Allocation Of Human Resources Research Articles

Optimizing Human Resource Allocation in Construction Projects: A Case Study

In construction, human resources are essential for workers to carry out tasks and work optimally from project initiation to completion. This entails having workers with the requisite skills and abilities for each job description. This research focuses on analyzing the feasibility of constructing the Iskandar Muda Military Regional Finance Office in Banda Aceh City from a human resources perspective. Findings from productivity calculations reveal a decrease in the relationship between duration and work productivity progress, rendering the current number of workers ineffective in ensuring construction feasibility from a human resources standpoint. Despite the presence of 32 workers with skills aligned with job descriptions, the research underscores the importance of optimizing labor allocation and time utilization to enhance productivity. By implementing efficient methods tailored for repetitive tasks and adjusting labor requirements throughout the project duration, this approach proves feasible and effective in achieving better overall results in constructing the Iskandar Muda Military Regional Finance Office.

Medical Support Vehicle Location and Deployment at Mass Casualty Incidents

Anticipating and planning for the urgent response to large-scale disasters is critical to increase the probability of survival at these events. These incidents present various challenges that complicate the response, such as unfavorable weather conditions, difficulties in accessing affected areas, and the geographical spread of the victims. Furthermore, local socioeconomic factors, such as inadequate prevention education, limited disaster resources, and insufficient coordination between public and private emergency services, can complicate these situations. In large-scale emergencies, multiple demand points (DPs) are generally observed, which requires efforts to coordinate the strategic allocation of human and material resources in different geographical areas. Therefore, the precise management of these resources based on the specific needs of each area becomes fundamental. To address these complexities, this paper proposes a methodology that models these scenarios as a multi-objective optimization problem, focusing on the location-allocation problem of resources in Mass Casualty Incidents (MCIs). The proposed case study is Mexico City in a earthquake post-disaster scenario, using voluntary geographic information, open government data, and historical data from the 19 September 2017 earthquake. It is assumed that the resources that require optimal location and allocation are ambulances, which focus on medical issues that affect the survival of victims. The designed solution involves the use of a metaheuristic optimization technique, along with a parameter tuning technique, to find configurations that perform at different instances of the problem, i.e., different hypothetical scenarios that can be used as a reference for future possible situations. Finally, the objective is to present the different solutions graphically, accompanied by relevant information to facilitate the decision-making process of the authorities responsible for the practical implementation of these solutions.

ANALISIS DURASI DAN BIAYA DENGAN METODE RESOURCES LEVELING PADA PEMBANGUNAN BALAI SERBAGUNA BANJAR WONGAYA BETAN TABANAN

In the Multipurpose Hall Advanced Development project in Banjar Wongaya Betan, Tabanan Regency, there was an overall allocation of human resources which caused a mismatch between plans and realization in the field, where implementation experienced delays in the 6th, 7th, and 8th weeks. Therefore, it is necessary to develop a human resource leveling method to minimize deviations between needs and the availability of existing human resources, namely by Resources Leveling using the help of Microsoft Office Project 2019. The Resources Leveling method is carried out by shifting non-critical activities within the available grace time so that available resources are not overloaded. This research aims to analyze the duration of activities and costs required for the project through descriptive research methods with a quantitative approach and using secondary data sources from the implementing contractor, namely CV. Sustainable Gold. Based on the analysis results, it was found that the number of human resources that were initially overallocated could be optimized after the leveling process was carried out using the resource leveling method with Microsoft Office Project 2019. The leveling process affected the project duration, from 90 days to 103 days. This is because of max. units of labor that the contractor is able to provide cannot meet the max. units required for project implementation. Meanwhile, the cost of human resources required is not affected by the leveling process, namely, it still costs IDR 71,981,700.

The weight of obesity: a retrospective analysis of the direct costs of hospitalizations due to obesity between 2011 and 2020 for the unified health system in Brazil

Aim: This study aimed to analyze the evolution of obesity-related costs over the past 10 years for Brazil's Unified Health System (SUS) and provide insights for guiding and expanding health management and promotion measures. Methods: An observational and retrospective study was conducted using secondary data from 2011 to 2020, extracted from DataSUS with the ICD-10 code for obesity. Statistical analysis was performed to assess trends in hospitalizations and costs related to obesity. Results: During the analyzed period, there was a substantial increase of 110% in hospitalizations and 167% in obesity-related costs for SUS. Female patients (86%) accounted for the majority of hospitalizations, while males (14%) had lower representation. Predominantly, white individuals (62%) were admitted, whereas indigenous individuals had the lowest representation (0,007%). The Southern region contributed to 46% of total cases, in contrast to the Northern region, which accounted for only 0,9%. Conclusion: The findings of this study indicate a significant rise in hospitalizations and associated costs related to obesity for Brazil's Unified Health System. These results underscore the urgency of implementing health promotion and prevention measures, both in the public and private sectors. There is a need for optimized allocation of human resources, including trained professionals for obesity treatment, to mitigate the burden of obesity-related morbidity and mortality and alleviate the strain on the healthcare system.

Does the Concept of Property Rights Hold Relevance for Human Resource Performance?

In a world where information technologies (ITs) are globalizing and acting directly and explicitly on organizations, the question of property rights neutrality becomes strategic. In this study, the authors investigated whether ownership is a determinant of human resource performance or whether it is driven by factors other than ownership (e.g., technology and IT). Thus, the major objective of this research was to find out under what conditions ownership exerts a nonneutral effect on the performance of human resources and whether these effects are dependent on the technological aspects of organizations. The authors' methodology included two techniques, namely, nonparametric tests applied to the main indicators of 21 privatized companies (operating in the IT and other sectors) in the Tunisian case, and panel data to explain the impact of privatizations on human resources. The results showed that the privatization process has allowed an improvement in productivity indicators through an increase in incentive systems, particularly for companies with high technological content. The application of the econometric technique evidenced a whole policy of restructuring the allocation of human resources, in the postprivatization period. This makes sense because the incentive system of newly privatized companies strived to be more efficient. Furthermore, the second model showed that human resource dynamics after privatization depends on the business cycle and the nature of investors and IT. The third model confirmed the idea that privatization leads to an improvement in the workforce and its productivity in the long term. Overall, the study generated important managerial implications, the most important of which is that privatization can only generate a positive effect on human resource performance when employees feel involved in the process and as much as the organization is involved in new ITs.

County medical community, medical insurance package payment, and hierarchical diagnosis and treatment-Empirical analysis of the impact of the pilot project of compact county medical communities in Sichuan Province.

Hierarchical diagnosis and treatment (HDT) is an important exploration direction to alleviate the rising pressure of health expenses and medical insurance fund expenditure in China, and to maintain and protect the public health in this country. In recent years, the construction of compact county medical communities (CCMC) has become the primary approach for implementing the HDT. Utilizing the quasi-natural experiment of the pilot project of CCMC in Sichuan Province in 2019, coupled with county-level data extracted from the ' Sichuan Provincial Health Statistics Yearbook ' spanning the years 2008 to 2021, this research evaluates the effect of the pilot project of CCMC on promoting HDT under the medical insurance package payment model. The results show that the pilot project of CCMC has significantly increased the number of consultations per capita of medical and health institutions in pilot counties by 0.434 times, of which the number of consultations per capita of primary medical institutions has increased by 0.340 times; the number of hospitalizations per capita in public hospitals and primary medical institutions in pilot counties increased significantly, and the surgery rate of inpatients in public hospitals increased by 5% compared to before the pilot. There was no significant impact on the allocation of medical facilities and human resources in the pilot counties. Therefore, the construction of CCMC under the medical insurance package payment mode has promoted the realization of the county-level HDT. These findings provide valuable insights for healthcare policy, especially in developing and implementing effective strategies for HDT in county-level medical institutions.

Towards green governance and real economy development: how digital technology affects health human resource allocation?

ABSTRACT The adoption and integration of digital technology have profoundly reshaped societal and environmental governance within the healthcare sector. This study aims to explore the influence of digital technology development on the allocation of healthcare human resources, intending to contribute to the net-zero carbon process. Utilizing panel data from 30 provinces and cities across mainland China during the period 2011 to 2020, we computed three unique indices for health resource density. Employing the spatial Durbin model, our analysis unveiled a gradual augmentation in the overall level of healthcare human resource allocation in China due to the spatial impact of digital technology development. Robustness tests substantiated a noteworthy positive spatial spillover effect of digital technology, contributing to the augmentation of healthcare human resource allocation at the regional level. Heterogeneity results revealed a notably more pronounced promotional effect in the eastern region, contrasting with the central and western regions. From the perspective of sustainable development, the development of digital technology can contribute to the advancement of environmentally friendly healthcare by optimizing the allocation of healthcare human resources. In conclusion, this study offers valuable insights for China to formulate effective policies for healthcare human resource allocation, contributing to the attainment of sustainable development goals.

The impact of artificial intelligence on human resource management systems - Applications and risks

Organizations traditional human resource management model has been impacted by the ongoing optimization and advancement of artificial intelligence skills and technology, and the broadening of its application scope. The impact of artificial intelligence (AI) systems on employee recruitment, human resources allocations, and talent management is significant. This paper examines the interplay among AI, data applications, human resource management (HRM) systems and the resultant effects. It will examine the significance of effectively managing the deployment of AI systems, as existing literature defines. This study examines the effects of artificial intelligence AI technology on the effectiveness of company administration compared to traditional human resource management systems (HRMS). Several recommendations are offered to enhance the reformation and optimization of the organizations human resources (HR) division. The research findings indicate that incorporating the new system in conjunction with human involvement can significantly enhance the efficiency of employee recruitment, allocation of human resources, and management of talent within the firm. There was an improvement observed in both employee happiness and productivity elements.

Evaluating the Demand for Nucleic Acid Testing in Different Scenarios of COVID-19 Transmission: A Simulation Study.

The 2019 novel coronavirus (COVID-19) has been recognized as the most severe human infectious disease pandemic in the past century. To enhance our ability to control potential infectious diseases in the future, this study simulated the influence of nucleic acid testing on the transmission of COVID-19 across varied scenarios. Additionally, it assessed the demand for nucleic acid testing under different circumstances, aiming to furnish a decision-making foundation for the implementation of nucleic acid screening measures, the provision of emergency materials, and the allocation of human resources. Considering the transmission dynamics of COVID-19 and the preventive measures implemented by countries, we explored three distinct levels of epidemic intensity: community transmission, outbreak, and sporadic cases. Integrating the theory of scenario analysis, we formulated six hypothetical epidemic scenarios, each corresponding to possible occurrences during different phases of the pandemic. We developed an improved SEIR model, validated its accuracy using real-world data, and conducted a comprehensive analysis and prediction of COVID-19 infections under these six scenarios. Simultaneously, we assessed the testing resource requirements associated with each scenario. We compared the predicted number of infections simulated by the modified SEIR model with the actual reported cases in Israel to validate the model. The root mean square error (RMSE) was 350.09, and the R-squared (R2) was 0.99, indicating a well-fitted model. Scenario4 demonstrated the most effective prevention and control outcomes. Strengthening non-pharmaceutical interventions and increasing nucleic acid testing frequency, even under low testing capacity, resulted in a delayed epidemic peak by 78days. The proportion of undetected cases decreased from 77.83% to 31.21%, and the overall testing demand significantly decreased, meeting maximum demand even with low testing capacity. The initiation of testing influenced case detection probability. Under high testing capacity, increasing testing frequency elevated the detection rate from 36.40% to 77.83%. Nucleic acid screening proved effective in reducing the demand for testing resources under diverse epidemic prevention and control strategies. While effective interventions and nucleic acid screening measures substantially diminished the demand for testing-related resources, varying degrees of insufficient testing capacity may still persist. The nucleic acid detection strategy proves effective in promptly identifying and isolating infected individuals, thereby mitigating the infection peak and extending the time to peak. In situations with constrained testing capacity, implementing more stringent measures can notably decrease the number of infections and alleviate resource demands. The improved SEIR model demonstrates proficiency in predicting both reported and unreported cases, offering valuable insights for future infection risk assessments. Rapid evaluations of testing requirements across diverse scenarios can aptly address resource limitations in specific regions, offering substantial evidence for the formulation of future infectious disease testing strategies.

The Perceived Inequalities in Resource Allocation in Multi-Campus Universities in Ghana: The Case of University for Development Studies and Presbyterian University of Ghana

This paper examined and compared the resource allocation mechanisms in two multi-campus universities (MCUs) in Ghana. They are University for Development Studies (UDS) and Presbyterian University College, Ghana (PUCG), now known as Presbyterian University, Ghana (PUG). The main objective of the study was to investigate the perceived inequalities in the allocation of resources among the various campuses of the two Universities. The qualitative method, comparative case study approach and in-depth interview techniques were used to conduct the research. In all, eight senior management members (Pro Vice-Chancellors; Registrars; and Campus Heads) of the two Universities were purposively selected and interviewed. The findings revealed that these Universities do not have an established formula for the allocation of infrastructural and human resources for their respective campuses. It was also found that they use some percentages/ratios-based formula for the allocation of funds to the campuses. The paper recommends that physical infrastructure and human resources should be allocated based on deficits identified thorough need assessments. Secondly, to ensure a fair allocation of funds to the various campuses of the two universities, the deployment of a standardised mathematical formula is recommended.

Comparing Drug Handling Efficiencies and Expenses for Short- Acting Granulocyte-Colony Stimulating Factor Injection Originators and Biosimilars from the Perspective of Hospital Resource Management in Formulary Decision-Making

Background/Aim: With the availability of biosimilars, hospital formulary drug selection among biologics extends beyond clinical and safety considerations when comes to hospital resource management, to factors like human resource allocation and financial sustainability. However, research assessing the time and cost of labor, supplies, and waste disposal of biologics from the standpoint of hospitals remains limited. This study focuses on short-acting granulocyte-colony stimulating factor originators (Granocyte® and Neupogen®) and biosimilar (Nivestim®), comparing them based on mean total handling times per dose and total annual expenses. Materials and Methods: Ten nursesfrom a Taiwanese cancer centerwere recruited; they each prepared three doses of each drug. Results: Findings showedthat the mean total handlingtimes per dose of Granocyte® and Neupogen® were significantly higherthan that of Nivestim®. Handling Nivestim® required the lowest total annual expense. Conclusion: Nivestim® is an advantageous alternative to Granocyte® and Neupogen®, benefiting hospital resource management.

Reducing the length of stay for patients stranded in the emergency department: A single-center prospective study of 18,631 patients in China.

The purpose of this study was to reduce the length of stay (LOS) for patients stranded in the emergency department (ED) of a Grade III A hospital in China, and to improve patient flow and increase bed capacity. We utilized a pre-/postintervention design and employed the Six Sigma methodology, which is based on the DMAIC cycle (define, measure, analyze, improve, and control), to evaluate and improve the existing process. Data from 18,631 patients who were stranded in the ED were collected and analyzed. The median LOS for stranded patients decreased from 17.21 (6.22, 27.36) hours to 13.45 (5.56, 25.85) hours (P < .05). Similarly, the median LOS for admitted patients decreased from 19.64 (7.77, 27.68) hours to 15.92 (6.19, 26.24) hours (P < .05). The median LOS for patients with an ED triage Level IV decreased from 16.15 (5.80, 26.62) hours to 12.59 (5.20, 24.97) hours (P < .05). In addition, the average hospitalization days of hospitalized patients decreased from 0.92 days to 0.82 days (P < .05). Furthermore, the bed utilization rate increased from 66.79% to 72.29% (P < .05). The number of bed turnovers in the ED resuscitation room increased from 20.30 to 21.96 (P < .05). We had effectively met our goal of minimizing ED patient LOS. Six Sigma method can effectively shorten patient LOS by measuring and analyzing the key factors affecting patient LOS, and by implementing measures such as strict implementation of emergency classification and triage system, establishment of multidisciplinary cooperative team, reasonable allocation of human resources, information management of bed resources, and improvement of performance appraisal scheme to improve and control the effectiveness of patient LOS.

Assessment of Nursing Practice Environment and Its Influencing Factors: A Cross-Sectional Study at Shandong Province, Jinan.

To investigate the current nursing practice environment in Jinan, Shandong Province, and to identify the factors influencing the practice environment. This study is a cross-sectional study for nurses. From October to December 2022, using the clustering and stratified sampling methods, 2426 nurses from internal Medicine, Surgery, Obstetrics and Gynecology, Outpatient Department and Intensive Care Department of the Provincial Hospital of Shandong Medical University were selected and then investigated and analyzed using the revised Nurse Practice Environment Assessment Scale. The overall mean evaluation of the practice environment scored 75.13±19.87, with a minimum value of 59.74 and a maximum value of 95.82. The items with higher scores were "the hospital has systematic training for new nurses", "the work system is perfect", and "the hospital can provide continuing education for nurses in accordance with the needs of their positions". The items with lower scores were "nurses enjoy legal benefits", "nurses have the opportunity to participate in hospital management decisions", and "nurses have the opportunity to participate in hospital internal management". The results of the multiple linear regression analysis of the factors influencing nurses' practice environment showed that gender, education, position, and years of work were independent influences on nurses' practice environment scores (p < 0.05), and they explained 48.127% of the variation in the total scores of the nurses' practice environment scale. The estimated values (β) of sex, education, cheif nurse, nurses staff, work experience (year), and whether the only child variables were 3.141, 3.237, 2.713, 5.471, 2.074 and 0.732, respectively. The nurse practice environment still needs to be improved, mainly in terms of hospital management participation, human resource allocation and salary distribution system.

Top management team resource-based faultline and corporate green innovation: empirical evidence from listed Chinese manufacturing companies

PurposeThis study aims to focus on the resource-based faultline of a top management team (TMT) and intends to investigate the impact of TMT resource-based faultline on corporate green innovation, by indicating the environmental management as a mediator and slack resources as a moderator to understand the relationship.Design/methodology/approachBased on the empirical data of Chinese listed manufacturing companies from 2008 to 2020, this study assesses the hypotheses using an OLS model with fixed effects of time and industry.FindingsThe results indicate that TMT resource-based faultline is significantly negatively correlated with corporate green innovation. The conclusion remains valid after endogeneity tests and robustness checks. Mechanism test shows that environmental management plays a mediating role in the association between TMT resource-based faultline and corporate green innovation. Moreover, slack resources diminish the negative association between TMT resource-based faultline and corporate green innovation.Originality/valueThe study not only expands the theoretical understanding of the deeper motivation of TMT faultline on corporate green innovation, but also provides a practical reference for optimizing the human resource allocation of the TMT and accelerating green transformation development.

Evaluation Model of Human Resource Allocation Balance for Healthy Environment in Organizations Based on Big Data Driven and Internet of Things

Abstract To improve the ability of balanced evaluation, dynamic allocation, level of output, and profitability of human resources, a balanced evaluation model of human resources allocation is proposed based on big data driven and the Internet of Things. An evaluation architecture model of human resource allocation balance in view of big data driven and the Internet of Things is established; a multithread big data driven configuration model and the Internet of Things are used to construct a table model of enterprise human resource optimal allocation in the form of reports; statistical regression analysis method is used to detect the risks and process parameters in the process of enterprise human resource optimal allocation; and employment elasticity theory analysis is taken to establish a resource factor analysis model of human resource balanced allocation under the constraint of economic growth mode. According to the changing trend of the scale and structure of labor resources, statistical regression analysis is adopted to make big data driven analysis in the process of balanced evaluation of human resources allocation, and balanced game control is adopted to analyze the relevant factors affecting human resources allocation to realize balanced scheduling of population flow and human resources allocation and automatic post adjustment. The empirical analysis results show that the system has a good balance in human resource allocation, the output efficiency among the various elements of human resource allocation is improved, and there is a high level of efficiency in human resource output.

An ethical framework for human resource allocation in nursing.

An ethical framework for human resource allocation in nursing.

Fair-satisfied-based group decision making with prospect theory under DHLTS: The application in enterprise human resource allocation

Fair-satisfied-based group decision making with prospect theory under DHLTS: The application in enterprise human resource allocation

Human Resources Allocation of the Centers for Disease Control and Prevention in China.

To analyze the equity of human resources allocation of the Centers for Disease Control and Prevention (CDCs) and to predict the development in the next five years in China, and to provide a scientific basis for promoting the development of human resources. The data of the CDCs from 2017 to 2021 were obtained from the "China Health Statistical Yearbook", and descriptive analysis, health resource density index (HRDI), Theil index, and health resource agglomeration degree (HRAD) were used to evaluate the equity, and the grey prediction model GM (1, 1) was used to predict the development from 2022 to 2026. Measured by the HRDI, the shortage of human resources in the western region was relatively obvious, with a shortage of more than 11,656 health technicians, more than 6418 licensed (assistant) physicians, and more than 693 registered nurses. The Theil index of human resources allocation by population was between 0.016 and 0.071, and the Theil index of human resources allocation by geography was between 0.312 and 0.359. The allocation of human resources by geography was more unequal than those allocated by population. In terms of HRAD, human resources are over-allocated equitably by geography in the eastern and central regions, while they are under-allocated equitably by geography in the western region. In terms of the difference between the HRAD and PAD, the eastern region has a shortage of human resources relative to the concentration population, and the western region has an excess of human resources relative to the concentration population. The human resources allocation of the CDCs in China was uneven. The human resources of the CDCs were allocated more equitably by population than by geography. There was a situation where the equity of human resource allocation of the CDCs was contrary to the actual demand for medical care.

Confronting the Disruption of the Infectious Diseases Workforce by Artificial Intelligence: What This Means for Us and What We Can Do About It.

With the rapid advancement of artificial intelligence (AI), the field of infectious diseases (ID) faces both innovation and disruption. AI and its subfields including machine learning, deep learning, and large language models can support ID clinicians' decision making and streamline their workflow. AI models may help ensure earlier detection of disease, more personalized empiric treatment recommendations, and allocation of human resources to support higher-yield antimicrobial stewardship and infection prevention strategies. AI is unlikely to replace the role of ID experts, but could instead augment it. However, its limitations will need to be carefully addressed and mitigated to ensure safe and effective implementation. ID experts can be engaged in AI implementation by participating in training and education, identifying use cases for AI to help improve patient care, designing, validating and evaluating algorithms, and continuing to advocate for their vital role in patient care.

Research on Human Resource Allocation Algorithm for Application Integration Feature Selection in the Internet of Things Environment

Abstract In the context of the Internet of Things, the existing human resource optimization allocation methods have problems such as time-consuming resource allocation, improper allocation, improper matching between tasks and resources, and unsatisfactory human resources. This paper proposes a new human resource allocation method based on the multi-objective method, that is, the use of comprehensive feature selection for resource allocation. The method first extracts human resource features to establish a database, then completes feature selection based on the comprehensive feature selection method, establishes the human resource allocation model, and allocates resources according to various factors and resource characteristics. Finally, the genetic algorithm is used to solve the human resource allocation model to achieve the optimal allocation of human resources. The experimental results show that the proposed method takes a shorter time to allocate human resources and a shorter time to execute tasks after the allocation is completed, which verifies the high scheduling efficiency and effectiveness of the proposed method.