Benchmarking Management Research Articles

Ecosystem Services’ Supply–Demand Assessment and Ecological Management Zoning in Northwest China: A Perspective of the Water–Food–Ecology Nexus

The coordinated development of the water–food–ecology (WFE) nexus is a practical issue that has to be addressed urgently for northwest China’s (WTL) sustainable development. Optimizing the linkage relationship and accomplishing the rational distribution of resources from the perspective of the supply and demand for ecosystem services (ESSD) are imperative. Thus, in this study, a numerical indicator system for ESSD from the perspective of the WFE nexus was constructed with the incorporation of the water and carbon footprint. Based on this premise, the ecological management zoning method was enhanced by integrating supply and demand risks, and optimization suggestions were proposed for various zones. The results showed that (1) carbon sequestration (CS), food production (FP), and water yield (WY) supply and demand significantly increased between 2000 and 2021. High ESSDs were concentrated in the west side of northwest China. Maize, wheat, cotton, vegetables, and garden fruits had a higher demand for ecosystem services (ESs). (2) The three ESSDs were bound in a synergistic relationship. The synergy between supply exhibited significant spatial heterogeneity, while the synergies between demand showed similar distribution patterns. (3) Regarding quantity matching, the supply for FP and CS surpassed demand, while the WY supply could not meet the demand. The three ESs’ supply and demand deficits rose. Ecological supply–demand ratio (ESDR) regional differentiation for the three ESs was apparent. Regarding spatial matching, FP and CS concentrated on low supply–low demand, while WY focused on high supply–high demand. FP risk was concentrated in Qaidam Basin, whereas WY risk was mostly in Hexi inland river basin (HX), the Yellow River Basin area (HH), and both sides of the “Qice line”. (4) The ecological management zones were formed by integrating WTL’s three dominant weak functional zones, four categorized strategy regions, and four governance models. This study can serve as a scientific benchmark for regional ecological management, which is significant in ensuring northwest China’s water, food, and ecological safety.

A unified benchmark for deep reinforcement learning-based energy management: Novel training ideas with the unweighted reward

Deep reinforcement learning stands as a powerful force in the realm of intelligent control for hybrid power systems, yet some imperfections persist in the positive progression of learning-based strategies, necessitating the proposal of essential solutions to address these flaws. Firstly, a public and reliable benchmark model for hybrid powertrains and the optimization results of energy management strategies are essential. Hence, two Python-based standard deep reinforcement learning agents and four Simulink-based hybrid powertrains are employed, forming a co-simulation training approach as the reliable solution. Secondly, a detailed analysis from the perspectives of range, magnitude, and importance reveals that the optimization terms in traditional reward functions can mislead the agent during the training process and require cumbersome weight tuning. Accordingly, this paper proposes a novel training idea that combines the rule-based engine start-stop with an unweighted reward tailored for optimizing engine efficiency and facilitating training progress. Finally, a hardware-in-the-loop test is performed, treating the P2 hybrid electric vehicle as the target. The results show that two deep reinforcement learning-based energy management strategies achieved fuel economies of 6.537 L/100 km and 6.330 L/100 km, respectively, and more efficient and reasonable control sequences ensure the working state of the engine as well as the state of charge of batteries.

How COVID-19 pandemic affected business excellence: case studies from Greek companies

PurposeThis paper is the third part of a research effort that aims to identify how various crises affected basic business processes using Institut Européen d'Administration des Affaires (INSEAD’s) industrial excellence framework (IEF) in large organizations.Design/methodology/approachThis research compares three data sets from the same four companies against quality management benchmarks, with a span of more than two decades: (1) data collected in 2005 operating under a financially thriving corporate environment; (2) data collected in 2015, operating under a strong financial crisis and (3) data collected in 2022, operating under the serious COVID-19 crisis.FindingsThe authors identify the characteristics that helped them navigate successfully through almost two crises in a row. These companies successfully navigated crises by applying assessment and continuous improvement processes, forging close relationships with their suppliers and training their people systematically.Practical implicationsThe findings can be adopted by practitioners who wish to navigate their organizations during serious crises. Researchers and academics may also find this study interesting for managing quality during a pandemic.Originality/valueThere are not many studies that investigate how the pandemic influenced the quality management practices in organizations in Greece in sequential crises. This paper brings insights into the enduring advantages of adopting a quality framework.

Analysis of the Effect of Outdoor Thermal Comfort on Construction Accidents by Subcontractor Types

The impact of climate on construction site safety varies significantly depending on subcontractor types due to the diverse nature of workplaces and work methods. This study introduces a novel approach by categorizing construction work according to subcontractor types and assessing accident risk probabilistically through the Physiologically Equivalent Temperature (PET), an outdoor thermal comfort index. Additionally, a Hidden Markov Model (HMM)-based clustering methodology was proposed to classify new groups using PET and accident probability. This study proceeded in the following sequence: (i) collection and classification of data, (ii) PET calculation, (iii) calculation of accident probability, and (iv) clustering and Pearson correlation coefficient analysis. As a result of clustering, each group was classified according to the workplace. Groups 2 and 3 demonstrated a strong positive correlation between accident probability and PET, with correlation coefficients of 0.837 and 0.772, while Group 1 exhibited a moderately positive correlation of 0.474. This study quantitatively evaluated the impact of climate on workers for each subcontractor type using PET, an outdoor thermal comfort index for construction work, and accident probability, resulting in the identification of new groups. The findings of this study may serve as novel benchmarks for safety management in construction worker safety based on PET.

Analysis and Reflection on the Strategy Benchmarking of Power Battery Management in China and Europe

In 2023, the European Union (EU) enacted the Regulation on Batteries and Waste Batteries (hereinafter referred to as the New Law on Batteries), which strengthens the regulatory framework for the entire lifecycle of power batteries. This development presents both challenges and opportunities for global power battery manufacturers and operators. As a significant player in the global power battery industry chain and the world’s largest producer of electric vehicles and power batteries, China must systematically assess the impact of global battery management strategies, including the EU’s New Law on Batteries, from a lifecycle perspective. This understanding is crucial for maintaining China’s competitive edge in the global power battery market and achieving mutually beneficial outcomes in international trade negotiations. This paper constructs a strategy analysis framework based on the lifecycle approach. By summarizing the power battery management strategies of both the EU and China, it provides a comprehensive overview of strategies across different countries, highlights the key regulatory focus areas, and offers relevant strategy recommendations. The main conclusions and insights are as follows: (1) The New Law on Batteries achieves lifecycle regulation from “cradle” to “grave” and back to “cradle”. (2) China emphasizes the management of waste power batteries, with an increasingly robust strategy system at the recycling stage, yet lacks comprehensive measures for other lifecycle stages. (3) The EU has established a comprehensive lifecycle strategy management system centered on the New Law on Batteries, characterized by strong coordination and a synergistic combination of strategies across different sectors. Finally, this paper identifies three major compliance challenges posed by the New Law on Batteries, necessitating enhanced strategy development and implementation in the areas of carbon footprint management, circular economy, and digital battery passports.

Clinical evaluation of primary human papillomavirus (HPV) testing with extended HPV genotyping triage for cervical cancer screening: A pooled analysis of individual patient data from nine population-based cervical cancer screening studies from China.

To assess the clinical values of extended human papillomavirus (HPV) genotyping in triage of high-risk HPV-positive women, focusing on the trade-off between cervical precancer detections and colposcopy referrals. A bivariate random-effects model was used to estimate the diagnostic accuracy of primary HPV screening with following triage strategies to detect cervical precancers: (i) partial genotyping for HPV16/18 combined with cytological testing at atypical squamous cells of undetermined significance threshold (used as the comparator), (ii) genotyping for HPV16/18/58/52, (iii) genotyping for HPV16/18/58/52/33, (iv) genotyping for HPV16/18/58/33/31, (v) genotyping for HPV16/18/58/52/33/31, and (vi) genotyping for HPV16/18/58/52/33/31/39/51. Internal risk benchmarks for clinical management were used to evaluate the risk stratification of each triage strategy. A total of 16,982 women (mean age 46.1 years, range 17-69) were included in this analysis. For CIN3+ detection, triage with HPV16/18/58/33/31 genotyping achieved lower positivity (6.85% vs. 7.35%, p = 0.001), while maintaining similar sensitivity (91.35% vs. 96.42%, p = 0.32) and specificity (94.09% vs. 93.67%, p = 0.56) compared with the comparator strategy. Similar patterns were observed for CIN2+ detection. Women with a positive HPV16/18/58/33/31 genotyping test had high enough risk for CIN3+ for colposcopy referral, while the risk for women with a negative test was below the 1-year return decision threshold according to internal benchmarks. Our findings suggested extended HPV genotyping is of potential to be used as a triage technique integrated into HPV-based cervical cancer screening, leading to reduced need for colposcopy referral while maintaining similar disease detection and efficient risk stratification.

THE EFFECT OF WORK ENVIRONMENT AND INNOVATION ON JOB SATISFACTION OF MILLENNIAL EMPLOYEES AT PT.XYZ WITH CAREER DEVELOPMENT AS AN INTERVENING VARIABLE

Abstract Employees are an important company asset who have quality work competencies to provide the best performance to support company programs. In practice, the Human Capital (HC) team has a competency improvement program that requires motivation from employees as an internal factor so that the program can run effectively. Work motivation is affected by a variety of factors such as salary, work environment, job security, relationships with coworkers, awards, and so on. This influences whether an employee is satisfied with his or her job. The proportionate stratified random sampling approach was utilized, which is a sampling methodology for populations with mixed or variable features, and the data in this study uses a quantitative approach. The population is millennial employees at PT XYZ with a total of 139 millennial employees. The data was collected by distributing a questionnaire with 28 closed questions and response options indicating how strongly respondents agreed or disagreed with the questions posed. The results show it is possible to conclude that the millennial employees at PT XYZ have a level of job satisfaction that is influenced by work environment factors, innovation, and career development factors that can mediate changes in the level of job satisfaction. This finding could be an overview of benchmarks for management in departments, so that job satisfaction obtained by employees does not become a saturation point but becomes a driving force to improve their performance in this company continuously.

Swimming ability of Schizothoracinae fishes in Yarlung Zangbo River of China.

The Yarlung Zangbo River is a river with abundant hydropower resources but fragile biodiversity in China. As an important benchmark for both research and ecological management, there is still a lack of knowledge about the swimming ability of fishes in the Yarlung Zangbo River. The induced flow velocity (Uind), critical swimming speed (Ucrit), and burst swimming speed (Uburst) of five Schizothoracinae species were tested in this study. Relative swimming ability related to body length and body shape was calculated. The results indicated that the average absolute swimming speeds (Uind-a, Ucrit-a, and Uburst-a) of all the experimental fish were 10.20 ± 0.01, 57.58 ± 3.28, and 69.54 ± 2.94 cm/s, respectively, and the corresponding relative Uind, Ucrit, and Uburst related to body length (Uind-l, Ucrit-l, Uburst-l) were 1.15 ± 0.07, 5.04 ± 0.26, and 7.23 ± 0.28 BL/s, respectively. Moreover, relative Uind, Ucrit, and Uburst related to body shape (Uind-s, Ucrit-s, and Uburst-s) were 0.80 ± 0.13, 2.49 ± 0.51, and 4.32 ± 0.57 cm-2/s, respectively. No significantly differences in relative swimming speeds existed among five species. Only Oxygymnocypris stewartii was significantly weaker in Uburst-s than Schizothorax o'connori. The body shape showed a stronger relationship with swimming speed than the body length did. Schizothoracinae fish in the Yarlung Zangbo River basin are less sensitive to the water flow and performed weaker Ucrit and Uburst compared to those in the Yangtze River basin, indicating that Schizothoracinae fish in the Yarlung Zangbo River may be more susceptible to threats from environmental changes. The paper enriched the research on the swimming ability of Schizothoracinae fishes and provided efficient data for the fish conservation in the Yarlung Zangbo River.

Multisite prospective study of perioperative pain management practices for anterior cruciate ligament reconstruction in adolescents: Society for Pediatric Anesthesia Improvement Network (SPAIN) Project Report

IntroductionAlthough 200 000 adolescents undergo anterior cruciate ligament reconstruction (ACLR) surgery annually, no benchmarks for pediatric post-ACLR pain management exist. We created a multicenter, prospective, observational registry to describe pain...

Design of an Iterative Method for Dynamic Resource Management in 5G Networks with IoT Integration Operations

In the realm of fifth-generation (5G) wireless networks, the escalating demands for high-speed, reliable, and efficient communication are paramount, especially with the widespread deployment of Internet of Things (IoT) devices & scenarios. Despite the advancements in 5G technologies, existing network management strategies often fall short in addressing the dynamic nature of network conditions, the heterogeneity of IoT device requirements, and the need for stringent privacy measures. These limitations underscore the necessity for innovative approaches that can adapt in real-time to varying demands while ensuring optimal network performance and user privacy. This paper introduces a suite of machine learning models designed to enhance the efficiency and reliability of 5G networks, catering specifically to the diverse needs of IoT applications. At the forefront, DynamicSlicerNet, a deep reinforcement learning-based model, dynamically slices 5G network resources tailored to IoT devices' requirements, addressing device mobility, application demands, and network congestion. This model demonstrates a substantial reduction in latency by up to 30% and improvement in reliability by up to 20%, outperforming static resource allocation methods. Further enhancing edge computing capabilities, FedEdgeAI leverages federated learning to train models directly on edge devices, a move that not only slashes latency by minimizing data transmission to centralized servers but also fortifies data privacy. Experimental evaluations highlight FedEdgeAI's efficacy in maintaining model accuracy while halving communication overhead. PredictiveNetCare, employing time-series analysis and anomaly detection, anticipates network failures, facilitating preemptive maintenance strategies. This predictive approach has shown a marked precision over 90% in identifying potential disruptions, significantly reducing maintenance-related downtime by 30% and bolstering network reliability by 15%. OptiAllocRL and AdaptiveQoSDL, both harnessing reinforcement and deep learning techniques, respectively, optimize resource allocation and manage Quality of Service (QoS) parameters adaptively. OptiAllocRL's strategy results in a 40% latency reduction and a 25% throughput increase, while AdaptiveQoSDL minimizes packet loss by up to 50% and enhances end-to-end delay by up to 35%, ensuring high QoS levels under fluctuating network conditions. This comprehensive approach sets a new benchmark for future 5G network management, paving the way for a more connected, efficient, and secure digital world.

欧盟科学数据发展政策与规划

The continual advancement of global scientific and technological innovation capabilities has spurred a rapid growth of scientific data. As a global benchmark for scientific data management and sharing, the European Union (EU) constantly place a high priority on the management and development of scientific data, and has formed a comprehensive array of policies and plans to advance scientific data development. Through network investigation and literature analysis, this paper focuses on consolidating and summarizing the EUs scientific data support and regulatory bodies, management policies, development plans, and evaluates the effectiveness and challenges in data application practices. Moreover, it also outlines the issues confronting the development of scientific data in China and puts forward insightful recommendations. The analysis shows that the EU’s efforts to promote open science and open scientific data, the scientific data development policy system and sustainable development program are crucial to the open sharing, effective scientific management, maximizing benefits and sustainable development of scientific data in the EU, making the EU stand at the forefront of open scientific data and open science in the world. Furthermore, the ongoing integration of science data centers into the science and innovation infrastructure system of the EU. These practices of the EU can serve as valuable references for China in the development of scientific data, the construction of scientific data centers, the formulation of scientific data policies and development plans, and the play of scientific benefits.

Advancing Efficiency Sustainability in Poultry Farms through Data Envelopment Analysis in a Brazilian Production System.

The production efficiency factor is widely used to measure the zootechnical performance of a batch of broilers. The unit cost of production brings new elements to improve efficiency evaluation and financial sustainability for this activity in agriculture. This research aims to evaluate the production efficiency level of the crop to maximize the return on investment. This study uses Data Envelopment Analysis (DEA) with the computational processing of the SIAD software (Integrated Decision Support System). The variables selected were poultry housing, age at slaughter, feed consumed, mortality, and unit cost. The chosen output variable was the total available weight. The analysis spans 31 decision-making units (DMUs) composed of integrated producers, unveiling a frontier of efficiency delineated by the most exemplary DMUs. Notably, only two DMUs, specifically DMU 4 and DMU 23, approached the threshold of maximum relative efficiency. This research illuminates the critical role of unit cost in enhancing the assessment of production efficiency and financial sustainability within the agriculture environment. By setting benchmarks for efficient management and operational protocols, our findings serve as a cornerstone for improving practices among less efficient DMUs, contributing significantly to the literature on agricultural efficiency and offering actionable insights for the poultry farming sector.

The quest for an optimal capital structure: an empirical analysis of European firms using GMM regression analysis

Purpose This paper explores the connection between capital structure and financial performance within European listed firms. The primary objective is to demonstrate an inverse U-shaped relationship between these two variables and pinpoint an optimal debt-equity mix.Design/methodology/approach In this study, we adopt a dynamic modeling approach to investigate the relationship between a firm’s capital structure and financial performance. Drawing on well-established theories and prior empirical studies, our model examines 3,121 dividend-paying firms from 41 European countries over 14 years, from 2008 to 2021. To enhance the reliability of our findings, we employ two distinct estimation techniques: the fixed effect model (FE) and the system generalized method of moments (System-GMM).Findings This study reveals an inverse U-shaped relationship between the firm’s financial performance, measured by the return on equity (ROE) and its capital structure (total liability to total assets ratio). Furthermore, an optimal capital structure of about 29% is determined for all firms in the sample, and about 21%, 28% and 41% industry-specific capital structure for manufacturing, real estate and wholesale trade, respectively.Originality/value This paper contributes to existing knowledge by empirically determining an optimal capital structure for listed firms across various industries in Europe, which very few studies have attempted to do in the past. An optimal capital structure is an invaluable benchmark for managers and other stakeholders, informing their decision-making.

Analisis Rasio Keuangan dalam Pengukuran Kinerja Keuangan pada Perusahaan Sub-Sektor Rokok

Research Aims: The cigarette industry is one of the leading segments of various sectors in Indonesia and is one of the largest commodities contributing to Indonesian state revenues obtained from Value Added Tax (PPN), Excise, and local taxes. The purpose of this study was to determine the performance of financial performance as measured by the value of financial ratios, namely profitability ratios, liquidity ratios, activity ratios, and solvency ratios of several companies engaged in the tobacco industry as a sample study. The results of this study revealed that there are some companies that have an increase in the value of financial ratios from year to year, but there are also companies whose value decreases in the following year, this indicates that financial ratios can describe financial performance over time and become a management benchmark in performance evaluation to improve company performance in the future.

Stochastic linear programming model for the shelter’s location in small Colombian cities

This article addresses the problem of locating temporary shelters in small Colombian cities through the construction of a stochastic linear programming model that considers different scenarios where the affected population is a factor that generates uncertainty in the location of shelters and the respective flows in the humanitarian supply chain. The model is validated through the construction of a case study referring to the floods presented in a city in the center of the department of Valle del Cauca, which constantly causes the need to relocate the affected population, seeking to reduce attention times to the victims while considering restrictions associated with the budget available for emergency care. The generated proposal becomes a benchmark for the efficient management of shelters in similar disasters in small Colombian cities.

How does hotline and incident management stack up in the financial services industry? An analysis of comparative metrics

An efficient and trusted mechanism by which employees can anonymously or confidentially report allegations of suspected or actual misconduct is the hallmark of a well-designed compliance programme. Yet, every industry will have different metrics related to their reporting processes and systems. There is not a ‘right’ answer because all metrics will be influenced by the risk areas facing each industry. The finance sector is no exception. So, what does the data show for the finance sector and how can the data be used to impact programme effectiveness? To answer this question, in 2023, NAVEX®, a provider of governance, risk and compliance information system software and services, examined financial-industry specifics within a large global data set of anonymised hotline and incident management metrics. This research, published here for the first time, follows the release of NAVEX's 2023 ‘Hotline & Incident Management Benchmark Report’ — an annual, publicly available analysis of hotline reporting data generated through the intake channels NAVEX provides to its customers. This research publication, published in March, involved a total of 1.52 million reports worldwide. Financial services was the third-most represented sector across the larger benchmark report. Comparing financial services to global benchmarks, it appears the industry is outperforming other sectors in several key incident management metrics. Yet for individual financial firms, the industry-specific benchmark data revealed in this analysis could provide a more refined look into the ways organisations can compare their programmes to their industry peers. Overall, the financial services industry received more reports per 100 employees, fewer anonymous reports, and were consistently closing cases even with a different mix of issue types, ie more business-related issues than other industries.

Competency Modeling at an International Freight Forwarding Company in Bangkok, Thailand

This study presents a competency modeling exercise conducted at a company located in Bangkok, Thailand. The company provides international logistics and freight forwarding services. The findings of this study include the key competencies and competency gaps, as well as the organization development methods to fill those competency gaps. The study identifies the need for competency modeling and management based on the company’s strategic plan. Based on the review of the literature and the identification of one in-depth interview and multiple focus groups as the data collection method, a competency modeling process is devised. Referring to the data collected from the in-depth interviews and focus group discussions; the authors present the competency modeling process and identify the gaps for each job category. In the latter part of the study, the authors present the organization’s development methods, recommend ways to fill the competency gaps, and indicate the relevance of updating the competency scorecard every year. This study will be helpful for human resource managers, line managers, and supervisors in the logistics and supply chain industry. Moreover, the findings of this study will be helpful for the employees of such companies and their leadership and management alike. Considering the changes brought about by the pandemic, this study can be used by other logistics service providers as a benchmark for competency management.

The Effect Of LDR, ROA, PER, DER, NPL On Stock Prices In Banking Sub-Sector Companies In 2019-2021

The purpose of this work is to analyze the impact of financial indicators on the stock prices of bank subsidiaries in 2019–2021. This study focuses on five ratios which are Loan to Deposit (LDR), Return on Assets (ROA). , price/earnings ratio (PER), debt/equity ratio (DER) and non-performing loans (NPL). The research method is panel regression analysis, which uses secondary information obtained from the financial statements of listed banking companies. The research sample consists of several banking companies of a certain period. The results of this study show that LDR, ROA, PER, DER and NPL significantly affect the stock prices of bank subsidiaries. LDR, ROA and PER have a positive effect on stock prices, while DER and NPL have a negative effect. This indicates that investors tend to pay attention to these financial ratios when evaluating a company and setting stock prices. This study helps to understand the factors affecting stock price of banking companies. The results of this study can be used as benchmarks for investors, corporate management and regulators in making investment decisions and policies related to banking.

The Influence Of Solvatibility Ration, Company Size, TATO, ROA, DER On Return Price Of Properties Subsectors In 2019-2021

The purpose of this paper is to analyze the effect of solvency ratios, firm size, total turnover (TATO), return on equity (ROA) and debt-to-equity ratio (DER) on company performance/share prices in real terms. in the real estate subsector. 2019-2021 The purpose of this research is to understand the factors affecting the stock price of real estate. The research method is panel regression analysis, which uses secondary information obtained from the financial statements of listed real estate companies. The research sample consists of several companies in the real estate subsector covering a certain period. The results of the present study show that the solvency ratio, firm size, TATO, ROA and DER significantly affect the performance/share price of companies in the real estate sub-sector. Importance ratios, firm size, and ROA positively affect stock return/price, while TATO and DER affect negatively. This shows that investors tend to pay attention to these factors when evaluating the performance of real estate and determining stock prices. This study helps to understand the factors influencing the performance/share price of companies in the real estate sub-sector. The results of this study can be used as a benchmark for investors, company management and regulatory authorities in making investment decisions and policies related to real estate.

Whole genome assessment of a declining game bird reveals cryptic genetic structure and insights for population management.

Population genomics applied to game species conservation can help delineate management units, ensure appropriate harvest levels and identify populations needing genetic rescue to safeguard their adaptive potential. The ruffed grouse (Bonasa umbellus) is rapidly declining in much of the eastern USA due to a combination of forest maturation and habitat fragmentation. More recently, mortality from West Nile Virus may have affected connectivity of local populations; however, genetic approaches have never explicitly investigated this issue. In this study, we sequenced 54 individual low-coverage (~5X) grouse genomes to characterize population structure, assess migration rates across the landscape to detect potential barriers to gene flow and identify genomic regions with high differentiation. We identified two genomic clusters with no clear geographic correlation, with large blocks of genomic differentiation associated with chromosomes 4 and 20, likely due to chromosomal inversions. After excluding these putative inversions from the data set, we found weak but nonsignificant signals of population subdivision. Estimated gene flow revealed reduced rates of migration in areas with extensive habitat fragmentation and increased genetic connectivity in areas with less habitat fragmentation. Our findings provide a benchmark for wildlife managers to compare and scale the genetic diversity and structure of ruffed grouse populations in Pennsylvania and across the eastern USA, and we also reveal structural variation in the grouse genome that requires further study to understand its possible effects on individual fitness and population distribution.