Effective Management Policies Research Articles

Аnalysis of the current state and main trends in the formation of the waste management system

The scale and significance of the waste problem intheUkrainian economy is associated both with thedomination ofresource-The scale and significance of thewaste problem in the economy of Ukraine is related bothto the dominance of resource-intensive technologies andthe lack of an effective waste management policy formany years. Significant volumes of accumulated waste,an increase in the number of unauthorized landfills andoverloaded landfills that do not meet environmentalsafety standards; low regulation of the issue of wastemanagement at the legislative level; the lack of aneffective waste management system and effectivemeasures aimed at preventing the generation, recycling,recovery and disposal of waste are the main factors thatnegatively affect the environmental safety of our country.Environmental assessment methods and the level of detailof accounting and analytical information on wasterequire improvement. The article examines the dynamicsof waste formation in Ukraine, the current situation ofwaste growth is worsened by the military aggression ofthe Russian Federation against Ukraine. The maindirections of the National Waste Management Strategyare considered. The necessity of forming an effectiveinformation system at the stage of implementation of thewaste management process at each enterprise, which hasboth national and regional significance, is substantiated.The need for the formation of reliable data by enterprisesof various forms of ownership for the formation oftransparent and objective information about waste inorder to implement a five-level hierarchy of wastemanagement, which is based on recovery and rationalconsumption of resources, uses economic approaches tominimize the negative impact on the environment, isemphasized. waste-free production and achieving thegoals of sustainable development. The need to regulatethe concepts of "waste" and "irreversible waste" inregulatory acts has been proven. The method ofaccounting for standard and non-standard nonreturnablewaste at the enterprise has been clarified.Thestudy notes that the formation of an effective wastemanagement system is one of the key tools for authoritiesto implement the basic principles of waste legislation atboth the national and regional levels.

A new model for residential location choice using residential trajectory data

Traditional residential location choice (RLC) models are based on the characteristics of location and demographics, revealing important patterns of RLC, but no RLC models have yet incorporated individual preferences. This study fills this gap by integrating the pattern of home-based travel into the RLC model. Firstly, by analysing residential trajectory data collected from Beijing and Shenzhen, we find that both residents’ commuting time, that is, time spent commuting to work, and home-based non-commuting (HBNC) time, that is, time spent on the consumption of amenities when departing from homes, follow an extreme value distribution (EVT). This indicates that, based on time budget and financial constraints, residents strive to minimise commuting time and maximise HBNC time. Subsequently, by integrating these findings into individual-level RLC analysis, we obtain an RLC model that aligns with the gravity model. Throughout the model training process, we demonstrate that the RLC model exhibits strong robustness by incorporating control variables, changing the spatial scale of the observation unit, testing for endogeneity, and considering historical RLC. Moreover, the model performs well in applications including assessing dynamic changes in RLC behaviours and making predictions based on previous travel behaviours. The RLC model in this study advances our understanding of human habitat selection behaviour and can be utilised by policymakers to develop and implement effective urban planning and epidemic management policies.

Global Trends in the Incidence of Anxiety Disorders From 1990 to 2019: Joinpoint and Age-Period-Cohort Analysis Study.

Anxiety disorders (ADs) are the most common mental illness with high prevalence, chronicity, and comorbidity. Despite rapid economic and cultural development, the global incidence of ADs continues to increase, with predominance in male individuals. To address the above issues, we analyzed the dynamic trends of the global incidence and disease burden of ADs from 1990 to 2019 and their different effects on age, period, and birth cohort and predicted the future trend of AD incidence. The data were obtained from the Global Burden of Disease study in 2019. A joinpoint regression model was used to calculate the annual percent change in AD incidence, and age-period-cohort analysis was used to estimate the independent effects of age, period, and cohort. Nordpred age-period-cohort analysis was used to predict the incidence of ADs from 2020 to 2044. The age-standardized incidence rate of ADs increased by 1.06% for both sexes, and the age-standardized disability-adjusted life-year (DALY) rate (ASDR) decreased by 0.12%. Joinpoint regression indicated that increments in average annual percent changes in the age-standardized incidence rate (0.068 vs 0.012) and ASDR (0.035 vs -0.015) for ADs globally were higher among male individuals than female individuals. The age-period-cohort analyses revealed that the relative risk (RR) of the incidence and DALYs of ADs among people of different sexes increased with age in adolescence and middle age and then decreased. For the period effect, the RR of incidence decreased, whereas the RR of DALYs increased in both sexes. Moreover, the RR of the incidence gradually increased and DALYs slowly decreased with birth year for both male and female individuals. New cases of ADs in male individuals are predicted to increase in the coming 25years. This study provided the changing trend of the global incidence and disease burden of ADs in the past 3 decades, indicating that early prevention and effective control cannot be ignored. We analyzed the age-period-cohort effect of potential trends in ADs and predicted future incidence trends. The results suggest that we should take active intervention measures, focusing on high-risk groups and developing effective management and control policies to reduce the global burden of disease.

Deciphering the evolving trajectories of China's megaregions from 1992 to 2020: A novel morphological approach based on global land cover products

The monitoring of megaregion boundaries (MBs) is of vital importance for optimizing land use decision-making. However, the morphological structure of megaregions is currently insufficiently identified due to the nontransparent proprietary or inherent deficiency data sources. Thus, this study utilized land cover products integrated with morphological approaches to delineate the evolving trajectories of China's megaregions from 1992 to 2020. Firstly, core areas of megaregions and periphery affected areas were extracted from urban land density maps based on the gravity model and landscape metrics. Secondly, contiguous urban-rural fringes were improved based on the morphological operations and the rank-size distribution. Thirdly, urban land was automatically allocated to megaregions, considering planning policies. Furthermore, three indicators (gross domestic product, population, and land use density) are considered to validate our results, and our extracted MBs show a better understanding than the administrative divisions. The dynamic expansion patterns of twenty identified MBs were captured. As urbanization continues, the boundaries between megaregions become increasingly blurred and eventually merged into large-scale continuous megaregions that extend far beyond administrative divisions. Our study provides valuable insights for megaregion planning, including the effective urban management policies, the role of core cities in each megaregion in terms of radiation and capability.

Improving model performance in mapping cropland soil organic matter using time-series remote sensing data

Faced with increasing global soil degradation, spatially explicit data on cropland soil organic matter (SOM) provides crucial data for soil carbon pool accounting, cropland quality assessment and the formulation of effective management policies. As a spatial information prediction technique, digital soil mapping (DSM) has been widely used to spatially map soil information at different scales. However, the accuracy of digital SOM maps for cropland is typically lower than for other land cover types due to the inherent difficulty in precisely quantifying human disturbance. To overcome this limitation, this study systematically assessed a framework of “information extraction-feature selection-model averaging” for improving model performance in mapping cropland SOM using 462 cropland soil samples collected in Guangzhou, China in 2021. The results showed that using the framework of dynamic information extraction, feature selection and model averaging could efficiently improve the accuracy of the final predictions (R2: 0.48 to 0.53) without having obviously negative impacts on uncertainty. Quantifying the dynamic information of the environment was an efficient way to generate covariates that are linearly and nonlinearly related to SOM, which improved the R2 of random forest from 0.44 to 0.48 and the R2 of extreme gradient boosting from 0.37 to 0.43. Forward recursive feature selection (FRFS) is recommended when there are relatively few environmental covariates (<200), whereas Boruta is recommended when there are many environmental covariates (>500). The Granger-Ramanathan model averaging approach could improve the prediction accuracy and average uncertainty. When the structures of initial prediction models are similar, increasing in the number of averaging models did not have significantly positive effects on the final predictions. Given the advantages of these selected strategies over information extraction, feature selection and model averaging have a great potential for high-accuracy soil mapping at any scales, so this approach can provide more reliable references for soil conservation policy-making.

Public water quality in surface and groundwater collection systems in Brazil

Water is a vital natural resource for the existence of life, maintenance of ecosystems and the development of society. Many cities and communities rely on surface catchment systems, which involve collecting water from rivers, lakes and dams. Others, in turn, use underground collection systems, obtaining water from aquifers and artesian wells. Each of these methods presents specific challenges regarding water quality, as surface water is more exposed to organic and inorganic pollutants, while groundwater may contain minerals and dissolved substances that affect its potability. In general, the quality of water that reaches homes and commercial establishments is determined by the analysis of microbiological indicators, free residual chlorine, turbidity, total coliforms and fluoride. This narrative review seeks to clarify the nuances of water capture systems, their particularities and the factors that affect water quality in Brazil, highlighting the importance of constant monitoring, adequate treatment and effective water management policies in guaranteeing access to fresh water high quality for everyone.

Analysis of Factors Affecting Turnover Intention in BPR Batam City Bank Employees

The growth of the banking sector in Indonesia has experienced rapid development in recent decades, playing a key role in supporting the economy and the well-being of the community. Employees in the banking sector, including Bank Perkreditan rakyat (BPR), have a significant impact on the success of the bank. However, employee turnover intention has become an important issue that needs to be addressed in the midst of increasing competition in the banking sector. This study identifies the factors influencing employee turnover intention at BPR Batam City and proposes strategies to minimize turnover, Data obtained through the distribution of 192 questionnaires to respondents. The study's findings also explain the relationship between compensation, organizational culture, job stress, and job satisfaction on employee turnover intention. These results can serve as a basis for developing more effective human resource management policies in the banking sector.

МЕТОДИКА ОЦЕНКИ АКТИВНЫХ ОПЕРАЦИЙ КОММЕРЧЕСКОГО БАНКА

The generation of the main financial result of commercial banks directly depends on the effectiveness of active operations. The evolution of financial relations, the achievement of the main goal of the credit institution’s activ- ities to obtain a positive financial result and the desire of commercial banks to use and diversify free cash flows in the economic environment – all this has determined the relevance of this scientific research. In their activities, all credit institutions constantly apply an effective banking management policy through methods of evaluating active transactions, as well as obtaining complete and timely information about the functioning of a credit institution is ensured by constant monitoring, timely prompt response to rapid changes in the banking services market in modern conditions, which contributes to their more efficient functioning. Generating a high financial result, maintaining an acceptable level of solvency and liquidity of banking activities is ensured by effective management of active operations of a credit institution, competent placement of available funds.

PRINCIP ZERO WASTE U FUNKCIJI POVEĆANJA EKONOMSKOG RAZVOJA U HOTELSKOM POSLOVANJU

The aim of this research is to determine the impact of implementing the Zero Waste strategy on economic benefits in the hotel industry of the Republic of Serbia. A quantitative methodology was employed, comprising a survey among managers from various hotels, combined with statistical data analysis to verify hypotheses. The results indicate that investments in employee education, effective waste management policies, and investments in sustainable technologies significantly contribute to profit enhancement. This research contributes to the theoretical understanding and practical application of the Zero Waste strategy in the hospitality sector, providing evidence supporting the economic and environmental value of sustainable practices.

Security Awareness Programs and Behavioral Patterns in Nigeria Deposit Money Banks: Adopting a Robust Cybersecurity Culture.

In an era marked by evolving cybersecurity threats, understanding the interplay between Security Awareness Programs, Behavioral Patterns, and Cybersecurity Culture is essential for safeguarding organizational assets and maintaining trust in financial institutions. This study investigated this relationship within Nigeria’s Deposit Money Banks, employing a comprehensive analysis of key variables such as Compliance Adherence, Security Policy Acknowledgements, Training Completion Rate, Risk Awareness and Management, Behavioral Analytics, Employee Feedback and Engagement, and Incident Response Time.Utilizing data gathered from a field survey, the study employed multiple regression analysis and tested for hypotheses. Specifically, the study revealed that Compliance Adherence, Training Completion Rate, and Risk Awareness and Management significantly influenced Employee Feedback and Engagement. Compliance Adherence increased Employee Feedback and Engagement by 0.065 (t-stat: 0.750, p = 0.014), Training Completion Rate by 0.397 (t-stat: 3.846, p &lt; 0.001), and Risk Awareness and Management by 0.237 (t-stat: 2.031, p = 0.028). Similarly, Compliance Adherence, Security Policy Acknowledgements, Training Completion Rate, and Risk Awareness and Management significantly impacted Incident Response Time. Compliance Adherence increased Incident Response Time by 0.067 (t-stat: 0.721, p = 0.041), Security Policy Acknowledgements by 0.087 (t-stat: 0.911, p = 0.033), and Training Completion Rate by 0.188 (t-stat: 1.118, p &lt; 0.001). However, Risk Awareness and Management didn’t show significant impact on Incident Response Time. Moreover, Compliance Adherence, Security Policy Acknowledgements, Training Completion Rate, and Risk Awareness and Management significantly contributed to Cybersecurity Culture. Compliance Adherence increased Cybersecurity Culture by 0.523 (t-stat: 0.101, p &lt; 0.001), Security Policy Acknowledgements by 0.041 (t-stat: 0.279, p = 0.011), Training Completion Rate by 0.188 (t-stat: 1.139, p &lt; 0.001), and Risk Awareness and Management by 0.239 (t-stat: 1.453, p = 0.041). These findings offered valuable insights for policymakers, bank management, cybersecurity professionals, and employees, informing the development of effective cybersecurity strategies and risk management policies. By understanding the intricate relationship between Security Awareness Programs, Behavioral Patterns, and Cybersecurity Culture, stakeholders could better navigate the complexities of the cybersecurity landscape and safeguard organizational interests.

Initial Discovery of Microplastic Presence in the Gastrointestinal Tract of Certain Fish Species in Al-Hoceima Bay

The accumulation of plastic waste in ocean environments is a critical ecological issue impacting marine wildlife and human health. This study assesses the presence of microplastics in the gastrointestinal tracts of fish from Al-Hoceima Bay, a key part of the Mediterranean marine ecosystem. Using Fourier Transform Infrared (FT-IR) spectroscopy, we analyzed 90 individuals from two different species, finding that 33% of the examined fish contained microplastics. Specific occurrences were 26% in mackerel and 40% in gilthead sea bream. These findings highlight significant contamination even in commercial fishing areas, raising urgent questions about the long-term ecological effects and health risks. Therefore, the need for effective plastic waste management policies is critical to protect our marine ecosystems and food safety.

Assessment of Public concerns and Behaviours towards Scientific Solid Waste Management in Kanpur City (U.P.), India

The study evaluates household civic amenities, behaviour, and perspective on the management of garbage and trash in different zones of Kanpur city, using primary data collected through interviews with 622 randomly selected households. The study calculates Household Amenities Index, Behaviour Index and Pollution Perception Index, based on variables: toilet facilities, drinking water sources, ways of discarding garbage and readiness to pay for pickup.The study finds that zone 6 residents are more diligent in scientific waste management, and there is high pollution in the city centre due to poor management and lack of civic facilities. The finding would guide effective solid waste management policies.

Talent management of library and information science professionals: A review of research and future directions.

This study aims to review the extant literature on talent management with the objective of influencing library and information management by addressing the key facets of talent management, such as talent management strategies, importance of career development, evaluation of talented employees, and organizational resilience. Literature on the development of talent and career management was retrieved from various scholarly papers indexed in Scopus and Web of Science to have a meticulous literature review serving as the platform of the present study. In light of the authors' observations, two models were developed. The literature provides precise information that talent management plays a decisive role in promoting organizational excellence invariably in all kinds of organizations in general and libraries in particular. This study provides constructive recommendations for the implementation of effective talent management and retention policies for library and information professionals. Moreover, this study adds immense value to the corpus of existing literature to set a platform for the augmentation of library management in futuristic vision. This study provides constructive recommendations to policy makers and library administrators to foster talented employees for excelling library and information services for the next several decades.

Intention to receive Latent Tuberculosis Infection (LTBI) treatment and its associated factors among healthcare workers in a Malaysian teaching university hospital.

The acceptability of latent tuberculosis infection (LTBI) therapy remains low among healthcare workers (HCWs). Up to 10% of LTBI cases can reactivate into active tuberculosis, posing risks to HCWs and patients. Understanding HCWs' intention to undergo LTBI treatment is crucial for designing effective management policies, especially where no LTBI policy exists. This cross-sectional study investigated the intention to receive LTBI therapy and its associated factors among HCWs in a Malaysian teaching hospital. The study was conducted from 5th to 30th May 2023, in a hospital without an LTBI screening program. Stratified random sampling was used to select HCWs, excluding those undergoing TB or LTBI therapy. Respondents completed a questionnaire measuring intention to receive LTBI treatment, LTBI knowledge, attitude, perceived norm, and perceived behavioral control. Of the 256 respondents, the majority were female (63.7%), under 35 years old (64.45%), had no comorbidities (82.0%), and worked in clinical settings (70.3%). However, 60.5% of respondents had low LTBI knowledge and 60.5% held unfavorable attitudes toward LTBI treatment. Despite this, 53.5% of respondents intended to undergo LTBI therapy if diagnosed. Factors positively associated with this intention included being female [aOR: 2.033, 95% CI: 1.080-3.823], having high LTBI knowledge [aOR 1.926, 95% CI: 1.093-3.397], had favorable attitude [aOR 3.771, 95% CI: 1.759-8.084], and strongly perceiving social norms supportive of LTBI treatment [aOR 4.593, 95% CI: 2.104-10.023]. These findings emphasize the need for an LTBI management policy in the teaching hospital. To boost HCWs' intention and acceptance of LTBI treatment, a focused program improving knowledge, attitude, and perception of social norms could be introduced.

Research progress on sources, harms and countermeasures of marine pollution

Human behavior is posing a serious threat to the ecological environment of the global ocean. This paper explores three important issues related to the marine environment: nuclear pollution, ocean acidification and marine microplastic pollution. First, the problem of nuclear pollution focuses on the potential threat to marine ecosystems and human health from nuclear sewage discharge from the nuclear power plant in Japan. Although the Japanese government has taken some response measures, the relevant risks and impacts still need attention to and addressed. It is suggested to strengthen supervision and management, promote technological innovation, and reasonably support the affected communities. Second, the ocean acidification problem is exacerbated by excessive atmospheric carbon dioxide emissions, which has a serious impact on marine life and ecosystems. The article advocates reducing global greenhouse gas emissions, promoting renewable energy development, and strengthening international cooperation and scientific research to protect marine ecosystems. Finally, in response to marine microplastic pollution, it calls for strengthening the development and use of plastic alternatives, improving waste management and treatment, and promoting innovation in microplastic detection and removal technologies. Addressing these issues requires the combined efforts of governments, researchers and the public, including enhanced monitoring, research and development of effective management policies.

지역안전지수 개선을 위한 민간경비의 역할 모색

This study seeks to explore ways to utilize private security to improve the local safety index. It is an approach that emphasizes the need to create a culture that can expand citizen participation by engaging private security in various programs related to local safety. The analysis of the status of the local safety index is limited to 2022. It is mainly conducted through literature research and uses press reports to review major improvement activities.&#x0D; It is difficult to manage the local safety index announced every year and to implement new policies. The solution to this problem is to consider the participation of private security. Strictly speaking, it is a way to improve the local safety index by engaging private security in activities related to the local safety index.&#x0D; There are several advantages to including private security in the activities of community safety. First, private security is already functioning for the safety of the community. Second, private security is organized nationwide. Third, it is easy to secure the expertise of private security.&#x0D; Local safety index improvement efforts should be continuous from various perspectives. Local governments should strive to accurately grasp the safety situation of the community and to establish effective safety management policies.

Coupling analysis of land use change with landscape ecological risk in China: A multi-scenario simulation perspective

The continuous change of global land use and intense human activities lead to the constant change of landscape ecological risk (LER). The increase of LER will pose a serious threat to human welfare and sustainable development. In previous studies, there were few studies on coupling coordination between land use intensity (LUI) and LER in multi-scenario simulation. Therefore, it is of a certain significance to study the coupling and coordination relationship between LUI and LER in a long-term multi-scenario simulation in the future for the sustainable use of land resources and the management of ecological risk. Based on the multi-scenario land use simulation data of China in 2010, 2050, and 2100, this study selects the comprehensive index of land use intensity, landscape pattern index, spatial autocorrelation, and coupling coordination methods to analyze the spatio-temporal characteristics of LUI and LER from 2010 to 2100, as well as the coupling coordination relationship between them. The results show that the overall LUI of China remains stable at around 200 from 2010 to 2100, with a spatial distribution that is “low in the northwest and high in the southeast.” The LUI of China decreases under the balanced resources scenario and global environmental protection scenario, while the regional economic development scenario and regional environmental protection scenario exhibit an increasing trend. The overall LER in China is approximately 0.150, with a spatial distribution that is “high in the north and low in the south.” The four scenarios exhibit a downward trend from 2010 to 2100. There is significant spatial dependence between LUI and LER in China, with the largest number of counties exhibiting reluctant coordination between the two (accounting for nearly 45%), while their interaction and mutual influence remain strong. Thus, this study may contribute to understanding this relationship and to creating effective landscape ecological risk management policies.

A comparative study of Machine Learning and Deep Learning methods for flood forecasting in the Far-North region, Cameroon

Flood crises are the consequence of climate change and global warming, which lead to an increase in the frequency and intensity of heavy rainfall. Floods are, and remain, natural disasters that result in huge loss of lives and material damage. Flood risks threaten all countries of the globe in general. The Far-North region of Cameroon has suffered of flood crises on several occasions, resulting in significant loss of human lives, infrastructural and socio-economic damage, with the destruction of homes, crops and grazing areas, and the halting of economic activities. The models used for flood forecasting in this region are generally physical-based, and produce unsatisfactory results. The use of artificial intelligence based methods for flood forecasting in order to limit its consequences is a way to be explored in the Far-North region of Cameroon. The aims of the present research work is to design and compare the performance of Machine Learning and Deep Learning based models such as one dimensional Convolutional Neural Network, Long and Short Term Memory and Multi Layer Perceptron for short-term and long-term flood forecasting in the Far-North region of Cameroon. The models designed take as input the temperature and rainfall time series recorded in this region. Performance criteria used for evaluating models are Nash–Sutcliffe Efficiency, Percent Bias, Coefficient of Determination and Root Mean Squared Error. As the results of the design and performance comparison of the models, the best model for short-term flood forecasting is the LSTM model , and the best model for long-term flood forecasting is still the LSTM model. The best models obtained from the comparisons have satisfactory performance and good generalization capabilities, as reflected by the performance criteria. The results of our research work can be used for implementation of floods warning systems and for definition of an effective and efficient flood risk management policies in order to make the Far-North region of Cameroon more resilient to flood crises.

Understanding the Reliability of the Complex System Having Two Standby Units: A Transdisciplinary Approach

The main objective of this study is to thoroughly investigate the reliability of a complex system that consists of four components and two standby units. The complicated system is modeled using the Markov technique. The study formulates differential equations and solves them using a matrix method with the assistance of a computer program. Statistical methods, such as correlation and regression, are applied using SPSS software to understand the relationship between time and the reliability of this complex system. A statistical model is utilized to determine the system's reliability, identify potentially faulty components, and prioritize the protection of the most critical elements. The presentation of significant findings involves conducting a comprehensive analysis using tables and graphs created with Python programming language. The outcomes of this study aim to assist in identifying crucial units in various process industries, thereby facilitating the establishment of effective management policies and strategies for the optimal operation of complex and large-scale systems in the industry. This paper incorporates numerous disciplines, viewpoints, and methodologies to examine and enhance reliability in process industries. Reliability can indeed benefit from a matrix approach, which can be considered transdisciplinary. This study serves as both an introductory guide to reliability analysis for novice researchers and a survey highlighting the latest advancements in the field for experienced researchers.

Trend Analysis of Seasonal Drought in Northern Karnataka, India

Trend analysis of climatic data is often carried out in water resources management studies to understand its distribution over a given region. This paper presents an analysis of trends in meteorological drought in 12 districts in the northern part of Karnataka state, India over the period 1991–2020. Trends in the 3-month timescale standardized precipitation index (SPI-3) were analyzed using the Mann-Kendall (MK) trend test and Sen’s slope estimator for the Kharif season. The results of analysis showed an increasing trend of droughts in four districts however, the trend in most of the districts was not statistically significant. The findings were validated with the trend of the declared area under drought (AUD) by the state government for the study area. The findings of this work might be useful for a better understanding of regional drought trends and also for establishing effective water resources management policies.