Utilities Research Articles

Forecasting Energy Consumption Trends with Machine Learning Models for Improved Accuracy and Resource Management in the USA

Accurate prediction of energy consumption patterns is vital for attaining sustainability and efficient economic planning. In the USA energy consumption trends have evolved substantially because of factors such as population growth, technological advancements, and shifts in consumption behaviors. The prime objective of this research project was to develop and evaluate machine learning algorithms with accuracy in predicting trends in America's consumption of energy. By employing complex methodologies such as neural networks, regression analysis, and ensemble approaches, this work aims to enhance the accuracy of forecasts in terms of demand for energy in residential, commercial, and industrial sectors. The U.S. consumption datasets covered a wide variety of information representing the consumption of electricity, use of fuel, and integration of renewable sources in residential, commercial, and transportation sectors. Most datasets used for analysis are taken from the U.S. Energy Information Administration (EIA) and the Department of Energy (DOE), offering in-depth statistics about production, consumption trends, and price trends. With our dataset consisting of continuous values for consumption of energy and many predictor factors, we compared a variety of machine algorithms, encompassing XG-Boost, Logistic Regression, and Random Forest. The implemented code compared three algorithms – Logistic Regression, Random Forest, and XG-Boost – in terms of performance via calculation and visualization of key evaluation metrics. It devised a function calculate-metrics to calculate accuracy, precision, recall, and F1-score for a prediction of each model over a test set. Retrospectively, comparing accuracy values, one can observe that Logistic Regression got a high score, with Random Forest following closely, and XG-Boost following a little behind them. Overall, through strategic plots, the comparative strengths and weaknesses of all three algorithms were seen, proving that Logistic Regression was the most reliable algorithm for predicting values in a dataset. Utility companies can benefit a lot through machine learning (ML)-based prediction in terms of distribution efficiency and overall operational efficiency. With ML algorithms, utility companies can utilize humungous volumes of consumption in the past to make future demand predictions with high accuracy.

Optimizing Maternal Healthcare Access: A Mixed Method Study on Dual Utilization of Public and Private Antenatal Care Services in Puducherry, India

Abstract Background: Access to antenatal care (ANC) services has improved. However, it is also noted that some antenatal women seek multiple healthcare services. Exploring this practice will identify gaps in service provision and pave the path toward improving the quality of services. Objective: This study aimed to measure the concurrent use of public and private healthcare services for various components of ANC and understand the reasons for the dual utilization. Methodology: This explanatory mixed-method study enrolled 177 mothers residing in Puducherry, who had given birth in the last three years. A pretested, semi-structured questionnaire was administered, and six key informant interviews were conducted. Integration was performed in the interpretation stage, and a joint display was used to depict the results. We adopted the Donabedian model during the analysis and organized the codes under these major themes[1] Access;[2] Delivery of the Services;[3] and Quality of Care. Result: Most pregnant women (81.9%, 95% CI = 75.2%–86.8%) sought care from both public and private healthcare facilities, however, they preferred public facilities for delivery (74.6%, 95% CI = 67.6%–80.4%). The qualitative analysis revealed three major themes[1] Access;[2] Delivery of the Services;[3] and Quality of Care. Primary reasons for opting for private facilities included perceived superior ANC quality, organized care evident in scheduled appointments, reduced waiting time, frequent ultrasounds, personalized medication, and enhanced rapport with family. Women also believed that visits to government facilities are essential to avail the monetary benefits and have a seamless admission during delivery. They felt that government hospitals perform fewer cesarean sections. Conclusion: Strengthening public-private partnerships could enhance antenatal care utilization, benefiting pregnant women and streamlining healthcare delivery.

Design of field trials for the evaluation of transmissible vaccines in animal populations.

Vaccines which can transmit from vaccinated to unvaccinated animals may be especially useful for increasing immunity in hard to reach populations or in populations where achieving high coverage is logistically infeasible. However, gauging the public health utility for future use of such transmissible vaccines and assessing their risk-benefit tradeoff, given their potential for unintended evolution, hinges on accurate estimates of their indirect protective effect. Here, we establish the conditions under which a two-stage randomized field trial can characterize the protective effects of a transmissible vaccine relative to a traditional vaccine. We contrast the sample sizes required to adequately power these trials when the vaccine is weakly and strongly transmissible. We also identify how required sample sizes change based on the characteristics of host ecology such as the overdispersion of the contact structure of the population, as well as the efficacy of the vaccine and timing of vaccination. Our results indicate the range of scenarios where two-stage randomized field trial designs are feasible and appropriate to capture the protective effects of transmissible vaccines. Our estimates identify the protective benefit of using transmissible vaccines compared to traditional vaccines, and thus can be used to weigh against evolutionary risks.

A cross-sectional study characterizing the prevalence of utility service outages across demographic characteristics and health correlates in New York City.

Utility services for electricity, gas, heat, and hot water are necessities for everyday activities (e.g., lighting, cooking, and thermal safety). Utility outages can threaten health; however, information is limited on the prevalence of electricity, gas, heat, and hot water outages in representative studies. We characterized infrastructure-related electricity, gas, heat, and hot water outages in New York City (NYC) and within subgroups. Using a representative 2022 survey of NYC adults (18+), we assessed the prevalence for 6+ hour utility outages and compared across building, demographic, and health subgroups. Building characteristics included age, number of floors, rental type, and owner/rental status. Demographics included household poverty, neighborhood poverty, and race/ethnicity. For health, we focused on cognitive impairment, electricity-dependent medical equipment use, and mental health conditions. Outages impacted 20% of NYC residents. Heat outages were nearly 3× and 2× more common in mid-rise and high-rise buildings respectively, vs. low-rise buildings. Similarly, hot water outages were 5× and over 6× more prevalent in mid-rise and high-rise residences. Renters faced 2× more heat and hot water outages compared with owners. Compared with low-poverty households, high-poverty households faced 2× more hot water outages. Residents with mental health conditions experienced more electricity (11% vs. 5%), heat (15% vs. 7%), and hot water (16% vs. 8%) outages compared with those without. NYC utility outage prevalence varied by type with heat and hot water being most common. Disparities across building, sociodemographic, and health characteristics were also larger and more frequent for heat and hot water outages.

Chatbot-delivered mental health support: Attitudes and utilization in a sample of U.S. college students.

Chatbots' rapid advancements raise the possibility that they can be used to deliver mental health support. However, public utilization of and opinions toward chatbots for mental health support are poorly understood. Survey study of 428 U.S. university students who participated in early 2024, just over one year after the release of ChatGPT. Descriptive analyses examined utilization of and attitudes toward both traditional mental health services (i.e. psychotherapy, counseling, or medication) and chatbot-delivered mental health support. Nearly half (49%) of participants reported having used a chatbot for any purpose, yet only 5% reported seeking mental health support from a chatbot (8% when only considering participants with probable depression or generalized anxiety disorder). Attitudes toward traditional mental health services were broadly positive, and attitudes toward chatbot-delivered support were neutral and significantly less positive (d = 1.18, p < .001). Participants reported lack of need and doubts about helpfulness as barriers to using chatbot-delivered support more frequently than they reported them as barriers to traditional services. Cost, time, and stigma barriers were less frequently reported for chatbot-delivered support than for traditional services. Attitudes were generally consistent as a function of mental health status. Among U.S. students, utilization of chatbots for mental health support is uncommon. Chatbots are perceived as less likely to be beneficial, yet also less affected by cost, time, and stigma barriers than traditional services. Rigorous outcome research may increase public trust in and utilization of chatbots for mental health support.

About LIFE REMEMBRANCE

About LIFE REMEMBRANCE LIFE REMEMBRANCE’s ambition is a demonstrated circular production process of safe and innovative granules and cartridges for drinking water purification from emerging contaminants. The objectives will be achieved through the development of a novel technology based on the recycling of high-value industrial waste derived from hollow fibre membranes (HFM) filter production and validated with the collaboration of an internationally recognised utility company.

P-2224. Clinical and Public Health Implications of Tularemia Diagnoses by Microbial Cell-Free DNA Testing

Abstract Background Tularemia is a nationally notifiable disease and Category A potential bioterrorist threat caused by Francisella tularensis. Microbial cell-free DNA (mcfDNA) sequencing is a pathogen-agnostic diagnostic method using human plasma. mcfDNA detections of F. tularensis are not currently included in public health surveillance criteria for a tularemia case and are not automatically reported to public health jurisdictions. We reviewed recent F. tularensis mcfDNA detections to better understand their clinical and public health implications.Table 1.Francisella tularensis diagnostic test results and reported exposure histories among 15 patients with F. tularensis detected by mcfDNA sequencing — United States, 2018–2023. Methods Available residual patient samples, in which F. tularensis mcfDNA were detected by the Karius CLIA certified/CAP accredited laboratory, were sent to the Centers for Disease Control and Prevention (CDC) for F. tularensis testing by PCR. Treating clinicians and local/state public health jurisdictions where these patients lived at the time of testing were invited to complete a survey regarding clinical details and public health reporting.Table 2.Demographic and clinical characteristics of patients with Francisella tularensis detected by microbial cell-free DNA (mcfDNA) testing, as reported by the ordering clinician — United States, 2018–2023. Results During 2018–2023, mcfDNA sequencing detected F. tularensis in 15 patient samples in 6 states. CDC detected F. tularensis by PCR in 4 (31%) of 13 residual samples, all in samples with higher DNA quantities. All invited jurisdictions (n=6) and most clinicians (8/13, 62%) participated in the survey. Most cases (12/15, 80%) were reported to public health; 3 of 12 (25%) were determined not to meet the tularemia surveillance case definition, and only 1 case reported to CDC mentioned mcfDNA results. Among 11 cases with clinical information, tularemia was not suspected before receipt of mcfDNA results in 10 (91%), despite all patients reporting outdoor activities that could increase F. tularensis exposure risk. Other diagnostic tests for tularemia were positive in 7 of 11 (64%) cases; blood cultures were negative in all cases. mcfDNA results changed clinical management in all cases, resulting in antibiotic changes.Figure 1.Cross-sectional computed tomography of the lungs in a patient diagnosed with pneumonic tularemia by microbial cell-free DNA (mcfDNA) testing, showing bilateral moderate pleural effusion and right upper and middle lobe pulmonary nodules. This patient also exhibited nonspecific mediastinal and bilateral axillary lymphadenopathy and typhoidal symptoms. In this case, mcfDNA testing identified Francisella tularensis nearly 50 hours before any conventional testing confirmed the diagnosis and prompted changes in antibiotic therapy and infection prevention efforts to begin. Conclusion mcfDNA appears to be clinically impactful and highly sensitive for diagnosis of tularemia, particularly in febrile patients with consistent exposure history. New diagnostic methods may pose a challenge to public health surveillance and require changes to case definitions and reporting practices to ensure robustness of public health utility and timely prevention efforts.Figure 2.Left medial knee with 3 cm nodular ulcer with purulence and adjacent erythema at location of suspected tick bite in a patient diagnosed with ulceroglandular tularemia by microbial cell-free DNA (mcfDNA) testing. Disclosures Sarah Y. Park, MD, FAAP, Karius, Inc.: employee

Falling Rates of Public Orthopaedic Surgery Reimbursements and Utilization, 2016 to 2024.

Declining reimbursement rates can lead to decreased access and utilization of common orthopaedic surgeries for patients on Medicare, which is a particularly vulnerable population for musculoskeletal injuries. Using the Centers for Medicare & Medicaid Services Physician Fee Schedule Look-Up Tool from 2016 to 2024 and utilization data for Medicare and part B beneficiaries from 2016 to 2022, we analyzed reimbursement and utilization trends. Simple linear regressions were executed to measure the annual trends, and Wilcoxon matched-pairs signed rank test were used to analyze the statistical significance of price and utilization changes. Between 2016 and 2024, mean reimbursements for all evaluated orthopaedic surgeries decreased 26.2% with a -3.34% compound annual growth rate, from $1,558 to $1,150 (P < 0.0001). Comparatively, reimbursement rates for evaluation and management (E/M) services fell by 15.82% or a -1.91% compound annual growth rate, from $102.3 to $86.12 (P < 0.0021). The federal utilization of all orthopaedic surgeries fell from 2016 to 2022 (P < 0.0001), although no significant changes were seen for E/M services (P = 0.9102). We observe that Medicare reimbursement rates for orthopaedic surgeries from 2016 to 2024 have fallen consistently with a large drop in utilization, especially during the Covid-19 pandemic. Reimbursements for E/M services have fallen at attenuated rates with minimal changes in utilization. This demonstrates the supportive role that declining reimbursement rates may play in utilization and accessibility of orthopaedic surgery.

Framework of Smart Multi-purpose Utility Tunnel Information Modeling for Lifecycle Management

Multi-purpose Utility Tunnels (MUTs), as an alternative to buried and above-ground utilities, can accommodate multiple utilities, such as gas, water, and sewer pipes, and electrical and telecommunication cables. Despite MUTs' advantages, their high initial construction cost and the need for coordination among utility companies hindered their wide usage. Building Information Modeling (BIM) can solve some of these problems by facilitating the design, construction, operation, and coordination of utility companies. However, BIM is mainly developed for buildings and extended to some civil structures. There is a lack of a comprehensive framework covering MUT components and information requirements for other use cases, and its integration with Geographic Information Systems (GIS) and other technologies. This paper proposes an integrated framework for Smart MUT Information Modeling (SMUTIM) by (1) gathering the information requirements for all the phases of lifecycle management, (2) analyzing the use cases of SMUTIM, and (3) extending the Industry Foundation Classes (IFC) to SMUTIM. A case study demonstrates the benefits of the proposed framework.

Exploring the Impact of Work from Home on Sustainable Transport and Car Ownership: A Leeds Case Study

Leeds City Council (LCC) aims to reduce car dependency by decreasing annual car travel by 30% (approximately 900 miles per person) by 2030. Heavy reliance on private vehicles is unsustainable, contributing to pollution, traffic congestion, and increased traffic accidents—issues that disproportionately impact vulnerable communities and raise social equity concerns. This study investigates how Working from Home (WFH) and non-WFH groups influence car ownership reduction and the willingness to adopt sustainable transportation options. An online survey was conducted in Leeds, gathering data on socio-demographics, travel behaviours, and perceptions of public transport. The survey data was analysed using Chi-Square and Binary Logistic Regression to assess the relationship between WFH and travel demand management, focusing on shared mobility schemes and public transport adoption as ways to discourage car ownership. Results indicate that WFH can reduce car ownership and promote sustainable transport usage. These findings suggest that encouraging WFH could help boost participation in shared mobility schemes, enhance public transport utilisation, and ultimately lower car ownership.

Powering Change: A Methodology for Prioritizing Locations When Burying Power Lines to Minimize Wildfire Damage in Communities

Purpose: Overhead power lines can spark and cause extremely devastating wildfires. This has happened with power lines from utility companies such as Pacific Gas and Electric Company (PG&amp;E), Southern California Edison (SCE), and San Diego Gas and Electric (SDG&amp;E). One method of preventing widespread wildfires is to bury power lines underground. When planning to bury lines, utility companies must evaluate where power lines should be buried to minimize collateral damage from wildfires while enhancing infrastructure strength. This research paper advances a novel methodology for identifying and prioritizing the ideal locations for underground power lines. Methodology: Using California as a case study, I examine low, medium, and high wildfire risk locations in PG&amp;E’s, SCE’s, and SDG&amp;E’s jurisdictions. I determine which locations should be prioritized regarding the construction of underground lines by looking at the following factors in geographic information system (GIS) mapping: overhead power lines, critical infrastructure, past wildfire activity, population density, disadvantaged communities, and thermal hotspots. Findings: The results reveal the importance of considering variables like population and infrastructure density when mitigating wildfire risk with underground power lines, expanding the evaluation beyond typical factors like dry vegetation. Unique Contribution to Theory, Practice and Policy: My methodology can be used by utility companies in order to conserve resources and time due to the structured approach. Doing so will also expedite the process of burying power lines which minimizes the impact of wildfires caused by overhead lines.

Ownership in times of water scarcity: are inhabitants supplied by private utilities consuming more water?

ABSTRACT The growing public focus on water resource issues highlights the effectiveness of demand-side management in reducing water consumption, a strategy adopted worldwide. In Brazil, where water scarcity remains a concern, the 2020 regulatory framework accelerated water utilities' privatization. This study examines how the expanded role of private companies in the water and sanitation sector influences residential water consumption behaviors. Using a three-level hierarchical linear model, we analyzed per capita water consumption data from 858 Brazilian municipalities between 2002 and 2019. Results show that, on average, residents in municipalities served by private companies consume less water than those served by public providers. While rising tariffs from privatization may partially explain these outcomes, the literature offers mixed support for this claim. Nonetheless, findings emphasize the importance of state-owned water providers, which serve most Brazilians, in revisiting their water demand management strategies. Key actions could include informational campaigns and economic incentives to promote voluntary water-saving behaviors.

Legal regulation of energy relations in Ukraine in the context of sustainable development

The article is devoted to the analysis of legal regulation of energy relations in Ukraine in the context of sustainable development. The main challenges of the energy sector are considered, in particular the issues of energy efficiency, the use of renewable energy sources and the introduction of the latest technologies. The role of international standards and obligations of Ukraine is analyzed, in particular within the framework of European integration and the implementation of the UN’s sustainable development goals. It is found that the current legislation of Ukraine is mainly focused on traditional energy sources, which creates obstacles to the development of renewable energy. However, the introduction of European standards contributes to the transformation of energy policy. In particular, legal regulation of renewable energy sources and energy saving are priority areas within the framework of sustainable development. Particular attention is paid to the analysis of the regulatory and legal aspects of the energy system functioning during martial law. The key role of state authorities in regulating energy relations in Ukraine and in ensuring the efficient functioning of the energy sector, protecting the interests of consumers and the State, as well as in implementing the State policy in this area is established. The author describes the main functions of the state authorities responsible for regulating energy relations: The Ministry of Energy of Ukraine, the National Commission for State Regulation of Energy and Public Utilities, the State Service of Ukraine for Geology and Subsoil, the State Environmental Inspectorate of Ukraine, the State Energy Supervision Service, and the State Statistics Service of Ukraine. The report identifies the adaptation of the national energy system to the European energy system and further implementation of energy reforms to fulfil Ukraine’s commitments to approximate its energy legislation to EU legislation as priorities for further transformation of Ukraine’s national energy policy in the context of European integration.

Goods and Services Tax (GST) and Its Impact on North East India: A Study of Revenue Generation and Public Utilities

India introduced the Goods and Services Tax (GST) in 2017 to replace multiple indirect taxes and bring in a united taxation system. The impact of this on North East India is investigated in this study with regard to revenue generation, public utilities and related sectors. However, the findings suggest that GST has made major strides in improving revenue collection for the region, but its effects on public utilities as well as agriculture and the SME sector are mixed.

Utilization of Electronic Information Resources as Correlates of Publication Output by Researchers in Agricultural Research Institutes in Oyo State, Nigeria

The study examined the utilization of electronic information resources (EIRs) as correlates of publications among research scientists in National Agricultural Research Institutes (NARIs) headquarter in Ibadan, Oyo State, Nigeria. Correlational research method was used to determine the relationship between utilization of EIRs and publications output among research scientists. Simple random sampling technique was used to select 217 respondents from a sample frame of 282 researchers based on Morgan’s table for sample size in four (Institute of Agricultural Research and Training, National Institute of Horticultural Research, Forestry Research Institute of Nigeria and Cocoa Research Institute of Nigeria) NARIs. Data were obtained on types of EIRs utilized, extent of use, effect of EIRs utilization on publication and the total of researchers’ publications using a structured questionnaire. The results obtained were analyzed using descriptive statistics (frequency counts, percentages, mean and standard deviation) and Pearson Product Moment Correlation coefficient (PPMC). Results revealed that major types of EIRs utilized by the researchers for their publications were Access to Global Online Research in Agriculture ( 3.46), Online Access to Research in the Environment ( 3.41) and The Essential Electronic Agricultural Library ( 3.32). The result further revealed that researchers have a high extent of use of EIRs with 100% utilization. The researchers stated that utilization of EIRs enhances efficient and effective publications ( 3.58) improve the quality of their publications ( 3.52) and enhance their decision making in publishing ( 3.48). Results further revealed that 74.9% and 85.3% of the researchers published more in local journals and proceedings respectively compared to 25.1% and 14.7% that published in international journals and proceedings respectively. PPMC revealed a significant (p&lt;0.05) relationship between utilization of EIR (r = 0.127) and researchers publications. In conclusion, utilization of EIRs enhances the publication output of researchers in agricultural research institutes. Therefore, the study recommended that stakeholders and policy makers in agricultural research institutes should invest in facilities that will facilitate utilization of EIRs for publications activities among research scientists.

Decomposing disparities in the utilization of basic public health services between locals and internal migrants in China: the role of social determinants

BackgroundInternal migrants in China have long been at a disadvantage in terms of access to publicly financed services, as well as the utilization of public health services. The aim of the study was to examine inequities in the use of basic public health services between internal migrants and the local population and estimate the factors that contributed to inequity in use.MethodsThe data for this study was derived from the 2017 wave of the China Migrants Dynamic Survey. Basic public health services utilization was measured by the establishment of health records, health education and chronic disease management. We performed multivariable logistic regressions to examine inequities in the utilization of basic public health services between locals and internal migrants, and Oaxaca-Blinder decomposition was used to explore possible explanations for such inequities between the two groups.ResultsA total of 27,998 cases were included in the analysis. We found that the utilization rates for establishment of health records, health education and chronic disease management among internal migrants were 71.3%, 49.2% and 65.7% lower than their local counterparts, respectively. The decomposition results indicated that the inequities in the establishment of health records between locals and internal migrants were mainly explained by whether people had heard of the National Basic Public Health Services Program (NBPHSP) (17.67%) and by health insurance (5.99%). The contributors to the inequities in health education between locals and internal migrants were community involvement (14.71%) and whether people had heard of the NBPHSP (13.89%). The main factors contributing to the difference in utilization of chronic disease management between the two groups were whether people had heard of the NBPHSP (14.49%) and community involvement (8.43%).ConclusionsTo reduce inequities in the utilization of basic public health services between locals and internal migrants, measures need to be taken to improve knowledge about the basic public health services and to help migrants integrate into the local community.

The Impact of EU Taxonomy for Sustainable Activities on European Utilities' Performance

ABSTRACTThis study investigates the relationship between European utility companies' compliance with the EU Taxonomy for Sustainable Activities and their overall performance. The EU Taxonomy is a new regulation proposed by the European Commission to promote sustainable finance by 2050. The literature shows that nonfinancial disclosures have a favorable impact on financial performance. However, no research has been conducted to assess the implementation of the EU Taxonomy and its effect on firm performance. Using a sample of European utilities from 2012 to 2022, a difference‐in‐differences (DiD) model was applied to analyze the causal relationship between compliance and performance. Based on institutional and signaling theories, the results show that companies reporting alignment with the Taxonomy exhibit higher market value, profitability, and efficiency than those that do not. This study contributes to firms' transparency and enriches academic discussions by offering insights for policymakers and by improving industry practices.

An optimization model for the energy management of the network of tanks in a drinking water distribution system

Abstract“L'eau c'est la vie” is a well‐known French expression for “water is life,” which reflects the fact that water is undoubtedly the most vital resource in the world. The main mission for water utility companies is to convey and distribute water that is of acceptable quality to satisfy the demand of the population at any time of the day. In the recent years, achieving this mission has become very challenging for these companies. Indeed, on the one hand, the rapid growth of population and the expansion of urbanization have significantly increased the demand for water, while on the other hand, natural phenomenon, such as drought, as well as the impact of climate changes are making it almost impossible for water distribution companies to convey the right amount of water where and when it is needed. The presence of water storage tanks in a water distribution network is aimed at alleviating this pressure by storing water and distributing it later in response of the variability of the demand across the network. The management of the tanks of the network is done based on the assignment of three‐level set points, which allows to meet the outflow demand of water from each tank, while maintaining the adequate flow rate through the network. The set points define the level at which the valves that enable inflow and outflow of water to the tank have to be switched on or off. However, operating the valves during different periods of the day to meet the water demand may yield extremely high operational cost because opening some of the valves will induce the running of pumps to maintain an adequate flow rate of water in the network. We present a network optimization model for managing the network of storage tanks in a drinking water distribution system while minimizing the total cost of electricity involved. Computational experiments have been conducted on up to three sets of distribution networks. The results show that our proposed optimization model can be used to reduce the operational cost of managing the network of storage tanks for a water distribution system by up to 38%, while still being able to maintain the right amount of water in the tanks.

Regional Government Obligations in Fulfilling the Right to Clean Water

This study examines the regional government’s obligations in fulfilling the right to clean water to achieve public utility benefits, focusing on the Regional Water Utility Company (PDAM) in Bone Regency. The research adopts an empirical juridical method, combining field studies on the implementation of existing laws with data gathered through observation, interviews, and documentation. The results indicate that the fulfillment of the right to clean water by PDAM Bone Regency is not optimal. Challenges persist in three key aspects: quality, quantity, and continuity of water supply. The water quality often fails to meet standards, with issues such as turbidity reported by consumers. The quantity of water distributed remains insufficient to meet the needs of all citizens, particularly during extended dry seasons, and the continuity of water flow is inconsistent, disrupting daily activities. These issues hinder the realization of public welfare and equitable access to clean water, as mandated by Indonesia’s legal framework and human rights principles. This study highlights the need for improved management, infrastructure upgrades, and policy interventions to ensure the right to clean water is upheld for all citizens of Bone Regency.

Analysis of Concession, Technology, and Service Implementation on Port Infrastructure Performance: A Case Study in DKI Jakarta and Banten Provinces

As an archipelagic country, Indonesia relies heavily on ports as the main infrastructure to support the national logistics system and international trade. Despite its importance, port management in Indonesia faces challenges such as lack of government support, corruption, bureaucratic inefficiency, and gaps between policy and implementation. This study aims to analyze the effect of concession implementation, technology utilization, and port services on the role of Port Business Entities (BUP) and their impact on port infrastructure performance in DKI Jakarta and Banten Provinces. The study used a quantitative method with a Likert scale questionnaire based on 31 indicators covering five variable constructs: concession implementation, technology utilization, port services, BUP role, and port infrastructure performance. Data were collected from 310 respondents selected through stratified sampling, consisting of users of port services managed by BUP from November 2023 to January 2024. Data analysis was carried out using SmartPLS 3.2.9 software to validate the relationship between variables through the Structural Equation Modeling (SEM) approach. The results of the study indicate that concession implementation, technology utilization, and port services significantly influence the role of BUP, which in turn improves port infrastructure performance. In addition, the indirect influence of these variables reinforces the importance of strategic management and technology utilization in port optimization. This study confirms that implementing good concession policies, integrating modern technology, and improving port services can significantly improve the performance of port infrastructure in Indonesia. These findings provide important implications for policymaking and strategy development to optimize port operations in the future.