Level Of Operational Efficiency Research Articles

A Novel Advanced IoT System for Predictive Maintenance Systems and Supply Chain Optimization Solutions for Manufacturing Industries

This paper presents a pioneering approach to revolutionize manufacturing industries through the development of a novel advanced Internet of Things (IoT) system tailored for predictive maintenance and supply chain optimization. Leveraging the vast array of data generated within manufacturing environments, the proposed system integrates cutting-edge IoT technologies with advanced predictive analytics to enable proactive identification of equipment failures and optimization of supply chain operations. The research encompasses a comprehensive dataset comprising sensor data, maintenance records, and supply chain information sourced from industrial pumps, facilitating the creation of robust predictive maintenance models and insightful supply chain optimization strategies. Experimental procedures involve data pre-processing, feature engineering, and model development, followed by rigorous evaluation against ground truth data. The results showcase significant enhancements in equipment up-time; maintenance cost reduction, and supply chain responsiveness, demonstrating the efficacy and scalability of the IoT-based solutions. Through this innovative approach, manufacturing industries can achieve unprecedented levels of operational efficiency, cost savings, and competitive advantage, paving the way for transformative advancements in predictive maintenance and supply chain management paradigms.

SOFTWARE AND HARDWARE MODULE FOR AUTOMATED DETECTION AND RECOGNITION OF INTEREST OBJECTS TO INCREASE THE LEVEL OF PROCESSING EFFICIENCY AND RELIABILITY OF AERIAL RECONNAISSANCE DATA

The requirements for the air reconnaissance system using unmanned aircraft systems are being studied. Problematic aspects of the air reconnaissance data processing process are analyzed from the point of view of ensuring the required level of operational efficiency and reliability of intelligence information. The possibility of automating the process of detecting aerial reconnaissance objects on video images is being investigated. A software-hardware module for automated detection and recognition of objects of interest is being developed to increase the level of processing efficiency and reliability of air reconnaissance data. Modern models of detection and recognition of objects of interest based on algorithms of the YOLO platform are studied. The software component of the module is being developed using the YOLOv8 algorithm architecture and a set of data formed in the conditions of air reconnaissance. The analysis of the results of experimental studies shows that: the developed model allows to ensure the required level of operational efficiency of video image processing and the reliability of aerial reconnaissance data; practical implementation of the developed model at ground command and control stations is possible without the use of additional computing equipment. The hardware component of the module is being developed using Raspberry Pi components. The analysis of quantitative evaluations of the efficiency of data processing using the developed software and hardware module on board the UAV of the studied class indicate an increase in time delays compared to the implementation at the command-and-control station, but it allows to ensure the required level of reliability. Further scientific research will be aimed at investigating the peculiarities of the implementation of the conceptual foundations of the developed module for various classes of UAV in order to increase the level of processing efficiency and reliability of aerial reconnaissance data.

Smart Energy Management Construction of Electric Power with Application of Bioelectricity Technology

Abstract The search for sustainable energy solutions has become urgent against the current energy crisis and increasing environmental pollution. Biomass energy conversion and utilization technology, a clean and renewable energy source, constantly evolves, particularly in biomass power generation technology. This technology can effectively reduce greenhouse gas emissions and dependence on fossil fuels. Biomass conversion and utilization techniques include combustion, gasification, and biochemical methods that generate different energy forms, including heat, electricity, and fuel. Developing these technologies provides strong technical support for optimizing energy structures and protecting the environment. The article explores the application of biopower technology in intelligent energy management of electricity and improves its efficiency. The efficiency of biopower technology and its influencing factors were investigated using the Data Envelopment Analysis (DEA) model and Tobit regression analysis. A study was conducted on ten biopower energy companies. The energy management efficiency score of 1 was present in six of these companies, suggesting a relatively high operational efficiency level. Company C has a super-efficiency value of 2.654, indicating its outstanding energy management efficiency. Factors such as human resource input, total investment, and annual production costs significantly affect energy management efficiency. By optimizing resource allocation and improving management efficiency, biopower technology can be applied more effectively to intelligent energy management, thus promoting sustainable development.

ANALISIS RISIKO KREDIT DAN TINGKAT EFISIENSI OPERASIONAL TERHADAP PRFITABILITAS PADA KOPERASI DI KOTA MATARAM

The purpose of this study was to determine the effect of credit risk and the level of operational efficiency on the profitability of cooperatives in the city of Mataram. This study uses quantitative analysis with an associative approach. The type of data used is secondary data with data processing using the SPSS version 25.0 program. Data collection techniques used are observation and documentation. The samples used were five cooperatives with a purposive sampling technique with certain criteria. The data analysis used is multiple linear regression analysis with a determination coefficient of 55.90% on profitability. The results of the t-test stated that credit risk had no significant effect on profitability, while the level of operational efficiency had a significant effect on the profitability of cooperatives in the city of Mataram. The results of the F-test show that credit risk and the level of operational efficiency jointly affect the profitability of cooperatives in the city of Mataram.

Factors Affecting Return on Asset with The Moderation Role of Non-Performing Loans in National Private Banking

The aim of this research is to determine the influence of capital adequacy levels, liquidity levels, bank operational efficiency levels, inflation and interest rates on banks' ability to generate profits before tax with the moderating role of non-performing loans. The level of capital adequacy is proxied by the Capital Adequacy ratio (CAR), the level of liquidity is proxied by the Loan to Deposit Ratio (LDR), the level of operational efficiency is proxied by operational cost to operating income ratio (CI) and the level of the bank's ability to generate profits before tax is proxied by Return on Assets (ROA) while non-performing loans are proxied by Non-Performing Loans (NPL). The indicator for measuring the level of inflation is the Consumer Price Index (CPI) while the interest rate used in this research is the BI rate. The sample was selected using the purposive sampling method, 45 banks were selected as samples. The analysis technique in this research is partial least squares (PLS) for testing measurement and structural models. The results of this research are: 1) CAR has no effect on ROA, 2) LDR has no effect on ROA, 3) CI has a significant negative effect on ROA, 4) Inflation has no effect on ROA, 5) Bank Rate has a significant positive effect on ROA, 6) NPL does not strengthen the influence of CAR on ROA, 7) NPL does not strengthen the influence of CAR on ROA, 8) NPL does not strengthen the influence of CI on ROA, 9) NPL does not strengthen the influence of inflation on ROA, 10) NPL does not strengthen the influence of the BI rate on ROA.

Tingkat Bagi Hasil Mudharabah Bank Umum Syariah: Analisis Kinerja Keuangan

This study aims to examine the signaling theory by analyzing the effect of financial performance such as profitability, financing risk, liquidity, operational efficiency and capital adequacy on the profit sharing rate of Islamic Commercial Banks (BUS) mudharaba deposits. The method used in this research is a quantitative descriptive method with panel data regression analysis techniques. Data collection techniques were carried out through documentation and literature study methods. The population in this study were 14 Islamic Commercial Banks. The method used for sampling in this research is purposive sampling with predetermined criteria, with a total sample of 11 Islamic Commercial Banks for four years (2017-2020), with a total of 176 observational data. The results showed that simultaneously the level of profitability, the level of financing risk, the level of liquidity, the level of operational efficiency and the level of capital adequacy had a significant effect on the rate of profit sharing for mudharaba deposits. Partially, the level of profitability and the level of operational efficiency have a positive and significant effect on the rate of profit sharing for mudharaba deposits. The level of liquidity has a negative and significant effect on the rate of profit sharing for mudharaba deposits. The level of financing risk and the level of capital adequacy have no effect on the rate of profit sharing for mudharaba deposits.

Enhancing Manufacturing Competitiveness in UAE SMEs: The Influence of Process Quality Improvement and Lean Practices

This research investigates the relationship between process quality improvement, lean practices, and manufacturing competitive performance in Small and Medium-sized Enterprises (SMEs) within the United Arab Emirates (UAE). The UAE has emerged as a dynamic hub for SME manufacturing, making it crucial to examine factors that contribute to their competitive advantage. The research employs a mixed-methods approach, combining qualitative data from in-depth interviews with key industry experts and quantitative data obtained through structured surveys distributed among a diverse sample of SME manufacturing firms across different sectors. The study focuses on evaluating the adoption and implementation of process quality improvement initiatives and lean practices within these organizations. The findings highlight a strong positive correlation between effective process quality improvement and lean practices and improved manufacturing competitive performance among UAE SMEs. Firms that successfully integrated lean methodologies into their processes demonstrated higher levels of operational efficiency, reduced waste, increased productivity, and improved product quality. Additionally, the research identifies critical success factors and challenges in the implementation of process quality improvement and lean practices in the context of UAE SMEs. Factors such as top management commitment, employee involvement, and access to training and resources are instrumental in fostering a culture of continuous improvement.

Analisis Pengaruh Kinerja Keuangan Terhadap Bagi Hasih Deposito Mudharabah Bank Umum Syariah di Indonesia Periode 2017-2022


 
 
 
 The goal of this study was to examine the impact of various factors on the profit-sharing level of Mudharabah deposits held by fully-fledged Islamic banks, including profitability level, profitability level, financing risk level, liquidity level, operational efficiency level, and capital adequacy level. A quantitative descriptive method with panel data regression analysis techniques was used in this investigation. The approaches used for data collecting included documentation and literature study. 168 observational data were collected across 7 Full-Fledged Islamic Banks over the course of six years, from 2017 to 2022. The findings demonstrated that the profit sharing rate of Mudharabah deposits was significantly influenced by the levels of profitability, financing risk, liquidity, operational efficiency, and capital sufficiency at the same time. The amount of profitability, the level of financing risk, and the level of operational efficiency all somewhat influence the profit-sharing rate for Mudharabah deposits in a positive and significant way. The profit sharing rate of Mudharabah deposits is unaffected by both liquidity and capital adequacy levels.
 Keywords: Financial ratio, signaling theory, level of profit sharing mudaraba deposits
 
 
 
 

Microfinance's digital transformation for sustainable inclusion

PurposeThe purpose of this paper is to evaluate the performance of Microfinance Institutions (MFIs) offering FinTech services. This study contributes to the existing literature on microfinance digitalization, financial inclusion and sustainable development. The study also takes into consideration a behavioral perspective through the efficiency evaluation process of MFIs offering FinTech services.Design/methodology/approachThe following study employs the Stochastic Frontier Analysis approach to estimate the operational and social efficiency scores of the 387 MFIs over the period 2005–2019. Then, it tries to consider factors influencing MFIs' efficiency and assess their effects. Hence, two separate models for operation and social efficiency introducing a set of factors, including FinTech proxies and overconfidence proxies, are tested. The first model for operational efficiency uses a random-effects estimator while the second one for social efficiency uses a fixed-effects estimator.FindingsThe results show that innovative MFIs have weaker averages of operational efficiency than non-innovative ones but higher averages of social efficiency. This was justified by the fact that innovative MFIs are more socially oriented. Further, findings of this study depict that the proxies of FinTech affect negatively the level of operational efficiency of MFIs. They also depict a negative relationship between FinTech proxies and the level of social efficiency. These results hold through robustness tests.Originality/valueThe highlight of this study is that it takes heed of the indirect effect of technological innovation on the efficiency of MFIs. It has been proved that it moderates the impact of managerial overconfidence (manifested by excessive risk-taking, viz., high levels of PAR30, LGR and NIM) on the level of both operational and social efficiencies.

A Three-Tiered Analysis of the Factors Influencing the Adoption of Forensic Accounting Field in Saudi Arabia

Purpose: The study shows how several perceptionistic, environmental, and economic aspects can be systematically assessed in advance of investment decisions to launch a proposed Master's program in Forensic Accounting. Theoretical framework: Since the final decade of the twentieth century there has been increasing global interest in adopting and applying forensic accounting, fraud detection methods, and financial fraud examination . However, there are no specialized postgraduate programs in this field at either the local (Saudi) or regional (Middle Eastern) level, despite its importance to meeting the needs of accountancy and judicial employers. Design/methodology/approach: An inductive and analytical approach evaluates the proposed program using a three-stage model that can be adopted by any higher education institution (HEIs) wishing to develop an educational program. Findings: The results show that the vast majority of the program's beneficiaries support its implementation due to its novelty both locally internationally. The program gives the University of Tabuk, its initiator, a sustainable competitive advantage over other local and regional universities through supplying the labor market with graduates qualified in financial criminal investigation. Finally, the financial analysis indicates that the program will be strong financially and have a high level of operational efficiency and expected demand. Research, Practical & Social implications: The findings are beneficial for HEIs seeking to achieve a competitive advantage over their rivals by offering attractive academic programs that meet the demands of the labor market. Originality/value: The study is the first that it uses a three-stage assessment model to show how several perceptionistic, strategic, and economic aspects can be systematically assessed in advance of investment decisions related to launching new academic programs in HEIs.

An Efficient Metaheuristic Algorithm for Job Shop Scheduling in a Dynamic Environment

This paper proposes an Improved Multi-phase Particle Swarm Optimization (IMPPSO) to solve a Dynamic Job Shop Scheduling Problem (DJSSP) known as an non-deterministic polynomial-time hard (NP-hard) problem. A cellular neighbor network, a velocity reinitialization strategy, a randomly select sub-dimension strategy, and a constraint handling function are introduced in the IMPPSO. The IMPPSO is used to solve the Kundakcı and Kulak problem set and is compared with the original Multi-phase Particle Swarm Optimization (MPPSO) and Heuristic Kalman Algorithm (HKA). The results show that the IMPPSO has better global exploration capability and convergence. The IMPPSO has improved fitness for most of the benchmark instances of the Kundakcı and Kulak problem set, with an average improvement rate of 5.16% compared to the Genetic Algorithm-Mixed (GAM) and of 0.74% compared to HKA. The performance of the IMPPSO for solving real-world problems is verified by a case study. The high level of operational efficiency is also evaluated and demonstrated by proposing a simulation model capable of using the decision-making algorithm in a real-world environment.

Unraveling the Link between Financial Performance and Mudaraba Deposit Returns: The Case of Full-fledged Islamic Bank

The goal of this study was to examine the impact of various factors on the profit-sharing level of Mudaraba deposits held by fully-fledged Islamic banks, including profitability level, profitability level, financing risk level, liquidity level, operational efficiency level, and capital adequacy level. A quantitative descriptive method with panel data regression analysis techniques was used in this investigation. The approaches used for data collecting included documentation and literature study. 168 observational data were collected across 7 Full-Fledged Islamic Banks over the course of six years, from 2017 to 2022. The findings demonstrated that the profit-sharing rate of Mudaraba deposits was significantly influenced by the levels of profitability, financing risk, liquidity, operational efficiency, and capital sufficiency at the same time. The amount of profitability, the level of financing risk, and the level of operational efficiency all somewhat influence the profit-sharing rate for Mudaraba deposits in a positive and significant way. The profit-sharing rate of Mudaraba deposits is unaffected by both liquidity and capital adequacy levels.

Russia-Ukraine conflict: The effect on European banks’ stock market returns

We examine the short-term market impact of the beginning of the military conflict between Russia and Ukraine (February 24, 2022) on the largest European listed banks. Using an event study, for the 100 largest European listed banks, we observe a negative and statistically significant stock price reaction at and around the beginning of the military conflict. These results are consistent with investor sentiment, investment portfolio rebalancing and the asset pricing perspective. Furthermore, we use a cross-sectional analysis against a set of country- and bank-specific variables. The results show a higher negative stock market reaction for Russian listed banks and for foreign banks with a high exposure to Russia. The magnitude of the stock market reaction to the military conflict is reinforced or mitigated by bank-specific determinants such as size, profitability, risk aversion, operational efficiency level, institutional ownership and exposure to Russia.

An IIoT-Based Approach to the Integrated Management of Machinery in the Construction Industry

In recent years, considerable advances in connecting industrial equipment to the Internet allowed a higher level of operational efficiency, productivity, and automation. Nevertheless, the construction industry still presents challenging requirements, like long-distance wireless communication, interconnection of out-of- coverage areas, constant mobility of machinery, and support for legacy and proprietary systems. All these requirements pose different challenges when compared with traditional smart factory Industry 4.0 solutions. This paper discusses some of the current key questions regarding fleet management in the construction industry, identifies requirements for heavy-duty machinery, and proposes an Industrial Internet of Things (IIoT)-based solution for the integrated monitoring of such machinery. Also, it proposes and presents an open, innovative solution for the integrated management of non-standardized civil construction vehicle technologies. The developed prototype uses the J1939 protous and protocol to collect machinery status and Long-Range Wide Area Network (LoRaWAN) to communicate the monitored data. The solution was assessed at the construction site of the new port of Sines in Portugal. A detailed description of the proposed system is provided, along with information on trials and evaluation results regarding its performance. Additionally, the paper provides insights into open issues and challenges in this field and how our solution can contribute to overcoming them.

Evaluation Analysis of the Operational Efficiency and Total Factor Productivity of Container Terminals in China

As crucial international trade and global logistics players, container terminals worldwide handle more than 80% of the global merchandise trade. After analyzing and summarizing the previous studies, we use container terminal companies as the research object to fill the gap left by previous studies. Based on the above research status, this study analyzes the operational efficiency and total factor productivity of 32 container terminal companies in China using the super -efficiency DEA–SBM model and the Malmquist index method. The results show that (1) the operational efficiency level of 32 container terminals in China from 2017 to 2020 has a huge gap, and 15 container terminal companies have operational efficiency below 0.6, which indicates that most container terminals have excess inputs and a waste of resources. (2) The container terminals in the Bohai Rim, Pearl River Delta and Yangtze River Delta regions have higher operational efficiency. This shows that the development of container terminals cannot be separated from the economic hinterland of the cities where the ports are located. (3) The Malmquist index analysis shows a 2.8% decrease in total factor productivity, a 3.2% increase in the composite technical efficiency index and a 5.8% decrease in the technological progress index, which indicates that most container terminal companies have imperfect management practices and decision making. Based on the study’s results, this research provides relevant and feasible recommendations for policymakers who formulate policies for the development of the shipping industry to promote high quality and sustainable development of the shipping industry and the economy.

Analysis on operational efficiency and its influencing factors of China’s nuclear power plants

After implementing the new reform policy of the electric system in 2015, the market-oriented reform of nuclear power prices has been further deepened, as China's nuclear power plants, like other market participants, have also faced increasingly fierce competition. One critical issue worth investigating is how well these plants perform and the influencing factors. To address that issue, we construct an SBM-ML-Tobit model based on plant-level data over five years, from 2016 to 2020. And for all we know, this is the first study to examine Chinese nuclear power plants' operational efficiency. The empirical results indicate significant differences in operational efficiencies between these plants; the operational efficiency levels of all the plants are improved to varying degrees in the sample interval with the increasingly fierce market competition. In addition, our findings suggest that operational efficiencies of power plants are significantly promoted by capacity utilization, average unit size, and unit capacity factor, significantly suppressed by plant size. Again, the operational efficiency levels of plants with higher unit capacity factors are less adversely affected by plant size. Accordingly, our study provides important policy suggestions for better design of the mechanisms to improve the operational efficiency of China's nuclear power plants.

Software-Based Studios

<i>The digital transformation for media production has been set in motion by the transition from serial digital interface (SDI) to Internet Protocol (IP). Given the digital shift in consumption, how is media production adapting? More media channels must be served with more differentiated content. How does a public broadcaster with limited budget deal with these changes? With these constraints, sometimes the most innovative, yet simple solutions emerge. Delaying the new broadcast building highlighted an impending problem; the current infrastructure is wearing out. The issue of how to bridge the next five years was turned into a learning opportunity for both the technology and the operations departments. To achieve a new level of operational efficiency, software-based production seems to be the direction to take to create a production environment that is flexible, scalable, and shareable for both recurring and one-off productions at Vlaamse Radio en Televisie (VRT)</i>.

The Performance and Efficiency of XYZ Bank Work Units

Bank is an institution or business entity that has a big role in the financial system in the world, especially in Indonesia. The banking industry, which consists of government-owned banks and private banks with sharia and conventional systems, are mutually exclusive to survive the current tough competition. There have been various ways that have been done to attract attention to its customers. Bank XYZ realizes that the competition between companies is getting bigger, therefore the management of XYZ Bank issued a policy by building a new work unit. The operational sustainability of XYZ Bank in the Indonesian banking industry is closely related to the ability to maintain high competitiveness. Bank competitiveness can be reflected in the level of operational efficiency. This study uses secondary data from the XYZ Bank work unit and is analyzed by Data Envelopment Analysis. It is known that in the Bogor work unit, from the 17 times studied, 5 of them experienced inefficient conditions, while the Yogyakarta work unit was known to have 6 times that were inefficient. Keywords: data envelopment analysis, efficiency, work unit, banking industry, bank competitiveness

Analysis of the Effect of Credit Expansion, Operational Efficiency Rate, Lending Interest Rate, NPL of the Previous Period and Capital Adequacy Ratio (CAR) on Non-Performing Loans Based on the Generalized Method of Moment

This study aims to determine the effect of credit expansion, operational efficiency, lending interest rate, NPL in the previous period and Capital Adequacy Ratio (CAR) on Non-Performing Loans (NPL). This type of research was quantitative and used secondary data from annual reports. This study used a sample of 20 conventional commercial banks registered on the IDX in 2017-2019 with sample determination using the purposive sampling method. The technique for analyzing data in this study used the Generalized Method of Moment (GMM) with data processing using the help of the Eviews 9 application. Based on the Generalized Method of Moment (GMM) analysis, it was obtained that credit expansion as measured by loan to deposit ratio and lending interest rate did not significantly affect non-performing loans. The level of operational efficiency as measured by Operating Expenses on Operating Income (BOPO), NPL of the previous period, and Capital Adequacy Ratio (CAR) significantly affected non-performing loans.

Operational efficiency analysis of China's electric power industry using a dynamic network slack-based measure model

Operational efficiency analysis is the foundational work for the management policy adjustment of the electric power industry in China and many other countries, but it is difficult to conduct because of the system complexity. This research uses a network structure to simulate the operating process of this industry. Through introducing the dynamic slack-based measure algorithm into this structure, the operational efficiencies of the entire industry and each stage (power generation and transmission–distribution) in each period are evaluated. On this basis, extended methods are also designed to measure the factor efficiency and the technological gap of each group. The model is applied to China's electric power industry, and the following conclusions are drawn: (I) The operational efficiency levels of provinces and regions are relatively different. (II) Generally, the operational efficiency of the generation stage is significantly lower than that of the transmission–distribution stage. (III) Factors with efficiencies ranked from highest to lowest are capital, labor, and energy. (IV) Major policy implications include breaking down the barriers to prompt interprovincial electricity transmission, developing the energy storage industry, implementing the flexibility transformation of thermal power units, and reducing the cross subsidy to the residual electricity consumption.