Resource Management Policies Research Articles

Application of a Random Forest Method to Estimate the Water Use Efficiency on the Qinghai Tibetan Plateau During the 1982–2018 Growing Season

Water use efficiency (WUE) reflects the quantitative relationship between vegetation gross primary productivity (GPP) and surface evapotranspiration (ET), serving as a crucial indicator for assessing the coupling of carbon and water cycles in ecosystems. As a sensitive region to climate change, the Qinghai Tibetan Plateau’s WUE dynamics are of significant scientific interest for understanding carbon water interactions and forecasting future climate trends. However, due to the scarcity of observational data and the unique environmental conditions of the plateau, existing studies show substantial errors in GPP simulation accuracy and considerable discrepancies in ET outputs from different models, leading to uncertainties in current WUE estimates. This study addresses these gaps by first employing a machine learning approach (random forest) to integrate observed GPP flux data with multi-source environmental information, developing a predictive model capable of accurately simulating GPP in the Qinghai Tibetan Plateau (QTP). The accuracy of the random forest simulation results, RF_GPP (R2 = 0.611, RMSE = 69.162 gC·m−2·month−1), is higher than that of the multiple linear regression model, regGPP (R2 = 0.429, RMSE = 86.578 gC·m−2·month−1), and significantly better than the accuracy of the GLASS product, GLASS_GPP (R2 = 0.360, RMSE = 91.764 gC·m−2·month−1). Subsequently, based on observed ET flux data, we quantitatively evaluate ET products from various models and construct a multiple regression model that integrates these products. The accuracy of REG_ET, obtained by integrating five ET products using a multiple linear regression model (R2 = 0.601, RMSE = 21.04 mm·month−1), is higher than that of the product derived through mean processing, MEAN_ET (R2 = 0.591, RMSE = 25.641 mm·month−1). Finally, using the optimized GPP and ET data, we calculate the WUE during the growing season from 1982 to 2018 and analyze its spatiotemporal evolution. In this study, GPP and ET were optimized based on flux observation data, thereby enhancing the estimation accuracy of WUE. On this basis, the interannual variation of WUE was analyzed, providing a data foundation for studying carbon water coupling in QTP ecosystems and supporting the formulation of policies for ecological construction and water resource management in the future.

Hydrogeochemical investigation and water quality assessment of the Indus River in the semiarid region of Ladakh, India.

The decline in water quality, particularly in river water, is a significant concern, especially in semi-arid areas and tourist destinations such as Ladakh. Periodic assessment of water quality could be a crucial step for ensuring its potability and serve as a foundation for formulating effective policies for sustainable water resource management. Consequently, this research aimed to analyze the periodic variations in the water quality of Indus River for domestic and agricultural use, focusing on the impact of geochemical processes within the basin. Various physicochemical parameters namely temperature, pH, electrical conductivity, turbidity, total dissolved solids, total hardness, total alkalinity, K+, Na+, Mg2+, Ca2+, Cl-, SO42-, SiO2, HCO3-, CO32-, and NO3- for sixty-five water samples from seven key locations were assessed during three distinct periods: April-May (early melting period, EMP), July-August (peak melting period, PMP), and October-November (late melting period, LMP), 2023. The ion contents found were in the following order: Ca2+>Na+>Mg2+>K+ and HCO3->SO42->Cl->SiO2>NO3->F-, reflecting Ca-HCO3 water types. However, temporal and spatial variation in ion content and hydrochemical facies were observed when the water moved downstream and confluences with the Zanskar River to give calcium‑magnesium-sulphate facies. Water quality indices- Canadian Council of the Ministers of the Environment Water Quality Index (CCMEWQI) and Weighted Arithmetic Water Quality Index (WAWQI) were employed to assess the water quality over these periods, identify long-term trends, evaluate the water quality status, and provide insights into immediate conditions. WAWQI values recorded for EMP (56.89-509.53), PMP (289.82-3419.23), and LMP (55.16-159.14) found were poor to unsuitable for drinking while using CCMEWQI, it was in the marginal range. Additionally, the Wilcox diagram and other important irrigational indices like Percent sodium, Sodium Absorption Ratio, Residual Sodium Carbonate, Magnesium hazard, Permeability Index, Kelly's ratio, Ryznar stability index indicated the suitability of the water for agricultural use in all the periods. Apart from arsenic (54μg/L), all other heavy metal ions measured were within the permissible limits according to the Heavy Metal Pollution index. Principal Component Analysis identified different principal components contributing to the hydrochemistry of the river water whereas correlational analysis was conducted to understand the correlation among different parameters and their potential source in water. Rapid carbonate mineral reactions and sulphate reduction were found to affect the alkalinity and hardness of the water. This study will serve as a scientific reference and methodological guide for researchers- to understand water chemistry; committee awareness on health and agricultural impacts; and policymakers for decision-making on water use, policy, and conservation.

Material and Immaterial Compensation as a Determinant of Employee Organizational Commitment

The success and failure of any organization largely depend on talented and competent employees. Through human resource management (HRM) practices and policies, organizations strive to ensure committed employees. One of the fundamental practices they use is undoubtedly material and immaterial compensation. Adequate management of such compensation may contribute to greater employee engagement in achieving the set goals, realizing the mission, and fulfilling the vision of the organization. In such ways employees confirm their affiliation with the organization, which classifies them as committed employees. The paper assumes that the adequate application of material and immaterial compensation in organizations in Bosnia and Herzegovina (BiH) may improve employee organizational commitment. This ultimately has a positive impact on the effectiveness and efficiency of organizations. The research was conducted in 128 BiH organizations with more than 50 employees across four sectors. The hypotheses were tested applying the Principal Components Analysis (PCA) through the Kaiser-Meyer-Olkin (KMO) values and Bartlett's test of sphericity and the regression analysis. The results show a statistically significant positive impact of material and immaterial compensation on employee organizational commitment. Creating more agile policies and practices of human resource management, especially those related to material and immaterial compensation, can significantly improve employee commitment as well as the entire organizational effectiveness.

Proposed policy for strategic human resource management in the Office of the Cane and Sugar Board

The objective of this study was to analyze the strategic plan of human resource management and formulate a policy proposal for human resource management regarding strategic plans 2022–2026, in the Office of the Cane and Sugar Board Ministry of Industry of Thailand (OCSB). The researchers used a policy research methodology where the data collection process consisted of seven steps as follows: 1) Research related to documents and studies 2) Workshops 3) Consulting team meetings based on expertise 4) In-depth interviews 5) Focus group discussions 6) Group meetings between executives and working groups of the OCSB. together with the researchers of this study, and 7) Organizing the public hearing; key informants in this research were executives, government officials, and personnel of the OCSB. The research results showed that: 1) The OCSB reached a consensus on formulating a strategic plan, which includes: vision, mission, strategic issues, goals and objectives, and various strategies for human resource management operations for the years 2022–2026. 2) Policy proposals for the Human Resource Management Strategic Plan 2022–2026 should be divided into three dimensions: a strategic dimension of human resource management strategy transfer, an implementation dimension of the supervision and monitoring of human resource management strategic plans, and dimensions of review and evaluation of human resource management strategic plans.

Morphometrics and Meristics of Senangin (Eleutheronema Tetradactylum) Results of Gillnet Catch in Mendahara Ilir of East Tanjung Jabung District

Mendahara Ilir is an area located on the coast with the majority of the community working as fishermen. Fishermen in this area catch fish using Gillnet fishing gear. Overfishing is a form of excessive fishing, the fish population is decreasing over time so that it can cause extinction and will cause degradation of fish resources leading to the extinction of the Senangin species. The purpose of this study was to determine the morphometric and meristic measurements of Senangin (Eleutheronema tetradactylum) in the waters of Mendahara Ilir which can be used as a consideration in making fisheries resource management policies. The method used in this study was the survey method. Data collection was carried out on 30 Senangin samples. Morphometric measurements used 11 characters and meristic calculations used 7 characters. The results of this study showed that the longest Senangin was 65.8 cm and the shortest was 19.0 cm. The average length of the Senangin obtained was 34.7 cm. The determination coefficient R2 of senangin from morphometric characters to total length (TL) ranges from 0.94 to 0.99 where the value shows a very close relationship. The correlation results are influenced by food availability. Meristics of senangin are D.II; D17-19, A.II: A15-70, P.II: 10-76, C.II: 31-182, scales on the tail stem with a total of 136 and a minimum number of 40, lateral line scales with a total of 170 and a minimum number of 62. The conclusion is that Senangin in the Mendahara Ilir waters are still well maintained habitat in Mendahara Ilir.

Out of sight, out of mind? Investigating the impact of emotional intelligence on counterproductive work behavior in remote work

PurposeThe purpose of this research is to investigate the relationship between emotional intelligence (EI) and counterproductive work behavior (CWB) in remote work (RW).Design/methodology/approachIn total, 489 currently employed people were surveyed in April 2022 – 2 years after the start of the pandemic and 1 year before “the great return” to the workplace.FindingsResults reveal that EI is negatively associated with CWB and that RW moderates this relationship. The more people work remotely, the more likely they are to adopt CWB. However, this tendency is lower for people with higher EI.Originality/valueThis research contributes to the literature on CWB by highlighting the role EI plays in the specific context of RW. In terms of practical implications, it sheds lights on the importance of carefully designing human resource management policies towards RW.

Applying the Eightfold Path to Morocco's Cabinet Order 2.23.105

ABSTRACTMorocco is fighting its sixth year of drought. As part of its comprehensive response to the drought, the Moroccan cabinet passed order 2.23.105 in December 2023. The new rules require the regulation of well drilling entities. The problem of illegal wells, often dug by farmers who do not know that they need a license, represented a threat to the country's water tables long before the current drought and constitutes a significant barrier towards the adoption of effective Integrated Water Resource Management and Demand Side Management policies. The paper is based on an examination of the current laws including order 2.23.105, by applying the eightfold path of policy analysis, interviews with water officials, and including the views of farmers concerning their efficacy. The paper argues that the state is an essential player in framing an effective response to drought and to climate change. Soil and Water Analysis Tools (SWAT) like ArcSWAT will help improve the state's response and enable it to identify and engage key stakeholders.

The Mediating Effect of Accountability on the Relationship between Job Satisfaction and Apparatus Performance with Organizational Commitment as a Moderating Variable: Evidence from the Government of Tanjung Balai

This study aims to analyse job satisfaction's influence on government apparatuses' performance in the Tanjung Balai City Government, considering accountability as a mediating variable and organizational commitment as a moderating variable. Against the backdrop of challenges, the Tanjung Balai City Government faces through 2025, this research focuses on enhancing public service quality and public welfare. The study employs a quantitative approach with a survey design. The research sample, selected through purposive sampling, consists of 130 structural officials of the Tanjung Balai City regional government involved in budget preparation processes. The findings are expected to provide strategic recommendations for improving performance through better human resource management policies, accountability practices, and organizational commitment initiatives. Furthermore, this study aims to offer insights into the impact of job satisfaction on apparatus performance and the mediating role of accountability in enhancing performance effectiveness.

Research on Groundwater Drought and Sustainability in Badain Jaran Desert and Surrounding Areas Based on GRACE Satellite

Groundwater plays a crucial role in the formation of the Badain Jaran Desert-Sand Dune Lake System, which has been designated a UNESCO World Heritage Site in 2024. However, the region’s wetland ecosystem is significantly impacted by climate change and human activities. This study utilizes GRACE satellite data and in situ observation data to establish a groundwater storage anomaly (GWSA) time series for the Badain Jaran Desert and its surrounding areas (BJDCA) from 2003 to 2022. The analysis reveals the spatiotemporal patterns of groundwater drought and sustainability, as well as the underlying factors affecting regional groundwater sustainability. The results indicate that 99.2% of the study area exhibited a significant decline in GWSA (α ≤ 0.01), with the annual mean GRACE Groundwater Drought Index (GGDI) dropping from 1.44 to −1.54, reflecting a worsening groundwater drought. In 2022, the GGDI in the southeastern part of the BJDCA reached as low as −3.04, highlighting severe groundwater stress. Furthermore, the Sustainability Index (SI) of the study area declined markedly from 1.00 to 0.01, underscoring the critical impact of human activities on groundwater resources in the BJDCA. These findings provide valuable insights for formulating more effective groundwater resource management policies and promoting sustainable development in arid regions.

Spatiotemporal patterns in precipitation whiplash over China during 1901–2100 based on CMIP6 simulations

Abstract The increasing risk of precipitation whiplash, characterized by rapid transitions between extreme drought and wet conditions, is largely related to atmospheric circulation changes due to anthropogenic greenhouse gas emissions. This study aims to examine the changing patterns of precipitation whiplash events for future projections (2021–2100) with regard to the current climate (1981–2020), and to unveil the relations between intensity, duration, and frequency of these events for various return periods across different regions of China. Multi-source observational datasets were also used to analyze the trend of precipitation whiplash indices for the current climate and to assess the ability of the CMIP6 ensemble model for reproducing the characteristics of precipitation whiplash events. The Intensity-Duration-Frequency (IDF) curves were estimated by using the nonstationary Generalized Extreme Value (GEV) model combined with Bayesian inference. The results show an increasing trend in frequency, intensity, and severity of precipitation whiplash events, particularly for the long-term future, while the duration of these transitions shows a decreasing trend. The peak occurrence months during the long-term future period exhibit notable changes in most parts of China. Specifically, the dry-to-wet whiplash events occur approximately two months earlier than in the current period, while the wet-to-dry whiplash occurs approximately two months later. The results also indicated that IDF curves shifted upward, particularly in the long-term future projections, suggesting an increased likelihood of more severe events. The findings of this study will serve as an essential reference for local authorities to develop more effective water resource management and disaster mitigation policies to tackle the impact of future climate change.

Climate change driven land use evolution and soil heavy metal release effects in lakes on the Qinghai Tibet Plateau.

In recent decades, global warming has intensified hydrological cycles, raising concerns about the impacts of climate change on hydrological processes, water quality, and water resources across various temporal and spatial scales. These changes significantly affect water resource management and environmental protection policies and may also influence the ecological health and socio-economic well-being of lake regions. Qinghai Lake, the largest inland lake and a major water source reservoir in China, plays a crucial role in the ecological security of the Qinghai-Tibet Plateau. However, in recent years, with the ongoing development of the economy and society throughout the province, there has been an increase in algal blooms in the nearshore area of Qinghai Lake, with the affected area expanding annually. There is currently no clear consensus on the causes of eutrophication in lakes, and comprehensive, in-depth research on how different land use types-critical to the material migration and transformation processes of natural water bodies-affects water quality and ecological security, as well as the interactions between nutrients and heavy metals, is lacking. Therefore, it is essential to monitor and understand the effects of climate change on lakes and to develop adaptive strategies to mitigate and respond to these impacts amidst rapid economic and social development. The lake environmental pollution early warning system developed in this study provides a scientific research paradigm for lake water pollution control and offers valuable data support for policymakers in formulating ecological protection and development strategies.

Study of Drinking Water Supply System (SPAM) regulations after the enactment of Law Number 6 Year 2023 About Job Creation

Abstract This study will outline the impacts of policy direction changes on the legal structure management of the Drinking Water Supply System (SPAM) and propose the regulatory concepts for the Drinking Water Supply System (SPAM) that should be implemented following the enforcement of Law Number 6 of 2023 concerning Job Creation. This research is a doctrinal legal study that focuses on examining the legal aspects of Water Supply and Sanitation for Rural and Urban Areas (SPAM) within the Job Creation Law, using a statutory approach and a conceptual approach. The legal materials required for this study include legal instruments and factual data regarding the regulation of SPAM management in the Job Creation Law, employing a triangulation method for the validity of the research materials. Research findings indicate that the policy of resentralisation of licensing in water resource management will lead to disharmony and inconsistency with the management of Drinking Water Supply Systems (SPAM) based on the concept of regional autonomy, which embodies the principle of State Control in the welfare state doctrine. When the direction of water resource management policy is not aligned with the spirit of decentralisation, it hinders the development of SPAM within the legal framework and management culture from a business entity perspective. Post the enactment of Law Number 6 of 2023, the management of water resources should be followed up with efforts to harmonise it with regulations concerning regional autonomy and technical rules related to the management of drinking water supply systems (SPAM). Considering that the concept of decentralisation embodies the fundamental principle of state control within the framework of a welfare state, the regulation of water resource management and SPAM following the implementation of the Job Creation Law must be designed in accordance with the decentralisation concept to meet the basic water needs relevant to regional characteristics.

Vietnam resources management policy due to global climate change

Vietnam resources management policy due to global climate change

Anthropogenic coal mining reducing groundwater storage in the Yellow River Basin.

Anthropogenic coal mining and water consumption affect groundwater storage (GWS) and impose substantial pressure on water resources. However, the responses and mechanisms of GWS to these activities and climate change are not well understood. In this study, the impacts of anthropogenic coal mining, water consumption, vegetation restoration and climate change on GWS in the Yellow River Basin (YRB) of China were quantitatively assessed, based on the Gravity Recovery and Climate Experiment (GRACE) satellite data, land surface model simulations, Random Forest (RF) model, normalized vegetation index data, the statistical information in yearbooks and bulletins, and in situ observations. The results revealed a significant decline at a rate of -7.52mm⋅year-1 in GWS from 2003 to 2020, with the most pronounced decreasing trends in the middle and lower reaches of the YRB. Seventy-five percent of the regions with a gain in GWS showed an increasing trend in the net water flux (precipitation minus evapotranspiration). The RF model results show that water consumption by coal mining is the main factor influencing changes in GWS in the eastern and northern coal mining areas of the basin, with importance scores of 50-53. Significant vegetation restoration increased groundwater drought in the YRB, especially in the growing season. This study provides valuable scientific insights for formulating water resource management policies in the YRB.

Enterprise generative artificial intelligence technologies, Internet of Things and blockchain-based fintech management, and digital twin industrial metaverse in the cognitive algorithmic economy

Research background: Enterprise generative AI system-based worker behavior tracking and monitoring, socially responsible organizational practices, employee performance management satisfaction, and human resource management procedures, relationships, and outcomes develop on hiring and objective performance assessment algorithms in terms of human resource management activities, functions, processes, practices, policies, and productivity. Deep reinforcement and machine learning techniques, operational and analytical generative AI and cloud capabilities, and real-time anomalous behavior recognition systems further fintech development for credit and lending services, payment analytics processes, and risk assessment, monitoring, and mitigation. Generative AI tools can bolster predictive analytics by collaborative and interconnected sensor and machine data for tailored, seamless, and fine-tuned product, operational process, and organizational workflow development, efficiency, and innovation, driving agile transformative changes in digital twin industrial metaverse. Purpose of the article: We show that enterprise generative AI-driven schedule prediction tools, job search and algorithmic hiring systems, and synthetic training data can improve team selection, job performance and firing decisions, hiring decision processes, and workforce productivity in terms of prediction and decision-making by use of algorithmic management, system performance, and production process tracking tools. Blockchain-based fintech operations can shape cloud-based financial and digital banking services, quote-to-cash process automation, cash-settled crypto futures, digital loan decisioning, asset tokenization simulated transactions, transaction switching and routing operations, tailored peer-to-peer lending, and proactive credit line management. Collaborative unstructured enterprise data processing, infrastructure, and governance can develop on AI decision and behavior automation technology, retrieval augmented generation and development management systems, and real-time data descriptive and predictive analytics, driving productivity surges and competitive advantage in digital twin industrial metaverse. Methods: Reference and review management tools, together with evidence synthesis screening software, harnessed were Abstrackr, AMSTAR, ASReview Lab, CASP, Catchii, Citationchaser, DistillerSR, JBI SUMARI, Litstream, PICO Portal, and Rayyan. Findings & value added: The current state of the art is improved for theory on organizational issues and for policy making as deep learning-based generative AI tools and workplace monitoring systems can augment performance and productivity, gauge employee effectiveness, build resilient, satisfied, and engaged workforce, assess human capital, skill, and career development, drive employee and productivity expectations in relation to flexibility and stability, and shape turnover, retention, and loyalty. Cloud and account servicing technologies can be deployed in generative AI fintechs for embedded cryptocurrency trading, transaction monitoring and processing, digital asset transfers, payment screening, corporate and retail banking operations, and fraud prevention. Generative AI technologies can reshape jobs and reimagine meaningful work, involving creativity and innovation and adaptable and resilient sustained performance, providing valuable constructive feedback, optimizing workplace flexibility and psychological safety, and measuring and supporting autonomy and flexibility-based efficiency, performance, and productivity, while configuring demanding, engaging, and rewarding experiences by cloud and edge computing devices in digital twin industrial metaverse.

The Implementation of Human Resource Management Policies in Increasing Student Participation and Engagement in Academic Activities

This research aims to analyze the implementation of Human Resource Management (HRM) policies in increasing student participation and engagement in academic activities at the Faculty of Cultural Management and Business. The study utilized a qualitative approach, including interviews, surveys, and document analysis to gather data. Results indicated that effective HRM policies positively impacted student involvement, particularly through training programs, resource provision, and a supportive learning environment. Key challenges included the gap between theory and practice, along with limited access to advanced training due to time constraints. The findings emphasize the need for continuous evaluation and integration of flexible training opportunities to improve student engagement and academic achievement.

VISUALIZATION OF COLLABORATIVE NETWORKS AND TOPIC TRENDS IN PROACTIVE ENVIRONMENTAL STRATEGIES TOWARDS SUSTAINABLE DEVELOPMENT: A BIBLIOMETRIC REVIEW

This study aims to identify research themes and emerging trends through a systematic bibliometric literature review on proactive environmental strategies towards sustainable development, using data from the Web of Science and Scopus databases over the past 20 years from 2004 to 2024. In this paper, a bibliometric analysis, a quantitative method for evaluating academic literature, was conducted to analyze and visualize the number of documents, collaborative networks, and keyword networks. The results indicate that research on proactive environmental strategies towards sustainable development has been increasing year by year. The main research themes were identified through keyword analysis using bibliometric tools including environmental management, environmental performance, corporate social responsibility, and product life cycle assessment. Emerging trends in this field include stakeholders, human resource management, green innovation, and environmental policy. Based on the literature analysis, this study proposes a future research agenda suggesting that future studies should focus on cross-country and cross-industry comparative studies, the influence of national political policies, stakeholder-driven green innovation, and the role of government in promoting proactive corporate environmental strategies. Focusing on these areas is important as they address the multi-faceted and interconnected nature of corporate environmental strategies. By examining the comparative contexts, policy influences, stakeholder roles, and governmental support, researchers can provide comprehensive insights and actionable recommendations for promoting sustainable business practices globally.

Water quality prediction and carbon reduction mechanisms in wastewater treatment in Northwest cities using Random Forest Regression model

With the accelerated urbanization and economic development in Northwest China, the efficiency of urban wastewater treatment and the importance of water quality management have become increasingly significant. This work aims to explore urban wastewater treatment and carbon reduction mechanisms in Northwest China to alleviate water resource pressure. By utilizing online monitoring data from pilot systems, it conducts an in-depth analysis of the impacts of different wastewater treatment processes on water quality parameters. This work pays particular attention to their impact on key indicators such as Chemical Oxygen Demand (COD), NH4+-N, Total Phosphorus (TP), and Total Nitrogen (TN), and the application of predictive models. The work first establishes a Random Forest Regression (RFR) model. The RFR algorithm integrates Bagging ensemble learning and random subspace theory to construct multiple decision trees and aggregate their predictions, thereby enhancing the model’s prediction accuracy and stability. Using bootstrap sampling, the RFR model generates multiple training subsets from the original data and randomly selects subsets of variables to construct regression trees. Its performance in predicting various water quality indicators is then evaluated. The results show that the RFR model exhibits excellent performance, achieving high levels of prediction accuracy and stability for all indicators. For example, the R2 for COD prediction is 0.99954, while the R2 values for NH4+-N, TP, and TN predictions reach 0.99989. Compared to five other models, the RFR model demonstrates the best performance across all water quality indicator predictions. This work provides critical support for optimizing wastewater treatment technologies and developing water resource management policies. These findings also offer essential theoretical and empirical insights for the future improvement of urban wastewater treatment technologies and water resource management decision-making.

Investigating land cover changes and their impact on land surface temperature in Tay Ninh province, Vietnam.

Land surface temperature (LST) serves as a crucial indicator for evaluating the effects of different environmental factors on the ecosystem, including alterations in land use, climate variations, and emissions of greenhouse gases. This comprehensive study used remote sensing data to analyze changes and effects of land use/land cover (LULC) on LST in Tay Ninh province, Vietnam, from 1988-2023. Landsat satellite images in 1988, 2004, and 2023 were preprocessed and supervised classification on ArcGIS 10.8 software. The Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), and LST in the study area were determined using the Landsat image data. The classification results showed a decrease in the area of agricultural land, barren land, and forest classes by 8.30%, 8.82%, and 15.93%, respectively, from 1988 to 2023. Conversely, the area of built-up and waterbodies classes indicated an increase of 33.00% and 0.06%, respectively, during the same period. In terms of LST, the study area exhibited temperature ranges of approximately 19.75°C-35.28°C, 26.26°C-46.33°C, and 21.05°C-40.60°C in 1988, 2004, and 2023, respectively. Contribution Index (CI) and multiple regression analysis evaluated the relationship between land cover, LST, NDVI, and NDBI. The regression analysis preliminary showed a negative correlation between NDVI and LST, while a positive correlation was observed between NDBI and LST. The CI of built-up areas has increased from 0.01 in 1988 to 0.77 in 2023, which shows that this coating has contributed to rising temperatures in the study area. Meanwhile, the forest and water body classes have consistently negative CI throughout the period 1988-2023, which has contributed to the decrease in temperature. This comprehensive study provides policymakers with valuable information regarding LULC and LST, instilling confidence in developing effective policies for land resource management.

ბიზნესის სოციალური პასუხისმგებლობა (უცხოეთის და საქართველოს გამოცდილება)

At the present stage of the development of socio-economic relations, the world community faces acute social problems, the solution of which is the responsibility of not only the state but also international organizations and business entities that carry out positive actions for the benefit of society. Today, the concept of corporate social responsibility is popular in the activities of business entities in both developed and developing countries and includes social, economic and environmental aspects of their activities, namely resource economy, human resource management policy, environmental protection, consideration of the needs of the local population, responsible supply chain management and others. Since the end of the 20th century, the concept of "corporate social responsibility" of business entities has become an important component of their successful activities, their image and recognition.