Technical Efficiency Measures Research Articles

KAPASITAS PERIKANAN CANTRANG DI PELABUHAN PERIKANAN PANTAI TEGALSARI KOTA TEGAL PROVINSI JAWA TENGAH PADA PENGELOLAAN PERIKANAN DEMERSAL

Demersal fish resources are one of the main commodities in the waters of the Java Sea. Tegalsari coastal fishing port is one of the fish landing locations around the Java Sea where most of the demersal commodities landed at the port were caught by cantrang fishing gear. Generally, every fishing activity expects ideal catches by using an efficient input. Technical efficiency can be used as an indicator of performance measurement of fishing gear. This study aimed to determine the fishing capacity of cantrang fisheries in Tegalsari fishing port. The fishing capacity analysis was carried out using fish landing data from PPP Tegalsari from 2008 to 2019. The measurement of technical efficiency by using the DEA (Data Envelopment Analysis) approach. The result showed that fishing capacity in 2013, 2015, 2017, 2018, and 2019 have to be maintained because it is in a fully utilized, and the rest of them were overcapacity caused by an excess capacity of the value of fishing gear and number of efforts. Keywords: Data Envelopment Analysis, Decision Making Unit, fish resources, fishing efficiency, Java Sea-Indonesia

The economic impact of E-commerce on the U.S. airports: Cost savings and productivity growth

The rise of e-commerce, fueled by digitalization and shifting in consumer demand, has revolutionized air cargo. While all e-commerce stakeholders are engaged in fierce competition to increase their market share, airports as integral elements of the air cargo supply chain could not be apathetic to this competition. This study examines the economic implication of e-commerce on high cargo volume airports, focusing on cost savings and productivity growth. Utilizing the Farrell measure of input-oriented technical efficiency, we estimate scope economies for the U.S. airports between 2009 and 2019. The results reveal higher scope economies for high cargo volume airports, indicating greater cost savings resulting from e-commerce activities. In addition, the Malmquist index is employed to assess productivity growth. The index is decomposed into technical change, efficiency change, and scale change. The findings show a 3.3% overall productivity growth in the U.S. airport industry, primarily driven by technical change. Besides, high cargo volume airports exhibit higher productivity growth compared to low cargo volume airports, with 4.1% and 2.9% growth rates, respectively. The gap between high cargo volume and low cargo volume airports widened in 2017, aligning with the pre-pandemic peak in e-commerce activity. Furthermore, high cargo volume airports experience higher efficiency gains and technical advancements. While efficiency gains are attributed to improved performance and increased capacity utilization, the technical advancements can be explained by the digitalization and customized operations associated with e-commerce. Overall, the results highlight the significant contribution of e-commerce to cost savings and productivity growth in high-cargo volume airports.

A Study on Three-Dimensional Modelling of the Baitul Ilmi Mosque's Itera Using Terrestrial Laser Scanner Technology

As advancements in three-dimensional (3D) modeling continue to progress, the demand for precise and efficient measurement techniques has led to significant innovations in the methods and tools used for creating 3D models. Among these, the utilization of Terrestrial Laser Scanners (TLS) has become increasingly popular. This study focuses on the integration of TLS and total station technologies for 3D modeling of a mosque. The total station was employed to conduct five sets of perfectly bonded closed polygon measurements, each consisting of five polygon points, from which three marker points were derived. Concurrently, the TLS was used to perform a comprehensive scan of the mosque from 17 different positions. The data obtained from the TLS scan provided a detailed 3D model, while the total station measurements served as control points to ensure the model's global coordinate accuracy. The processing of the closed polygon data was executed using the Bowditch method, and the TLS data was registered using the cloud-to-cloud method. This approach yielded an overall quality assessment, including a bundle error of 0.008 m, an overlap of 27%, a strength of 65%, and a cloud-to-cloud discrepancy of 0.008 m. The integration of point clouds with total station coordinates resulted in an error margin of 0.160 m. Geometric validation of the model was conducted by comparing its dimensions to measurements obtained using a measuring tape, which yielded a Root Mean Square Error (RMSE) of 0.045 m.

Batch Specular Plane Flatness Measurements Based on Phase Measuring Deflectometry.

Flatness is a critical parameter in the manufacturing industry, directly impacting the fit and overall product performance. As the efficiency of manufacturing continues to advance, there is an increasing demand for more accurate and efficient measurement techniques. Existing methods often struggle to strike a balance between precision and efficiency. In response, this article introduces a novel approach that is capable of achieving high-precision and rapid measurements concerning multiple surfaces. By enhancing the traditional phase measuring deflectometry (PMD) method, employing a matching technique based on polar lines and normal vector constraints to address discrete surface measurement challenges, and implementing a plane pre-positioning method to tackle low efficiency in binocular matching and solving, we successfully performed swift and synchronized measurements for a large batch of specular surfaces and obtained the three-dimensional surface profile of each measured surface. Through experimental validation, the method proposed in this paper can perform the batch measurement of specular planes while maintaining high measurement accuracy.

Relationship between microfinance institutions' self‐sustainability and financing sources: Moderating role of external governance

AbstractThe self‐sustainability of microfinance institutions (MFIs) is a growing concern as they work as non‐profit organizations to achieve global poverty reduction goals. This study aims to examine the MFIs' self‐sustainability using an efficiency measurement technique based on Data Envelopment Analysis (DEA). It also determines the influence of different financing sources on MFIs' self‐sustainability as well as the moderating impact of external governance on this relationship. It uses the Generalized Method of Moments (GMM) estimator to analyze the panel data from 661 MFIs in 86 countries during the 2010–2018 period. The DEA analysis reveals that MFIs are still in the intermediate stage of self‐sustainability in terms of technical and cost efficiency. The second‐stage regression results reveal that financing sources such as retained earnings and equity have a robust positive and statistically significant effect on the MFIs' self‐sustainability, implying that MFIs that rely more on these two sources are more likely to be self‐sustainable. The moderation analysis reveals that good governance accelerates the positive effect of financing sources on MFIs' efficiency. Given these empirical findings, MFIs' decision‐makers can benefit from considering their own funding and equity. Quality governance can be ensured by government agencies and regulatory bodies to support the MFIs' sustainability.

Adaptive measurement strategy for quantum subspace methods

Estimation of physical observables for unknown quantum states is an important problem that underlies a wide range of fields, including quantum information processing, quantum physics, and quantum chemistry. In the context of quantum computation, in particular, existing studies have mainly focused on holistic state tomography or estimation on specific observables with known classical descriptions, while this lacks the important class of problems where the estimation target itself relies on the measurement outcome. In this work, we propose an adaptive measurement optimization method that is useful for the quantum subspace methods, namely the variational simulation methods that utilize classical postprocessing on measurement outcomes. The proposed method first determines the measurement protocol for classically simulatable states, and then adaptively updates the protocol of quantum subspace expansion (QSE) according to the quantum measurement result. As a numerical demonstration, we have shown for excited-state simulation of molecules that (i) we are able to reduce the number of measurements by an order of magnitude by constructing an appropriate measurement strategy (ii) the adaptive iteration converges successfully even for a strongly correlated molecule of H4. Our work reveals that the potential of the QSE method can be empowered by elaborated measurement protocols, and opens a path to further pursue efficient quantum measurement techniques in practical computations.

A novel group decision-making method for interval-valued q-rung dual hesitant fuzzy information using extended power average operator and Frank operations

This paper advances the field of multi-attribute group decision making (MAGDM) by proposing a novel framework based on interval-valued q-rung dual hesitant fuzzy sets (IVq-RDHFSs). IVq-RDHFSs, which surpass most existing fuzzy sets, effectively represent complex fuzzy information by describing membership and non-membership degrees through interval value sets. However, prior MAGDM methods based on IVq-RDHFSs have been limited by the functions of operation rules and aggregation operators (AOs). This limitation is addressed through the construction of a new MAGDM framework, leveraging the robust Frank t-norm and t-conorm (FTT) operation and the extended power average (EPA) operator. The proposed framework features the interval-valued q-rung dual hesitant fuzzy Frank weighted extended power average (IVq-RDHFFWEPA) operator to obtain comprehensive evaluation values. The paper also introduces novel techniques for determining the weights of decision-makers and attributes. Practical applications of the proposed method are demonstrated through the assessment of desalination technology selection and rural green eco-tourism projects. Sensitivity and comparison analyses validate the superior functionality, accuracy, and flexibility of this method compared to many state-of-the-art methods. The contributions of this paper are two-fold: it develops efficient measurement techniques for IVq-RDHFSs, such as distance and weight calculation, and it introduces a comprehensive MAGDM method by integrating FTT and EPA under IVq-RDHFSs, which improves the efficiency of solving decision-making problems.

Scale elasticity and technical efficiency measures in two-stage network production processes: an application to the insurance sector

In performance analysis with tools such as data envelopment analysis, calculations of scale properties of the frontier points are studied using both qualitative and quantitative approaches. When the production process is a bit complicated, the calculation needs to be modified. Most existing studies are focused on a single-stage production process under the constant or variable returns to scale specification. However, some processes have two-stage structures, and, in such processes, the concepts of scale elasticity and returns to scale are inextricably related to the conditions of the stages of production. Thus, an evaluation of efficiency, scale elasticity, and returns to scale is sensitive to stages. In this study, we introduced a procedure to calculate technical efficiency and scale elasticity in a two-stage parallel-series production system. Then, our proposed technical efficiency and scale elasticity programs are applied to real data on 20 insurance companies in Iran. After applying our estimations to a real-world insurance industry, we found that, (i) overall, the total inputs of insurers in the life insurance sector should be reduced by 9%. Moreover, the inputs of nonlife insurers should be reduced by 50%. The final output in the investment sector must be increased by 48%. (ii) There are inefficiencies among all insurers in the investment sector, and to improve technical efficiency, the income from investments should be increased significantly. (iii) Finally, the efficiency and elasticity characterizations of insurers are directly subject to stages.

Technical efficiency measurement in insurance companies by using the slacks-based measure (SBM-DEA) with undesirable outputs: analysis case study

PurposeThe purpose of this study is to measure the technical efficiency of 20 Algerian insurance companies from 2016 to 2020, by using slacks-based measure (slacks-based measure [SBM] data envelopment analysis [DEA]) model. This research aims to provide a comprehensive assessment of this companies' efficiency, taking into account both the desirable and undesirable outputs.Design/methodology/approachThe study uses a nonoriented, SBM model with the assumption of constant returns to scale to estimate the technical efficiency of commercial insurance companies over a five-year period. The inputs used are labor expense, agent expense and investments, while the outputs included are gross premiums and investment income as desirable outputs and gross claims as undesirable output.FindingsAmong 20 insurance companies evaluated, only 5 companies consistently achieved technical efficiency during the study period (Caisse Nationale de Mutualité Agricole [CNMA], MACIR, CARDIF, MUTUALISTE and AGLIC); so they represent the best practices in the Algerian insurance sector, with overall average of the technical efficiency is 81%. However, the reference sets analysis showed that CNMA and AGLIC had high robustness. Also, the results demonstrate the impact of ignoring the undesirable outputs on the accuracy of the assessment.Research limitations/implicationsThe sample of the study consists of the active insurance companies in Algeria, based on the Annual Insurance Reports of Algeria; there are 20 companies as shown in the table. The data are taken from the annual reports of insurance companies during the 2020 period, issued by the Algerian Ministry of Finance.Practical implicationsThe challenge for insurance company is how to find a balance between reducing claims paid and simultaneously improving the quality of insurance services. In fact, it is observed that studies evaluating their efficiency ignore claims in the analysis process. Therefore, the study highlights the importance of considering undesirable outputs within the DEA framework; this allows for a more accurate assessment of the company's performance and helps in improvement. Furthermore, although the insurance sector plays a crucial role, it has not received enough research attention compared to other financial sectors, especially in Arab and developing countries.Originality/valueThe literature on efficiency assessment in the insurance companies shows a lack of addressing undesirable outputs (such as claims) within the DEA framework; so this study aims at bridging this research gap. Also, the study provides an overview of the efficiency of Algerian insurance companies.

Technical efficiency in banks: a review of methods, recent innovations and future research agenda

AbstractTechnical efficiency in banking is a critical aspect of the financial industry and has been widely studied using various measurement techniques. This systematic literature review offers a comprehensive examination of 305 studies on the application of technical efficiency measurement techniques in both Islamic and conventional banking sectors from 1989 to 2019. Our comprehensive analysis not only provides a broad view of the efficiency measurement literature but also outlines a future research agenda. Despite the extensive research in this field, several issues remain unresolved, including input–output selection, a comparison of efficiency between Islamic and conventional banks, limited cross-country studies, and a lack of exploration into the impact of regulation and Shariah principles. To address these gaps, this review highlights the most commonly used methods, variables, and findings and provides three key recommendations for future research. Three key themes emerge from our examination. First, there is a need to better understand and the application of new frontier techniques other than the traditional methods, which currently dominate the existing literature. Second, the intermediation approach is the most frequently used in variable selection, thus more studies with comparative findings with applications of production and value-added approaches are suggested. Third, the most frequently used input variables are ‘labor’, ‘deposits’ and ‘capital’, whilst ‘loans’ and ‘other earning assets’ are the most popular output variables. We recommend three vital directions for future research: (i) non-interest expenses to be included amongst the inputs, while non-interest income should be added to the list of outputs, especially when estimating efficiency scores of Islamic banks. (ii) The impact of environmental variables such as, inter alia, Shariah principles, country-specific factors, and management quality is suggested to be considered simultaneously in models measuring and comparing the efficiency of Islamic and conventional banks. (iii) The selection of performance metrics employed should be expanded to include both the standard efficiency scores and the Malmquist Total Factor Productivity Index (TFP). The paper concludes with research needs and suggests directions for future research.

Application of artificial neural networks to predict the particle-scale contact force of photoelastic disks

Measuring the contact force of photoelastic granular materials in a two-dimensional system either has a high dependence on the experimental parameters or requires expensive computations. This study proposes a supervised machine learning strategy that constructs a universal relation between the features of a stressed photoelastic disk and the corresponding total contact force acting on it via an artificial neural network (ANN). Most of the common circumstances of particle–particle contact that occurs in real photoelastic granular flow experiments are considered in the data. The ANN reached a test R-squared value of about 0.96. Therefore, the proposed machine learning framework is an efficient and accurate force measurement technique for two-dimensional photoelastic granular flows.

A practical subcritical rod worth measurement technique based on the improved neutron source multiplication method

The control rod worth is a key safety parameter required to be measured in commercial pressurized water reactors (PWRs). Conventionally, the control rod worth is measured after reaching the critical state, which occupies the considerable time in the zero-power physics test. In this study, an efficient control-rod worth measurement technique has been proposed based on the improved neutron-source multiplication method, which can be implemented with the source-range detector count rates in the subcritical states. Moreover, the noise reduction technique has been adopted to smooth the large fluctuation existing in the original signals. In order to verify the engineering performance of the proposed measurement technique, the measured source-range detector count rates during the rod withdrawal process before reaching critical state in a CNP1000 reactor have been employed. It demonstrated that almost all estimated results of control rod worth satisfy the engineering acceptance criteria, except one control rod with the relative difference over 10 %, which indicates the capability of the proposed method in estimating control rod worth.

Use of catch and effort data to monitor trends in economic performance in fisheries

Abstract In many low-valued fisheries, the quantity and types of data that might be available to support fisheries management are often limited. Generally, information on the economic performance of the fishery is low in priority in these fisheries. Basic catch and effort information, however, may contain implicit information about economic performance of the vessels. From these data, technical efficiency scores and measures of capacity utilization can be derived. The technical efficiency score can provide a proxy measure of the distribution of economic performance, while changes in capacity utilization theoretically reflect changes in the economic conditions in the fishery. Given this, changes in these measures over time should also reflect changes in economic outcomes and performance. To test this, we use data from a data-rich fishery, including catch and effort information as well as detailed economic information (i.e. vessel-level profitability). Key technical performance measures are estimated using data envelopment analysis and compared with the economic performance measures. We show that these technical performance measures can provide useful indicators of changes in economic performance when economic information is not available.

On aggregation of technical and revenue efficiency measures

On aggregation of technical and revenue efficiency measures

Deep eutectic solvents with solid supports used in microextraction processes applied for endocrine-disrupting chemicals

The determination of endocrine-disrupting chemicals (EDCs) has become one of the biggest challenges in Analytical Chemistry. Due to the low concentration of these compounds in different kinds of samples, it becomes necessary to employ efficient sample preparation methods and sensitive measurement techniques to achieve low limits of detection. This issue becomes even more struggling when the principles of the Green Analytical Chemistry are added to the equation, since finding an efficient sample preparation method with low damaging properties for health and environment may become laborious. Recently, deep eutectic solvents (DESs) have been proposed as the most promising green kind of solvents, but also with excellent analytical properties due to the possibility of custom preparation with different components to modify their polarity, viscosity or aromaticity among others. However, conventional extraction techniques using DESs as extraction solvents may not be enough to overcome challenges in analysing trace levels of EDCs. In this sense, combination of DESs with solid supports could be seen as a potential solution to this issue allowing, in different ways, to determine lower concentrations of EDCs. In that aim, the main purpose of this review is the study of the different strategies with solid supports used along with DESs to perform the determination of EDCs, comparing their advantages and drawbacks against conventional DES-based extraction methods.

Investment preference for either technical or operational energy efficiency measures to achieve sustainable maritime shipping

AbstractThe reduction in energy consumption in shipping is a crucial issue to achieve a more sustainable sector. Nevertheless, investments in energy efficiency are inhibited by barriers. Consequently, under a Principal-Agent approach, this study aims to analyze the factors affecting the investment preference for either technical or operational measures. To date, the research problem has barely been addressed from a similar approach. This work further integrates agency theory with the identification of barriers and drivers, as well as the cost–benefit ratio from both an environmental and a financial perspective. This makes it possible to consider shipping management from a more comprehensive perspective. The study sample is current and representative (658 individual bulk carriers). The research was carried out utilizing two binominal logistic models that provide similar results when testing the proposed hypotheses. The outcomes show that regulatory factors, such as the distance of a vessel’s technical emissions from EEDI requirements (standardized coefficients: −2.8352 and −2.5069), and Principal-Agent problems, such as split incentives (standardized coefficients: −1.0059 and −0.9828), have the greatest influence on investment preferences. As a consequence of Principal-Agent problems, vessels operating under Time Charter contracts are less likely to invest in technical measures than in operational ones. Verified information and activity promote technical measures. Maritime regulation promotes technical measures in younger vessels, especially those meeting only the minimum requirements. Better knowledge can help achieve a more environmentally responsible shipping sector. The role of shipowners and charterers should be highlighted, and transparency should be promoted to enable well-informed decisions to be made.

Artifact Correction of Light Induced Detuning in QCM-D Experiments.

The quartz crystal microbalance with dissipation (QCM-D) has become an efficient and versatile measurement technique for investigating in situ the external stimuli responsiveness such as pH, temperature, or chemical gradients of surface-active substances at solid-liquid interfaces. However, light responsive adsorption investigation is more challenging presumably since the quartz crystal itself reacts to optical stimulation, showing frequency and dissipation shifts known as light induced detuning (LID). This yields an effective measurement artifact and makes data interpretation with respect to dynamic interactions of light responsive materials rather challenging. Here we introduce a simple guideline for correcting the artifacts of the QCM sensor response on irradiation to ensure quantitative analysis for light responsive materials via OCM-D. We also show that the LID depends on the adsorption properties of the sensor and the solvent properties (ionic concentration or viscosity), providing a guideline to minimize impact of the LID.

Nonlinear phase error correction method based on multi-grayscale coding.

Fringe projection profilometry is a non-contact and highly efficient 3D measurement technique widely used in various applications. However, the nonlinear intensity response of digital projectors affects measurement accuracy. While increasing the number of fringe projections can reduce the errors caused by nonlinear problems, it significantly prolongs the measurement time. In order to improve both accuracy and speed simultaneously, a nonlinear phase error correction method based on multi-grayscale coding is proposed. The intensity response curve of the system is fitted by the grayscale images, and then the grayscale values of the phase-shifting fringe images are corrected to reduce the nonlinear error. In order to reduce the number of fringe projections and speed up the measurement, the multi-grayscale coding method is used to divide the phase interval by the order of the gray values of the same pixel in multiple grayscale images. The experimental results validate the efficacy of the proposed multi-grayscale coding method. An accurate phase calculation is achieved, and a single reconstruction can be achieved with only seven photos. After the nonlinear correction, the phase accuracy of the three-step phase-shifting algorithm is increased by 50.77%, and the reconstruction accuracy of the standard ball is increased by 46.38%.

Rail Corrugation Index Development by Sound-Field Excitation on the Carriage Floor of In-Service Train.

The steel rail and wheel in the railway system offer a high precision and smooth-running surface. Nevertheless, the point of contact between the rail and wheel presents a critical area that can give rise to rail corrugation. This phenomenon can potentially elevate sound and vibration levels in the vicinity considerably, necessitating advanced monitoring and assessment measures. Recently, many efforts have been directed towards utilizing in-service trains for evaluating rail corrugation, and the evaluation has primarily relied on axle-box acceleration (ABA). However, the ABA measurements require a higher threshold for vibration detection. This study introduces a novel approach to rail corrugation detection by carriage floor acceleration (CFA), aimed at lowering the detection threshold. The method capitalizes on the acceleration data sensed on the carriage floor, which is induced by the sound pressure (e.g., sound-field excitation) generated at the wheel-rail contact point. An exploration of the correlation between these datasets is undertaken by simultaneously measuring both ABA and CFA. Moreover, a pivotal aspect of this research is the development of the eigenfrequency rail corrugation index (E-RCI), a mechanism that culminates energy around specific eigenfrequencies by CFA. Through this index, a focused analysis of rail corrugation patterns is facilitated. The study further delves into the stability, repeatability, and sensitivity of the E-RCI via varied measurement scenarios. Ultimately, the CFA-based rail corrugation identification is verified, establishing its practical applicability and offering a distinct approach to detecting and characterizing rail corrugation phenomena. This study has introduced an innovative methodology for rail corrugation detection using CFA, with the principal objective of lowering the detection threshold. This approach offers an efficient measurement technique for identifying rail corrugation areas, thereby potentially reducing maintenance costs and enhancing efficiency within the railway industry.

Electrical design for efficiency: technical and operational measures for optimizing the use of electrical power on ships

There is currently a growing concern in the shipping industry about energy consumption and environmental impacts. According to the International Maritime Organization's (IMO) energy efficiency guidelines, today's ships must have an energy efficiency management plan to reduce the CO2 emission and other pollutants. In this article, a bibliographic review of methodologies for the optimization of energy consumption on ships is carried out, starting from the identification of sources of energy losses, to the implementation of technical and operational measures that contribute to their improvement, making a qualitative evaluation of the identified methodologies. Sources of energy losses associated with equipment and auxiliary systems are analyzed, as well as opportunities for improvement in the use of electrical energy through the implementation of intelligent energy management systems, high efficiency motors, and lighting. The technical and operational energy efficiency measures described above demonstrate the importance of their implementation from the early stages of the ship's electrical design, as well as monitoring energy consumption during its life cycle, to improve energy efficiency on board.