Cooper Rhodes and Slack-Based Measure Models

Measuring the efficiency of water supply services is very important, as the demands for water supply are increasing as the year goes by due to increasing population and development. Improving the efficiency of water supply services is also an economically viable way for water conservation. This paper examines the efficiency of water supply services using Charnes, Cooper, and Rhodes (CCR) output-oriented and Slack-Based Measure (SBM) models. SBM provides the input excesses and output shortfalls for the concerned decision-making units (DMUs). Meanwhile, the CCR output-oriented model interprets the efficiency by maximising the output produced by the DMUs whilst maintaining the input used. The results indicate that the optimal efficiency value for SBM model is lower than the optimal efficiency value of the CCR model. Furthermore, the SBM model provides the water supply providers with values for input excess and output shortfalls for future improvements.

Compact Electrolytic Hydrocapacitor for Direct Harvesting and Storing Energy from Water Droplet Achieving High Voltage

AbstractAs a renewable and low‐carbon emission energy source, water‐droplet‐based devices are attracting increasing interest. However, the uncertain mechanistic explanation, output shortage, and lack of storability remain huge barriers to their large‐scale applications. Herein, a compact quasi‐solid‐state electrolytic hydrocapacitor (HCelect) is successfully designed and fabricated with dual‐function of self‐charging and storage by employing novel bilayer graphene oxide/graphite flake composite films symmetrically sandwiched by poly(vinyl alcohol)–phosphoric acid electrolyte. The sandwich‐like HCelect can achieve a high‐level and repetitive self‐generation voltage of 0.94 V for over a month under a small‐scale water droplet. A possible model is proposed to explain the operating principle in detail based on the capillarity, ion diffusion, and streaming potential mechanisms. Simultaneously, the generated energy is continuously stored for ≈2.1 h due to water evaporation. In addition, unlimited output extension can be realized by integrating hydrocapacitors in an array for powering commercial devices. Interestingly, it is ascertained that prolonged finger touches on the HCelect can produce a high voltage. Therefore, this novel hydrocapacitor has notable potential applications in small portable and wearable devices owing to its compactness, low cost, environmental friendliness, safety, and flexibility, thereby providing a design idea for new innovative electronic devices.

Resource Efficiency and Economic Efficiency of Fish Farms in the Southeast of Côte d’Ivoire

In Côte d'Ivoire, fish farming is seen as a supplement to fish production. A more efficient use of resources in the production process would assure sustainable fish production. Using a data envelopment analysis (DEA) model and cost-benefit analysis, this study examines the resource efficiency and economic efficiency of 32 fish farms in the southeast of Côte d'Ivoire. The results revealed that fish farmers showed low performance, with average technical efficiency scores of 0.738 (CRS) and 0.575 (SBM) and an average economic score of 0.553. The most technically and economically efficient fish farmers use industrial feed. The study found that fish farmers caused excesses in resource utilization, resulting in a shortfall in output utilizing DEA model scenarios. Scenario-3, based on the slack-based model, minimizing resources while maximizing output, revealed that reducing resource excesses would have increased output by 16.18%. Based on the cost-benefit analysis, fish farms produced a positive gross and net profit margin. According to the findings of this study, policymakers should play a significant role in improving fish farmers' access to quality feed and fingerlings. Furthermore, fish farmers must be trained in sustainable production and pond management procedures.

Evaluating efficiency and ranking of suppliers using non-radial super-efficiency data envelopment analysis with uncontrollable factors

Supply chain management (SCM) has been received much attention from academics and corporates. Effective and sustainable SCM require proper efficiency evaluation of suppliers. Such evaluation can be performed using data envelopment analysis (DEA). Classical DEA models presume all inputs and outputs are under the control of suppliers’ management, as well as the models cannot provide a complete ranking of efficient and inefficient suppliers. However, in SCM and other real-managerial problems, some inputs and/or outputs may be uncontrollable (outside management control). Thus, this paper proposes a super efficiency of slacks-based measure (SE-SBM) approach that can handle uncontrollable factors. The proposed approach can distinguish between efficient and inefficient suppliers and identify their rankings. The discriminating power of the proposed approach is due to it concurrently deals with input excesses and output shortfalls to improve inefficient suppliers, as well as input savings and output surpluses of efficient suppliers to maintain their efficient status.

Determining the amount of the excess input and the output shortage of the congested decision-making units with negative data

Determining the amount of the excess input and the output shortage of the congested decision-making units with negative data

Inverter-Less Integration of Roof-Top Solar PV with Grid Connected Industrial Drives

Green energy from Solar PV is getting increased attention in the industries due to the falling price of solar panels in the world market. A grid-tied inverter is one of the major components in such a system, where the DC energy from PV is converted to AC and synchronized with the grid to obtain power sharing between the PV and the grid for the industrial drives. In this paper, a DC link has been proposed instead of an AC link for interconnection between the solar PV system and the grid to run those industrial drives. In most modern industrial applications, induction motors are driven by VVVF (Variable Voltage and Variable Frequency) inverters to achieve efficient speed control. The inverters commonly have a rectifier section at the front end that rectifies the input AC to DC and the DC is then used in PWM mode to generate the required voltage and frequency for the induction motor operating under variable speed and load conditions. Such an inverter can use both AC or DC as the input so long the supply voltage has the right value for the inverter to operate. In our proposition, we eliminate the grid-tied inverter and use a DC link, created from the rectified AC and the regular Solar PV, to obtain the power-sharing between the PV output and the grid. Using the DC link output directly to energize the VVVF inverter has an impact on the performance of the inverter. In the proposed system, the solar PV array is designed in such a way that the grid remains as the supplementary power source only to supplement any shortfall in the PV output due to variable sunshine conditions. The control circuit used in this novel technique is inexpensive, efficient, and simple in design when compared to the grid-tied inverters. The proposed system has been implemented at Niagara Textiles in Gazipur, Bangladesh. The experimental/practical results are presented to validate the basic concept. Around a 20% reduction in the cost of energy has been reported in this paper, with a more than 90% efficient system. This will definitely make solar PV energy more competitive with regular energy and attractive to industries for its simplicity.

Fiscal Expenditure Efficiency Measurement and Its Convergence Analysis on Aging Undertakings in China: Based on a Global Super-Efficiency Slacks-Based Measure Model

As the aging of China’s population continues to intensify as well as deepen, and fiscal support continues to increase, improving the efficiency of fiscal expenditure on aging undertakings has become the key to actively responding to the national strategy of sustainable population aging. This paper uses a global super-efficiency slacks-based measure model to measure the efficiency of fiscal expenditure on aging undertakings in China from 2011 to 2020. The results show, firstly, that the efficiency values are generally increasing. The eastern region’s fiscal expenditure efficiency has output deficiencies overall; all western, central, except Anhui, and northeast, except Jilin, provinces have input redundancies and output shortages. Secondly, the relatively effective provinces in terms of aging undertakings are mainly concentrated in the eastern coastal region; the number of effective provinces in the northeast is gradually increasing. Thirdly, excluding the eastern region, the efficiency values for all regions show a convergence trend; when controlling for region-specific influencing factors, the efficiency values of each region will converge to their respective steady-state levels. It is concluded that the trend in the fiscal management of aging undertakings in China is positive, and the levels of fiscal management as well as technology are higher in the east, lower in the west, less stable in the central, and more progressive in the northeast.

Опыт водосбережения при поливах овощных культур открытого грунта

Abstract. Purpose: on the basis of study and analysis of scientific sources to summa-rize the experience of water saving and to determine the features of modern irrigation regimes for vegetable crops in open ground. Discussion. Tomatoes and cucumbers are popular vege-table crops. The main areas of their cultivation in the country are the Southern and North Caucasian Federal Districts, where it is impossible to obtain yields without irrigation. The re-quirements of vegetable crops for moisture increase significantly during the periods of flower-ing, fruit setting and formation. Its deficiency during these periods leads to a decrease in productivity and a shortage of output. At present, both intensive irrigation with full irrigation rates and differential irrigation are practiced where irrigation is carried out with reduced irri-gation rates and the inter-irrigation periods and the number of watering are changed. An anal-ysis of the results of studies on tomato and cucumber cultivation on irrigated lands made it possible to determine that as a rule, under full irrigation, pre-irrigation soil moisture sill for these crops are maintained at least 80 % of the minimum moisture capacity. With differentiat-ed regimes, water saving is achieved by reducing the amount of irrigation water used. In this case, the differentiation criteria are the pre-irrigation soil moisture sill, the phases of crop growth and development, the depth of the calculated soil layer, the magnitude of irrigation rates, and the total evapotranspiration. The disadvantage of differentiated irrigation regimes is the lack of production, which can reach 14 % compared to the intensive irrigation regimes. Conclusions. An analysis of the water-saving experience during irrigating vegetable crops in open ground confirmed the effectiveness of differentiated irrigation regimes. Under such re-gimes, the yield decrease is not so significant, however, the most efficient use of irrigation water and higher product quality are noted. The combination of the optimal soil water regime and fertilization system contributes to the increase in the efficiency of production process of vegetable crops.

Evaluation to fixed-sum-outputs DMUs by non-oriented equilibrium efficient frontier DEA approach with Nash bargaining-based selection

Equilibrium efficient frontier DEA (EEFDEA) approaches have been developed specifically for the efficiency assessment of decision-making units (DMUs) with fixed-sum outputs in recent years. Still, current EEFDEA approaches can only evaluate either input- or output-oriented efficiency. This paper proposes a new non-oriented EEFDEA (NEEFDEA) approach, which measures efficiency by capturing input excesses and output shortfalls simultaneously. However, the NEEFDEA approach also encounters the difficulty of guaranteeing the uniqueness of the common equilibrium efficient frontier (EEF). To address the problem, we further present a new bargaining-based selection method to deal with multiple feasible EEFs. By regarding DMUs as game players to seek to optimize their own evaluation results, the screening process of EEFs is formulated as a bargaining game, it can generate a unique and Pareto-optimal EEF by solving the game. Such an EEF is essential to bring all DMUs to a consensus on the final evaluation results. Finally, to present the performance of our model, we apply the proposed approaches to conduct an empirical study of 30 companies in the vehicle industry in 2020.

Graph theoretic approach to expose the energy-induced crisis in Pakistan

Pakistan is an energy-deficient country and relies heavily on imported fossil fuels despite significant potential for it to instead develop renewable energy resources. This paper employs a newly developed causality determination scheme known as the Graph Theoretic Approach (GTA), which is based on the modified Peter and Clark algorithm. In this study the energy-inflation causal nexus has been investigated using real time-series data covering the past 30 years (1990–2019) based on nine key variables of the economy, i.e., inflation rate, oil prices, interest rate, money supply, GDP, exchange rate, unit value of import, unit value of export and output shortfalls. Results show that causality runs from energy prices and interest rate to inflation, suggesting that energy prices and interest rate are positively associated with inflation. Moreover, both energy prices and monetary policy have cost-side effects on inflation; however, the latter becomes counterproductive whenever a high interest rate is used to curtail energy-push-inflation. It is concluded that, an increased dependence on imported fossil fuels causes energy-push-inflation. Therefore, policymakers need to incorporate much more renewable energy resources in the fuel mix so that heavy energy import bills can be avoided in the long-run, thereby controlling the cost-side channel of inflation.

Malproduction of endogenous hydrogen gas in COVID-19.

The molecular footprints of COVID-19 occur everywhere, even reaching the family of biologically active gases and gasotransmitters. Besides nitric oxide and hydrogen sulfide, COVID-19 might also alter the homeostasis of dihydrogen (H2), another gaseous bioactive molecule produced endogenously by the human gut bacteria. Many studies have shown various alterations of the gut microbiota in patients with coronavirus disease 2019, including the lower abundance of hydrogen-producing bacteria that could instigate the shortage of hydrogen output. Since dihydrogen has many important bioactivities, including cytoprotective, antioxidant, anti-inflammatory, and antiapoptotic, its malproduction in COVID-19 might contribute to the disease progression and severity. On the other hand, replenishing dihydrogen by exogenous administration could be beneficial in COVID-19 for both patient- and clinical-reported outcomes. Assessing low dihydrogen along with H2 supplementation to restore normal levels could be thus combined via theranostic approaches to aid COVID-19 diagnosis and treatment.

A Wasserstein metric-based distributionally robust optimization approach for reliable-economic equilibrium operation of hydro-wind-solar energy systems

Hydro-wind-solar integrated operation is a promising way to balance the growing amount of variable renewable energy (RE) and enhance energy utilization efficiency. This study focuses on the short-term reliable-economic equilibrium operation of the hydro-wind-solar energy systems. A Distributionally Robust Optimization based on Wasserstein metric, which considers multiple power supply risks (output shortage, power curtailment and spilled water) and the economy (the water consumption and the stored energy) of hydropower operation simultaneously is proposed to address the above issue. The model is transformed into a mixed-integer linear programming framework using a reformation approach based on ϵ-constraint method, strong duality theory, and linearization technology. Case studies are conducted for a hydro-wind-solar energy system in Southwest China's Beipan River basin. Results indicate that: (1) with more available data, more information about RE uncertainties is involved in the decision-making process to hedge against RE variability's interference. (2) Decisions obtained from the proposed model overcome the issues of stochastic optimization's over-optimism and robust optimization's over-conservativeness. (3) Reliable-economic trade-off mechanisms are derived by imposing a decision-maker's risk attitude, the risks in dry and wet season typical cases decline from 10483.05 MW to 1606.39 MW and from 8394.15 MW to 118.08 MW by adjusting the economy.

Theoretical and Experimental Analysis of a New Intelligent Charging Controller for Off-Board Electric Vehicles Using PV Standalone System Represented by a Small-Scale Lithium-Ion Battery

Electric vehicles are rapidly infiltrating the power grid worldwide, initiating an immediate need for a smart charging technique to maintain the stability and robustness of the charging process despite the generation type. Renewable energy sources (RESs), especially photovoltaic (PV), are becoming the essential source for electric vehicle charging points. The stochastic behavior of the PV output power affects the power conversion for regulating the battery charger voltage levels, which influences the battery to overheat and degrade. This study presents a PV standalone smart charging process for off-board plug-in electric vehicles, represented by a small-scale lithium-ion battery based on the multistage charging currents (MSCC) protocol. The charger comprises a DC–DC buck converter controlled by an artificial neural network predictive controller (NNPC), trained and supported by the long short-term memory recurrent neural network (LSTM). The LSTM network model was utilized in the offline forecasting of the PV output power, which was fed to the NNPC as the training data. Additionally, it was used as an alarm flag for any possible PV output shortage during the charging process in the long- and short-term prediction to be supported by any other electricity source. The NNPC–LSTM controller was compared with the fuzzy logic and the conventional PID controllers while varying the input voltage and implementing the MSCC protocol. The proposed charging controller perfectly ensured that the minimum battery terminal voltage ripple and charging current ripple reached 1 mV and 1 mA, respectively, with a very high-speed response of 1 ms in reaching the predetermined charging current stages. The present simulated and experimental results are in good agreement with the previous related work in the literature survey.

An Application of the Super-SBM MAX and LTS(A,A,A) Models to Analyze the Business Performance of Hydropower Suppliers in Vietnam

As Vietnam continues to industrialize and modernize, such economic development and high-tech will require a major electrical energy source to operate the electrical equipment; hence, the hydropower plants are established and growing up to demand. Therefore, the purpose of this study is to evaluate the business performance of Vietnamese hydropower suppliers by integrating the LTS(A,A,A) model of the Additive Holt-winters method in Tableau and a super-slacks-based measure (super-SBM) max model in data envelopment analysis (DEA). The LTS(A,A,A) model is applied to forecast future valuation from 2022 to 2025 based on historical time series from 2012 to 2021. Next, with the actual and predicted data, the researcher uses the super-SBM max model to calculate the business performance of these hydropower suppliers from past to future. The empirical result reveals efficient and inefficient cases to explore which hydropower suppliers can achieve the business performance in their operational process. The position of hydropower suppliers in Vietnam from past to future time is determined particularly based on their scores every year. Further, the empirical result recommends a solution to deal with inefficient cases by deducting the input excesses and raising the output shortages based on the principle of the super-SBM Max model in DEA. The finding results create an overview of the operational process with the continuing variations in each period to equip hydropower suppliers in Vietnam which will determine their future and operational orientation.

Energy efficiency and congestion considering data envelopment analysis and bounded adjusted measure: A case of tomato production

Auditing energy usage of farming operations is a key step towards agricultural sustainability. The current systems of tomato production use a considerable quantity of energy. As a result, improving energy efficiency is a crucial stage in decreasing energy consumption in tomato production. Data envelopment analysis (DEA) model is an established methodology to assess energy efficiency in crop production. In this study, the bounded adjusted measure (BAM) is applied for improving the efficiency of tomato production as well as decreasing the carbon footprint. In this regard, the overall, environmental, production, and pure emission efficiency of tomato production in 24 provinces of Iran are investigated. The nine overall efficient tomato producing provinces recognized that showed they had no input excesses and/or output shortfalls. Also, similar to the overall efficiency, nine out of the 24 DMUs were recognized as environmental, production, and pure emission efficient. Finally, in order to measure the probable amounts of excessive investments in inputs, with the aim of obtaining more outputs, a new approach of determining congestion is proposed based on BAM model.

Evaluating the energy efficiency of wastewater treatment plants in the Yangtze River Delta: Perspectives on regional discrepancies

With priorities to reach a carbon emission peak and integrated development involving ecological demonstration, a systematic evaluation on the energy efficiency and internal discrepancies of wastewater treatment plants in the Yangtze River Delta region is needed. In this study, a slacks-based measure data envelopment analysis model was applied to quantify the relative energy efficiency of 270 regional wastewater treatment plants. Based on the score of relative energy efficiency, the internal discrepancies of the region were identified through a method combining spatial and sensitivity analysis. Although the wastewater treatment plants had met the pollutant limits of discharge standards, the result of data envelopment analysis showed that 253 wastewater treatment plants were inefficient (with efficiency scores less than 1) due to input excess or output shortfall, indicating substantial potential for improving the energy efficiency. Besides, binary logistic regression demonstrated the significant impact from explanatory factors including designed capacity (104 m3/d), loading rate (%), influent ratio of chemical oxygen demand to total nitrogen, and influent concentration (mg/L) of chemical oxygen demand. Moreover, with regards to regional discrepancies, proportion of efficient wastewater treatment plants for Shanghai, Jiangsu, Zhejiang, and Anhui differs significantly. The area surrounding Taihu Lake was recognized as the trough of the Yangtze River Delta region in terms of the relative energy efficiency of wastewater treatment plants. This paper would give a reference for optimization of wastewater treatment plants in the study area and the evaluation framework on internal discrepancies might also be useful for other regions worldwide.

Extremum-seeking control of left ventricular assist device to maximize the cardiac output and prevent suction

The rotary blood pump is one of the latest generations of left ventricular assist devices (LVAD), helping patients to deal with shortage of cardiac output. The main challenge of the LVAD controller is to finely regulate the pump speed in a variety of physical activities from sleep (50 beats/min) till running (180 beats/min). If the pump speed exceeds the low/high extremes, the blood will inversely move (backflow), or the heart muscle will collapse (suction state). This paper shows that the LVAD behaves like a limit cycle and optimizing the amplitude of this limit cycle leads to improve the performance of the LVAD. Therefore, in this paper, a nonlinear controller is proposed based on extremum-seeking theorem in order to regulate the heart performance. The controller objective is to provide the maximum pump flow, while the suction phenomenon is prevented. This goal can be achieved by the proposed controller since it can assure reaching the extremum, taking into account the constraints for preventing suction. The control strategy is applied to an in-silico model, and the results declare that the proposed controller can maintain proper cardiac response, while the mean arterial pressure remains within the demanding range, preventing the suction. The controller's robustness is investigated under different levels of external noise, and the results are compared to the state-of-the-art approaches. The comparison results imply the superiority of the proposed approach to the counterparts.

An integrated bi-objective data envelopment analysis model for measuring returns to scale

Classical efficiency studies on data envelopment analysis (DEA) consider all its inputs and outputs are desirable factors and real valued-data. Additionally, the DEA models only focus either on input-oriented projection minimizing inputs for an inefficient decision making unit (DMU) while keeping outputs at their maximum level, or output-oriented projection maximizing outputs under the present level of input consumption. To simultaneously deal with input excesses and output shortfalls maximizing both projections, this paper proposes a bi-objective DEA model in the context of undesirable factors and mixed integer requirements. These factors and requirements were integrated into the objective function and constraints of the existing bi-objective models. In addition, the proposed model estimates the returns to scale of DMUs that depends on the projections of input reduction and output augmentation. The applicability and usefulness of the proposed model were tested using the dataset of 39 Spanish airports retrieved from the literature. Besides, the proposed model was compared with the three existing bi-objective DEA models in the literature to test its validity.