Performance Measurement System Research Articles

Evaluation of the Influence of Water Content In oil on the Metrological Performance of Oil Flow Measurement Systems

According to current Brazilian regulations, if the volumes of oil produced used as a reference for the payment of government shares and third parties contain a water content greater than 2% v/v, these volumes must be arbitrarily increased between 1.44% and 10.89% due exclusively to water content, which has caused operational problems for oil companies such as differences between volumes produced and volumes sold, and additional payments from government shares and third parties. This study aimed to evaluate the metrological performance of oil measurement systems with ultrasonic, Coriolis and positive displacement flow meters when subjected to varied water content, fluid temperature and flow rate conditions using the Design of Experiments and the Response Surface Methodology. The analysis of variance showed that the models presented good fits for the ultrasonic meter (coefficient of determination R2 of 97.96%, p-value of 0.001, and a standard deviation of 5.89 × 10−5); Coriolis meter (R2 of 90.91%, p-value of 0.037, and a standard deviation of 5.88 × 10−5); and positive displacement meter (R2 of 99.07%, p-value of 0.000, and a standard deviation of 4.85 × 10−5). The results of the experiments carried out indicate that the contribution of each parameter analyzed to the metrological performance of the measurement system varies depending on the measurement technology used by the flow meter. However, the fluid temperature proved to be a relevant parameter common to all flow measurement technologies evaluated. All measuring technologies evaluated were influenced by water content in the range of 0% to 10% v/v, with the measurement error being less than 0.2% when compared to a standard positive displacement type meter in almost all experimental conditions. The Coriolis-type flow meter was the one that presented the smallest error among the measuring technologies evaluated.

Analysis of barriers for performance measurement system effectiveness in a company: perceptions across hierarchical levels

Purpose This study aims to identify the perception of people in a Portuguese company regarding the main barriers to the effectiveness of the existing performance measurement system (PMS) and whether those perceptions are dependent of people’s hierarchical levels, education levels, work shifts, gender and department. Design/methodology/approach Primary data was collected through structured interviews (adapted to three levels of interviewees in the company hierarchy) and Likert scale questionnaires. Descriptive statistical analysis of the collected data was performed as well as a chi-square test. Findings The results provide an insight on the perception of barriers to the PMS effectiveness in the company. After performing interviews and questionnaires it was possible to identify that the main perceived barriers were: poor communication system and issues on target definition, lack of trained resources, employee involvement, indicators understanding and use for improvement. Practical implications This study is the starting point to develop actions aiming to eliminate, or at least mitigate, the impact of the barriers on the PMS effectiveness. Originality/value PMSs play an essential role in an organization, so it is essential to identify what hinders its effectiveness. This study opens the discussion by diagnosing the company’s perception of the barriers to PMS effectiveness.

The Influence of It Governance and It Capability on The Performance of Private Higher Education Institutions: The Mediation Role of Performance Management Systems

This study examines the effect of information technology (IT) governance and IT capability on the organizational performance of private Higher Education Institutions (HEI) with a performance management system as a mediating variable. This quantitative study uses primary data from questionnaires distributed to respondents online. Respondents in this study were 270 management and IT management of private universities on the island of Sumatra. This study used a sample of 90 private HEIs. Furthermore, the data was processed using Partial Least Square (PLS) technique. The results are that the performance management system partially mediates IT governance with organizational performance, while IT capability mediates fully with organizational performance. IT capabilities can encourage organizational performance through a good performance management system. Theoretically, it contributes to implementing technological resources mobilized in the performance management system to improve college performance. College management should consider developing technology and performance measurement systems to achieve sustainable competitive advantage.

How performance measurement systems enable or hinder organizational ambidexterity

PurposeThis study aims to examine how different uses of performance measurement systems (PMS) enable or hinder organizational ambidexterity (OA), intended as the simultaneous pursuit of exploitation and exploration.Design/methodology/approachFollowing a qualitative research design, we gathered data through semi-structured interviews, observations and reviews of documents at four departments of an automotive firm.FindingsWe contribute to operations management research and practice by demonstrating how PMS, which are typically associated with exploitation, can also foster exploration and enable organizations to become ambidextrous. Specifically, we show how PMS can be structured and used in more agile ways and, in relation to innovation, we identify which PM practices should be introduced and with what effects and those that should be avoided. We also contribute to organization theory by highlighting how a single management tool can promote the achievement of both exploration and exploitation.Practical implicationsIn investigating PMS uses and their effects, we identify several positive practices. For example, we show how managers can use PMS more effectively and how targets could be deployed to stimulate creativity and innovation. We also emphasize the need for managers to opt more often for team incentives rather than individual ones to encourage the collaboration needed for OA.Originality/valueWe provide in-depth insight into how PM tools affect an organization’s ability to pursue exploitation and exploration, thus contributing to research in operations, innovation and organization theory.

Power Dynamics in Accounting-Related Strategic Decision-Making within Hospital Management: A Narrative Literature Review

This paper aims to explore how power dynamics shape strategic decisions and performance measurement systems in hospital management, elucidating their impact on managerial choices in healthcare settings. Key themes and factors related to power dynamics in hospitals are identified, including the distribution of power among management teams, the influence of individual and group power dynamics, and the effects of power on decision-making across organizational levels. By synthesizing insights from previous research, this paper informs the development of theoretical frameworks and methodological approaches for studying the interplay between power dynamics and strategic decision-making in hospital management. Furthermore, it offers practical implications for hospital administrators and managers, providing guidance on navigating power dynamics to enhance decision-making effectiveness and organizational performance. This paper contributes to advancing our understanding of the complex dynamics of power and decision-making in hospital management, offering valuable insights for both research and practice in healthcare administration.

The Performance Measurement Construction for Developing Prosperity and Sustainability of Social Enterprises

Objective: This research seeks to enhance existing knowledge by proposing an approach for social enterprises to evaluate their impact across social, environmental, and economic dimensions. Method: Drawing on insights in accounting and anthropology, we employ a synchronic-diachronic approach. Our research utilizes deep ecology to build a comprehensive framework for measuring SE performance. Results and Conclusion: Our study advocates a multidimensional perspective rooted in the principles of deep ecology, which includes environmental and community well-being, internal processes, human and natural empowerment, and equitable distribution. By embracing this multidimensional view, SEs can work towards achieving their ultimate goals of sustainability and well-being. Implications of The Research: Despite the proliferation of methodologies and tools to assess social impact, there is a lack of systematic analysis and comparison across these approaches. SE should adopt systematic performance measurement to inform decision-making and promote environmental and social sustainability. Originality/Value: This research contributes to the existing literature by specifically focusing on the performance measurement of social enterprise, with comprehensive approaches uses deep ecology.

Evaluating supply chain performance measurement system (SCPMS) lifecycle during unexpected events

ABSTRACT Supply chain management is recognized as a crucial element in boosting organizational performance and competitiveness. However, the COVID-19 crisis has demonstrated that many corporations were unprepared and lacked a recovery strategy, which led to significant supply chain disruptions. Hence, the purpose of this study is to evaluate the Supply Chain Performance Measurement System (SCPMS) lifetime under unforeseen situations, particularly in developing nations like Egypt, and its relevance during the pandemic and post-pandemic periods. A systematic questionnaire was used to gather data from 100 manufacturing firms (supply chain and retailers) with large business volume who provided a total of 562 questionnaires. The findings indicated that there were four main measurement systems: SCPMS Design, SCPMS Implementation, SCPMS Use, and SCPMS Review. The results of the AHP method found that the SCPMS implementation was the most important system, while the least important was SCPMS design.

Revolutionizing performance measures and criteria for the facilities management industry in the UAE

PurposeAmidst the complicated nature of the UAE’s facilities management (FM) industry, the need to recalibrate the existing performance measurement (PM) system measures and criteria has been resonating to ensure their ability to capture the FM industry trends and dynamics, thus enhancing organizational excellence. Therefore, this research aimed to propose a specific PM tool to the country’s FM industry to accurately assess performance and establish strategic enhancements.Design/methodology/approachThe study reviewed literature on the available PM systems to gather the available measures, which were presented to a focus group of seven participants, who were purposively selected based on their expertise in FM and PM implementation in the UAE to adjust them and add ones relevant to the UAE’s FM industry.FindingsThe focus group conducted various changes, from retaining certain measures and criteria, renaming them to simplify or make them more representative of the industry, ranking them based on their importance to limit their numbers, to finally categorizing them as enablers or results. Consequently, the final proposed tool was composed of nine dimensions with 51 measures as performance enablers and three dimensions with 11 measures as performance results. Seven measures were added by the experts, who highlighted their increasing popularity in the UAE’s FM industry.Originality/valueThrough addressing the critical void in literature, this paper develops a specific PM tool aligning with the intricacy of the UAE’s FM industry, thus providing proactive contribution to the industry’s effective and sustainable growth.

Evaluation of Measurement System Analysis Techniques for Screw Shaft Manufacturing in Teaching Factory Setting

This study examines the Evaluation of Measurement System Analysis (MSA) Techniques for Screw Shaft Manufacturing in a Teaching Factory Setting at Politeknik STMI Jakarta. The research investigates the precision and accuracy of the measurement system using statistical methods such as Analysis of Variance (ANOVA), Number of Distinct Categories (NDC), and metrics like Total Gauge Repeatability and Reproducibility (GRR), Repeatability, and Reproducibility. Through comprehensive data collection, including multiple appraisers across various trials measured quantitative surveys and qualitative observations, Screw Shaft dimensions and tolerances. The collected data underwent thorough statistical analysis utilizing ANOVA to explore the sources of variation in measurements. The results of the MSA analysis provided critical insights into the measurement system's performance. Repeatability variability (9.97%) and reproducibility variability (3.80%) contribute to a total GRR of 10.67%, indicating an acceptable measurement system. Part-to-part variation emerged as the primary source of variability, emphasizing the importance of addressing part differences in quality control processes. Moreover, ANOVA highlighted the influence of different factors on measurement consistency. Part variations significantly impacted measurement variability, underscoring the need to manage part differences effectively. The assessment of repeatability and reproducibility revealed insights into measurement consistency and reliability. These findings carry significant implications for both industry and education. Understanding the factors affecting measurement variability enables the implementation of corrective measures to enhance product quality and consistency. Additionally, advancements in measurement techniques and quality management practices in Teaching Factory environments contribute to improved product quality and competitiveness in industrial settings. Continued research and evaluation are crucial for further enhancing measurement systems and manufacturing processes.

Procedural factors associated with successful recanalization in patients with acute ischemic stroke treated with endovascular thrombectomy-a nationwide register-based observational study.

Several studies have addressed technical aspects of endovascular thrombectomy (EVT), but it is not well known how procedural factors contribute to technical success in routine healthcare. The aim was to explore factors associated with technically successful EVT on nationwide scale. We did an observational register-based study assessing factors associated with technical success off anterior circulation EVT in Sweden. The main outcome was successful recanalization defined as modified treatment in cerebral ischemia score 2b-3. The association between baseline and treatment variables and successful recanalization were explored using Chi-square(d) test and univariable logistic regression. Multivariable logistic regression was used to define predictors of successful recanalization. The study included 3211 patients treated during 2015 to 2020. Successful recanalization was achieved in 83.1% (2667) with a gradual improvement in technical outcome over the period. After adjustment for age and occlusion location, thet use of general anesthesia, balloon guide catheter (BGC) and an operator with an overall success rate of >85% were independent predictors of successful recanalization. An overall operator success rate of <80% or 80-85%, and an annual center volume lower than 50 were predicitors of recanalization failure. This study illustrates factors associated with procedural success in endovascular thrombectomy on a nationwide scale including the use of general anesthesia, BGC, annual center volumes >50 cases per year and the overall success rate of the individual operator. It highlights the potential benefit of systematic performance measurements, benchmarking, and continuous training to bring all centers and operators to the highest level of performance.

Research on integration of enterprise ERP and E-commerce systems based on adaptive ant colony optimization

Integrating the E-commerce system with an enterprise resource planning tool can help the firm improve performance, maintain customers, and increase sales. In Enterprise Resource Planning, integration features can be provided either as developed features or as separate assignments and contributions. Problems with the online platform, improper addresses, rejected payments, and especially apparent transactions are frequent problems for online buyers. The enhanced Adaptive Ant Colony Optimization is utilized to optimize the rural E-commerce express of transportation. Several innovative routes can lower the downlink transportation cost and reach all collecting places with a fast delivery route. Convolutional Neural Networks were utilized to increase the collective innovation of the E-commerce platform and simplify network communication. E-commerce is a mechanism used to market information services and products. Hence, ERP-AACO-CNN has been designed to integrate Enterprise Resource Planning and E-commerce, and business operations can stream smoothly from the front to the back of the business. Statistics on sales orders, customers, stock levels, price, and essential performance measurement systems. The automated invoices, frequent communications, financial report preparation, product and service delivery, and material requirements planning. The most significant results will likely finance businesses that employ it as a stimulant for a wide-ranging process improvement. In addition, E-commerce is a valuable innovation that connects buyers and sellers in various corners of the globe. Customer satisfaction is projected to be more significant than fault detection at 95.2 % accuracy for the proposed method’s E-commerce system with the superior value. According to client demand, an E-commerce system is the most accurate development at a given input level, and a future ERP is 64.9% efficient. The proposed approach has a 24.5% random error rate and a 13.2% mean square error rate. A comparison of E-commerce and enterprise ERP precision to the proposed technique yields 83.8% better results.

Implementing organizational performance measurement systems: measures and success strategies

PurposeThis study assesses performance measurement (PM) system implementation efforts across various organizational contexts and investigates which factors are critical to achieving implementation success (IS).Design/methodology/approachAn empirical field study was conducted to refine a framework of PM system IS that consists of 5 dimensions of success and 29 factors. A survey questionnaire was used to investigate actual organizational practice and exploratory factor analysis was conducted to refine constructs corresponding to potential factors and dimensions of IS. The resulting variables were then investigated using multiple regression analysis to identify critical success factors for implementing PM systems.FindingsThe survey was completed by representatives from 124 organizations and the exploratory factor analysis results indicated that there are three underlying dimensions of IS (i.e. Use of the System, PM System Performance, and Improved Results and Processes) and 12 factors. Of the factors, nine can be considered critical success factors having a significant relationship with at least one dimension of IS: Leader Support, Design and Implementation Approach, Reward System Alignment, Organizational Acceptance, Organizational Culture and Climate, Easy to Define Environment, IT Infrastructure Capabilities, PM System Design Quality, and PM Participation and Training.Originality/valueThe results show that there are distinct dimensions of IS and, although some factors are associated with all dimensions, most are more closely related to only one dimension. This suggests that different strategies should be utilized based on the types of challenges experienced during implementation.

Traffic prediction via clustering and deep transfer learning with limited data

AbstractThis paper proposes a method based on the clustering algorithm, deep learning, and transfer learning (TL) for short‐term traffic prediction with limited data. To address the challenges posed by limited data and the complex and diverse traffic patterns observed in traffic networks, we propose a profile model based on few‐shot learning to extract each detector's unique profiles. These profiles are then used to cluster detectors with similar patterns into distinct clusters, facilitating effective learning with limited data. A Convolutional Neural Network ‐ Long Short‐Term Memory (CNN‐LSTM)‐based predictive model is proposed to learn and predict traffic volumes for each detector within a cluster. The proposed method demonstrates resilience to detector failures and has been validated using the Performance Measurement System dataset. In scenarios with less than 2 months of training data and 10% failed detectors, the mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) for station‐level traffic volume prediction increase from 12.7 vehs/5 min, 20.9 vehs/5 min, and 10.5% to 13.9 vehs/5 min, 24.2 vehs/5 min, and 11.7%, respectively. For lane‐level traffic volume prediction, the average MAE, RMSE, and MAPE increase from 4.7 vehs/5 min, 7.7 vehs/5 min, and 15% to 5.6 vehs/5 min, 9.6 vehs/5 min, and 16.8%. Furthermore, the proposed method extends its applicability to traffic speed and occupancy prediction tasks. TL is integrated to improve speed/occupancy prediction accuracy by leveraging knowledge obtained from traffic volume, considering the correlation between traffic flow, speed, and occupancy. When less than 1 month of traffic speed/occupancy data is available for learning, the proposed method achieves an MAE, RMSE, and MAPE of 0.7 km/h, 1.3 km/h, and 1.3% for station‐level traffic speed prediction and 0.5%, 1.1%, and 11% for station‐level traffic occupancy.

Pengaruh Penerapan Sistem Informasi Akuntansi Manajemen, Sistem Pengukuran Kinerja dan Sistem Penghargaan terhadap Kinerja Manajerial pada PT. BBI Indonesia

Management accounting information systems as systems that play a role in helping predict the possible consequences of several alternative actions taken in various activities such as planning, controlling and decision making are useful in helping managers fulfill their contribution in achieving managerial performance. The performance measurement system shows the relationship between the plans that have been set by the company and the results achieved which will provide information about the achievement of implementing a plan. Reward system as a motivator for employees in realizing company goals. This research aims to find out whether the implementation of a management accounting information system, performance measurement system, and reward system simultaneously influences managerial performance. The approach used is a quantitative approach. The location of this research was carried out at PT. BBI (Boma Bisma Indra) Indonesia whose address is Jalan Pulau Pinang VI-VII, KIM II, Medan, the population in this study were all employees totaling 53 people. The sampling technique used was saturated sampling where the entire population of 53 people was sampled and The data analysis technique used is multiple linear regression analysis. The results of this research are that in this research, the Management Accounting Information System partially has a positive and significant effect on the Managerial Performance of PT BBI (Boma Bisma Indra). In this research, the performance measurement system partially has a positive and significant effect on the managerial performance of PT. BBI (Boma Bisma Indra). In this research, the reward system partially has a positive and significant effect on the managerial performance of PT BBI (Boma Bisma Indra). In this study the independent variables consisting of the management accounting information system, performance measurement system, reward system together influence the performance of PT BBI (Boma Bisma Indra) employees.

Integrating accounting models with supply chain management in the aerospace industry: A strategic approach to enhancing efficiency and reducing costs in the U.S

This concept paper proposes the integration of accounting models with supply chain management in the aerospace industry as a strategic approach to enhancing efficiency and reducing costs in the United States. The aerospace sector faces numerous challenges, including complex supply chains, stringent regulatory requirements, and cost pressures. By combining accounting principles with supply chain management strategies, this approach aims to optimize operations, improve financial transparency, and foster collaboration among stakeholders. Key objectives of this initiative include streamlining financial processes, enhancing decision-making capabilities, and mitigating risks associated with supply chain disruptions. By leveraging accounting models such as activity-based costing, lean accounting, and performance measurement systems, organizations can gain insights into cost structures, identify inefficiencies, and allocate resources effectively across the supply chain. Moreover, integrating accounting with supply chain management enables real-time monitoring of financial performance metrics, enabling timely interventions and adjustments to achieve strategic goals. This approach also facilitates better coordination between finance and operations teams, leading to improved communication, alignment of objectives, and ultimately, enhanced organizational performance. In the context of the aerospace industry, where precision, reliability, and cost-efficiency are paramount, this integrated approach offers significant benefits. It enables companies to optimize inventory management, minimize waste, and identify opportunities for cost savings throughout the supply chain. Additionally, by fostering a culture of continuous improvement and data-driven decision-making, organizations can adapt more effectively to market dynamics and gain a competitive edge. This concept paper outlines the theoretical framework and practical implications of integrating accounting models with supply chain management in the aerospace industry. Through case studies, best practices, and implementation strategies, it provides a roadmap for organizations to embrace this strategic approach and realize its full potential in enhancing efficiency and reducing costs in the U.S. aerospace sector.

Cost efficiency analysis of logistics and warehouse business

Cost efficiency is a key focus in various aspects of a company's operational activities, and the supply chain plays an important role in achieving this goal. To better understand how the supply chain may affect cost-effectiveness, this study examines just-in-time, total quality management, and performance measurement systems in the context of Kosambi Warehouse Area, Tangerang, which involves collecting primary and secondary data using a quantitative approach. A total of 138 respondents were selected using a simple random sampling technique. SPSS software was used to analyze the data. The findings demonstrate that just-in-time has a negative and significant effect on cost efficiency. However, total quality management has a positive and significant influence on cost efficiency. The performance measurement system has a positive and significant influence on cost efficiency.

Assessment of Performance Measurement Systems’ Ability to Mitigate or Eliminate Typical Barriers Compromising Organisational Sustainability

Assessment of Performance Measurement Systems’ Ability to Mitigate or Eliminate Typical Barriers Compromising Organisational Sustainability

Development of a multi-stage fog droplet screening system based on the virtual impact principle.

Accurately measuring fog droplet spectra is essential for understanding fog's formation, dissipation, and composition, which makes a challenge to the performance of droplet sampling and measurement systems. Standard particles such as glass beads are widely used to characterize their performance. However, the disparities between glass beads and fog droplets, including refractivity, size distribution, and composition, may lead to calibration errors. In this context, we developed a three-stage fog droplet screening system based on the virtual impact principle. We determined the Stokes number and the diameter of the acceleration nozzle through theoretical analysis. Subsequently, we utilized the computational fluid dynamics software Fluent to explore the influence of key system parameters on screening efficiency, including the diameter of the collection nozzle (D1) and the distance between the acceleration nozzle and the collection nozzle (S). The simulation results indicated that the screening efficiency improved with S. The best performance was achieved when D1 = 1.35 D0 and S = 1.90 D0 (where D0 represents the diameter of the acceleration nozzle), resulting in an average screening efficiency of 75.4%. Finally, we conducted experiments to validate the effectiveness of the screening system. The screening efficiency of each outlet was estimated at 42.2%, 66.1%, 84.0%, and 95.3%, with differences of 2.0%, 3.3%, 4.1%, and 4.7% compared to the simulations. The average screening efficiency was 71.9%, with a deviation of 3.5% from the simulation. These findings demonstrated that the screening system could provide an alternative technical apparatus for characterizing droplet sampling and measurement systems.

The role of accounting in mitigating food supply chain risks and food price volatility

The global food supply chain is a complex network of interconnected processes and actors that play a critical role in ensuring food security and stability. However, this intricate system is susceptible to various risks and challenges, including natural disasters, geopolitical tensions, market fluctuations, and regulatory changes. These risks often result in food price volatility, which can have profound implications for both consumers and producers worldwide. In this context, accounting emerges as a vital tool for mitigating risks and managing food price volatility within the supply chain. Accounting serves as a cornerstone in providing accurate, timely, and reliable financial information essential for decision-making at every stage of the food supply chain. Through effective financial reporting and analysis, accounting enables stakeholders to identify, assess, and respond to potential risks proactively. By employing risk management techniques such as scenario planning, sensitivity analysis, and hedging strategies, accounting professionals can help organizations anticipate and mitigate supply chain disruptions, thereby reducing the impact of food price volatility. Furthermore, accounting facilitates transparency and accountability within the food supply chain, enhancing trust and cooperation among stakeholders. Through comprehensive cost accounting and performance measurement systems, organizations can identify inefficiencies, optimize resource allocation, and enhance operational resilience. Moreover, accounting frameworks such as sustainability accounting enable businesses to assess and report the environmental and social impacts of their operations, fostering sustainable practices across the supply chain. In addition to its role in risk management and performance optimization, accounting contributes to regulatory compliance and governance within the food industry. By adhering to accounting standards and regulations, organizations can ensure integrity and accuracy in financial reporting, thereby enhancing investor confidence and mitigating legal and reputational risks. Moreover, accounting professionals play a crucial role in designing and implementing internal control systems to prevent fraud, errors, and misconduct, safeguarding the integrity of the supply chain. Accounting plays a multifaceted role in mitigating food supply chain risks and food price volatility. By providing financial insights, promoting transparency, and ensuring compliance, accounting empowers organizations to navigate challenges and promote stability in the global food system.

Effectiveness of Digital Transformation in Data Warehouse Technology

Banking performance must always be maintained in providing fast and accurate services based on data processing results. PT Bank ABC has several data warehouse from various sources. The technology used makes the reporting process more complex, and maintenance costs are high. This research presents the data warehouse system transformation process using a single source of truth approach and the use of Extract, Transform, and Load (ETL) tools from IBM InfoSphere DataStage version 11.5. ETL testing is carried out on the Performance Measurement System (PMS) process by business units to monitor, identify, and analyze performance in each business unit. The results obtained proved to be faster than DB2 and Oracle database queries. Using the DataStage platform provides advantages in time efficiency, which is a crucial factor in overall data processing. In addition, DataStage Integration can have a positive impact on overall system performance, support smooth operations, and minimize the potential for database server overload.