Management Capacity Research Articles

Optimization of production, distribution, natural resources and capacity planning throughout process sector worldwide supply chains with various goals

This study delves into the intricate dynamics of green transformation within global mining and other process industries, focusing on production, distribution, and capacity planning under the framework of the Asian Mineral Vision. By addressing sustainability, resource efficiency, and cost reduction, the research highlights the multifaceted challenges faced by industry participants in achieving green objectives. In addition to financial efficiency, the study emphasizes the importance of customer service quality and responsiveness. To tackle these challenges, we propose a novel multiobjective mixed-integer linear programming (MILP) approach. The model incorporates key goals such as minimizing total cost, total flow time, and total missed sales, reflecting the interconnected nature of financial efficiency, operational agility, and customer satisfaction. To further enhance the model's flexibility, we integrate discrete strategies for plant capacity expansion, recognizing the crucial role of capacity management in responding to evolving demand dynamics. The multiobjective optimization problem is addressed using the lexicographic minimax technique and the ε-constraint method. A comprehensive numerical example illustrates the practical relevance and effectiveness of our proposed model and solution methods, providing valuable insights into improving the resilience and performance of green supply chain networks in the process industry.

Bridging the Gap Between Training and Competition in Elite Rink Hockey: A Pilot Study.

Monitoring training load and competition load is crucial for evaluating and improving athlete performance. This study proposes an applied approach to characterize and classify the training task specificity in relation to competition in a top-level rink hockey team, considering external and internal load from training tasks and competition. Training tasks and game demands have significant dose-response differences, and exercises can be classified successfully based on their physiological and biomechanical demands. Cross-sectional study. Level 5. Ten elite-level male rink hockey players participated in this study. Players were monitored on 6 different task categories during 8 training sessions and 2 official games. A linear mixed model with random intercepts was used to compare training tasks and competition load, accounting for individual repeated measures. A 2-step cluster analysis was performed to classify the training tasks and games based on physiological and biomechanical load, employing log-likelihood as the distance measure and Schwartz's Bayesian criterion. Average heartrate , maximum heartrate, and high-speed skating (18.1-30 km/h) were the best physiological load predictors, while the most effective biomechanical load predictors were impacts [8-10] g(n), decelerations [-10 to -3]m/s²(n), and accelerations [3-10]m/s²(n). Different physiological and biomechanical responses were verified between training tasks and match demands. A 4-quadrant efforts assessment for each task category revealed that training tasks used by the team in the analysis presented lower biomechanical and physiological load demands than competition. Training tasks failed to adequately replicate the specific demands of competition, especially regarding high mechanical stress, such as the absence of high-intensity impacts and decelerations. This method of classification of training tasks may allow coaches to understand further the specificity and contribution of each task to competition demands, consequently improving the capacity of load management and the preparedness and readiness of players for competition.

Assessing the importance-performance analysis of adaptive capacity programs for sustainable mangrove conservation in the Taman Nasional Bali Barat conservation area

Mangroves, which are vital for maintaining the stability of coastal ecosystems, are facing increasing threats from global changes. This highlights the urgent need for effective adaptive capacity programs. This study focuses on the evaluation of such programs within Taman Nasional Bali Barat, Indonesia, specifically looking at their effectiveness in promoting sustainable mangrove conservation. To obtain a comprehensive understanding of the community's involvement and perspectives, a survey was conducted, including a wide range of local stakeholders, not just those already involved in conservation efforts. The findings revealed that programs that prioritize flexibility, learning, and agency are crucial, but are currently underperforming. Interestingly, there was a significant variation in the willingness to participate among different groups. Fishermen and students displayed negative tendencies, while limited interest communities (a population segment historically less engaged in conservation), those with previous experiences with conservation programs, those seeking advice on marine activities, and those influenced by policies showed positive and significant responses. For example, tourist operators also exhibited a significantly positive engagement. Based on the analysis, this study provides targeted policy recommendations to enhance stakeholder engagement, improve program flexibility, and emphasize educational efforts. These recommendations aim to strengthen the adaptive capacity for sustainable mangrove management in the face of ongoing global changes.

Assessment of Hospital Managers' Sustainable Leadership Levels

This study aims to evaluate the sustainable leadership levels of hospital managers with the participation of healthcare professionals working in public hospitals in Bitlis province. The cross-sectional and descriptive study was conducted on 354 healthcare professionals and the information form and Sustainable Management Behaviors Scale were used as data collection tools. The demographic analysis of the study shows that the majority of the participants are male, under the age of 30 and have a bachelor's degree. In terms of occupational groups, it was observed that other health personnel and nurses were predominant. The findings revealed that the participants generally evaluated the sustainable leadership behaviors of the managers at a level above medium. Especially environmental sensitivity and conservation sensitivity dimensions have high mean values. Nurses were found to have the most negative opinions about managers' sustainable leadership levels, while administrative staff had the most positive opinions. It was determined that positive perceptions were higher for managers who are experienced, act in accordance with ethical principles and adopt the philosophy of continuous learning. The study draws attention to the importance of sustainable leadership practices in the healthcare sector and offers strategic recommendations to increase the leadership capacity of hospital managers.

Chief Sustainability Officer (CSO) power and sustainability-based compensation for climate change disclosure and carbon performance: is it different for developed and developing nations?

Purpose Companies are increasingly appointing a Chief Sustainability Officer (CSO) to anchor the need to highlight climate change at the senior management level. This study aims to examine how CSO power and sustainability-based compensation influence climate reporting and carbon performance. Design/methodology/approach Using one of the largest data sets to date, consisting of 18,834 company years through the author’s observations, spanning an 11-year period (2011–2021) in 33 countries. This paper used quantitative methods – specifically, ordinal logistic regression estimation. This paper measures the level of climate change disclosure based on the carbon disclosure leadership methodology. Carbon performance is based on the intensity of carbon emissions (Scope 1, Scope 2), which is a quantitative and relatively more objective measure. Findings The results suggest that climate change disclosure continued to increase and the carbon emissions intensity of the companies in this study gradually decreased over the sample period. This paper finds that the presence of the CSO within the top management team has a positive and significant influence on the level of information on climate change of the companies in the sample. This finding confirms the idea that the managerial capacity of CSOs motivates the disclosure of climate change. The empirical results confirm that there are differences in the role that the CSO and sustainability-based compensation play in influencing the quality of climate information disclosure in developed and developing countries. Originality/value The recourse on a mixed theoretical framework, which highlights upper echelons theory, argues the understanding of the role of CSOs in explaining the relationship between climate change disclosure–carbon performance relationship. The novelty of the study lies in the approaches adopted to describe the quality of climate change disclosure. To control for endogeneity, this paper uses a difference-in-difference analysis by adding a firm to the Morgan Stanley Capital International index as an exogenous shock.

How Runoff Elections and the Form of Local Administration Affect the Costs of Elections

To what extent do states’ administrative and policy choices affect their election costs? Previous scholarship highlights how the costs and demand sides of the public sector cost model correlate with election administration spending, and more recent evidence has added political considerations such as the partisanship of county commissions. Using Georgia’s unique election processes—runoff elections and multiple methods of election administration at the county level—we contribute to understanding election administration expenditures. We demonstrate that general election runoffs and Boards of Election, rather than probate judge-run elections, are related to significant increases in expenditures per registered voter between 2014 and 2020. This further develops the literature regarding procedural costs and the impact of the managerial capacity of election bureaus.

Unlocking thermal management capacity: Optimized organic-inorganic hybrid shell phase change microcapsules with controllable structure and enhanced conductivity

Microencapsulated phase change material (MPCM) stands as a strong candidate for temperature control of thermal management systems in broad fields like building construction. A novel design strategy for hybridized shell-based MPCM (HMPCM) containing methyl methacrylate (MMA) and silica was developed by the interfacial hydrolysis-condensation method, with characteristics of controllable structure and enhancement in the interaction between the polymer and inorganic thermal conductivity additives. Two hybridized shell structures, including a homogeneous structure and another unique porous cavity structure shaped like a foam, can be obtained by adjusting for preparation conditions. The results reveal that the thermal conductivity is significantly enhanced by hybridized shells compared to pure MMA shells, with a dramatic increment of 92.16 %. Therefore, a highly satisfactory microcapsule material characterized by superior thermal conductivity and energy storage efficiency exceeding 99.9 % was fabricated. The results of thermal cycling reliability assessments underscore the favorable attributes of microcapsules, encompassing stable charging/discharging behavior, exceptional phase change reversibility, and prompt thermal responsiveness. Moreover, the feasibility of microcapsules in building thermal management applications has been verified. The temperature difference of 10.3 °C between the matrix with and without microcapsules demonstrates the capability of HMPCMs to effectively regulate the temperature of the surrounding environment. Consequently, these newly developed HMPCMs reinforced by hybridized shells are promising thermoregulation materials for thermal management systems that await further applications.

Characterization of Strategic Deconflicting Service Impact on Very Low-Level Airspace Capacity

European airspace is poised for significant transformation as it prepares to accommodate a new class of unmanned traffic that will reshape the transport of people and goods. Unmanned aerial vehicle traffic will introduce a new level of services, but it remains unclear how safety and operators’ time flexibility in flight planning will impact capacity. This study focuses on the impact of strategic deconflicting services on the capacity of the very low-level airspace, a critical area in the future management of unmanned aerial vehicle traffic. The results validate the assumptions regarding the roles of airspace managers and drone operators through simulation studies; highlight the limitations of the first come, first served policy; and propose a batch policy as a potential optimization strategy for future airspace capacity management. The forecasting model developed using regression techniques provides a general method for predicting airspace capacity under specific conditions, contributing to the safe and efficient integration of unmanned aerial vehicles into European airspace.

Capacity management in supply chains under risk of supply disruptions: a mathematical model for establishing capacity reservation contracts

ABSTRACT Capacity management and supply chain disruptions are the most challenging problems faced in high tech industries. This paper focuses on establishing a capacity reservation contract between a single supplier and two heterogeneous retailers in a two-stage supply chain, wherein the retailers purchase a product from the supplier and sell it to the customers. In this study, a mathematical model is built for all parties involved, incorporating numerous essential elements of a real contract. The proposed model aims to assist in determining the best solutions for the retailers’ reserved capacities to the supplier and the supplier’s constructed capacity. Analytical results and sensitivity analyses are presented to demonstrate how various cost elements, price, and uncertainty affect the optimal capacity decisions.

Mental Workload as a Predictor of ATCO’s Performance: Lessons Learnt from ATM Task-Related Experiments

Air Traffic Controllers’ (ATCos) mental workload is likely to remain the specific greatest functional limitation on the capacity of the Air Traffic Management (ATM) system. Developing computational models to monitor mental workload and task complexity is essential for enabling ATCOs and ATM systems to adapt to varying task demands. Most methodologies have computed task complexity based on basic parameters such as air-traffic density; however, literature research has shown that it also depends on many other factors. In this paper, we present a study in which we explored the possibility of predicting task complexity and performance through mental workload measurements of participants performing an ATM task in an air-traffic control simulator. Our findings suggest that mental workload measurements better predict poor performance and high task complexity peaks than other established factors. This underscores their potential for research into how different ATM factors affect task complexity. Understanding the role and the weight of these factors in the overall task complexity confronted by ATCos constitutes one of the biggest challenges currently faced by the ATM sphere and would significantly contribute to the safety of our sky.

Healthcare practitioners' experiences in managing HIV among young people in Namibia.

Low viral load suppression rates among older adolescents and young adults with HIV are a global challenge, including in Namibia. Healthcare providers struggle with managing these age groups due to their unique demographic characteristics. Monitoring viral load suppression is vital for evaluating antiretroviral treatment effectiveness, making it essential to identify and address existing gaps. This study aimed to explore and describe healthcare practitioners' understanding and experiences in managing older adolescents and younger adults living with HIV in seven high-burden districts of Namibia. Qualitative descriptive phenomenological research was followed in this study. Healthcare practitioners directly managing older adolescents and younger adults living with HIV were purposively recruited. Telephonic individual interviews were conducted, and data saturation was achieved with the 29th participant. Colaizzi's seven-step analysis was used to analyse the data. Two themes emerged from the study: (1) healthcare practitioners' knowledge of viral load management and (2) the strategies employed to manage high viral load in these age groups. These strategies included implementing differentiated service delivery, adopting interprofessional and Ubuntu approaches, psychosocial support, community engagement, enhancing adherence counselling, and support from implementing partners. The findings revealed inadequate knowledge among healthcare practitioners regarding viral load management, which negatively impacts the provision of quality care and an effective HIV response within the spirit of Ubuntu.Contribution:This study enhances healthcare practitioners' capacity in viral load management and guides policy makers in supporting this unique population, thus improving their health outcomes.

Scale diseconomies and capacity in fund management: variation across equity markets

PurposeWe model the relation between excess returns, fund size and industry size for active equity funds.Design/methodology/approachWe study and contrast four markets – global equities, emerging markets, Australia core and Australia small caps – and use the results to investigate the extent to which funds deviate from estimated capacity.FindingsWe uncover a significantly negative relation between returns and both fund size and industry size across all markets. The estimated percentage of funds operating above versus below capacity varies both across markets and over time, as does the role played by fund size versus industry size. We find a greater prevalence of funds operating significantly below than above capacity, in contrast to findings for US equity mutual funds. Significant deviations from estimated capacity persist for a median of between two and six quarters.Originality/valueOur main contribution is to show that the dynamics governing deviations from capacity for active equity funds vary across markets.

Rural human settlement environment, non-agricultural transfer of labour and arable land abandonment in China

The arable land abandonment caused by the large-scale non-agricultural transfer of labour has attracted substantial attention from all walks of life in China. Promoting improvement in human settlement environment can accelerate the construction of infrastructure, ameliorate grassroots organization and enhance management capacities while simultaneously decelerating agricultural production costs. High level of human settlement environment can also attract the labour force to return, stimulate the vitality of rural elements and endogenous powers. Then, can improving rural human settlement environment alleviate the phenomenon of arable land abandonment caused by non-agricultural labour transfer? In order to answer this question, based on the micro-survey data of 1325 households in 5 provinces of China, this paper uses the Tobit model to empirically test the effects of rural human settlement environment and non-agricultural transfer of labour on arable land abandoned. The results revealed that rural human settlement can alleviate the arable land abandonment caused by non-agricultural transfer of labour to a certain extent. In particular, the improvement of rural human settlement environment that mainly based on the infrastructure construction and organizational management level, has significantly alleviated the arable land abandonment caused by the non-agricultural transfer of labour. Heterogeneity analysis disclosed that, compared with mountainous and hilly areas, the improvement of rural human settlement environment had a more obvious mitigation effect on arable land abandonment in plain areas. Promoting infrastructure construction and strengthening organizational management ability were effective ways to alleviate arable land abandonment in plain areas. Farmer households with high place attachment level were more likely to be attracted by the improvement of rural human settlement environment to return to their hometown, so as to make use of arable land resources. Improving infrastructure, strengthening organizational management level, and promoting cultural and community development were the main measures for farmer households with high place attachment level to reduce arable land abandonment. In addition, there were significant differences in arable land abandonment and its driving factors in different regions. In the central and eastern regions or major grain-producing areas, improving human settlement environment had a significant mitigation effect on arable land abandonment. Therefore, improving the rural human settlement environment according to local conditions, promoting the supportive policy will be inclined to mountainous and hilly areas, enhancing the attractiveness of rural areas, encouraging farmers with high place attachment level to return to their hometowns for employment and entrepreneurship, and accelerating the cultivation of new types of agricultural operators, which will help alleviate the arable land abandonment caused by non-agricultural transfer of labour.

Thermally enhanced flexible phase change materials for thermal energy conversion and management of wearable electronics

The developing trend of miniaturization and integration for electronics imposes challenges of efficient heat dissipation technology, where novel materials with advanced thermal energy conversion and management are urgently needed. In this work, we propose an emerging phase change material (PCM) system with polyvinyl alcohol/expanded graphite network loading paraffin wax (PE-PW), which exhibits superb flexibility, thermal energy storage capacity and thermal conductivity. The phase change enthalpy is from 115.61 J/g to 168.93 J/g without any leakage, which can be maintained even after 500 thermal cycles. The thermal conductivity can reach 1.46 W/mK, 484% enhanced compared with that of pure PCM. Meanwhile, the thermal management test indicates that the PE-PW composites can quickly absorb and store the generated heat to achieve temperature control, thus protecting the system from overheating and indicating excellent thermal management capacity. This flexible PE-PW system has broad application prospects in the field of thermal energy conversion and management for wearable electronics.

Capacity management under uncertain demand and distribution policies: the case of Indian vaccine supply chain

The present study investigates the cause-and-effect relationships between production capacity decisions and the choice of distribution policy aspects of managing an extensive vaccination programme. The Indian COVID-19 vaccine supply chain is taken as a case study, and Indian demographic data is utilised. A Monte Carlo Markov Chain (MCMC) model is developed to estimate time period-wise demand corresponding to each distribution policy. Furthermore, eight different capacity management models involving different capacity addition and transfer strategies for four different distribution policies are formulated. The trade-off between effectiveness and efficiency objectives, namely Vaccine Supply Chain total cost and service level, is investigated by comparing the Pareto frontiers of the proposed models. Furthermore, the models are compared based on capacity transfer cost, capacity addition cost, and variation in region-wise service level. The results reveal that organisations can simultaneously save significant costs and achieve higher service levels if they cautiously align their capacity management approach and the distribution policy on the demand front. Capacity management interventions at the national level result in more service levels and lower variation and costs than at the regional level.

Evaluation of water resource balance in the Urmia Lake Basin: Integrating carrying capacity and water footprint model for sustainable management

Given the scarcity of water resources and the ever-growing demand, effective water flow management becomes crucial. The Lake Urmia Basin, a critical region in Iran, faces severe water scarcity exacerbated by climatic changes, land use alterations, over-extraction of groundwater, and mismanagement. This study evaluates the water resource balance by integrating carrying capacity and water footprint models to assess sustainable water management practices. Utilizing the InVEST model, water provisioning ecosystem services have been estimated as the supply, while the ecological footprint method quantifies water demand across various sectors. Three scenarios are evaluated: continuation of the current situation, an ideal scenario with substantial reductions in water consumption and pollution, and implementation of operational programs. The findings reveal significant water deficits in certain sub-basins, highlighting the need for a fundamental revision of resource allocation based on each region’s ecological capacity. Lake Urmia, the central nucleus of the basin, has experienced a significant size reduction, approximately 10 % of its original size, from the early 1990s to 2018, due to climatic changes, land use alterations, over-extraction of groundwater, and mismanagement. The environmental deficit in some sub-basins raises serious concerns, even in the best scenario where ecological footprint reduction is considered. These results underscore the effectiveness of ecosystem-based comprehensive capacity analysis for sustainable watershed development. This research offers a unified spatial system for quantifying ecological footprints and land resilience, providing critical insights into addressing water scarcity and supporting holistic regional planning.

From conflict to collaboration through inclusive landscape governance: Evidence from a contested landscape in Ghana

The Western Wildlife Corridor (WWC) in Ghana’s Northern Savannah ecological zone is a contested landscape where efforts to reverse widespread environmental degradation often conflict with local livelihood concerns and broader development objectives. Despite policy measures to devolve natural resource decision-making authority, poor environmental management, persistent socioeconomic challenges, and increasingly limited livelihood opportunities for people living within the corridor prevail. This study investigates environmental degradation in the WWC and natural resource governance using information on stakeholder perceptions from stakeholder workshops, focus group discussions, and key informant interviews. We also explore how natural resource management might be strengthened to better deliver social, economic, and environmental goals. We found that despite a history of contestation, stakeholders were able to agree upon specific issues of common concern and generate a collaborative vision for the WWC landscape. Transitioning toward such a vision requires significant investment in strengthening current governance structures and building natural resource management capacity within the corridor and beyond. Furthermore, persistent challenges of conflicting stakeholder objectives and issues related to coordination, corruption, and non-inclusion in decision-making about natural resources must be addressed to advance progress. Stakeholders were able to formulate specific recommendations and a participatory theory of change to inform the development of a sustainable landscape management plan and future evidence-based policy that could steer the WWC toward a more resilient and multifunctional system that equitably supports livelihoods, biodiversity, and wider economic development. The methods for inclusive engagement in environmental decision-making are extrapolatable to other contexts facing similar social-environmental challenges.

The Impact of Forest Management Inventory Factors on the Ecological Service Value of Forest Water Conservation Based on Machine Learning Algorithms

Based on forest management inventory data, this study applies machine learning algorithms to explore the relationships between forest water conservation capacity and forest management inventory factors, thus providing more extensive insights into forest water conservation services. By integrating the InVEST model and machine learning algorithms, this study identifies the key factors related to water conservation services based on forest management inventory factors and investigates the differences in and accuracy of forest water conservation models using the random forest algorithm. The results are as follows: (1) The determination coefficients (R2) of the three machine learning models range from 0.508 to 0.869, with root mean square errors (RMSEs) ranging from 28.380 to 69.339. The performance of these models is generally satisfactory, with the random forest algorithm showing superior results. (2) By leveraging the advantages of the three machine learning algorithms in handling categorical data, this study analyzes the contributions of forest management inventory factors, revealing the impact mechanisms of forest-type water conservation services. (3) The integration of machine learning algorithms allows for better processing of the scale and correlation of independent variables, providing more objective information on the main controlling factors of forest water conservation. (4) Predictions of water conservation capacity using machine learning are consistent with that of the InVEST model. The water conservation per unit area shows a variation trend as follows: slow-growing broadleaf forests > shrub forests > middle-growing broadleaf forests > cunninghamia lanceolata forests > fast-growing broadleaf forests > pine forests > bamboo forests. (5) Since this study considers only the factors available in the forest management inventory, which does not encompass all relevant influencing factors, it is difficult to fully address the complexities of how forest water conservation services interact with forest structure. Therefore, further research is needed to investigate the intrinsic mechanisms underlying the interactions between water conservation and forest management inventory factors.

Exploring strategies promoting interprofessional collaborative practice in spinal cord injury rehabilitation at a private South African hospital group

Background. Implementing an interprofessional collaborative practice (IPCP) in hospitals improves health outcomes, enhances patient safety and reduces length of stay by optimising resource utilisation. Although this approach was desired at a private hospital group in South Africa (SA), the specific strategies for clinical guidelines and capacity management pertaining to spinal cord injury (SCI) patients and the implementation of IPCP were unknown. Objective. To explore strategies for implementing clinical guidelines and capacity management for SCI rehabilitation to promote IPCP in a private hospital group in SA. Method. This exploratory descriptive qualitative study included participants who were selected through purposive sampling. The participants comprised 11 staff from various disciplines and management of the private hospital group, one local and one international expert in IPCP. Three online focus groups (n=13) were conducted, involving three to five participants. The transcriptions were analysed thematically using Braun and Clarke’s framework. Results. Interprofessional communication and tools as well as capacity development were three emergent themes from the data. Strategies pertaining to communication methods, digitisation, visual displays, patient care information, educational information and education of healthcare workers were suggested to promote IPCP. Conclusion. These findings from the emergent themes could assist in implementing and integrating an IPCP approach into the rehabilitation service. Further research assessing the efficacy of implementing the IPCP strategies and digital platform would be beneficial.

Prevalence of Lassa Fever Infections in Ondo State, Nigeria

Emerging and re-emerging infectious diseases have been of immense threat to public health in this 21st century. Among these diseases are COVID-19, Lassa fever, monkeypox, yellow fever, ebola, chicken pox disease and many others. Out of all the above mentioned diseases, Lassa fever is the most recurrent and trending infectious disease in Nigeria which affects many states. It is of great concern that Ondo State is one of the major epicentres of the virus. The objective was to examine the incidence of Lassa fever in Ondo State, Nigeria. A descriptive research design using a purposive sampling technique was used to collect data. Findings revealed that in 2018, Ondo State accounted for 25% of total Lassa fever incidence cases in Nigeria, which suggests that Ondo State was one of the major epicentres of the virus in 2018. As of March 19, 2022, the figure rose to 28% of total Lassa fever incidence. This implies that Ondo State was also the major epicentre of the virus as of March 19, 2022. Furthermore, in the 42nd week of 2022, the predominant age group of the patients affected by Lassa fever in Ondo State was 21–30 years. There has been a significant increase in the number of suspected and confirmed cases as compared with 2021. The factors contributing to the reemergence of LF epidemics in Nigeria are nosocomial transmission, travel and migration, the public health system, socio-cultural factors, conflicts and the COVID-19 pandemic. In conclusion, health education of indigenous people at the community levels (especially residents of Owo and Ose Local Government Areas) about LF causes, preventive measures and avoidance of cultural practices that could predispose them to Lassa fever infection should be given priority. Also, case management capacity and contact tracing must also be strengthened through the establishment of well-equipped and dedicated treatment/referral centers in the epicentre. Training and re-training of clinical care teams should also be given priority.